How To Build A Diversified Portfolio Of Trading Strategies (Why You Need It As A Trader) – [Two Examples]
It would be best if you built a portfolio of trading strategies that differ in markets, time frames, and types. Why? Because you want to have a portfolio of trading strategies that both complement each other and make the portfolio diversified and uncorrelated. To do this, you preferably need to test and simulate on a trading platform.
The most important task of a quantitative trader is to find trading edges and turn them into good stand-alone strategies. However, many traders neglect to test how those strategies perform together as a portfolio of trading strategies (the other strategies you might have). Just as a long-term investment manager puts together a portfolio of stocks, a short-term trader must have a portfolio of trading strategies. Moreover, he or she must evaluate how the strategies perform together as a portfolio. An investor doesn’t compose a portfolio or basket of only oil stocks. The investor looks for stocks that both diversify the portfolio and complement it. A trader needs to have the same mentality.
Does your trading strategy complement your portfolio of strategies? That is the first thing you should address if you consider adding more trading strategies. It’s impossible to predict a stock’s future value; likewise, it’s impossible to know the future predictive power of a quantified trading strategy. This is the reason why you want to have a portfolio of many strategies. Some strategies will gradually deteriorate, some might blow off spectacularly, and others perhaps perform much better. You need to diversify your strategies just as you diversify your stock holdings.
Perhaps surprisingly, many strategies don’t complement each other because they are too similar and overlapping. Thus, you might add more losing trades to your already winning trades if you add a trading strategy that has the same attributes as the existing ones.
How do you complement or add value to a portfolio? This article shows how via some naive examples.
First, let’s start by explaining what we mean by a portfolio of trading strategies:
What is a portfolio of trading strategies?
A portfolio of trading strategies is several short-term trading strategies traded simultaneously. For example, you might have 5 different trading strategies, but how do you trade them? Do you allocate 100% of the equity to the first strategy that gives a buy signal, or do you allocate 20% to each strategy? You need to simulate such scenarios before you start trading.
Furthermore, you need uncorrelated strategies. The key to successful trading is to understand correlation in trading and understand how the strategies interact in both good and bad times.
The most difficult task as a trader, alongside finding new strategies, is finding strategies that work well together. Unfortunately, two strategies that work well on their own don’t necessarily translate into an improved “portfolio” of strategies for many different reasons.
Why is the composition of the trading strategies important?
The composition of the trading strategies is important because they might not complement each other well. There could be several reasons for that, like for example:
- You have overlapping trades in the same instrument/asset class.
- The strategies might correlate too much.
- Strategies in the same instrument might not overlap, but the winning trades might overlap a bit, making the average gain substantially less.
- The types of strategies are too similar (only mean reversion, for example).
- You are only trading one market direction (long or short).
- You are only trading one asset class (stocks for example).
Any addition to you existing strategies must be complementary:
Does your trading strategy complement your portfolio of strategies?
An additional reading strategy needs to complement the ones you have and preferably increase returns while it might also mitigate risk. Remember, even mediocre trading strategies can improve portfolio performance metrics if they mitigate risk, something Mark Spitznagel has explained well.
Instead of spending (wasting?) time on finding something perfect, most traders are much better off trading “mediocre” systems that might complement each other.
Why you shouldn’t spend too much time on one trading strategy
We know many traders who spend years fine-tuning just one or a few strategies. They are trying to hit the jackpot by adding more variables or filters for their quant strategies. But we believe this is a very bad idea. It’s a bad idea because:
- You end up curve-fitting the strategy to the past and lose prediction in the future.
- All strategies, sooner or later, end up barbed away or become victims of changed market behavior.
- Strategies that don’t perform perfectly on their own might work well in a portfolio of trading strategies.
We believe in this: It’s better to have a portfolio of many sub-optimal trading strategies than one or a few “perfect” strategies.
Why have a portfolio of trading strategies?
You should have a portfolio of trading strategies to smooth your returns. You want a steady rising equity curve from the left to the right (what is a good equity curve?) without too many long and deep drawdowns.
The most important factor in quantified trading is having unrelated strategies, ie. strategies that don’t correlate with each other. That is, of course, no easy task and requires a lot of work.
For example, finding strategies that don’t correlate among stocks is pretty difficult. Stocks move up and down mostly in tandem, and thus, trading a mean-reverting strategy on a basket of stocks gives many signals at the same time. It would be best if you diversified away from stocks to avoid this.
Another obstacle is that during panics, the correlation among all asset classes increases. During a short-term panic, as we saw during the GFC in 2008/09 and the Covid-19 in March 2020, most assets move together. The good thing is, if there is a long-term bear market, like we saw during 2000-2003, the correlations are much weaker, something we covered in the anatomy of a bear market.
How can you make uncorrelated trading strategies?
It would be best if you looked at different factors to differentiate your strategies. Let’s look at some factor you should consider:
Trade different asset classes and markets
The best way is to look at different markets. Commodities, for example, often go the opposite way of stocks. Thus, one of the first things you should do is to look at different markets, such as commodities (gold, oil), bonds, cryptos, etc.
