Profitable Trading Strategies

Profitable Trading Strategies (Video, Backtest, Rules, Performance, Example Analysis)

A profitable trading strategy is one that consistently makes money over a reasonable period of time. It is not just enough for a strategy to make some winning trades over a short time because market conditions can change and it stops making money; the strategy must have a combination of a reasonable winning rate and a sizeable gain per win such that after summing the wins and losses, it is in net profit and must do so consistently over a reasonable period that spans across different market conditions.

To succeed in trading depends on having a profitable trading strategy and implementing it well. Of course, this seems like a no-brainer, but what exactly does a profitable trading strategy mean?

In this post, we look at what it means for a trading strategy to be profitable. We end the article by making a backtest of a profitable trading strategy.

What does a profitable trading strategy mean?

A profitable trading strategy is one that consistently makes money over a reasonable period of time. It is not enough for a strategy to make some winning trades over a short time because market conditions can change and it stops making money; the strategy must be able to make money across different market conditions.

One thing to note is that having a high winning rate does not necessarily translate into a profitable strategy. A strategy can have a high win rate and not be profitable because the few losing trades are huge enough to wipe out all the profits made from the numerous winning trades. A profitable strategy must have a combination of a reasonable winning rate and a sizeable gain per win such that after summing the wins and losses, it is in net profit. And it must do that consistently for a reasonable period of time.

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Features of the most profitable trading strategy

There are many features a profitable strategy must have. These are some of them:

  • Reasonable win rate: While the win rate is not everything for a strategy, to make money, a strategy must win some trades. No strategy makes money losing all its trades. Every other thing being equal, the more the number of wins, the more the profit. Depending on the reward/risk ratio, the number of winners may not necessarily need to be more than the number of losers.
  • Reasonable average gain per trade: The average gain per trade is gotten by dividing the total amount won by the number of trades. The higher the value, the better. A high value indicates that the strategy has a good win rate and reward/risk ratio combination.
  • Optimal reward/risk ratio: The reward/risk ratio is the ratio of what is gained per winning trade to what is lost per losing trade. As a trader, you may plan for this with a profit target (and perhaps a stop loss). A 3/1 reward/risk ratio means that the profit target is 3x the size of the stop loss. While a 3/1 reward/risk ratio or higher is desirable, the profit target may be too high for the price to get to, leading to some would-be winners turning to losers, breakeven, or lesser profit (when stopped out by a trailing stop). Find out the optimal ratio from backtesting.
  • Positive expectancy: This refers to how much money, on average, you can expect to make or lose for every dollar you risk. If the value is positive, the strategy is likely to make money. Expectancy can be expressed as the expected returns per trade or an expectancy ratio. The expected return is given as ER = (win rate X average win size) – (loss rate x average loss size).
  • High profit factor: This is the ratio between gross profits and gross losses. For example, a strategy that won $400 and lost only $200 would have a profit factor of 2. The higher the profit factor, the better. A profitable strategy must have a profit factor that is not too low so as to leave room for strategy degradation, which is inevitable.
  • Low maximum drawdown: A maximum drawdown (MDD) is the maximum decline a trading strategy has experienced. It is seen in an equity curve as the difference between the value of the lowest trough and that of the highest peak before the trough. A profitable strategy should not have a huge drawdown, otherwise, the strategy would be too risky.

Related reading: Best Trading Rules for Successful Traders

What you should know about a profitable trading strategy

Here are some of the things you should know about a profitable strategy:

  • A profitable trading strategy does not always depend on a high win rate: Expect a trade-off between the win rate and reward/risk ratio. A strategy with a high win rate may take a little profit in each trade and use a huge stop loss, which gives a very poor reward/risk ratio. As you would expect, there are two extremes when it comes to trading strategies. On one hand, you can have a trading strategy with a high win rate and poor reward/risk ratio. While this type of strategy can still be profitable, it relies heavily on a high win rate. But that does not mean that for a strategy to be profitable, it must have a high win rate. A strategy can have a modest 30-40% win rate and still be profitable because, in each winning trade, the trader makes several times what he losses in a losing trade. Such a strategy would have a high reward/risk ratio, say 5:1. This means that out of 100 trades, if it has 35 winning trades and risk, the profit would be 5×30 – (100-30) = 80%. That is the magic of a huge reward/risk ratio.
  • A profitable trading strategy can lose money with poor risk management: Apart from the strategy having a statistical edge in the market, with positive expectancy, an important ingredient for profitability is risk management, and this includes position sizing. No matter how good a strategy is, it has its period of losing streaks. So, trading a huge position size may not allow the strategy enough sample size to pass through its losing streak before the trading account blows up. For instance, when trading with a 10% position size, a streak of 9 or 10 losses, which can easily happen to a winning strategy, would almost blow the trading account. If the trader is trading only 1% position size, after a streak of 10 losses, he still has over 90% of the account capital to trade with, which allows it to recover and become profitable.
  • A profitable trading strategy does not depend on how frequently it generates a signal: While having more trading opportunities could increase the amount of profit made, every other variable being the same, the frequency of the trading signal is not a determinant of whether a strategy can be profitable or not. A swing trading strategy that generates only 12 signals in a year can have a 70% win rate with 3:1 reward/risk ratio and be amazingly profitable, while a scalping strategy that generates thousands of trades in a year may not be profitable.

