Trading Strategies for Sale (Ranked And Sorted)

Below, you will find backtested and researched trading ideas and analysis for our Trading Strategies for Sale. This little shop contains performance metrics, statistics, risks, historical performance, and figures.

The historical performance and figures for strategies found in our shop may not indicate future success (they are hypothetical). One of the limitations of hypothetical performance results is that they are prepared with the benefit of hindsight and may not reflect the future. The strategy is only backtested on the indicated asset; a backtest has limitations, and strategies might fail after backtesting (despite all strategies having at least one year of incubation before release). If you are unsure, please read our full disclaimer. Simulations are done at the close unless otherwise stated (how to trade at the close – or alternative entries).

Table of contents:

Ranking our Strategies

For a summary of the strategies, please see the table below. Each strategy from our shop is listed in detail under the table.

Trading Strategy #	Asset	Strategy Name/Type	No. of Trades	Avg. Gain per Trade	Win Ratio	Profit Factor	CAGR	Exposure/Time in Market	Risk-Adjusted Return	Max Drawdown
1	QQQ	Swing Trade Nasdaq (volatility bands)	189	1.6%	80%	3.1	12.1%	11%	110%	-19.5%
2	SPY	IBS Swing Trade in the S&P 500	596	0.77%	73%	2.2	14.5%	36%	40%	-22%
3	QQQ	Williams R% Swing Trade in Nasdaq	255	1.1%	75%	2.8	11.4%	14%	81%	-20%
4	QQQ	Two Indicator Swing Trade Strategy	232	1.2%	73%	2.7	10.7%	14%	76%	-19%
5	QQQ	Double Indicator Swing Trade in Nasdaq	285	1.0%	75%	2.5	11%	17%	66%	-25%
7	XLP	XLP swing trade	477	0.35%	72%	1.8	8.1%	32%	20%	-15%
8	XLP	XLP Swing Trade (two variables)	163	0.5%	80%	2.2	3.6%	10%	N/A	-10%
9	QQQ	Overnight Edge in Nasdaq	474	0.15%	60%	1.5	2.9%	7.3%	N/A	-10%
10	QQQ	End Of Month Overnight Edge In Nasdaq	192	0.18%	61%	1.9	1.1%	3%	N/A	-3%
11	TLT	Seasonal Bond Trade	288	0.3%	70%	1.8	3.7%	16%	N/A	-9%
12	GLD	Breakout Strategy (Long) In Gold	509	0.32%	76%	1.8	8%	28%	28%	-13%
13	QQQ	QQQ Collapse Trading Strategy (Long)	400	0.56%	62%	1.7	8.8%	10%	80%	-23%
14	QQQ	Long Momentum Strategy for Nasdaq	131	1.05%	82%	3	5.3%	15%	34%	-26%
15	TLT	Short swing trade in TLT (bonds)	211	0.47%	12%	1.8	4.3%	26%	16%	-13%
16	XLU	Long swing trade in XLU (utilities)	158	0.72%	62%	1.9	4.3%	14%	30%	-17%
17	SPY	Long volatility swing trade in SPY	394	0.34%	77%	2.1	4.1%	10%	39%	-18%
18	SPY	Overnight long trade in SPY	374	0.28%	60%	1.6	3.1%	5%	68%	-16%
19	SMH	Short Swing Strategy Semiconductors	109	0.79%	75%	2.4	3.5%	3%	110%	-12%
20	SPY	Overnight long trade in SPY (Seasonal)	318	0.37%	62%	2	3.5%	4%	90%	-8%
21	QQQ	Long swing trade in QQQ	189	0.75%	72%	2.1	6.0%	12%	49%	-19%
22	QQQ	Long overnight trade in QQQ/SPY	431	0.55%	61%	1.9	9%	6%	135%	-12%
23	XLP	Short swing trade XLP	210	0.3%	69%	2.1	2.1%	6%	36%	-6%
24	XLV	Long swing trade XLV/XLU (Seasonal)	160	0.55%	62%	2	3.3%	9%	34%	-7%
25	TLT	Long and short swing trade TLT (Seasonal)	416	0.42%	62%	1.7	9.3%	37%	25%	-18%
26	QQQ	Long QQQ volatility strategy	324	0.95%	75%	2.3	12.6%	20%	62%	-23%
27	SPY	Long holiday swing trade S&P 500	123	0.3%	60%	2	1.2%	2%	60%	-7%
28	FGBL	Long seasonal swing trade German bunds	179	0.36%	71%	2.5	2.8%	15%	N/A	-5%
29	VNQ	Long swing trade real estate stocks	375	0.82%	61%	2.1	14.5%	51%	28%	-33%
30	TLT	Long swing trade Treasury bonds	242	0.31%	69%	2	3.3%	13%	24%	-9%
31	QQQ	Trading volume strategy	225	1.4%	79%	3.5	12.4%	10%	127%	-19%
32	GLD	Long swing trade GLD (gold)	179	0.5%	71%	2.1	4.4%	10%	42%	-14%
38	SPY	RSI Trading Strategy	402	0.6%	73%	2.3	7.9%	13%	57%	-16%
39	SPY	Stochastic Indicator Trading Strategy	397	0.5%	72%	2.2	6.2%	13%	47%	-20%
40	QQQ	MACD (Histogram) Trading Strategy	121	1.3%	80%	4.5	6.1%	6%	103%	-20%
41	SPY	Bollinger Band Trading Strategy	568	0.4%	70%	1.7	6.5%	20%	16%	-18%
42	SPY	Bundle: 3 Trend following Strategies	22	31.9%	77%	6	7.6%	81%	9.4%	-35%
43	QQQ	Bundle: 3 Swing Trading Strategies	492	0.75%	71%	2.3	14.3%	29%	49%	-31%
44	QQQ	MACD Indicator Trading Strategy	181	1%	77%	3	7.2%	9%	81%	-11%
45	SPY	Heikin Ashi Trading Strategy (Long-term)	84	4.6%	50%	3	5.1%	66%	7.5%	-29%
46	SMH	LL & LH Trading Strategy (Mean Reversion)	236	1%	74%	2.4	9.8%	13%	73%	-48%
47	Combined	Bundle: Combining long and short strategies	607	0.58%	70%	1.9	19%	27%	59%	-17%
48	BTC-USD	Bundle: Bitcoin Trading Strategy (3 Strategies)	163	5.7%	47%	2	100%	60%	168%	-49%
49	SPY	Buy the dip Trading Strategy (Mean Reversion)	284	0.4%	71%	2.4	3.4%	9%	34%	-14%
50	SPY	Super indicator Trading Strategy (Weekly)	39	10.8%	66%	4	5.9%	62%	9.5%	-24%
51	SPY	Money Flow Index Trading Strategy	895	0.3%	72%	1.7	7.5%	28%	26%	-23%
52	S&P 500	Momentum Trading Strategy	43	10.1%	67%	7	5.9%	65%	9%	-25%
53	SPY	Short-Term Pullback Strategy	379	0.47%	69%	2.52	5.5%	14%	39%	-14%
55	QQQ	IBS Trading Strategy	525	0.65%	68%	2.2	13.3%	26%	50%	-41%
56	GLD	Gold Seasonal Trend Strategy	87	0.72%	72%	3	3.1%	4.1%	76%	-6%
57	SPY	Coppock Trading Strategy	13	44%	100%	NA	6.4%	73%	8.6%	-30%
58	SPY	200-Day Moving Average Trading Strategy	81	6.4%	50%	2.9	6.9%	70%	9.9%	-22%
59	SPY	Triple RSI Trading Strategy	97	1.2%	90%	8	3.8%	5%	69%	-13%
60	QQQ	Nasdaq Interest Rate Strategy	264	0.76%	73%	2.5	8.8%	16%	55%	-19%
61	QQQ	Rubber band Trading Strategy	277	1.05%	70%	2.2	11.2%	16%	68%	-23%
62	GLD	Gold Weekly Momentum Strategy	144	1%	80%	2.3	6.9%	35%	20%	-24%
63	S&P 500	Chopiness Strategy	319	0.6%	74%	2.3	5.5%	10%	55%	-19%
64	SPY, GLD, TLT	Monthly momentum strategy (Rotation)	476	0.8%	56%	1.4	8.6%	90%	9.5	-19%
65	SPY	Last Trading Day Of The Month Strategy	197	0.54%	78%	2.5	3.4%	6%	59%	-13%
66	^RUT (IWM)	Russell 2000 rebalancing strategy (Seasonal)	25	1.4%	68%	3	1.4%	2%	69%	-6%
67	QQQ	ADX Trading Strategy	340	0.85%	78%	2.2	11.3%	17%	65%	-21%
69	Monthly (Rotation)	Monthly (Or Weekly) Sector Rotation (monthly metrics)	187	1.4%	60%	2	12.5%	100%	N/A	-21%
70	SMH	Bollinger Bands + RSI Trading Strategy (Long/Short)	297	0.65%	67%	1.9%	8.3%	16%	51%	-13%
71	SMH	MACD + RSI Trading Strategy	235	0.9%	73%	2.3	8%	14%	56%	-46%
72	QQQ	ADX + RSI Trading Strategy	258	1%	73%	2.4%	10.5%	15%	70%	-23%
73	SPY	Day Trading Strategy (Short) For S&P 500	109	0.28%	69%	2.5	1.3%	2%	671%	-3%
74	TLT	Long Panic Strategy For Bonds	85	0.35%	76%	3	1.3%	2.5%	52%	-2.7%
75	QQQ	Bundle: 3 VIX Trading Strategies	506	0.7%	73%	1.8	13.4%	30%	45%	-23%
76	SPY	DMI Trading Strategies	400	0.35%	74%	2	5.7%	12%	34%	-17%
77	SPY	Bear Market Day Trading Strategy (Long)	100	0.5%	62%	2	1.5%	1%	126%	-5%
78	SPY	Day Trading Strategy S&P 500	166	0.45%	60%	1.9	2.3%	2%	110%	-9%
79	IWM	Short Strategy For Russell 2000	167	0.6%	65%	2.3	3.9%	4%	86%	-11%
80	SPY	End-of-Month Strategy S&P 500	641	0.35%	72%	2	6.4%	21%	30%	-16%
81	SPY	Turnaround Tuesday Strategy	400	0.65%	75%	2.7	7.9%	12%	63%	-18%
82	S&P 500	Turn of the Month Strategy	650	0.65%	62%	2	6.3%	24%	26%	-28%
83	SMH	Ultimate Oscillator Strategy	311	0.85%	70%	2.2	10.4%	20%	50%	-46% (!)
84	SPY	Double Seven Trading Strategy	370	0.6%	77%	2.2	6.8%	28%	24%	-14%
85	IWM	Overnight Strategy for Russell 2000	152	0.31%	77%	4	2%	2.5%	79%	-2%
86	UGA	Overnight Strategy for Gasoline (Seasonal)	123	0.6%	62%	2.2	4.3%	2.5%	177%	-7%
87	QQQ	Combined: Trend Following + Mean Reversion	99	4.4%	66%	3	15%	72%	21%	-32%
88	SPY/TLT	Combined: Seasonal Effects (Stocks & Bonds)	467	0.5%	63%	1.7	5.5%	22%	24%	-7%
89	SPY	First Trading Day Of The Month Strategy	76	0.7%	76%	3	1.7%	2.4%	68%	-6%
90	QQQ	Combined: Trend Following + Mean Reversion	237	1.8%	51%	3.2	14%	79%	17%	-50%
91	QQQ	Day Of Week Effect On Stocks	458	0.85%	76%	2.7	15%	25%	58%	-27%
92	QQQ	Short (Tail Risk) Trading Strategy	156	1.2%	67%	2	7.2%	10%	75%	-23%
93	TLT	Short Trading Strategy In Bonds	215	0.3%	59%	1.7	2.5%	12%	21%	-10%
95	SPY	24-hour (Overnight) Strategy SPY/QQQ	405	0.4%	63%	2.2	5.1%	5%	102%	-7%
96	BTC-USD	Seasonal Strategy For Bitcoin	103	2.7%	60%	2.3	28%	10%	280%	-20%
97	GLD	Long Pullback Strategy for Gold	90	0.75%	73%	2.5	3.3%	5%	58%	-8%
98	SPY	Long Bear Market Strategy for S&P 500	197	0.6%	73%	2	3.6%	4%	84%	-16%
99	SPY	Short Strategy for S&P 500	147	0.75%	69%	2.1	3.3%	7.5%	45%	-11%
100	GLD	Long Gold Strategy	214	0.45%	58%	1.6	4.5%	21%	22%	-15%

A portfolio equity line chart for a quantified trading strategy showing a steady upward performance trend from $100,000 to a final value of $487,012. — AmiBroker is a leading platform used to develop and execute the top-ranked trading strategies for sale.

Strategy 1: Swing Trade Nasdaq (volatility bands)

The strategy uses volatility bands but additionally uses two other criteria. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

The strategy was our monthly Trading Edge for August 2021 (but published a few years before that).

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 189
Average gain per trade: 1.6%
Win ratio: 80%
Profit factor: 3.1
Annual returns (CAGR): 12.1%
Exposure/time in the market: 11%
Risk-adjusted return: 110% (CAGR divided by time spent in the market (0.1))
Max drawdown: -19.5%

The equity curve (log scale) on QQQ:

A long-term portfolio equity curve for a Nasdaq swing trading strategy using volatility bands, showing growth from $100,000 in the year 2000 to over $2.3 million by 2024. — This Nasdaq volatility-based model is one of our top-performing trading strategies for sale, showcasing consistent growth over two decades.

Order by clicking here (check for strategy no.1):

Once you have paid you can download the strategy on this link.

Strategy 2: IBS Swing Trade in the S&P 500

The strategy uses the IBS indicator, but we made a small twist. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy was our monthly Trading Edge for October 2021.

Statistics and figures (SPY) – including 0.03% commissions and slippage per trade:

No. of trades: 596
Average gain per trade: 0.77%
Win ratio: 73%
Profit factor: 2.2
Annual returns (CAGR): 14.5%
Exposure/time in the market: 36%
Risk-adjusted return: 40% (CAGR divided by time spent in the market (0.36))
Max drawdown: -22%

The equity curve (log scale) in SPY:

A long-term portfolio equity line chart for an IBS swing trade strategy in the S&P 500, showing consistent growth from $100,000 in the early 1990s to a final value of $6,027,290. — The IBS swing trade in the S&P 500 is one of our most robust trading strategies for sale, demonstrating significant long-term capital appreciation.