Make sure you trade different time frames
Trading different time frames in trading can also be helpful. Day trading, for example, should not correlate much to the market’s overall trend.
Trading books like to mention you should always go with the underlying trend, but much of this is nonsense and has never been tested in any quantitative way. The fact is that longs could be fantastic for short-term gains in a bear market – it all depends on the time frame. For example, did you know that the most powerful up days come in a bear market? Please see the stats we provided in the link above about the anatomy of a bear market.
Type of trading strategies: Mean-reverting, trend-following, or momentum?
Mean-reversion means a move in the opposite direction follows a move either up or down. Stocks are typical very mean-reverting in the short term, and this is how you create a mean-reversion strategy
There are three main ways to trade the markets: mean-reverting, trend following, and momentum. Mean-reverting and trend following are opposites: when one is not working, the other should absorb or offset the losses.
Trend-following strategies are very difficult to trade because they have a low win rate. Thus, you need to prepare to absorb many small losses while waiting for the one big winner that recoups all the previous losses.
Very few traders can withstand many losses in a row before they either abandon the strategy or start tinkering, usually at the worst moment.
This is precisely why you shouldn’t be either a trend follower or a mean-reverting trader only. You can use both strategies. There is no bad or good type of strategy, you have to be open and adaptive and use all the options there are in the markets.
We can add breakouts to the list, however, breakout strategies are quite similar to trend-following strategies, and sometimes you can’t separate the two. Both trade on market strength and assume that once momentum has picked up, the market will likely continue in the dominant direction.
Breakouts refer to the price when it breaks out of a range or a price level, and you want to be long or short this breakout in anticipation of further movement in the same direction. You define the breakout yourself, but breakouts might be a bit complicated to formulate by code and exact math.
Make sure you trade both long and short strategies
Some investment managers focus only on the short side. The reason is simple: even if short, for example, has a CAGR of 2% annually, it might offer tremendous value in a portfolio because of risk mitigation, something described very well by Mark Spitznagel. It gives downside risk reduction and, at the same time, might contribute to a better overall CAGR of the portfolio. Short selling is difficult, but it adds lots of value to diversification.
You must understand the difference between the equity curve of a single strategy and an overall portfolio. An “ugly” strategy might be the medicine your portfolio of trading strategies needs!
As a trader, you need to think very much the same. Unfortunately, finding short strategies is challenging. In most markets, you can’t reverse long strategies and expect them to perform well on the short side.
Strategies deteriorate or get arbed away
One piece of advice is something you will never read on the internet:
Strategies stop working!
If you find one good trading strategy you can be pretty sure it will stop working at some point in the future, or at least have a long period where it performs badly. We have covered this in a separate article called why trading strategies are not working.
No matter how prepared you are, markets change and evolve. This is yet another reason why you should have an arsenal of strategies that vary in markets, types, and time frames. Not all strategies will stop working at the same time.
You have to look at failed strategies as the cost of doing business.
Why do strategies ultimately stop working? There are many reasons for that:
Curve fitting
No matter how much you try to avoid curve fitting, it’s inevitable that you, to a certain degree, curve fit. Most of us backtest many ideas and strategies, and some perform well simply by chance. If you do proper out-of-sample backtesting, this fallacy can greatly be avoided.
Avoiding many variables in the strategy is also a good start to avoid curve fitting. You must always have in the back of your mind that most movements are completely random and just noise. Ask yourself this: Why should the strategy work? Is there any logic?
If you test many strategies, some are surely just a product of luck and noise.
Trading strategies ultimately deteriorate
Strategies usually deteriorate over time. Why does this happen? It’s inevitable because markets change, and the ever-changing market cycles take years to develop. And many get arbed away:
Statistical arbitrage
Let’s use an example from the investment world:
Factor investing has gained a lot of attention over the last 5-6 years. We believe many of these strategies will likely be unprofitable over the next decade.
Take low-volatility stocks, for example. Because of their popularity, their earnings multiple has increased a lot. This type of investing attracts a lot of capital and thus getting “crowded”. When something gets too crowded and too popular, it stops working. Think of strategies the same way.
Some years ago, we wrote an extensive article about how to approach day trading. We recommend reading how to make money day trading to make you understand our thinking.
An example of two trading strategies and how they perform together
Let’s compare two very simple strategies and look at how they perform together.
The first strategy is this and reads like this in plain English:
- Buy when the two-day RSI indicator is below 15. Read here for how the RSI indicator works.
- Enter at the close.
- Sell when today’s close is higher than yesterday’s high.
- Exit on the close.
The strategy performs like this on the S&P 500 (100 000 compounded from 1993 until today):
And the equity curve looks like this:
Not bad for being invested 24% of the time!
But let’s look at another somewhat similar strategy, i.e. mean-reverting. The trading rules are simple:
- The strategy goes long when today’s close has dropped more from yesterday’s close than the 100-day average difference of the high minus the low.
The strategy is, of course, very similar to the RSI strategy and returns a pretty similar result:
But how do these two strategies perform together? Let’s assume you want to trade both strategies but only have one position in SPY at all times. Hence, you only trade when you have no position; you don’t enter an additional position when you are already long.