How do you create a profitable trading strategy?

Creating a profitable strategy is not easy in today’s world where algorithmic and high-frequency trading rule the market. Finding the right strategy that works is daunting, but following these steps can make your work easier.

1. Research

The first step in creating a profitable strategy is finding an inefficiency in the market that can give a trading edge. This requires some serious research. You can start by checking out some financial market publications in academic journals. If you find those boring, you can check some trading blogs like this one. We break down all those academic jargon to find some tradable edge.

Another way to generate some trading ideas is to interact with other traders. if you don’t have traders around you, check out some trading forums online and engage traders. While many try to hoard their main strategies, some may be willing to share some trading ideas. Just be patient enough to integrate yourself into their community and contribute one or two so they don’t feel you come to gain alone without contributing.

We have written a long and separate article about how to find trading ideas and strategies.

2. Formulating the trading rules

After finding an edge you want to exploit in the market, you have to turn it into a tradable strategy. For example, if your research shows that a particular market, say Nasdaq 100, tends to decline on Fridays, you have to formulate your entry and exit rules to exploit that edge.

Your entry rule could be to place a short order at market open on Friday or even just before market close on Thursday if you find that Fridays usually open with a gap down. Next would be your exit rule, which could be just before the day’s close, at noon on Fridays, or even a specific profit target.

3. Creating a trading algo

The next thing would be to code your strategy into a trading algo that can execute and manage your trades automatically. Trading algos ensures that the odds of the strategy work out by taking all the trade setups without missing a trade. This may be easy for you if you already have some coding skills. But even if you don’t, some platforms like TradeStation use an easy language that you can easily code.

Alternatively, you can hire freelance programmers to code your strategy. But it is good to learn in case you may want to tweak the system later in the future.

Automation is power! You can literally trade an unlimited number of strategies:

4. Backtesting and optimization

After coding your trading algo, you have to backtest on historical price data. Some platforms offer a strategy tester that allows you to test the algo to see how it would have performed if it was deployed in the past.

We are great fans of backtesting. Data-driven strategies perform well if done correctly, and it gives you power in the form of automation. The best proof is Jim Simons and the Medallion Fund, which has accomplished 66% annually.

From the results of your backtesting, you will know whether to vary the parameters of the strategy and test again, in a process known as optimization. While optimization may lead to curve fitting, it enables you to find the best parameters, such as entry and exit, for the strategy. Note that past performance is not indicative of future performance, so don’t rely so much on the result of backtesting.

We have already written an article that explains why backtesting works. Also, we have covered why strategy optimization is good done correctly.

5. Forward testing

While backtesting helps you to know how the strategy performed in the past, forward testing helps you to know whether the strategy still performs well in the current market condition.

But one problem with forward testing is that it is time-consuming, especially if the strategy uses higher timeframes which take time to have trade setups. Forwarding testing may be best for scalping strategies that can have tens and hundreds of setups in a day/week. For swing trading and so on, you may have to rely on out-of-sample testing.

If you want to dig deeper, please read our take on out of sample testing and walk forward.

Which trading strategy is the most profitable?

From our experience, mean reversion strategies tend to be the most profitable. One of the reasons for that is that the market moves sideways more of the time than it trends. Even when it trends, it moves in waves that often oscillate around its moving average. Thus, mean reversion strategies, which try to exploit that tendency of the price to oscillate around its mean, offer the best chances of profiting from the market.

There is no way to know the most profitable trading strategy without testing all the strategies to rank them. Moreover, some strategies work better in some markets than in others. You have to backtest the strategies in different markets to know the market it works best in.

There are different ways of exploiting the mean-reverting nature of price. Some of them involve the use of overbought/oversold indicators like the Bollinger Bands, RSI, and stochastic. There are also mean reversion strategies that use only price action.

Profitable trading strategy example

A good example of a mean reversion strategy is the 5-day low in the S&P 500. As the name implies, the strategy is made for the S&P 500 index, which can be traded as S&P 500 index e-mini futures or SPDR S&P 500 ETF (SPY). Published in 2012, the rules of the strategy are as follows:

  • If today’s close is below yesterday’s five-day low, go long at the close.
  • Sell at the close when the two-day RSI closes above 50.
  • There is a time stop of five days if the sell criterium is not triggered.