Order by clicking here (check for strategy no.2):

Once you have paid you can download the strategy on this link.

Strategy 3: Williams R% Swing Trade in Nasdaq

The strategy uses the famous and handy Williams %R indicator, but we added a second indicator. Backtested on the ETF that tracks Nasdaq 100 (QQQ). Commissions of 0.025% each way are included.

Published October 2021.

Statistics and figures (QQQ) – including 0.03% commissions and slippage per trade:

No. of trades: 255
Average gain per trade: 1.1%
Win ratio: 75%
Profit factor: 2.8
Annual returns (CAGR): 11.4%
Exposure/time in the market: 14%
Risk-adjusted return: 81% (CAGR divided by time spent in the market (0.14))
Max drawdown: -20%

The equity curve (log scale) in QQQ:

A long-term portfolio equity line chart for a Williams %R Nasdaq swing trading strategy showing growth from $100,000 in the year 2000 to a final value of $2,438,040. — This Williams %R model for the Nasdaq is among our top-ranked trading strategies for sale, demonstrating over two decades of robust capital appreciation.

Order by clicking here (check for strategy no.3):

Once you have paid you can download the strategy on this link.

An infographic displaying performance statistics for three quantified trading strategies, including the Nasdaq Volatility Bands model with a 79% win ratio and the S&P 500 IBS swing trade with a 2.4 profit factor. — Detailed performance metrics for our top-ranked trading strategies for sale, featuring win ratios, CAGR, and risk-adjusted returns.

Strategy 4: Two Indicator Swing Trade Strategy (Nasdaq – QQQ)

The strategy uses the widely used IBS indicator, but we added a second indicator. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published October 2020.

Statistics and figures (QQQ – including commissions and slippage of 0.03% per trade):

No. of trades: 232
Average gain per trade: 1.2%
Win ratio: 73%
Profit factor: 2.7
Annual returns (CAGR): 10.7%
Exposure/time in the market: 14%
Risk-adjusted return: 76% (CAGR divided by time spent in the market (0.14))
Max drawdown: -19%

The equity curve (log scale) in QQQ:

A long-term portfolio equity line chart for a two-indicator swing trading strategy on the Nasdaq (QQQ), showing steady capital growth from $100,000 in 2000 to nearly $2 million by 2024. — This dual-indicator Nasdaq system is a top-tier example of our trading strategies for sale, offering a balanced approach to trend-following and risk management.

Order by clicking here (check for strategy no.4):

Once you have paid you can download the strategy on this link.

Strategy 5: Double Indicator Swing Trade in Nasdaq

The strategy uses the often ignored ADX indicator. We backtest the ADX indicator alongside another indicator. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published October 2020.

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 285
Average gain per trade: 1.0%
Win ratio: 75%
Profit factor: 2.5
Annual returns (CAGR): 11%
Exposure/time in the market: 17%
Risk-adjusted return: 66% (CAGR divided by time spent in the market (0.16))
Max drawdown: -25%

The equity curve (log scale) in QQQ:

A long-term portfolio equity line chart for a double indicator swing trading strategy on the Nasdaq, showing consistent growth from $100,000 in 2000 to nearly $2 million by 2024. — This high-performing Nasdaq model is a standout among our trading strategies for sale, utilizing a dual-signal approach to maximize gains while managing risk.

Order by clicking here (check for strategy no.5):

Once you have paid you can download the strategy on this link.

Strategy 6: 23 Candlestick formations

We have Amibroker code for 23 candlestick formations (If you want Tradestation code for all 75 candlesticks, click here). Please check out this candlestick article where we tested these 23 formations. The candlesticks are put down into trading rules and backtested on S&P 500 (SPY).

Published December 2021.

Order by clicking here (check for strategy no.6):

Once you have paid you can download the strategy on this link.

Strategy 7: XLP swing trade

The ETF XLP tracks consumer stocks like Wal-Mart, Procter&Gamble, etc. Its movements are different than the main stock indices.

We have made a backtest that generates signals in XLP based on another relevant ETF.

This strategy was our monthly Trading Edge for May 2021.

Statistics and figures (XLP) – including commissions and slippage of 0.03% per trade:

No. of trades: 477
Average gain per trade: 0.35%
Win ratio: 72%
Profit factor: 1.8
Annual returns (CAGR): 8.1%
Exposure/time in the market: 32%
Risk-adjusted return: 20% (CAGR divided by time spent in the market (0.32))
Max. drawdown: -15%

The equity curve (log scale):

A long-term portfolio equity line chart for a Consumer Staples (XLP) swing trading strategy, showing consistent growth from $100,000 in 2003 to a final value of $529,755 by 2024. — The XLP swing trade is a top-ranked defensive model in our collection of trading strategies for sale, offering steady growth through diverse market cycles.

Order by clicking here (check for strategy no.7):

Once you have paid you can download the strategy on this link.

Strategy 8: XLP Swing Trade

The ETF XLP tracks consumer stocks like Wal-Mart, Procter&Gamble, etc. Its movements are different than the main stock indices.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

The strategy is based on two variables.

The strategy was our monthly Trading Edge for April 2021.

Statistics and figures (XLP) – including commissions and slippage of 0.03% per trade:

No. of trades: 163
Average gain per trade: 0.5%
Win ratio: 80%
Profit factor: 2.2
Annual returns (CAGR): 3.6%
Exposure/time in the market: 10%
Max. drawdown: -10%

The equity curve (log scale):

A long-term portfolio equity curve for a Consumer Staples (XLP) swing trading strategy, showing a steady upward progression from $100,000 in 2003 to a final value of $229,390 in 2024. — This secondary XLP model is a key component of our trading strategies for sale, offering a conservative but consistent growth profile for risk-averse traders.

Order by clicking here (check for strategy no.8):

Once you have paid you can download the strategy on this link.

Strategy 9: Overnight Edge in Nasdaq

The strategy buys at the close and sells on the next open. The strategy is based on two variables. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

This strategy was our monthly Trading Edge for March 2021.

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 474
Average gain per trade: 0.15%
Win ratio: 60%
Profit factor: 1.5
Annual returns (CAGR): 2.9%
Exposure/time in the market: 7.3%
Max. drawdown: -10%

The equity curve (log scale):

A long-term portfolio equity line chart for an overnight trading strategy on the Nasdaq, showing consistent growth from $100,000 in the year 2000 to a final value of $218,118. — This overnight system is a specialized model in our list of trading strategies for sale, capturing the unique price tendencies that occur while the market is closed.

Order by clicking here (check for strategy no.9):

Once you have paid you can download the strategy on this link.

Strategy 10: End Of Month Overnight Edge In Nasdaq

The strategy buys at the close and sells on the next open (no matter what). The strategy is based on one variable. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

This strategy was our monthly Trading Edge for February 2021.

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 192
Average gain per trade: 0.18%
Win ratio: 61%
Profit factor: 1.9
Annual returns (CAGR): 1.1%
Exposure/time in the market: 3%
Max. drawdown: -3%

The equity curve (log scale):

A long-term portfolio equity line chart for an end-of-month overnight trading strategy on the Nasdaq, showing consistent growth from $100,000 in 2000 to a final value of $218,119. — This end-of-month overnight model is a specialized entry in our trading strategies for sale, capturing recurring seasonal price tendencies in the Nasdaq.

Order by clicking here (check for strategy no. 10):

Once you have paid you can download the strategy on this link.

Strategy 11: Seasonal Bond Trade (TLT)

The strategy is based on seasonality and has additionally two simple criteria based on where the close is in relation to the previous days. Backtested on the ETF that tracks bonds (TLT).

This strategy was our monthly Trading Edge for June 2021.

Statistics and figures (TLT) – including commissions and slippage of 0.03% per trade:

No. of trades: 288
Average gain per trade: 0.3%
Win ratio: 70%
Profit factor: 1.8
Annual returns (CAGR): 3.7%
Exposure/time in the market: 16%
Max. drawdown: -9%

The equity curve (log scale):

A long-term portfolio equity curve for a seasonal bond trading strategy on the TLT ETF, starting at $100,000 in 2004 and reaching an ending capital of $262,215 by 2025 — Equity growth of a seasonal bond strategy, illustrating the long-term compounding potential of data-driven trading strategies for sale

Order by clicking here (check for strategy no.11):

Once you have paid you can download the strategy on this link.

Strategy 12: Breakout Strategy (Long) In Gold (GLD)

The strategy is based on breakouts, entering at the close and exiting a few days later. There are three variables. Backtested on the ETF that tracks gold (GLD).

This strategy was our monthly Trading Edge for November 2023.

(Originally, we had an FXI strategy as #12, but we removed it due to zero interest.)

Statistics and figures (GLD) – including commissions and slippage of 0.03% per trade:

No. of trades: 509
Average gain per trade: 0.32%
Win ratio: 76%
Profit factor: 1.8
Annual returns (CAGR): 8%
Exposure/time in the market: 28%
Risk-adjusted return: 28% (CAGR divided by time spent in the market (0.28))
Max. drawdown: -13%

The equity curve (log scale):

A portfolio equity line chart showing the long-term performance of a breakout strategy in gold (GLD) from 2006 to 2024, with ending capital reaching $446,705. — Backtested performance of a gold breakout strategy, demonstrating the capital appreciation possible with high-quality trading strategies for sale

Order by clicking here (check for strategy no.12):

Once you have paid you can download the strategy on this link.

Strategy 13: QQQ Collapse Trading Strategy

The strategy enters at the open and exits at the close based on two simple criteria. The holding period is short. Backtested on the ETF that tracks Nasdaq 100 (QQQ). It’s a long strategy.

This strategy was our monthly Trading Edge for January 2024.

Statistics and figures (QQQ) – including 0.03% commissions and slippage per trade:

No. of trades: 400
Average gain per trade: 0.56%
Win ratio: 62%
Profit factor: 1.7
CAGR: 8.8%
Exposure/time in the market: 10%
Risk-adjusted return: 80% (CAGR divided by time spent in the market (0.1))
Max. drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart for the QQQ Collapse Trading Strategy, showing growth from $100,000 in 2000 to an ending capital of $848,755 by 2025. — 25-year backtest of a QQQ collapse strategy, showcasing the resilience and profit potential of high-performing trading strategies for sale during market downturns

Order by clicking here (check for strategy no.13):

Once you have paid you can download the strategy on this link.

Strategy 14: Long Momentum Strategy for Nasdaq (QQQ)

The strategy can be labeled a momentum strategy. It has two parameters to buy and one for when to sell.

This strategy was our monthly Trading Edge for August 2025.

Statistics and figures (QQQ) – including 0.03% commissions and slippage per trade:

No. of trades: 131
Average gain per trade: 1.05%
Win ratio: 82%
Profit factor: 3
CAGR: 5.3% (assuming no leverage)
Exposure/time in the market: 15%
Risk-adjusted return: 34% (CAGR divided by time spent in the market (0.15))
Max. drawdown: -26%

The equity curve (log scale):

A portfolio equity line chart for a long momentum strategy on the Nasdaq (QQQ), showing consistent capital growth from $100,000 in 1999 to an ending capital of $447,276 by 2025 — Long-term equity curve of a QQQ momentum strategy, demonstrating the compounding potential of high-quality trading strategies for sale

Order by clicking here (check for strategy no.14):

Once you have paid you can download the strategy on this link.

Strategy 15: Short swing trade in TLT (bonds)

The strategy has two variables for entry and exits after n days. Backtested on the ETF that tracks bonds (TLT).

This strategy was our monthly Trading Edge for December 2021.

Statistics and figures (TLT) – including commissions and slippage of 0.03% per trade:

No. of trades: 211
Average gain per trade: 0.47%
Win ratio: 12%
Profit factor: 1.8
CAGR: 4.3% (assuming no leverage)
Exposure/time in the market: 26%
Risk-adjusted return: 16% (CAGR divided by time spent in the market (0.26))
Max. drawdown: -13%

The equity curve (log scale):

A long-term portfolio equity line chart for a short swing trade strategy in TLT bonds, showing growth from $100,000 in 2003 to an ending capital of $264,196 by 2025. — Backtested results of a tactical short swing strategy for the TLT bond ETF, highlighting the potential for profit in varying market conditions.

Order by clicking here (check for strategy no.15):

Once you have paid you can download the strategy on this link.

Strategy 16: Long swing trade in XLU (utilities)

The strategy has two variables for entry and exit after n days. Backtested on the ETF that tracks utilities (XLU).

This strategy was our monthly Trading Edge for January 2022.

Statistics and figures (XLU) – including commissions and slippage of 0.03% per trade:

No. of trades: 158
Average gain per trade: 0.72%
Win ratio: 62%
Profit factor: 1.9
Annual returns (CAGR): 4.3% (assuming no leverage)
Exposure/time in the market: 14%
Risk-adjusted returns: 30%
Max. drawdown: -17%

The equity curve (log scale):

A portfolio equity line chart for a long swing trade strategy using the XLU utilities ETF, showing consistent growth from $100,000 in 2000 to an ending capital of $311,743 by 2025. — 25-year backtest of a utilities sector swing strategy, showcasing the defensive growth potential of trading strategies for sale.

Order by clicking here (check for strategy no.16):

Once you have paid you can download the strategy on this link.

Strategy 17: Long volatility swing trade in SPY (S&P 500)

The strategy has two variables for entry and one for exit. The strategy is a volatility long strategy and about 65% of the trades enter on a day where the close is higher than the previous close, even high RSI. Backtested on the ETF that tracks S&P 500 (SPY).

This strategy was our monthly Trading Edge for February 2022.