Combining the two strategies, we get this result:
All parameters deteriorate – the average per trade and the profit factor both decline while the time spent in the market increases from 24% to 31%.
The strategies are very similar and have a lot of overlapping trades.
But that is the point of showing these two strategies: you need to have different strategies. You can’t add reasonably similar strategies; you need to complement the portfolio.
Let’s make a second example showing two mean reverting strategies:
Portfolio of trading strategies example: Two mean-reverting strategies
Let’s make an example to easier illustrate what we mean. On our landing page of free trading strategies we have backtested several of Larry Connors’ trading strategies, taken from his book called High Probability ETF Trading, published in 2009.
Let’s pick two of Connors’ strategies:
How do these strategies perform together? Both strategies are tested on a basket of different ETFs:
DIA, EEM, EFA, EWH, EWJ, EWT, EWZ, FXI, GDX, GDXJ, GLD, ILF, IWM, IYR, QQQ, SPY, TLT, XHB, XLP, XLE, XLF, XLI, XLP, XLV, AND XME.
The first strategy, multiple days up and down, returns these numbers:
The second strategy, 3-day high/low, returns these numbers:
As you can see, both strategies perform reasonably well and have ending capital of 368,000 and 322,000. In other words, they yield the same results (in the ballpark, at least).
If we add the two strategies together, the strategy and system performance metrics look like this:
If we trade both strategies (taking only one trade simultaneously), the combined result is worse than if you only traded the first strategy!
Example 3: Add one strategy to an existing portfolio
Let’s assume you already have a few strategies that you are trading and that they have the following equity curve combined:
The average is 0.3% over more than 1,500 trades since SPY’s inception in 1993. The above equity curve is based on overnight trading strategies.
Then you come across a promising mean-reverting strategy that has the following equity curve (and you consider adding it to the other strategies):
The average gain is 0.33%, and the win rate is 65%.
What happens when you add the extra strategy together with the other strategies? Something surprising happens – the trading metrics deteriorate:
The last strategy makes your overall portfolio perform worse despite having such good trading statistics. The average gain per trade goes down from 0.3 to 0.26%, and the overall equity is reduced.
Why does this happen?
It happens because most of the trades are overlapping. The extra trades you get are the ones that are more likely to turn out to be losers.
This is why you must always backtest how your strategies perform together as a portfolio overall.
How many strategies do you need to succeed?
There are, in practice, no limits on how many strategies you can run via automated software. We at Quantified Strategies use Amibroker and Tradestation, and the most significant limitation is our imagination and creativity. For example, at the most, we have run about 75 strategies via both platforms without any problems.
Why Build A Portfolio Of Quantified Trading Strategies – conclusion
A portfolio of trading strategies might smooth your equity curve and make you avoid behavioral mistakes like abandoning trading or acting irrationally during a market panic. You need an arsenal of strategies to keep you diversified.
True inefficiencies don’t happen often. A strategy doesn’t need more than 10-20 trades per year to be fruitful. If you for example have 20 strategies that are all somewhat different in markets, time frames, and types, you generate about 200-400 trades per year. As a swing trader that should get you a good start.
However, it takes time to build a portfolio of trading strategies. Take your time and be patient. Make sure you enjoy the process!
FAQ:
– Why is it essential to have a portfolio of trading strategies?
It’s essential to have a portfolio of trading strategies because of diversification and risk management. It helps mitigate the impact of poorly performing individual strategies and ensures stability in overall trading performance.
– What happens if you have overlapping trades in a portfolio of trading strategies?
Overlapping trades in a portfolio of trading strategies can lead to increased correlation and reduced effectiveness of the portfolio. It’s essential to ensure that strategies don’t simultaneously generate signals for the same instrument.
– Why is diversification important in trading strategies?
Diversification in trading strategies is crucial to spread risk and avoid over-reliance on a single strategy. A diversified portfolio helps manage the impact of strategy failures and market changes.
Why is it important to ensure that trading strategies complement each other?
It’s important to ensure that trading strategies complement each other because when strategies overlap or are too similar, they often react similarly to market conditions.
In times of adversity, this can lead to a concentration of losses. Complementary strategies, on the other hand, can act as a hedge, mitigating risk during challenging market scenarios. Ensuring that trading strategies complement each other is crucial to avoid overlap and potential negative impacts on your overall portfolio.
How does diversification play a role in short-term trading strategies?
The role of diversification in short-term strategies lies in developing strategies that complement each other, rather than relying solely on individual strategies. Short-term traders require a diverse portfolio of uncorrelated strategies to achieve success, highlighting the importance of understanding correlation in trading.
How does combining two trading strategies affect overall performance?
Combining two trading strategies affects overall performance well as long as they are complementary. Beyond risk management, complementary strategies have the potential to maximize returns. When one strategy may underperform, another might shine, balancing out the overall performance of your portfolio. Combining two strategies may not necessarily improve performance; assessing their interaction and potential impact on the overall portfolio is essential.