It can hardly get any simpler than this!

A $100, 000 capital compounded from 1993 until July 2021 shows this equity curve (the graph on the bottom is the drawdown):

Profitable trading strategy

It shows that such a simple work pretty well over many decades, but it’s no guarantee it will continue.

Let’s go on to backtest an even better strategy:

Profitable trading strategies (backtest and performance)

Let’s show you another example of a trading strategy that is backtested. It’s strategy number 4 in our strategy library and has worked well for 30 years.

It consists of two variables/indicators for entry and a straightforward exit criteria. The strategy has worked remarkably well for over 30 years. We first published this strategy on our website in 2012, but since then we have put it behind a paywall.

Let’s backtest the strategy. We first start with backtesting S&P 500 (SPY):

Profitable trading strategy backtest

As you can see, it has been consistent with low and short drawdowns (see lower pane – blue lines). Despite being invested only 13% of the time, it has generated 7.8% annual returns compared to buy & hold’s 9.7% (dividends included).

The average gain per trade is 0.85%, leaving much room for slippage and commissions. Commissions are low (we pay 0.025% for a round trip), and slippage in liquid instruments is also very low (sometimes even positive). A few years back, we looked at slippage from live trading compared to our backtest. The result was that slippage is mostly a non-issue in liquid instruments.

Let’s backtest the same strategy on Nasdaq 100 (QQQ):

The most profitable trading strategy example

Pretty nice! It works even better on QQQ than on SPY: annual returns increase to 13.1% (buy & hold is 8.6%), drawdowns are smaller, and time spent in the market is 14%. The average gain per trade is 1.35%.

If we look at the risk-adjusted return, it is 94%. We calculate the risk-adjusted return by dividing the annual return on time spent in the market (13.2% dividend by 0.14). We believe this is a good performance metric for a strategy that spends most of the time on the sidelines.

Does the strategy work on other assets?

Let’s try the same trading rules on bonds (long-term Treasuries – TLT):

Profitable trading strategy performance and metrics

The result is not as good as on SPY and QQQ, but still decent. A bonus with TLT is that it generates signals that often are uncorrelated to stocks, thus offering some diversification benefits.

As a rule of thumb, the strategy works on most stock-related assets. However, it doesn’t work so well on forex and commodities. This is to be expected. Our strategy is based on mean-reversion, which is not typical in forex and commodities. You’ll never find a strategy that works on most assets.

You might want to click if you are looking for an investment strategy.

Profitable trading strategies – conclusions

To find a profitable trading strategy, you need to backtest. We have been trading full-time for over two decades, and all successful traders we have worked with have been very systematic. Thus, we strongly recommend backtesting if you want a profitable strategy. How else do you know if the strategy is working? Guessing?

FAQ:

Why is having a high winning rate not enough for a profitable strategy?

A high winning rate alone doesn’t guarantee profitability. Profits can be wiped out if losing trades are significant. A profitable strategy needs a balance between a reasonable winning rate and a sizeable gain per win to remain consistently profitable.

How do you calculate the reward/risk ratio in a trading strategy?

The reward/risk ratio is the ratio of what is gained per winning trade to what is lost per losing trade. For example, a 3/1 reward/risk ratio means the profit target is three times the size of the stop loss. Finding the optimal ratio is crucial for strategy success.

What is positive expectancy in a trading strategy?

Positive expectancy refers to how much money, on average, one can expect to make or lose for every dollar risked. A positive value indicates the likelihood of the strategy making money. Expectancy is calculated as (win rate X average win size) – (loss rate x average loss size).

What makes a trading strategy profitable?

A trading strategy becomes profitable when it consistently generates more gains than losses over time.

How to identify high-profit opportunities in trading?

Identifying high-profit opportunities in trading involves analyzing market trends, conducting thorough research, and staying informed about economic indicators and news events that could impact prices. Additionally, employing technical analysis techniques such as chart patterns and indicators can help pinpoint potential entry and exit points for trades with favorable risk-reward ratios.

What are the key components of a successful trading strategy?

Key components of a successful trading strategy include robust risk management, thorough market analysis, clear entry and exit criteria, disciplined execution, continuous evaluation and adaptation, and adherence to a well-defined trading plan.

Which markets offer the most profit potential for traders?

The markets that offer the most profit potential for traders vary depending on their expertise, risk tolerance, and market conditions. However, traditionally, highly liquid markets such as foreign exchange (Forex), stocks, and commodities tend to offer significant profit potential due to their volatility and trading volumes.

How to manage risk while pursuing profitable trades?

To manage risk while pursuing profitable trades, it’s essential to employ strategies such as diversification, setting stop-loss orders, conducting thorough research, managing position sizes, and continually reassessing and adjusting your approach based on market conditions.

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