Statistics and figures (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 363
Average gain per trade: 0.4%
Win ratio: 75%
Profit factor: 2.1
Annual returns (CAGR): 4.5% (assuming no leverage)
Exposure/time in the market: 12%
Risk-adjusted return: 36% (CAGR divided by time spent in the market (0.12))
Max. drawdown: -19%

The equity curve (log scale):

A long-term portfolio equity line chart for a long volatility swing trade strategy on the SPY (S&P 500), showing growth from $100,000 in 1993 to a final capital of $426,404 by 2025 — 30-year backtest of a volatility-based swing strategy for the S&P 500, illustrating the stability offered by professional trading strategies for sale

Order by clicking here (check for strategy no.17):

Once you have paid you can download the strategy on this link.

Strategy 18: Overnight long trade in SPY (S&P 500)

The strategy has three variables for entry and one for exit. Entry is at the close and the exit is at the close the next day. Backtested on the ETF that tracks S&P 500 (SPY).

This strategy was our monthly Trading Edge for March 2022.

Statistics and figures (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 374
Average gain per trade: 0.28%
Win ratio: 60%
Profit factor: 1.6
CAGR: 3.1% (assuming no leverage)
Exposure/time in the market: 5%
Risk-adjusted returns: 68%
Max. drawdown: -16%

The equity curve (log scale):

A portfolio equity curve showing the results of an overnight long trading strategy on the SPY S&P 500 ETF from 1993 to 2025, reaching a final capital value of $309,278. — 30-year backtest of an overnight trading edge in the S&P 500, demonstrating the historical reliability of specialized trading strategies for sale

Order by clicking here (check for strategy no.18):

Once you have paid you can download the strategy on this link.

Strategy 19: Short Swing Strategy Semiconductors SMH

The strategy has two variables for both short entry and short covering.

The strategy works well for SPY (S&P 500) and IWM (Russell 2000) as well.

This strategy was our monthly Trading Edge for May 2024.

Statistics and figures (SMH) – including commissions and slippage of 0.03% per trade:

No. of trades: 109
Average gain per trade: 0.79%
Win ratio: 75%
Profit factor: 2.4
Annual returns (CAGR): 3.5% (assuming no leverage)
Exposure/time in the market: 3%
Risk-adjusted return: 110% (CAGR divided by time spent in the market (0.03))
Max. drawdown: -12%

The equity curve (log scale):

A portfolio equity line chart for a short swing trading strategy on the SMH semiconductor ETF, showing growth from $100,000 in 2001 to a final capital value of $200,398 by 2025 — 24-year backtest of a tactical short swing strategy for semiconductors, illustrating how high-quality trading strategies for sale can profit from sector-specific volatility

Order by clicking here (check for strategy no.19):

Once you have paid you can download the strategy on this link.

Strategy 20: Overnight long trade in SPY (S&P 500)

The strategy has three variables for entry (seasonal trading strategy) and one for the exit. Entry is at the open and the exit is at the close the next day. Backtested on the ETF that tracks S&P 500 (SPY).

This strategy was our monthly Trading Edge for May 2022.

Statistics and figures (SPY): – including commissions and slippage of 0.03% per trade

No. of trades: 318
Average gain per trade: 0.37%
Win ratio: 62%
Profit factor: 2
Annual returns (CAGR): 3.5%
Exposure/time in the market: 4%
Risk-adjusted return: 90% (CAGR divided by time spent in the market (0.04))
Max. drawdown: -8%

The equity curve (log scale):

A long-term portfolio equity line chart showing a consistent upward trajectory from $100,000 in the early 2000s to a final value of $240,424 by 2026. — Backtested results demonstrating the steady capital appreciation possible when utilizing professional trading strategies for sale.

Order by clicking here (check for strategy no.20):

Once you have paid you can download the strategy on this link.

Strategy 21: Long swing trade in QQQ (Nasdaq)

The strategy has three variables for entry and one for exit. Entry is at the close and the exit is at the close one or more trading days later. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

This strategy was our monthly Trading Edge for June 2022.

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 189
Average gain per trade: 0.75%
Win ratio: 72%
Profit factor: 2.1
Annual returns (CAGR): 6.0% (assuming no leverage)
Exposure/time in the market: 12%
Risk-adjusted return: 49%
Max. drawdown: -19%

The equity curve (log scale):

A portfolio equity line chart for a long swing trade strategy on the Nasdaq (QQQ), showing growth from $100,000 in 2004 to a final capital of $412,664 by 2025. — 21-year backtest of a QQQ long swing strategy, illustrating the long-term capital appreciation potential of premium trading strategies for sale.

Order by clicking here (check for strategy no.21):

Once you have paid you can download the strategy on this link.

Strategy 22: Long overnight trade in QQQ/SPY (Nasdaq/SP500)

The strategy has two variables for entry and one for exit. Entry is at the close and the exit is at the close of the next trading day. You hold it for 24 hours only. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

This strategy was our monthly Trading Edge for July 2022.

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 431
Average gain per trade: 0.55%
Win ratio: 61%
Profit factor: 1.9
Annual returns (CAGR): 9% (assuming no leverage)
Exposure/time in the market: 6%
Risk-adjusted return: 135%
Max. drawdown: -12%

The equity curve (log scale QQQ):

A long-term portfolio equity line chart for an overnight trading strategy combining QQQ and SPY, showing capital growth from $100,000 in 2000 to a final value of $1,100,591 by 2025. — 25-year backtest of a multi-asset overnight trading strategy, highlighting the significant growth potential available through professional trading strategies for sale.

Order by clicking here (check for strategy no.22):

Once you have paid you can download the strategy on this link.

Strategy 23: Short swing trade XLP

The strategy has five variables for entry and two for exit. Entry is at the close and the average holding time is 2.7 days. Backtested on the ETF that tracks consumer staples (XLP).

This strategy was our monthly Trading Edge for August 2022.

Statistics and figures (XLP) – including commissions and slippage of 0.03% per trade:

No. of trades: 210
Average gain per trade: 0.3%
Win ratio: 69%
Profit factor: 2.1
Annual returns (CAGR): 2.1% (assuming no leverage)
Exposure/time in the market: 6%
Risk-adjusted return: 36%
Max. drawdown: -6%

The equity curve (log scale):

A portfolio equity line chart for a short swing trading strategy on the XLP Consumer Staples ETF — 25-year backtest of a tactical short swing strategy for consumer staples, demonstrating the diversification benefits of professional trading strategies for sale.

Order by clicking here (check for strategy no.23):

Once you have paid you can download the strategy on this link.

Strategy 24: Long swing trade XLV/XLU

The strategy has three variables for entry and two for exit. It’s a seasonal strategy. Entry is at the open and exit is after 4 or 5 days. Backtested on the ETF that tracks healthcare stocks (XLV).

This strategy was our monthly Trading Edge for September 2022.

Statistics and figures (XLU) – including commissions and slippage of 0.03% per trade:

No. of trades: 174
Average gain per trade: 0.5%
Win ratio: 62%
Profit factor: 2
Annual returns (CAGR): 3.1% (assuming no leverage)
Exposure/time in the market: 9%
Max. drawdown: -12%
Risk-adjusted return: 32% (CAGR divided by time spent in the market (0.09))

The equity curve (log scale – XLU – dividends included):

A portfolio equity line chart for a long swing trade strategy combining Healthcare (XLV) and Utilities (XLU) ETFs, showing capital growth from $100,000 in 1999 to a final value of $253,898 by 2025. — 26-year backtest of a defensive sector swing strategy, showcasing the steady growth potential of diversified trading strategies for sale.

Order by clicking here (check for strategy no.24):

Once you have paid you can download the strategy on this link.

Strategy 25: Long and short swing trade TLT (Long-Term Treasuries)

Both long and short are based on seasonal anomaly strategies. Entry is at the close and exit is after a few days. Backtested on the ETF that tracks bonds (TLT).

This strategy was our monthly Trading Edge for October 2022.

Statistics and figures (TLT) – including commissions and slippage of 0.03% per trade:

No. of trades: 440
Average gain per trade: 0.4%
Win ratio: 62%
Profit factor: 1.7
Annual returns (CAGR): 9.2% (assuming no leverage)
Exposure/time in the market: 37%
Risk-adjusted returns: 45%
Max. drawdown: -18%

The equity curve (log scale):

A long-term portfolio equity line chart for a combined long and short swing trade strategy in TLT bonds, showing explosive growth from $100,000 in 2003 to a final capital of $756,254 by 2025 — 22-year backtest of a comprehensive long-short bond swing strategy, illustrating the massive compounding power of professional trading strategies for sale

Order by clicking here (check for strategy no. 25):

Once you have paid you can download the strategy on this link.

Strategy 26: Long QQQ volatility strategy

This strategy was our monthly Trading Edge for June 2025.

(Strategy 26 was previously a DAX strategy. The strategy has been moved to future strategies.)

Statistics and figures (QQQ – commissions and slippage of 0.03% trade is included):

No. of trades: 324
Average gain per trade: 0.95%
Win ratio: 75%
Profit factor: 2.3
CAGR: 12.6% (assuming no leverage)
Exposure/time in the market: 20%
Risk-adjusted return: 62% (annual return divided by time spent in the market(0.2))
Max drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart for a long volatility strategy on the Nasdaq (QQQ), showing significant growth from $100,000 in 2000 to a final capital of $2,518,721 by 2025. — 25-year backtest of a Nasdaq volatility strategy, demonstrating the exceptional wealth-building potential of high-performance trading strategies for sale.

Order by clicking here (check for strategy no. 26):

Once you have paid you can download the strategy on this link.

Strategy 27: Long holiday swing trade S&P 500 (SPY)

This strategy was our monthly Trading Edge for December 2022. Backtested on the ETF that tracks S&P 500 (SPY).

Statistics and figures (SPY) – including commissions and slippage of 0.03 per trade:

No. of trades: 123
Average gain per trade: 0.3%
Win ratio: 60%
Profit factor: 2
Annual returns (CAGR): 1.2% (assuming no leverage)
Exposure/time in the market: 2%
Risk-adjusted return: 60%
Max. drawdown: -7%

The equity curve (log scale):

A portfolio equity line chart for a long holiday-based swing trading strategy on the SPY S&P 500 ETF, showing growth from $100,000 in 1993 to a final value of $165,278 by 2025 — 32-year backtest of a seasonal holiday trading strategy for the S&P 500, highlighting the consistent edge found in specialized trading strategies for sale

Order by clicking here (check for strategy no. 27):

Once you have paid you can download the strategy on this link.

Strategy 28: End of Month Trading Strategy for Equity ETFs

This strategy was our monthly Trading Edge for February 2026. The strategy holds the position for one month.

Statistics and figures (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 128
Average gain per trade: 1.5%
Win ratio: 72%
Profit factor: 2.5
Annual returns (CAGR): 5.6%
Exposure/time in the market: 32%
Risk-adjusted return: 17%
Max. drawdown: -16%

The equity curve (log scale):

A portfolio equity line chart showing the backtested results of an end-of-month trading strategy for equity ETFs, growing from $100,000 in 1993 to a final value of $611,402 by 2025. — 32-year backtest of a systematic end-of-month trading edge, demonstrating the steady capital appreciation provided by professional trading strategies for sale.

Order by clicking here (check for strategy no. 28):

Once you have paid you can download the strategy on this link

Strategy 29: Long swing trade real estate stocks (VNQ)

This strategy was our monthly Trading Edge for February 2023. Backtested on the ETF that tracks real estate stocks (VNQ).

Statistics and figures (VNQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 375
Average unleveraged gain per trade: 0.82%
Win ratio: 61%
Profit factor: 2.1
Annual returns (CAGR): 14.5% (assuming no leverage)
Exposure/time in the market: 51%
Risk-adjusted return:28%
Max. drawdown: -33%

The equity curve (log scale):

A long-term portfolio equity line chart for a real estate swing trading strategy using the VNQ ETF, showing capital growth from $100,000 in 2004 to a final value of $1,237,090 by 2025 — 21-year backtest of a systematic real estate swing strategy, showcasing the million-dollar compounding potential of professional trading strategies for sale

Order by clicking here (check for strategy no. 29):

Once you have paid you can download the strategy on this link

Strategy 30: Long swing trade Treasury bonds (TLT)

This strategy was our monthly Trading Edge for March 2023. Backtested on the ETF that tracks bonds (TLT).

Statistics and figures (TLT) – including commissions and slippage of 0.03% per trade:

No. of trades: 242
Average unleveraged gain per trade: 0.31%
Win ratio: 69%
Profit factor: 2
Annual returns (CAGR): 3.3% (assuming no leverage)
Exposure/time in the market: 13%
Risk-adjusted return: 24%
Max. drawdown: -9%

The equity curve (log scale):

A portfolio equity line chart for a long momentum trading strategy on the Nasdaq (QQQ), showing consistent growth from $100,000 in late 1999 to a final value of $447,276 by 2025. — 25-year backtest of a QQQ momentum strategy, demonstrating the robust capital appreciation available through professional trading strategies for sale.

Order by clicking here (check for strategy no. 30):

Once you have paid you can download the strategy on this link

Strategy 31: Trading Volume Strategy (Nasdaq 100)

This strategy was our monthly Trading Edge for January 2026.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

The strategy buys the next open after the signal.

Statistics and figures (QQQ), including commissions of 0.03% per trade:

No. of trades: 225
Average unleveraged gain per trade: 1.4%
Win ratio: 79%
Profit factor: 3.5
CAGR: 12.5% (assuming no leverage)
Exposure/time in the market: 10%
Risk-adjusted returns: 127%
Max. drawdown: -19%

The equity curve (log scale):

A long-term portfolio equity line chart for a trading volume strategy on the Nasdaq 100, showing exponential growth from $100,000 in 2000 to a final capital of $2,337,798 by 2025. — 25-year backtest of a volume-based Nasdaq 100 strategy, illustrating the massive compounding potential of data-driven trading strategies for sale.

Order by clicking here (check for strategy no. 31):

Once you have paid you can download the strategy on this link

Strategy 32: Long swing trade GLD (gold)

This strategy was our monthly Trading Edge for May 2023. Backtested on the ETF that tracks gold (GLD). Gold is a useful strategy diversifier, but very hard to trade as strategies frequently “break down”.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Statistics and figures (GLD) – including commissions and slippage of 0.03% per trade:

No. of trades: 179
Average unleveraged gain per trade: 0.5%
Win ratio: 71%
Profit factor: 2.1
Annual returns (CAGR): 4.4% (assuming no leverage)
Exposure/time in the market: 10%
Risk-adjusted return: 42%
Max. drawdown: -14%

The equity curve (log scale):

A portfolio equity line chart for a long swing trading strategy on the GLD Gold ETF, showing capital growth from $100,000 in late 2004 to a final value of $237,659 by 2025. — 20-year backtest of a systematic gold swing strategy, highlighting the steady wealth preservation and growth potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 32):

Once you have paid you can download the strategy on this link.

