The Weekend Trend Trader Trading Strategy

The Weekend Trend Trader Trading Strategy – 22% Annual Return, Trading Rules Included

Nick Radge’s Weekend Trend Trader trading strategy is a mechanical and systematic trading system designed for part-time traders, allowing them to make decisions and manage trades during the weekend when markets are closed.

In this article, we explain the Weekend Trend Trader strategy, create trading rules based on its principles, and backtest it on several US stocks in different indices.

Here are the key trading rules and principles of this strategy:

What is the Weekend Trend Trader trading strategy? Introduction

The Weekend Trend Trader Strategy, as detailed in the Weekend Trend Trader eBook by Nick Radge (here you find the Weekend Trend Trader pdf), an Australian money manager, is a specific set of rules designed for this system. Initially developed and tested for the US market, its success has led to its adoption in markets worldwide. The strategy is all about trend trading – trend following strategy.

This strategy is tailored for individuals seeking a straightforward trading plan that requires action only once a week. Nick Radge argues it’s an excellent investment approach for those working full-time but actively planning for retirement.

Overall, it’s a weekend trading strategy for which you can scan, explore, and place trading orders before the market opens on Monday. If you are interested in market and systematic trading, is there a better way to spend the weekend than doing weekend market analysis? Systematic trend trading requires a solid trading plan, so you must expect to work a couple of hours weekly.

Overview of the Weekend Trend Trader Strategy

Let’s show you the basic overview and principles of the strategy:

  1. Stock Universe:
    • The strategy focuses on a universe of highly liquid stocks. Typically, these stocks are selected based on market capitalization, average daily trading volume, and other liquidity metrics.
    • A common choice for this strategy might be the top 500 or 1000 stocks by market capitalization in a given market.
    • However, no rules are written in stone, so you can easily backtest anything you want, but keep in mind that low-volume stocks tend to have high slippage.
  2. Entry Rules:
    • Trend Identification: The strategy uses technical indicators to identify the trend direction. Common indicators might include moving averages, trend lines, or breakouts.
    • Momentum: The stock must be among the winners based on momentum over the lookback period.
    • Relative Strength: Stocks showing relative strength compared to the broader market are preferred. This can be measured using indicators like the Relative Strength Index (RSI) or ranking stocks based on their performance over a certain period.
    • Breakouts: Entry signals are often based on price breakouts. For example, buying a stock when it breaks out above a recent high.
    • Market regime: Is the overall market bullish or bearish? Most stocks rise with the tide, and vice versa. You don’t want to fight the market, and thus, a market regime filter might be useful. Below, we included such a filter in our trading rules.
  3. Position Sizing:
    • The strategy often employs a fixed fractional position sizing model, where a predetermined percentage of the total trading capital is allocated to each trade.
    • Risk per trade is usually kept low, commonly around 1-2% of the total trading capital.
    • Nick Radge recommends adjusting the position size based on the volatility of the stock. Volatile stocks are allocated less capital than low-volume stocks.
  4. Risk Management:
    • Stop-Loss Orders: Each trade has a predefined stop-loss level to limit potential losses. This stop-loss might be set based on a percentage of the entry price or a volatility-based measure like the Average True Range (ATR).
    • Trailing Stops: As the trade moves in the favorable direction, trailing stops can be used to lock in profits. These trailing stops adjust based on the stock’s movement. A trailing stop can only be raised – not lowered.
  5. Exit Rules:
    • Profit Targets: Predefined profit targets can be set based on risk-reward ratios. For example, aiming for a reward that is 2-3 times the risk. However, we are unsure if Nick Radges uses profit targets – most likely not.
    • Trend Reversal: Exits can also be triggered by trend reversal signals, such as moving average crossovers or breakouts in the opposite direction.
    • Time-Based Exits: In some cases, trades might be closed after a certain period regardless of the outcome to free up capital and reduce risk.
  6. Weekly Review:
    • The strategy involves reviewing the trades and potential setups during the weekend. This allows for unemotional decision-making and adherence to the trading rules.

Implementation Example

Here is a simplified example of how you might implement the Weekend Trader strategy:

  1. Define Universe:
    • Select the top 500 stocks by market capitalization )for example, the S&P 500).
  2. Entry Signal:
    • Buy a stock if it closes above its 50-day high and ranks in the top 10% of stocks by 3-month relative strength.
  3. Position Sizing:
    • Allocate 10% of total trading capital to each trade.
  4. Stop-Loss:
    • Set an initial stop-loss at 20% below the entry price (we don’t recommend using stop losses, though, but for some reason, most traders are hell-bent on including it). We prefer to trade smaller sizes and different strategies instead of using a stop loss.
  5. Trailing Stop:
    • Use a trailing stop set at 20% below the highest close since the entry. However, this can also depend on the market regime (see our rules below).
  6. Weekly Review:
    • Check all positions and potential new entries every weekend. Adjust stop-losses, close trades hitting stop-loss or profit targets, and identify new entries.

If you want to read more about the strategy, please read the website of Mr. Radge. He also made a talk a few years back where he explained his main trading principles, but unfortunately we are unable to find it.

Weekend Trend Trader trading strategy – trading rules

Let’s show you an example of a Weekend Trader strategy with trading rules. We emphasize that these rules are not Nick Radge’s, but our own based on our interpretation of the strategy. We have not read Nick Radge’s ebook!

We also emphasize that the strategy trades single stocks and not indices.

The trading rules to buy are as follows:

THIS SECTION IS FOR MEMBERS ONLY. _________________ BECOME A MEBER TO GET ACCESS TO TRADING RULES IN ALL ARTICLES CLICK HERE TO SEE ALL 350 ARTICLES WITH TRADING RULES

If the above three trading rules are true, we go long the stock at the next open.