Strategy 33: (Bundle 1) S&P 500 Trading Strategies (SPY Bundle)

Please check our separate landing page for strategy bundles. Trading rules in plain English and code for Amibroker, Tradestation/Multicharts, and TradingView. Eligible as a “bundle pick” for the memberships.

Published spring 2022.

Strategy 34: (Bundle 2) Volatility Trading Strategies (SPY Bundle)

Please check our separate landing page for strategy bundles. Eligible as a “bundle pick” for the memberships.

Backtested on the ETF that tracks S&P 500 (SPY).

Published spring 2022.

Strategy 35: (Bundle 3) Short Selling Strategies (Bundle)

The strategies are backtested on SPY, SMH, and XLP.

Published spring 2022.

Strategy 36: (Bundle 4) Seasonal Strategies (The Holiday Trading Bundle for S&P 500/SPY)

Please check our separate landing page for strategy bundles. Trading rules and plain English and code for Amibroker. Not eligible for any of the membership strategy selections. Backtested on SPY.

Published autumn 2022.

Strategy 37: (40+) Futures Strategies

Please check our separate landing page for futures trading strategies. Not eligible for any of the membership strategy selections.

Strategy 38: RSI Trading Strategy (S&P 500- SPY)

A short-term trading strategy based on the RSI indicator. Backtested on the ETF that tracks S&P 500 (SPY).

Published first time around 2016/17.

The strategy has code for Amibroker, Tradestation/Easy Langauge, and TradingView/Pinescript.

Statistics and figures (SPY – S&P 500) – including commissions and slippage of 0.03% per trade:

No. of trades: 402
Average unleveraged gain per trade: 0.6%
Win ratio: 73%
Profit factor: 2.3
Annual returns (CAGR): 7.9% (assuming no leverage)
Exposure/time in the market: 13%
Risk-adjusted return: 57% (CAGR divided by time spent in the market (0.13))
Max. drawdown: -16%

The equity curve (log scale):

A portfolio equity line chart for a short swing trading strategy on the Semiconductor ETF (SMH), showing capital growth from $100,000 in late 2001 to a final value of $200,398 by early 2025. — 23-year backtest of a tactical short swing strategy for semiconductors, illustrating the diversification potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 38):

Once you have paid you can download the strategy on this link.

Strategy 39: Stochastic Indicator Trading Strategy (S&P 500 – SPY)

A short-term trading strategy based on the Stochastic indicator. Backtested on the ETF that tracks S&P 500 (SPY).

Published first time around 2016/17.

The strategy has code for Amibroker, Tradestation/Easy Langauge, and TradingView/Pinescript.

Statistics and figures (SPY – S&P 500) – including commissions and slippage of 0.03% per trade:

No. of trades: 397
Average unleveraged gain per trade: 0.5%
Win ratio: 72%
Profit factor: 2.2
CAGR/annual returns: 6.2%(assuming no leverage)
Exposure/time in the market: 13%
Risk-adjusted return: 47% (CAGR divided by time spent in the market (0.13))
Max. drawdown: -20%

The equity curve (log scale):

A portfolio equity line chart for a trading strategy based on the Stochastic indicator for the SPY S&P 500 ETF, showing growth from $100,000 in 1993 to a final value of $1,518,145 by 2025. — 32-year backtest of a Stochastic-based mean reversion strategy for the S&P 500, illustrating the high-alpha potential of quantitative trading strategies for sale.

Order by clicking here (check for strategy no. 39):

Once you have paid you can download the strategy on this link.

Strategy 40: MACD (Histogram) Trading Strategy (Nasdaq 100 – QQQ)

A short-term trading strategy that is based on the MACD indicator. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published spring 2023.

The strategy has code for Amibroker, Tradestation/Easy Langauge, and TradingView/Pinescript.

Statistics and figures (QQQ – Nasdaq 100) – including commissions and slippage of 0.03% per trade:

No. of trades: 121
Average unleveraged gain per trade: 1.3%
Win ratio: 80%
Profit factor: 4.5
Annual returns (CAGR): 6.1% (assuming no leverage)
Exposure/time in the market: 6%
Risk-adjusted return: 103% (CAGR divided by time spent in the market (0.16))
Max. drawdown: -20%

The equity curve (log scale):

A portfolio equity line chart for a trading strategy based on the MACD Histogram for the QQQ Nasdaq 100 ETF, showing capital growth from $100,000 in late 1999 to a final value of $478,555 by 2025. — 26-year backtest of a systematic MACD Histogram strategy for the Nasdaq 100, demonstrating the reliable growth found in verified trading strategies for sale.

Order by clicking here (check for strategy no. 40):

Once you have paid you can download the strategy on this link.

Strategy 41: Bollinger Band Trading Strategy (S&P 500 – SPY)

A short-term trading strategy that is based on Bollinger Bands. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Statistics and figures (SPY – S&P 500): – including commissions and slippage of 0.03% per trade

No. of trades: 568
Average unleveraged gain per trade: 0.4%
Win ratio: 70%
Profit factor: 1.7
CAGR: 6.5% (assuming no leverage)
Exposure/time in the market: 20%
Risk-adjusted return: 16% (CAGR divided by time spent in the market (0.2))
Max. drawdown: -18%

The equity curve (log scale):

A portfolio equity line chart for a Bollinger Band trading strategy on the SPY S&P 500 ETF, showing capital growth from $100,000 in 1993 to a final value of $1,196,006 by early 2025. — 32-year backtest of a systematic Bollinger Band mean reversion strategy, showcasing the institutional-grade performance of premium trading strategies for sale.

Order by clicking here (check for strategy no. 41):

Once you have paid you can download the strategy on this link.

Strategy 42: 3 Trend following Strategies (S&P 500/SPY Bundle)

The three strategies have different trading rules for entry but the same rules for exit. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published 2021/2022.

Statistics and figures (S&P 500) – including slippage and commissions of 0.03% per trade:

No. of trades: 22
Average unleveraged gain per trade: 31.9%
Win ratio: 77%
Profit factor: 6
CAGR: 7.6% vs 7.2% for Buy&Hold (assuming no leverage and no reinvested dividends – cash index)
Exposure/time in the market: 81%
Risk-adjusted return: 9.4% (CAGR divided by time spent in the market (0.81))
Max. drawdown: -35%

The equity curve when all 3 strategies are traded as a portfolio of strategies (log scale):

A long-term portfolio equity line chart showing the performance of a bundle of three trend-following strategies for the S&P 500 (SPY), with capital growing from $100,000 in 1960 to a final value of $13,340,310 by 2025. — 65-year backtest of a multi-strategy trend-following bundle for the S&P 500, demonstrating the massive compounding power of professional trading strategies for sale.

Order by clicking here (check for strategy no. 42):

Once you have paid you can download the strategy on this link.

Strategy 43: 3 Swing Trading Strategies (QQQ Bundle)

The strategies trade from the long side. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

The bundle is not eligible for any of the membership strategy selections.

Published early 2023.

Statistics and figures (QQQ) – including commissions and slippage of 0.03% per trade :

No. of trades: 492
Average unleveraged gain per trade: 0.75%
Win ratio: 71%
Profit factor: 2.3
Annual returns (CAGR): 14.3% (assuming no leverage)
Exposure/time in the market: 29%
Risk-adjusted return: 49% (CAGR divided by time spent in the market (0.29))
Max. drawdown: -31%

The equity curve when all three strategies are traded as a portfolio of strategies (log scale):

A long-term portfolio equity line chart for a bundle of three swing trading strategies on the QQQ Nasdaq 100 ETF, showing massive capital growth from $100,000 in late 1999 to a final value of $4,047,862 by early 2025. — 26-year backtest of a multi-strategy QQQ swing trading bundle, illustrating the superior compounding power of professional trading strategies for sale.

Annual returns:

A comprehensive performance table showing monthly and annual percentage returns for swing trading strategies from 1999 to 2025, featuring a 15.5% return in 2025 and an average monthly gain of 1.7% in January. — Yearly and monthly performance breakdown (1999–2025) for a diversified portfolio of trading strategies for sale, demonstrating consistent profitability across decades of market cycles.

Order by clicking here (check for strategy no. 43):

Once you have paid you can download the strategy on this link.

Strategy 44: MACD Indicator Trading Strategy (Nasdaq 100 – QQQ)

The strategy uses the MACD indicator in a rather creative way. The strategy is presented as strategy #3 in our MACD strategy video. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published spring 2023 (old strategy first mentioned on this blog in 2015).

The strategy has code for Amibroker, Tradestation/Easy Langauge, and TradingView/Pinescript.

Statistics and figures (Nasdaq- 100 – QQQ) including commissions and slippage of 0.03% per trade:

No. of trades: 181
Average unleveraged gain per trade: 1%
Win ratio: 77%
Profit factor: 3
CAGR: 7.2% (assuming no leverage and no dividends)
Exposure/time in the market: 9%
Risk-adjusted return: 81% (CAGR divided by time spent in the market (0.09))
Max. drawdown: -11%

The equity curve (log scale):

A portfolio equity line chart for an MACD indicator trading strategy on the QQQ Nasdaq 100 ETF, showing capital growth from $100,000 in late 1999 to a final value of $737,143 by early 2026. — 26-year backtest of a systematic MACD strategy for the Nasdaq 100, illustrating the reliable long-term compounding available through professional trading strategies for sale.

Order by clicking here (check for strategy no. 44):

Once you have paid, you can download the strategy on this link.

Strategy 45: Heikin Ashi Trading Strategy (S&P 500 – SPY)

The Heikin Ashi strategy uses monthly bars and is thus a long-term trend-following strategy. Backtested on the ETF that tracks S&P 500 (SPY).

Only available in Amibroker code.

Published spring 2023.

Statistics and figures (S&P 500) – including commissions and slippage of 0.03% per trade:

No. of trades: 84
Average unleveraged gain per trade: 4.6%
Win ratio: 50%
Profit factor: 3
CAGR: 5.1% (assuming no leverage and no dividends)
Exposure/time in the market: 66%
Risk-adjusted return: 7.5% (CAGR divided by time spent in the market (0.66))
Max. drawdown: -29%

The equity curve (log scale) – monthly bars:

A long-term portfolio equity line chart for a Heikin Ashi trading strategy on the SPY S&P 500 ETF, showing growth from $100,000 in 1960 to a final value of $2,705,452 by early 2025. — 65-year backtest of a systematic Heikin Ashi strategy for the S&P 500, demonstrating the high-performance potential of institutional-grade trading strategies for sale.

Order by clicking here (check for strategy no. 45):

Once you have paid, you can download the strategy on this link.

Strategy 46: LL & LH (Lower Lows & Lower Highs) Trading Strategy (Semis – SMH)

A mean reversion strategy. Backtested on the ETF that tracks semiconductors (SMH). Works on QQQ and SPY as well.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2021.

Statistics and figures (Semiconductors – SMH) – including commissions and slippage of 0.03% per trade:

No. of trades: 236
Average unleveraged gain per trade: 1%
Win ratio: 74%
Profit factor: 2.4
Annual returns (CAGR): 9.8% (assuming no leverage and no dividends)
Exposure/time in the market: 13%
Risk-adjusted return: 73% (CAGR divided by time spent in the market (0.13))
Max. drawdown: -48%

The equity curve (log scale):

A portfolio equity line chart for the Lower Lows & Lower Highs trading strategy, showing capital growth from approximately $100,000 in 2001 to a final value of $1,027,350 by early 2025. — 24-year backtest of the systematic Lower Lows & Lower Highs strategy, demonstrating the robust wealth-building potential of specialized trading strategies for sale.

Order by clicking here (check for strategy no. 46):

Once you have paid you can download the strategy on this link.

Strategy 47: Combining long and short strategies

Not eligible for any of the membership strategy selections.

This product offers a steep discount for two bundles: Strategy Bundle 1 (long strategies) and Strategy Bundle 3 (short strategies). Below are the performance metrics of combining both bundles for the following backtested assets:

Statistics and figures (S&P 500, (SPY/@ES), Consumer staples (XLP), and Semiconductors (SMH)) – including slippage and commissions if 0.03% per trade:

No. of trades: 725 (from 2005)
Average unleveraged gain per trade: 0.53%
Win ratio: 70%
Profit factor: 1.8
Annual returns (CAGR): 16% (assuming no leverage and no dividends)
Exposure/time in the market: 35%
Risk-adjusted return: 47% (CAGR divided by time spent in the market (0.35))
Max. drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart showing the combined performance of long and short trading strategies, with capital growing from $100,000 in 2005 to a final value of $2,642,390 by early 2026. — 21-year backtest demonstrating the powerful compounding and risk-adjusted returns achieved by combining long and short trading strategies for sale.

Order by clicking here (check for strategy no. 47):

Once you have paid you can download the strategy on this link.

Strategy 48: Bitcoin Trading Strategy (3 Strategies In One Bundle)

The three strategies are diverse: One strategy is a mean reversion strategy, a seasonal trade, and a momentum strategy.

The strategies come with code for Tradestation, TradingView/Pinescript, and Amibroker.

PS! Bitcoin trades around the clock, and thus, settings might influence the results, not to mention commissions, which are hard to predict. Bitcoin has historically suffered VERY deep drawdowns (also this backtest). Very few can stomach that.

Published in 2021 and 2022.

Statistics and figures (All 3 strategies as one portfolio of strategies):

No. of trades: 163 (from 2015)
Average unleveraged gain per trade: 5.7%
Win ratio: 47%
Profit factor: 2
Annual returns (CAGR): 100 (assuming no leverage)
Exposure/time in the market: 60%
Risk-adjusted return: 168% (CAGR divided by time spent in the market (0.6))
Max. drawdown: -49% (!!!)

The equity curve (log scale – all 3 strategies as one portfolio of strategies – 10,000 compounded):

A portfolio equity line chart for a Bitcoin trading strategy showing exponential capital growth from approximately $10,000 in 2015 to a final value of $6,690,855 by early 2026. — 11-year backtest of a systematic Bitcoin trading strategy, showcasing the extreme compounding potential found in high-alpha trading strategies for sale.

Order by clicking here (check for strategy no. 48):

Once you have paid you can download the strategy on this link.

Strategy 49: Buy the dip Trading Strategy (S&P 500 – SPY)

Mean reversion based on bullish long term trends and pullbacks. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Statistics and figures (S&P 500 – SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 284
Average unleveraged gain per trade: 0.4%
Win ratio: 71%
Profit factor: 2.4
CAGR: 3.4% (assuming no leverage)
Exposure/time in the market: 9%
Risk-adjusted return: 34% (CAGR divided by time spent in the market (0.09))
Max. drawdown: -14%

The equity curve (log scale):

A portfolio equity line chart for a "Buy the Dip" trading strategy, showing capital growth from $100,000 in early 1993 to a final value of $431,382 by early 2025. — 32-year backtest of a systematic Buy the Dip strategy, demonstrating the steady compounding power of high-quality trading strategies for sale.

Order by clicking here (check for strategy no. 49):

Once you have paid you can download the strategy on this link.

Strategy 50: Super indicator Trading Strategy (S&P 500 – SPY)

The SuperTrend Indicator is a weekly trend-following strategy (meaning weekly bars).

We have the trading rules in plain English and code for Amibroker (no code for Tradestation/Easy Langauge).

Backtested on the ETF that tracks S&P 500 (SPY).

Published late 2022.

Statistics and figures (S&P 500):

No. of trades: 39
Average unleveraged gain per trade: 10.8% (18.4% for winners and -4.2% for losers)
Win ratio: 66%
Profit factor: 4
CAGR: 5.9% (assuming no leverage and no dividends)
Exposure/time in the market: 62%
Risk-adjusted return: 9.5% (CAGR divided by time spent in the market (0.62))
Max. drawdown: -24%

The equity curve (log scale):

A long-term portfolio equity line chart for an End of Month trading strategy applied to Equity ETFs, showing capital growth from $100,000 in early 1993 to a final value of $611,402 by early 2025. — 32-year backtest of a systematic End of Month strategy for Equity ETFs, highlighting the consistent wealth-building potential of specialized trading strategies for sale.

Order by clicking here (check for strategy no. 50):

Once you have paid you can download the strategy on this link.

Strategy 51: Money Flow Index Trading Strategy (S&P 500 – SPY)

The money flow index (MFI) is a momentum indicator that measures the flow of money into and out of a security over a specified period of time by combining price and volume data. It oscillates between 0 and 100 and shows overbought and oversold conditions in the market. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (S&P 500 – SPY) Including slippage and commissions of 0.03% per trade:

No. of trades: 895
Average unleveraged gain per trade: 0.3%
Win ratio: 72%
Profit factor: 1.7
Annual returns (CAGR): 7.5% (assuming no leverage and no dividends)
Exposure/time in the market: 28%
Risk-adjusted return: 26% (CAGR divided by time spent in the market (0.28))
Max. drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart for the Money Flow Index (MFI) trading strategy, showing capital growth from $100,000 in early 1993 to a final value of $1,494,891 by early 2025. — 32-year backtest of a systematic Money Flow Index strategy, illustrating the superior compounding power of volume-weighted trading strategies for sale.

Order by clicking here (check for strategy no. 51):

Once you have paid you can download the strategy on this link.

Strategy 52: Momentum Trading Strategy (S&P 500 – SPY)

The momentum strategy has flexible rules that make it useful for stocks and crypto. The equity curve below is based on the S&P 500.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published autumn 2022.

Performance metrics (S&P 500):

No. of trades: 43
Average unleveraged gain per trade: 10.1%
Win ratio: 67%
Profit factor: 7
Annual returns (CAGR): 5.9% (assuming no leverage and no dividends)
Exposure/time in the market: 65%
Risk-adjusted return: 9% (CAGR divided by time spent in the market (0.67))
Max. drawdown: -25%

The equity curve (log scale):

A portfolio equity line chart for an RSI trading strategy on the SPY S&P 500 ETF, showing capital growth from $100,000 in early 1993 to a final value of $1,377,473 by early 2025. — 32-year backtest of a systematic RSI momentum strategy for the S&P 500, illustrating the long-term wealth-building potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 52):

Once you have paid you can download the strategy on this link.

Strategy 53: Short-Term Pullback Strategy For S&P 500 (SPY)

A strategy that tries to capture a pullback from new highs. Commissions and slippage of 0.03% are included for each trade.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

This was our trading edge for March 2024.

Performance metrics (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 269
Average unleveraged gain per trade: 0.5%
Win ratio: 72%
Profit factor: 2.5
Annual returns (CAGR): 4.4% (assuming no leverage and no dividends)
Exposure/time in the market: 11%
Risk-adjusted return: 37% (CAGR divided by time spent in the market (0.11))
Max. drawdown: -12%

The equity curve (log scale):

A long-term portfolio equity line chart for a Short-Term Pullback Strategy for the S&P 500, showing capital growth from $100,000 in early 1993 to a final value of $410,403 by early 2025. — 32-year backtest of a systematic S&P 500 Short-Term Pullback strategy, demonstrating the reliable wealth-building potential of specialized trading strategies for sale.

Order by clicking here (check for strategy no. 53):

Once you have paid you can download the strategy on this link.

Strategy 54: 6 Larry Connors Trading Strategies (S&P 500 – SPY)

We compiled 6 Larry Connors strategies into one product for the price of one strategy. We added a variable. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published in autumn 2021.

Once you have paid, you can download the 6 strategies on this link.

Strategy 55: IBS Trading Strategy (Nasdaq – QQQ)

The strategy is based on the IBS indicator. Backtested on the ETF that tracks Nasdaq 100 (QQQ), but it works on other stock ETFs.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023 (but previously published in 2016/17).

Performance metrics (Nasdaq – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 525
Average unleveraged gain per trade: 0.65%
Win ratio: 68%
Profit factor: 2.2
Annual returns (CAGR): 13.3% (assuming no leverage and no dividends – 3.5% better than Buy & Hold)
Exposure/time in the market: 26%
Risk-adjusted return: 50% (CAGR divided by time spent in the market (0.26))
Max. drawdown: -41% (Buy & Hold 82%)

The equity curve (log scale):

A long-term portfolio equity line chart for the IBS trading strategy, showing capital growth from $100,000 in early 1999 to a final value of $3,132,893 by early 2026. — 27-year backtest of a systematic IBS strategy, showcasing the exceptional compounding power and high-alpha potential of professional trading strategies for sale

Order by clicking here (check for strategy no. 55):

Once you have paid you can download the strategy on this link.

Strategy 56: Gold (GLD) Seasonal Trend Strategy

The strategy trades GLD on a certain trading day when the trend is strong.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

This was the trading edge for September 2024.

Performance metrics (GLD) – including commissions and slippage of 0.03% per trade:

No. of trades: 87
Average unleveraged gain per trade: 0.72% (1.4% for winners – minus 1% for losing trades)
Win ratio: 72%
Profit factor: 3
CAGR: 3.1% (assuming no leverage)
Exposure/time in the market: 4.1%
Risk-adjusted return: 76% (CAGR divided by time spent in the market (0.04))
Max. drawdown: -6%

The equity curve (log scale):

A portfolio equity line chart for a seasonal trend trading strategy applied to Gold (GLD), showing capital growth from $100,000 in late 2004 to a final value of $185,815 by early 2026. — 21-year backtest of a systematic Gold seasonal trend strategy, demonstrating the steady capital appreciation possible with specialized trading strategies for sale.

Order by clicking here (check for strategy no. 56):

Once you have paid you can download the strategy on this link.

Strategy 57: Coppock Trading Strategy (S&P 500/SPY)

The Coppock Curve was developed in the 1950s and is a trend-following strategy. It has historically worked for stocks and the gold price. Backtested on the ETF that tracks S&P 500 (SPY).

Only available in Amibroker code.

Published early 2023.

Performance metrics (S&P 500):

No. of trades: 13
Average unleveraged gain per trade: 44%
Win ratio: 100%
Profit factor: NA
CAGR: 6.4% (assuming no leverage and no dividends – slightly below Buy & Hold)
Exposure/time in the market: 73%
Risk-adjusted return: 8.6% (CAGR divided by time spent in the market (0.73))
Max. drawdown: -30% (Buy & Hold 55%)

The equity curve (log scale):

A long-term portfolio equity line chart for the Coppock trading strategy, showing capital growth from $100,000 in the early 1960s to a final value of $6,348,804 by early 2025. — 60-year backtest of the systematic Coppock Curve strategy, illustrating the massive compounding potential of long-term trading strategies for sale.

Order by clicking here (check for strategy no. 57):

Once you have paid you can download the strategy on this link.

Strategy 58: 200-Day Moving Average Trading Strategy (S&P 500/SPY)

We made a small twist to the 200-day moving average strategy. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (S&P 500) – including slippage and commissions of 0.03% per trade:

No. of trades: 81
Average unleveraged gain per trade: 6.4%
Win ratio: 50%
Profit factor: 2.9
Annual returns (CAGR): 6.9% (assuming no leverage and no dividends – same return as Buy & Hold)
Exposure/time in the market: 70%
Risk-adjusted return: 9.9% (CAGR divided by time spent in the market (0.7))
Max. drawdown: -22% (Buy & Hold 55%)

The equity curve (log scale):

A long-term portfolio equity line chart for the 200-Day Moving Average trading strategy, showing capital growth from $100,000 in 1960 to a final value of $8,535,194 by early 2025. — 65-year backtest of a systematic 200-Day Moving Average strategy, illustrating the massive compounding power of professional-grade trading strategies for sale

Order by clicking here (check for strategy no. 58):

Once you have paid you can download the strategy on this link.

Strategy 59: Triple RSI Trading Strategy (S&P 500 – SPY)

The strategy uses three different RSI variables plus a trend filter. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (SPY – S&P 500) – including slippage and commissions of 0.03% per trade:

No. of trades: 97
Average unleveraged gain per trade: 1.2%
Win ratio: 90%
Profit factor: 8
Annual returns (CAGR): 3.8% (assuming no leverage)
Exposure/time in the market: 5%
Risk-adjusted return: 69% (CAGR divided by time spent in the market (0.05))
Max. drawdown: -13%

The equity curve (log scale):

A long-term portfolio equity line chart for the Triple RSI trading strategy, showing capital growth from $100,000 in early 1993 to a final value of $372,221 by early 2025. — 32-year backtest of a systematic Triple RSI momentum strategy, demonstrating the steady compounding potential of data-driven trading strategies for sale.

Order by clicking here (check for strategy no. 59):

Once you have paid you can download the strategy on this link.

Strategy 60: Nasdaq Interest Rate Strategy (QQQ)

The strategy is based on interest rate levels. The strategy trades at the open the day after the signal.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

This was our monthly trading edge for August 2024.

Performance metrics:

No. of trades: 264
Average unleveraged gain per trade: 0.76%
Win ratio: 73%
Profit factor: 2.5
Annual returns (CAGR): 8.8% (assuming no leverage)
Exposure/time in the market: 16%
Risk-adjusted return: 55% (CAGR divided by time spent in the market (0.16))
Max. drawdown: -19%

The equity curve (log scale):

A portfolio equity line chart for a Nasdaq Interest Rate trading strategy, showing capital growth from $100,000 in 2003 to a final value of $589,913 by early 2026. — 23-year backtest of a systematic Nasdaq Interest Rate strategy, demonstrating the effective compounding power of macro-driven trading strategies for sale.

Order by clicking here (check for strategy no. 60):

Once you have paid you can download the strategy on this link.

Strategy 61: Rubber band Trading Strategy (Nasdaq 100 – QQQ)

Based on fast and volatile markets. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published first time in 2016/2017.

Performance metrics (Nasdaq 100 – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 277
Average unleveraged gain per trade: 1.05%
Win ratio: 70%
Profit factor: 2.2
Annual returns (CAGR): 11.2% (assuming no leverage)
Exposure/time in the market: 16%
Risk-adjusted return: 68% (CAGR divided by time spent in the market (0.16))
Max. drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart for the Rubber Band trading strategy, showing capital growth from $100,000 in early 1999 to a final value of $2,117,026 by early 2026. — 27-year backtest of the systematic Rubber Band strategy, illustrating the powerful compounding effect of mean-reversion trading strategies for sale.

Order by clicking here (check for strategy no. 61):

Once you have paid you can download the strategy on this link.

Strategy 62: Gold Weekly Momentum Strategy (GLD)

The strategy utilizes weekly bars and operates exclusively from the long side.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

The strategy was our monthly trading edge for October 2025.

Performance metrics (GLD – slippage and commission of 0.03% per trade is included):

No. of trades: 144
Average unleveraged gain per trade: 1%
Win ratio: 80%
Profit factor: 2.3
CAGR: 6.9%
Exposure/time in the market: 35%
Risk-adjusted return: 20% (CAGR divided by time spent in the market (0.35))
Max. drawdown: -24%

The equity curve (log scale):

A long-term portfolio equity line chart for the Gold Weekly Momentum Strategy, showing capital growth from $100,000 in early 2005 to a final value of $404,683 by early 2026. — 21-year backtest of a systematic Gold weekly momentum model, demonstrating the robust capital appreciation available through specialized trading strategies for sale.

Order by clicking here (check for strategy no. 62):

Once you have paid you can download the strategy on this link.

Strategy 63: Chopiness Strategy for S&P 500/Nasdaq 100

The strategy is partially based on the Choppiness Index, which determines whether the market is choppy or trending.

The strategy is available for Amibroker, Tradestation, and TradingVirew/Pinescript code. A reader provides the latter (Pinescript), so we are not responsible for the code.

(Previously, we had a momentum strategy for stocks, gold, and bonds as #63, but it has not performed well for 8 years.)

This was our monthly trading edge for June 2024.