We use the following trading rules to exit a trade:

THIS SECTION IS FOR MEMBERS ONLY. _________________ BECOME A MEBER TO GET ACCESS TO TRADING RULES IN ALL ARTICLES CLICK HERE TO SEE ALL 350 ARTICLES WITH TRADING RULES

Please keep in mind that the trading rules are not optimized in any way. They are taken from the top of our heads, and they can probably be improved massively. To keep it simple, we have also excluded any adjustments to the stock’s volatility.

Weekend Trend Trader strategy – backtest, returns, performance

Let’s backtest the trading rules described above. We backtest the stocks that are in these indexes (in parentheses are the relevant indexes to determine the trend of the market):

  • S&P 100 (OEX)
  • S&P 500 (SPX)
  • Nasdaq 100 (NDX)
  • S&P Midcap 400 (MID)
  • S&P Smallcap 600 (SML)
  • Russell 2000 (RUT)

We have used data from Norgate that is free from survivorship bias. We allocate 10% of the capital for each position, thus, we only have 10 stocks at any time. To illustrate the importance of using survivorship-free data, consider this: The S&P 600 Smallcap index has included 2473 stocks since 1990! This is three times the current index!

The backtest period is from January 1990 until today.

We have not included commissions and slippage. Commissions are close to zero, and there are relatively few trades.

We backtest on weekly bars. Thus, if you get a buy signal, you buy the open on Monday (and sell the Monday open).

S&P 100 (OEX) backtest

Let’s start with a backtest of the 100 biggest US companies (again, we use the trading rules described above).

This is the equity curve:

Weekend Trader example
Weekend Trader example

Trading statistics, returns, and performance:

  • # of trades: 217
  • CAGR (annual returns): 14.9%
  • Average bars held: 65 weeks
  • Amount capital invested (market exposure): 82%
  • Max drawdown: 51%

S&P 500 (SPX) backtest

The US’ 500 biggest companies returned the following equity curve:

Weekend Trader settings
Weekend Trader settings

Trading statistics, returns, and performance:

  • # of trades: 248
  • CAGR (annual returns): 19.9%
  • Average bars held: 103 weeks
  • Amount capital invested (market exposure): 85%
  • Max drawdown: 43%

Nasdaq 100 (NDX) backtest

The 100 biggest tech stocks returned the following equity curve:

Weekend Trader trading rules
Weekend Trader trading rules

Trading statistics, returns, and performance:

  • # of trades: 286
  • CAGR (annual returns): 16.5%
  • Average bars held: 72 weeks
  • Amount capital invested (market exposure): 84%
  • Max drawdown: 55%

S&P Midcap 400 (MID) backtest

The midcap stocks returned a pretty impressive equity curve:

Weekend Trader trading strategy
Weekend Trader trading strategy
Weekend trader strategy drawdowns
Weekend trader strategy drawdowns

Trading statistics, returns, and performance:

  • # of trades: 303
  • CAGR (annual returns): 22.9%
  • Average bars held: 121 weeks
  • Amount capital invested (market exposure): 82%
  • Max drawdown: 58%

S&P Smallcap 600 (SML) backtest

The small-cap segments didn’t perform as well as the larger companies (this backtest is from 1995 (not 1990) until today):

Weekend Trader strategy returns
Weekend Trader strategy returns

Trading statistics, returns, and performance:

  • # of trades: 377
  • CAGR (annual returns): 9.1%
  • Average bars held: 121 weeks
  • Amount capital invested (market exposure): 86%
  • Max drawdown: 69%

Russell 2000 (RUT) backtest

The Russell 2000 performed badly (we are not sure why):

Weekend Trader strategy performance
Weekend Trader strategy performance

Trading statistics, returns, and performance:

  • # of trades: 675
  • CAGR (annual returns): 0.1% (!!)
  • Average bars held: 100 weeks
  • Amount capital invested (market exposure): 81%
  • Max drawdown: 81% (!!)

Weekend Trader – further research

We backtested only US stocks, but we believe the strategy performs better in other markets. The reason for that is simple: the US markets are more prone to mean reversion than, for example, Canadian or Australian stocks. Nick Radge is Australian, and we believe the Weekend Trend Trader strategy was first backtested on Australian stocks. The more exposed an economy is to commodities, the better the strategy performs (?).

However, that is for another day. Currently, we only have US stocks in our database.

One other key finding we made is that lower capitalized stocks need to have bigger “wiggle room” than large caps. For example, S&P MID 400 performs much better when the trailing stop is 40%, not 20%. This is not necessarily the case for large caps. Adjusting the settings for such a finding is not overfitting, in our opinion. No market or industry is the same!

Weekend Trend Trader strategy – complete code

The strategy is backtested using Amibroker. Below is the complete code of the strategy:

THIS SECTION IS FOR MEMBERS ONLY. _________________ BECOME A MEBER TO GET ACCESS TO TRADING RULES IN ALL ARTICLES CLICK HERE TO SEE ALL 350 ARTICLES WITH TRADING RULES

Final Notes

The Weekend Trader strategy emphasizes discipline and consistency. The whole idea is to keep it simple and use a 100% mechanical and systematic approach to reduce the emotional pull from greed and fear.

Following a mechanical approach helps traders avoid emotional decision-making and maintain a structured trading plan. It’s essential to backtest the strategy on historical data to ensure its viability and understand its performance characteristics.

Additionally, it may be beneficial to adapt the strategy to fit your specific market conditions and personal trading preferences.

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