Performance metrics: – including commissions and slippage of 0.03% per trade (QQQ):

No. of trades: 154
Average unleveraged gain per trade: 1.1%
Win ratio: 80%
Profit factor: 2.3
Annual returns (CAGR): 6.1% (assuming no leverage)
Exposure/time in the market: 6%
Risk-adjusted return: 96% (CAGR divided by time spent in the market (0.06))
Max. drawdown: -17%

The equity curve (log scale):

A long-term portfolio equity line chart for the Choppiness Index trading strategy applied to the S&P 500 and Nasdaq 100, showing capital growth from $100,000 in early 1999 to a final value of $491,663 by early 2026. — 27-year backtest of a systematic Choppiness strategy for major indices, demonstrating the consistent wealth-building potential of specialized trading strategies for sale.

Order by clicking here (check for strategy no. 63):

Once you have paid you can download the strategy on this link.

Strategy 64: Monthly momentum strategy in gold, bonds, and stocks

The strategy rotates between three assets (SPY, GLD, and TLT). However, our experience is that rotation strategies frequently break apart.

The strategy has code for Amibroker only.

Published spring 2018.

Performance metrics:

No. of trades: 476
Average unleveraged gain per trade: 0.8%
Win ratio: 56%
Profit factor: 1.4
CAGR: 8.6% (assuming no leverage)
Exposure/time in the market: 90%
Risk-adjusted return: 9.5 (CAGR divided by time spent in the market (0.9))
Max. drawdown: -19%

The equity curve (log scale):

A portfolio equity line chart for a multi-asset monthly momentum strategy involving gold, bonds, and stocks, showing capital growth from $100,000 in early 2005 to a final value of $680,128 by early 2026. — 21-year backtest of a systematic monthly momentum strategy diversified across gold, bonds, and stocks, showcasing the steady growth and risk management found in professional trading strategies for sale.

Order by clicking here (check for strategy no. 64):

Once you have paid you can download the strategy on this link

Strategy 65: Last Trading Day Of The Month Trading Strategy S&P 500 (SPY)

The strategy uses a seasonal effect in stocks and enters on the last day of the month. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

This was the monthly trading edge for September 2023.

Performance metrics (S&P 500 – SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 197
Average unleveraged gain per trade: 0.54%
Win ratio: 78%
Profit factor: 2.5
Annual returns (CAGR): 3.4% (assuming no leverage)
Exposure/time in the market: 6%
Risk-adjusted return: 59% (CAGR divided by time spent in the market (0.06))
Max. drawdown: -13%

The equity curve (log scale):

A long-term portfolio equity line chart for the "Last Trading Day Of The Month" strategy on the S&P 500, showing capital growth from $100,000 in early 1993 to a final value of $339,735 by early 2025. — 32-year backtest of a systematic S&P 500 end-of-month strategy, demonstrating the steady capital growth potential of specialized trading strategies for sale.

Order by clicking here (check for strategy no. 65):

Once you have paid you can download the strategy on this link.

Strategy 66: Russell 2000 rebalancing strategy (IWM)

The strategy trades the Russell 2000 index (futures or ETF (IWM)), an annual seasonal trade.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published summer 2021.

Performance metrics (^RUT – Russell 2000) – including commissions and slippage of 0.03% per trade:

No. of trades: 25
Average unleveraged gain per trade: 1.4%
Win ratio: 68%
Profit factor: 3
Annual returns (CAGR): 1.4% (assuming no leverage)
Exposure/time in the market: 2%
Risk-adjusted return: 69% (CAGR divided by time spent in the market (0.02))
Max. drawdown: -6%

The equity curve (log scale):

A portfolio equity line chart for the Russell 2000 rebalancing strategy (IWM), showing capital growth from $100,000 in 2002 to a final value of $140,668 by early 2024. — 22-year backtest of a systematic Russell 2000 rebalancing strategy, highlighting the reliable alpha generated by index-specific trading strategies for sale.

Order by clicking here (check for strategy no. 66):

Once you have paid you can download the strategy on this link

Strategy 67: ADX Trading Strategy (Nasdaq 100 – QQQ)

The ADX is a trend indicator that usually needs a helping variable. We made an ADX strategy with another variable. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (QQQ – Nasdaq 100) – including slippage and commissions of 0.03% per trade:

No. of trades: 340
Average unleveraged gain per trade: 0.85%
Win ratio: 78%
Profit factor: 2.2
CAGR: 11.3% (assuming no leverage)
Exposure/time in the market: 17%
Risk-adjusted return: 65% (CAGR divided by time spent in the market (0.17))
Max. drawdown: -21%

The equity curve (log scale):

A portfolio equity line chart for the ADX trading strategy applied to the Nasdaq 100 (QQQ), showing capital growth from $100,000 in early 1999 to a final value of $1,524,776 by early 2026. — 27-year backtest of a systematic ADX-based trend strategy for the Nasdaq 100, illustrating the high-alpha potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 67):

Once you have paid you can download the strategy on this link

Strategy 68: Candlesticks Trading Strategies (Bundle -S&P 500 – SPY)

We have made a candlestick course available for both Amibroker and Tradestation/Easy Language users. Backtested on the ETF that tracks S&P 500 (SPY).

100% quantified, data-driven, and backtested with specific trading rules;
Choose the best pattern with our ranking methods based on past performance;
All patterns have Amibroker or Tradestation/Easy Language code.

Please click on the image below to read more or order:

Promotional graphic for the "Encyclopedia Of All 75 Candlestick Patterns," featuring a 3D book cover and a call-to-action button for historical backtests. — Unlock the data behind every major signal with our comprehensive guide to candlestick patterns and their historical performance—essential for anyone evaluating trading strategies for sale.

Strategy 69: Monthly (Or Weekly) Sector Rotation Trading Strategy

This is a sector rotation strategy in the S&P 500 (SPY), international stocks, etc. USA (EFA), gold (GLD), and bonds (TLT). It trades weekly or monthly (Fridays or the end of the month). Trading rules are in plain English and Amibroker.

The strategy has code for Amibroker and Tradestation.

This was our monthly trading edge for November 2025.

Performance metrics (monthly):

No. of trades: 187
Average unleveraged gain per trade: 1.4%
Win ratio: 60%
Profit factor: 2
CAGR: 12.5% (assuming no leverage and not including dividends)
Exposure/time in the market: 100%
Max. drawdown: -21%

The equity curve (log scale monthly):

A long-term portfolio equity line chart for a Monthly Sector Rotation trading strategy, showing capital growth from $100,000 in 2005 to a final value of $1,160,704 by early 2026. — 21-year backtest of a systematic sector rotation model, demonstrating the exceptional compounding potential of institutional-grade trading strategies for sale.

Order by clicking here (check for strategy no. 69):

Once you have paid, you can download the strategy on this link.

Strategy 70: Bollinger Bands + RSI Trading Strategy (SMH – semiconductors)

The strategy below trades BOTH long and short. Backtested on the ETF that tracks Semiconductors (SMH).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (Semiconductors (SMH) – including commissions and slippage of 0.03% per trade:

No. of trades: 297
Average unleveraged gain per trade: 0.65%
Win ratio: 67%
Profit factor: 1.9%
CAGR: 8.3% (assuming no leverage and not including dividends)
Exposure/time in the market: 16%
Risk-adjusted return: 51% (CAGR divided by time spent in the market (0.16))
Max. drawdown: -13%

The equity curve (log scale):

A long-term portfolio equity line chart for a combined Bollinger Bands and RSI trading strategy, showing capital growth from $100,000 in early 2000 to a final value of $1,027,606 by early 2026. — 26-year backtest of a systematic Bollinger Bands and RSI mean-reversion model, showcasing the high-performance potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 70):

Once you have paid you can download the strategy on this link

Strategy 71: MACD + RSI Trading Strategy (SMH – semis)

We combined both indicators to make a swing strategy that lasted a few days. Backtested on the ETF that tracks semiconductors (SMH).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

The strategy performs better with a trend filter (not included in the rules) and drawdowns are dramatically reduced.

Performance metrics (Consumer staples- SMH) – including commissions and slippage of 0.03%:

No. of trades: 235
Average unleveraged gain per trade: 0.9%
Win ratio: 73%
Profit factor: 2.3
Annual returns (CAGR): 8% (assuming no leverage but including dividends)
Exposure/time in the market: 14%
Risk-adjusted return: 56% (CAGR divided by time spent in the market (0.14))
Max. drawdown: -46%

The equity curve (log scale):

A long-term portfolio equity line chart for a combined MACD and RSI trading strategy, showing capital growth from $100,000 in late 2001 to a final value of $821,944 by early 2026. — 24-year backtest of a systematic MACD and RSI trend-momentum model, demonstrating the high-conviction growth available through professional trading strategies for sale.

Order by clicking here (check for strategy no. 71):

Once you have paid you can download the strategy on this link

Strategy 72: ADX + RSI Trading Strategy (Nasdaq 100 – QQQ)

Backtested on the ETF that tracks Nasdaq 100 (QQQ).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (Nasdaq 100 – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 258
Average unleveraged gain per trade: 1%
Win ratio: 73%
Profit factor: 2.4%
Annual returns (CAGR): 10.5% (assuming no leverage and not including dividends)
Exposure/time in the market: 15%
Risk-adjusted return: 70% (CAGR divided by time spent in the market (0.15))
Max. drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart for a combined ADX and RSI trading strategy, showing capital growth from an initial $100,000 in early 2000 to a final value of $1,701,520 by early 2026. — 26-year backtest of a systematic ADX and RSI strategy, demonstrating the high-performance growth potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 72):

Once you have paid you can download the strategy on this link

Strategy 73: Day Trading Strategy (Short) For S&P 500 (SPY)

Trading rules in plain English and code for Amibroker and Tradestation/Multicharts. It’s based on a seasonal pattern and uses one external indicator.

The strategy goes short at the open and covers at the close.

Backtested on the ETF that tracks Nasdaq 100 (QQQ).

This was our monthly trading edge for October 2024.

Performance metrics (S&P 500 – SPY):

No. of trades: 109
Average unleveraged gain per trade: 0.28% (0.65% for winners and -0.52% for losers)
Win ratio: 69%
Profit factor: 2.5
CAGR: 1.3% (assuming no leverage but including dividends)
Exposure/time in the market: 2%
Risk-adjusted return:671% (CAGR divided by time spent in the market (0.01))
Max. drawdown: -3%

The equity curve (log scale):

A portfolio equity line chart for a short-biased S&P 500 (SPY) day trading strategy, showing capital growth from $100,000 in 2003 to a final value of $133,280 by early 2025. — 22-year backtest of a systematic short-biased day trading strategy for the S&P 500, demonstrating how specialized trading strategies for sale can provide a vital hedge during market downturns.

Order by clicking here (check for strategy no. 73):

Once you have paid you can download the strategy on this link.

Strategy 74: Long Panic Strategy For Bonds (TLT)

The strategy does not trade often, but only when it’s “panic” and aims for a very short holding period.

The strategy was our monthly trading edge for April 2025.

Performance metrics (TLT) – including slippage and commissions of 0.03% per trade:

No. of trades: 85
Average unleveraged gain per trade: 0.35%
Win ratio: 76%
Profit factor: 3
Annual returns (CAGR): 1.3% (assuming no leverage but including dividends)
Exposure/time in the market: 2.5%
Risk-adjusted return: 52% (CAGR divided by time spent in the market (0.025))
Max. drawdown: -2.7%

The equity curve (log scale):

A portfolio equity line chart for the "Long Panic" trading strategy applied to Treasury Bonds (TLT), showing capital growth from $100,000 in early 2004 to a final value of $133,376 by early 2026. — 22-year backtest of a systematic “Long Panic” strategy for Bonds, demonstrating how specialized trading strategies for sale can profit from extreme market volatility and investor fear.

Order by clicking here (check for strategy no. 74):

Once you have paid you can download the strategy on this link.

Strategy 75: 3 VIX Trading Strategies (Bundle – Nasdaq 100 – QQQ)

Trading rules in plain English and code for Amibroker and Tradestation/Multicharts. Not eligible for any of the membership strategy selections. The bundle uses the VIX indicator to trade stocks (bonds with some modifications). Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published summer 2023.

Performance metrics (Nasdaq 100 – QQQ – as one portfolio of strategies) – including slippage and commissions of 0.03% per trade:

No. of trades: 506
Average unleveraged gain per trade: 0.7%
Win ratio: 73%
Profit factor: 1.8
Annual returns (CAGR): 13.4% (assuming no leverage but including dividends)
Exposure/time in the market: 30%
Risk-adjusted return: 45% (CAGR divided by time spent in the market (0.3))
Max. drawdown: -23%

The equity curve (log scale):

A long-term portfolio equity line chart for a combination of three VIX trading strategies, showing capital growth from $100,000 in 2000 to a final value of $3,073,887 by early 2026. — 26-year backtest of three systematic VIX-based trading strategies, illustrating the massive compounding potential of volatility-focused trading strategies for sale.

Order by clicking here (check for strategy no. 75):

Once you have paid you can download the strategy on this link.

Strategy 76: DMI Trading Strategies (S&P 500 – SPY)

The DMI is part of the ADX indicator. The strategy combines DMI with a trend and mean reversion filter. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (S&P 500 – SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 400
Average unleveraged gain per trade: 0.35%
Win ratio: 74%
Profit factor: 2
Annual returns (CAGR): 5.7% (assuming no leverage but including dividends)
Exposure/time in the market: 12%
Risk-adjusted return: 34% (CAGR divided by time spent in the market (0.12))
Max. drawdown: -17%

The equity curve (log scale):

A portfolio equity line chart for systematic DMI trading strategies, showing capital growth from $100,000 in the early 1990s to a final value of $465,175 by 2026. — 30-year backtest of systematic DMI (Directional Movement Index) strategies, showcasing the consistent long-term growth potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 76):

Once you have paid you can download the strategy on this link.

Strategy 77: Bear Market Day Trading Strategy

The strategy trades only during bear market and from the long side.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

The strategy was our monthly trading edge for September 2025.

Performance metrics (SPY – slippage and commission of 0.03% per trade is included):

No. of trades: 100
Average unleveraged gain per trade: 0.5%
Win ratio: 62%
Profit factor: 2
CAGR: 1.5%
Exposure/time in the market: 1%
Risk-adjusted return: 126% (CAGR divided by time spent in the market (0.1))
Max. drawdown: -5%

The equity curve (log scale):

A long-term portfolio equity line chart for a Bear Market Day Trading Strategy, showing capital growth from $100,000 in 1993 to a final value of $165,416 by early 2025. — 32-year backtest of a systematic Bear Market Day Trading Strategy, demonstrating how specialized trading strategies for sale can provide essential capital protection and growth during market downturns.

Order by clicking here (check for strategy no. 77):

Once you have paid you can download the strategy on this link

Strategy 78: Day Trading Strategy S&P 500 (SPY)

The strategy is backtested on stocks and related indices, futures, and ETFs. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

Published spring 2023.

Performance metrics (S&P 500 – SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 166
Average unleveraged gain per trade: 0.45%
Win ratio: 60%
Profit factor: 1.9
Annual returns (CAGR): 2.3% (assuming no leverage but including dividends)
Exposure/time in the market: 2%
Risk-adjusted return: 110% (CAGR divided by time spent in the market (0.02))
Max. drawdown: -9%

The equity curve (log scale):

A long-term portfolio equity line chart for an S&P 500 day trading strategy, showing capital growth from $100,000 in early 1993 to a final value of $210,123 by early 2025. — 32-year backtest of a systematic S&P 500 day trading model, demonstrating the steady compounding potential of institutional-grade trading strategies for sale.

Order by clicking here (check for strategy no. 78):

Once you have paid you can download the strategy on this link.

Strategy 79: Short Strategy For Russell 2000 (IWM)

Backtested on the ETF that tracks Russell 2000 (IWM). The strategy is a short strategy.

The strategy has code for Amibroker and Tradestation/Easy Langauge.

We previously had the Qstick Indicator strategy here but removed it due to little interest.

This was our monthly trading edge for April 2024.

Performance metrics (Russell 2000 – IWM) – including commissions and slippage of 0.03% per trade:

No. of trades: 167
Average unleveraged gain per trade: 0.6%
Win ratio: 65%
Profit factor: 2.3
Annual returns (CAGR): 3.9% (assuming no leverage but including dividends)
Exposure/time in the market: 4%
Risk-adjusted return: 86% (CAGR divided by time spent in the market (0.02))
Max. drawdown: -11%

The equity curve (log scale):

A long-term portfolio equity line chart for a short-biased Russell 2000 trading strategy, showing capital growth from an initial $100,000 in 2001 to a final value of $167,393 by early 2025. — 24-year backtest of a systematic short strategy for the Russell 2000, demonstrating how specialized trading strategies for sale can capture significant profit during small-cap market downturns.

Order by clicking here (check for strategy no. 79):

Once you have paid you can download the strategy on this link

Strategy 80: End-of-Month Strategy S&P 500 (SPY)

The backtest is based on the statistical end-of-month bias in the stock market. Backtested on the ETF that tracks S&P 500 (SPY).

The strategy has code for Amibroker and Tradestation/Easy Langauge.

This was our Monthy Trading Edge for June 2023 (for Gold Members).

Performance metrics (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 641
Average unleveraged gain per trade: 0.35%
Win ratio: 72%
Profit factor: 2
Annual returns (CAGR): 6.4%
Exposure/time in the market: 21%
Risk-adjusted return: 30% (CAGR divided by time spent in the market (0.21))
Max. drawdown: -16%

The equity curve (log scale):

A long-term portfolio equity line chart for the End-of-Month trading strategy on the S&P 500, showing capital growth from $100,000 in late 1993 to a final value of $972,048 by early 2026. — 32-year backtest of a systematic End-of-Month (turn-of-the-month) model, demonstrating the high-performance seasonality edge found in professional trading strategies for sale.

Order by clicking here (check for strategy no. 80):

Once you have paid you can download the strategy on this link.

Strategy 81: Turnaround Tuesday Strategy (S&P 500 – SPY)

The backtest is based on The Turnaround Tuesday bias. Backtested on the ETF that tracks S&P 500 (SPY).

Published 2016/17.

Performance metrics (SPY) – including commissions and slippage of 0.03%:

No. of trades: 400
Average unleveraged gain per trade: 0.65%
Win ratio: 75%
Profit factor: 2.7
Annual returns (CAGR): 7.9% (assuming no leverage and not including dividends)
Exposure/time in the market: 12%
Risk-adjusted return: 63% (CAGR divided by time spent in the market (0.12))
Max. drawdown: -18%

The equity curve (log scale):

A long-term portfolio equity line chart for the "Turnaround Tuesday" trading strategy, showing capital growth from $100,000 in early 1993 to a final value of $1,052,346 by early 2026. — 33-year backtest of the systematic Turnaround Tuesday strategy, showcasing the high-performance potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 81):

Once you have paid you can download the strategy on this link

Strategy 82: Turn of the Month Strategy (S&P 500 – SPY)

The backtest is based on the turn-of-the-month bias. Backtested on the ETF that tracks S&P 500 (SPY).

This strategy was our monthly Trading Edge for September 2023 (but published first in 2016/17).

Performance metrics (S&P 500 cash index since 1960) – including commissions and slippage of 0.03% per trade:

No. of trades: 650
Average unleveraged gain per trade: 0.65%
Win ratio: 62%
Profit factor: 2
Annual returns (CAGR): 6.3% (assuming no leverage and not including dividends)
Exposure/time in the market: 24%
Risk-adjusted return: 26% (CAGR divided by time spent in the market (0.24))
Max. drawdown: -28%

The equity curve (log scale):

A long-term portfolio equity line chart for the "Turn of the Month" trading strategy, showing capital growth from $100,000 in the early 1960s to over $5.3 million by 2026. — Multi-decade backtest of the Turn of the Month strategy, illustrating the massive compounding potential of seasonal trading strategies for sale.

Order by clicking here (check for strategy no. 82):

Once you have paid you can download the strategy on this link

Strategy 83: Ultimate Oscillator Strategy (SMH)

We backtested it in most settings for stocks (S&P 500) and bonds (TLT).

Published spring 2023.

Performance metrics (for SMH – an ETF that tracks semiconductors) – including commissions and slippage of 0.03% per trade:

No. of trades: 311
Average unleveraged gain per trade: 0.85%
Win ratio: 70%
Profit factor: 2.2
CAGR: 10.4% (assuming no leverage and not including dividends)
Exposure/time in the market: 20%
Risk-adjusted return: 50% (CAGR divided by time spent in the market (0.2))
Max. drawdown: -46% (!)

The equity curve (log scale):

A long-term portfolio equity line chart for the Ultimate Oscillator trading strategy, showing capital growth from $100,000 in early 2001 to a final value of $1,409,401 by early 2026. — 25-year backtest of the systematic Ultimate Oscillator model, showcasing the high-performance potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 83):

Once you have paid you can download the strategy on this link

Strategy 84: Double Seven Trading Strategy (S&P 500 – SPY)

Larry Connors’ Double Seven Strategy inspires the strategy, but we have changed the parameters. Backtested on the ETF that tracks S&P 500 (SPY).

Published spring 2023.

Performance metrics (for S&P 500 – SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 370
Average unleveraged gain per trade: 0.6%
Win ratio: 77%
Profit factor: 2.2
Annual returns (CAGR): 6.8% (assuming no leverage and including dividends)
Exposure/time in the market: 28%
Risk-adjusted return: 24% (CAGR divided by time spent in the market (0.28))
Max. drawdown: -14%

The equity curve (log scale):

A long-term portfolio equity line chart for the "Double Seven" trading strategy, showing capital growth from $100,000 in early 1993 to a final value of $899,893 by early 2025. — 32-year backtest of the systematic Double Seven strategy, illustrating the high-performance consistency of professional trading strategies for sale.

Order by clicking here (check for strategy no. 84):

Once you have paid you can download the strategy on this link.

Strategy 85: Overnight Strategy for Russell 2000 (IWM)

The strategy enters at the close and sells at the open the next day, thus holding for less than 24 hours.

The strategy comes with code for Amibroker, Tradestation/EasyLanguage, and plain rules in English.

This was Trading Edge for February 2024.

Performance metrics (Russell 2000 – IWM) – including commissions and slippage of 0.03% per trade:

No. of trades: 152
Average unleveraged gain per trade: 0.31%
Win ratio: 77%
Profit factor: 4
Annual returns (CAGR): 2% (assuming no leverage and including dividends)
Exposure/time in the market: 2.5%
Risk-adjusted return: 79% (CAGR divided by time spent in the market (0.025))
Max. drawdown: -2%

The equity curve since inception (log scale):

A portfolio equity line chart for an overnight trading strategy applied to the Russell 2000 index, showing capital growth from $100,000 in 2001 to a final value of $158,174 by early 2025. — 24-year backtest of the systematic Overnight Strategy for Russell 2000, showcasing how professional trading strategies for sale can capture the “night effect” for consistent capital appreciation.

Order by clicking here (check for strategy no. 85):

Once you have paid you can download the strategy on this link.

Strategy 86: Overnight Strategy for Gasoline (UGA)

Trading rules in plain English and code for Amibroker and Tradestation/Multicharts. It’s based on a seasonal pattern and uses two external indicators.

The strategy goes long at the close and sells at the close the next trading day.

Backtested on the ETF that tracks gasoline (UGA). It might work for the liquid corresponding futures contract and other relevant contracts.

This was our monthly trading edge for November 2024.

Performance metrics (Gasoline- UGA):

No. of trades: 123
Average unleveraged gain per trade: 0.6% (1.7% for winners and -1.3% for losers)
Win ratio: 62%
Profit factor: 2.2
CAGR: 4.3% (assuming no leverage but including dividends)
Exposure/time in the market: 2.5%
Risk-adjusted return: 177% (CAGR divided by time spent in the market (0.01))
Max. drawdown: -7%

The equity curve (log scale):

A long-term portfolio equity line chart for an overnight gasoline trading strategy, showing capital growth from $100,000 in 2008 to a final value of $199,327 by early 2026. — 18-year backtest of a systematic gasoline overnight model, showcasing the specialized commodity edges available in professional trading strategies for sale.

Order by clicking here (check for strategy no. 86):

Once you have paid you can download the strategy on this link.

Strategy 87: Of Combining A Trend Following And Mean Reversion Strategy (Nasdaq 100 – QQQ)

The only Holy Grail in trading is to trade strategies that complement each other. One way is trading two different types of strategies; in this example, we use trend following and mean reversion. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published spring 2023.

Performance metrics (for Nasdaq 100 – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 99
Average unleveraged gain per trade: 4.4%
Win ratio: 66%
Profit factor: 3
Annual returns (CAGR): 15% (assuming no leverage and including dividends)
Exposure/time in the market: 72%
Risk-adjusted return: 21% (CAGR divided by time spent in the market (0.72))
Max. drawdown: -32%

The equity curve (log scale):

A 3D product box for "All Candlestick Patterns Tested and Ranked" featuring a candlestick price chart background, alongside text promoting an "Encyclopedia Of All 75 Candlestick Patterns + Historical Backtests". — Discover which price patterns actually work with our comprehensive guide to 75 candlestick models and their historical performance data, part of our premium trading strategies for sale.

Order by clicking here (check for strategy no. 87):

Once you have paid you can download the strategy on this link.

Strategy 88: Combining Seasonal Effects In S&P 500 and Bonds

The only Holy Grail in trading is to trade strategies that complement each other. This example combines two seasonal effects in bonds and stocks that have existed for decades and that we covered many years ago.

Published spring 2023.

Performance metrics (for SPY and TLT) – including commissions and slippage of 0.03% per trade:

No. of trades: 467
Average unleveraged gain per trade: 0.5%
Win ratio: 63%
Profit factor: 1.7
Annual returns (CAGR): 5.5% (assuming no leverage and including dividends)
Exposure/time in the market/employed capital: 22%
Risk-adjusted return: 24% (CAGR divided by time spent in the market (0.22))
Max. drawdown: -7%

The equity curve (log scale):

A long-term portfolio equity line chart showing the combined performance of multiple seasonal trading strategies, with capital growing from $100,000 in early 2003 to a final value of $325,873 by early 2026. — 23-year backtest demonstrating the power of combining seasonal effects into a single diversified model, a core component of our professional trading strategies for sale.

Order by clicking here (check for strategy no. 88):

Once you have paid you can download the strategy on this link.

Strategy 89: First Trading Day Of The Month Trading Strategy for S&P 500 (SPY)

The strategy takes advantage of a historical and statistically strong seasonal effect/anomaly in the stock market: the first trading day of the month. Backtested on the ETF that tracks S&P 500 (SPY).

Published spring 2023.

Performance metrics (S&P 500 – SPY) – including slippage and commissions of 0.03% per trade:

No. of trades: 76
Average unleveraged gain per trade: 0.7%
Win ratio: 76%
Profit factor: 3
Annual returns (CAGR): 1.7% (assuming no leverage and including dividends)
Exposure/time in the market: 2.4%
Risk-adjusted return: 68% (CAGR divided by time spent in the market (0.024))
Max. drawdown: -6%

The equity curve (log scale):

A long-term portfolio equity line chart for the "First Trading Day Of The Month" strategy, showing capital growth from $100,000 in early 1993 to a final value of $179,714 by early 2025. — 32-year backtest of the systematic First Trading Day of the Month model, illustrating the reliable seasonal edges available in professional trading strategies for sale.

Order by clicking here (check for strategy no. 89):

Once you have paid you can download the strategy on this link.

Strategy 90: Combining A Trend Following And Mean Reversion Strategy for S&P 500 and Nasdaq 100 (QQQ)

We mix an example of a long-term trend-following strategy with a short-term mean reversion strategy. The strategy trades at the close (but the result is slightly better if entries and exits are at the next open). Backtested on the ETF that tracks S&P 500 (SPY) and QQQ. The equity curve is better for SPY than for QQQ.

Published spring 2023.

Performance metrics (Nasdaq 100 – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 237
Average unleveraged gain per trade: 1.8%
Win ratio: 51%
Profit factor: 3.2
Annual returns (CAGR): 14% (assuming no leverage and including dividends)
Exposure/time in the market: 79%
Risk-adjusted return: 17% (CAGR divided by time spent in the market (0.79))
Max. drawdown: -50% (-21% for SPY)

The equity curve (log scale):

A long-term portfolio equity line chart for the Trend Following and Mean Reversion strategy for S&P 500, showing capital growth from $100,000 in early 2000 to a final value of $3,249,519 by early 2026. — 26-year backtest of a dual-logic S&P 500 system, demonstrating the high-performance growth potential of professional trading strategies for sale.

Order by clicking here (check for strategy no. 90):

Once you have paid you can download the strategy on this link.

Strategy 91: Day Of Week Effect On Stocks (Nasdaq 100 – QQQ)

We mix price action and a day-of-week effect to create an example of a potential short-term trading strategy. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Published spring 2023.

Performance metrics (Nasdaq 100 – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 458
Average unleveraged gain per trade: 0.85%
Win ratio: 76%
Profit factor: 2.7
CAGR: 15% (assuming no leverage and including dividends)
Exposure/time in the market: 25%
Risk-adjusted return: 58% (CAGR divided by time spent in the market (0.25))
Max. drawdown: -27%

The equity curve (log scale):

A long-term portfolio equity line chart showing the Day of Week Effect on stocks, with capital growing from $100,000 in early 2000 to a final value of $4,239,952 by early 2026. — 26-year backtest of the Day of Week Effect strategy, illustrating how professional trading strategies for sale can exploit persistent weekly calendar anomalies.

Order by clicking here (check for strategy no. 91):

Once you have paid you can download the strategy on this link.

Strategy 92: Short (Tail Risk) Trading Strategy for QQQ

This short strategy trades infrequently but has historically performed well for volatile stock indices when volatility is high, but is bleeding during bull markets. Shorting is difficult! We offer the strategy in Amibroker, Tradestation/Easy Language, and TradingView/Pinescript code. Backtested on the ETF that tracks NASDAQ 100 (QQQ).

This was our Monthly Trading Edge for July 2023 (for Gold Members).

A monthly returns table for a QQQ Short Tail Risk trading strategy from 1999 to 2025, highlighting major annual gains of 42% in 2000, 79% in 2002, 38.4% in 2008, and 45.1% in 2022. — Monthly and annual performance matrix for the QQQ Short Tail Risk model, showcasing the defensive power of specialized trading strategies for sale during major market crashes.

Performance metrics (Nasdaq 100 – QQQ) – including commissions and slippage of 0.03% per trade:

No. of trades: 156
Average unleveraged gain per trade: 1.2%
Win ratio: 67%
Profit factor: 2
Annual returns (CAGR): 7.2% (assuming no leverage and including dividends)
Exposure/time in the market: 10%
Risk-adjusted return: 75% (CAGR divided by time spent in the market (0.1))
Max. drawdown: -23%

The equity curve (log scale):

Order by clicking here (check for strategy no. 92):

Once you have paid you can download the strategy on this link.

Strategy 93: Short Trading Strategy In Bonds (TLT)

The strategy enters at the open and exits at the close, but not on the same day. There are three variables for entry and one for exit. This is a short strategy. We offer the strategy in Amibroker, Tradestation/Easy Language, and TradingView/Pinescript code.

This was our Monthly Trading Edge for August 2023 (for Gold Members).

Performance metrics (bonds – TLT) – including commissions and slippage of 0.03% per trade:

No. of trades: 215
Average unleveraged gain per trade: 0.3%
Win ratio: 59%
Profit factor: 1.7
Annual returns (CAGR): 2.5% (assuming no leverage and including dividends)
Exposure/time in the market: 12%
Risk-adjusted return: 21% (CAGR divided by time spent in the market (0.12))
Max. drawdown: -10%

The equity curve (log scale):

A long-term portfolio equity line chart for a short trading strategy in bonds, showing capital growth from approximately $100,000 in 2003 to a final value of $169,794 by early 2025. — 22-year backtest of a systematic short-biased bond model, demonstrating how professional trading strategies for sale can profit from rising interest rate environments.

Order by clicking here (check for strategy no. 93):

Once you have paid you c an download the strategy on this link.

Strategy 94: (Bundle 6) 3 NASDAQ 100 Trading Strategies (QQQ Bundle)

Please check our separate landing page for strategy bundles. Not eligible for any of the membership strategy selections. Published November 2024. Backtested on the ETF that tracks Nasdaq 100 (QQQ).

Strategy 95: 24-hour (Overnight) Strategy SPY/QQQ

The strategy enters at the close and exits at the close the day after, thus holding it for 24 hours (one trading day). There are two variables for entry. This is a long strategy. Backtested on the ETF that tracks S&P 500 (SPY).

This was our Monthy Trading Edge for October 2023 (for Gold and Platinum Members).

Performance metrics (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 405
Average unleveraged gain per trade: 0.4%
Win ratio: 63%
Profit factor: 2.2
Annual returns (CAGR): 5.1% (assuming no leverage and including dividends)
Exposure/time in the market: 5%
Risk-adjusted return: 102% (CAGR divided by time spent in the market (0.05))
Max. drawdown: -7% (significantly less for SPY)

The equity curve (log scale):

A long-term portfolio equity line chart for a 24-hour overnight trading strategy using SPY and QQQ, showing capital growth from $100,000 in 1993 to a final value of $525,733 by early 2026. — 33-year backtest of a systematic 24-hour overnight model for SPY and QQQ, highlighting the consistent compounding available in professional trading strategies for sale.

Order by clicking here (check for strategy no. 95):

Once you have paid you c an download the strategy on this link.

Strategy 96: Seasonal Strategy For Bitcoin

The strategy is based on a day-of-the-week pattern. There is more info about this strategy on our website.

Performance metrics (BTC-USD)

No. of trades: 103
Average unleveraged gain per trade: 2.7%
Win ratio: 60%
Profit factor: 2.3
Annual returns (CAGR): 28%
Exposure/time in the market: 10%
Risk-adjusted return: 280% (CAGR divided by time spent in the market (0.1))
Max. drawdown: -20%

The equity curve (log scale):

A long-term portfolio equity line chart for a seasonal trading strategy for Bitcoin, showing capital growth from $100,000 in early 2015 to a final value of $1,125,647 by early 2026. — 11-year backtest of a systematic Bitcoin seasonal model, demonstrating the high-performance growth potential of professional trading strategies for sale in the crypto market.

Order by clicking here (check for strategy no. 96):

Once you have paid you c an download the strategy on this link.

Strategy 97: Long Pullback Strategy for Gold (GLD)

This is a long-swing strategy for gold (GLD); it also works for the main stock indices such as SPY and QQQ.

The strategy buys and sells at the close.

This strategy was our monthly trading edge for February 2025.

Performance metrics (GLD) – including commissions and slippage of 0.03% per trade:

No. of trades: 90
Average unleveraged gain per trade: 0.75%
Win ratio: 73%
Profit factor: 2.5
Annual returns (CAGR): 3.3% (assuming no leverage and including dividends)
Exposure/time in the market: 5%
Risk-adjusted return: 58% (CAGR divided by time spent in the market (0.05))
Max. drawdown: -8%

The equity curve (log scale):

A long-term portfolio equity line chart for a long pullback trading strategy for Gold, showing capital growth from $100,000 in early 2005 to a final value of $187,776 by early 2026. — 21-year backtest of a systematic Gold pullback model, illustrating the steady commodity growth potential available in professional trading strategies for sale.

Order by clicking here (check for strategy no. 97):

Once you have paid you c an download the strategy on this link.

Strategy 98: Long Bear Market Strategy for S&P 500 (SPY)

This is a long strategy but only trades in bear markets. Backtested on the ETF that tracks S&P 500 (SPY).

This was our Monthly Trading Edge for March 2025 (for Gold and Platinum Members).

Performance metrics (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 197
Average unleveraged gain per trade: 0.6%
Win ratio: 73%
Profit factor: 2
Annual returns (CAGR): 3.6% (assuming no leverage and including dividends)
Exposure/time in the market: 4%
Risk-adjusted return: 84% (CAGR divided by time spent in the market (0.04))
Max. drawdown: -16%

The equity curve (log scale):

Order by clicking here (check for strategy no. 98):

Once you have paid, you c an download the strategy on this link.

Strategy 99: Short Strategy for S&P 500 (SPY)

This is a short strategy. It has been most consistent for S&P 500, but also performed well for QQQ and SMH.

The strategy buys and sells at the close.

This strategy was our monthly trading edge for January 2025.

Performance metrics (SPY) – including commissions and slippage of 0.03% per trade:

No. of trades: 147
Average unleveraged gain per trade: 0.75%
Win ratio: 69%
Profit factor: 2.1
Annual returns (CAGR): 3.3% (assuming no leverage and including dividends)
Exposure/time in the market: 7.5%
Risk-adjusted return: 45% (CAGR divided by time spent in the market (0.033))
Max. drawdown: -11% (significantly less for SPY)

The equity curve (log scale) for long and short:

Order by clicking here (check for strategy no. 99):

Once you have paid you c an download the strategy on this link.

Strategy 100: Long Gold Strategy (GLD)

This is a long strategy for gold (GLD).

The strategy buys and sells at the close.

This strategy was our monthly trading edge for May 2025.

Performance metrics (GLD) – including commissions and slippage of 0.03% per trade:

No. of trades: 214
Average unleveraged gain per trade: 0.45%
Win ratio: 58%
Profit factor: 1.6
Annual returns (CAGR): 4.5% (assuming no leverage and including dividends)
Exposure/time in the market: 21%
Risk-adjusted return: 22% (CAGR divided by time spent in the market (0.21))
Max. drawdown: -15%

The equity curve (log scale) for long and short:

A long-term portfolio equity line chart for the "Long Bear Market Strategy for S&P 500," showing capital growth from $100,000 in early 1993 to a final value of $331,093 by early 2025. — 32-year backtest of a systematic S&P 500 bear market model, demonstrating the defensive growth potential of specialized trading strategies for sale during market downturns.

Order by clicking here (check for strategy no. 100):

Once you have paid you c an download the strategy on this link.

You can purchase backtested strategies individually (one by one), as strategy bundles, or via our memberships:

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Buy 1 Strategy (Without Becoming a Member) Pick 1 strategy from the strategy list or buy directly here.
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Buy Bundles!
Buy 34 Strategies (Incl Bundles) – Platinum member: Pick 15 strategies from the strategy list, and you will also get an additional 10 strategies over the next 12 months. Access to Amibroker and Tradestation code, access to gated trading rules for hundreds of strategies, 3 bundles of your choice (#33 – #36, #43, #68, or #75 from our strategy list), backtesting course, and trading course. Recurring annually at a 50% reduced price (needs to be canceled by the subscriber).
Futures Systems (Backtested): We have a separate list of trading strategies for futures.

Each strategy comes with trading rules in plain English and a strategy code of your choice (so you can backtest yourself – to trade live, you might need to change the code). Available right now are Amibroker, Tradestation, and plain English – unless stated (Tradingview where indicated). It is important to note that while every effort has been made to ensure the accuracy of the information provided, we cannot guarantee that the results obtained using this trading strategy will be replicated.

We do investment research and analysis based on statistics and history for informational and educational purposes. This is factual information without opinions. It is not personalized investment advice.

Summary from our shop of Trading Strategy Metrics

Key Insights from Metrics

• Highest CAGR: The Seasonal Strategy For Bitcoin (Strategy 96) reported the highest Compound Annual Growth Rate (CAGR) at 28%, followed by the combination of long and short strategies (Strategy 47) at 19%.

• Highest Risk-Adjusted Return: The Day Trading Strategy (Short) For S&P 500 (Strategy 73) had the highest calculated Risk-Adjusted Return at 671%. The Overnight Strategy for Gasoline (UGA) (Strategy 86) also showed a high return at 177%. These high figures correlate with very low market exposure (2% or 2.5% in those cases).

• Maximum Profit Factor: The Triple RSI Trading Strategy (Strategy 59) reported the highest Profit Factor at 8, closely followed by the Momentum Trading Strategy (Strategy 52) at 7.

• Highest Win Ratio: The Coppock Trading Strategy (Strategy 57) had a 100% Win Ratio, though based on only 13 trades. The Triple RSI Trading Strategy (Strategy 59) reported a 90% Win Ratio.

• Lowest Drawdown: The Overnight Strategy for Russell 2000 (Strategy 85) and the Long Panic Strategy For Bonds (Strategy 74) had the lowest maximum drawdowns, reporting -2% and -2.7%, respectively.

• High Risk/High Reward Bundles: The combined Bitcoin Trading Strategy (Strategy 48) offered a 100% CAGR but incurred the deepest maximum drawdown at -49% (!!!). Strategy 90 (Combined Trend Following + Mean Reversion on QQQ) also showed a significant drawdown of -50%.

Disclaimer (trading strategies for sale)

Quantified Strategies (SIA Lofjord) is not an investment advisor. The content and information provided are educational and should not be treated as financial advisory services or investment advice. Trading and investment in securities involve substantial risk of loss and is not recommended for anyone that is not a trained trader or investor – it shall be conducted at your own risk. It is recommended that you never risk more than you are willing to lose. Leverage can lead to substantial losses. Any use of leverage, margin, or shorting is at your discretion. Quantified Strategies (SIA Lofjord) is not responsible for any losses that occur as a result of its content and information. Always use a demo account for many months before you do live trading. Trading requires hard and systematic work – there is no easy money, and markets change all the time. And remember: always trade smaller position sizes than you’d like to.

We assume no responsibility or liability for your trading and investment results. The indicators, strategies, programming code, Trading Edges, columns, articles, and all other features of the website QuantifiedStrategies.com are provided for informational and educational purposes only and should not be construed as investment advice. We don’t provide investment advice.

Hypothetical or simulated performance results have certain limitations. Unlike an actual performance record, simulated results do not represent actual trading. Commissions and slippage are not included, and most trading signals are triggered at the close. Also, since the trades have not been executed, the results may have under or overcompensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated trading programs, in general, are also subject to the fact that they are designed with the benefit of hindsight. No representations are made that any account will or is likely to achieve profit or losses similar to those shown.