We recently introduced a new feature on algotest.in called Portfolio, which allows you to backtest multiple strategies together. In this blog, we’ll backtest a sample portfolio of multiple strategies, and also show you how to avoid common pitfalls when using this feature.
What do we mean by Portfolio on AlgoTest?
A portfolio is a collection of strategies. On AlgoTest, you can save strategies by inputting a strategy and clicking on “Save Strategy”
Once you’ve discovered some profitable strategies (click here to see example), the next step is to combine them in a portfolio.
To build a portfolio, click on Portfolio, then “Create new portfolio”. You can select the strategies you want to include in your portfolio, and finally give your portfolio a name. On clicking "Create", your portfolio will now be ready.
Finally, you can click on the portfolio and then run "Start Backtest". This will run a combined backtest for the entire portfolio. After this step, you will get an aggregate result, along with a correlation matrix.
What is a correlation matrix?
A correlation matrix shows the historical correlation coefficients between two trading strategies. This helps traders understand how different strategies are related. Understanding these relationships is important for building a diversified portfolio that reduces risk and maximizes returns by combining strategies that are not closely linked. By examining the correlation matrix, you can decide which strategies to combine and how to balance your portfolio for the best performance. Each cell in the matrix represents the correlation between two strategies, with values ranging from -1 to 1.
Here's a breakdown of what these values mean:
- Strong Positive Correlation (Close to 1): Indicates that the two strategies tend to perform similarly. When one strategy makes a profit, the other is also likely to make a profit.
- Strong Negative Correlation (Close to -1): Indicates that the two strategies tend to perform in opposite directions. When one strategy makes a profit, the other is likely to make a loss. We need to have a negative correlation between our strategies to have a smooth equity curve.
- No Significant Correlation (Around 0): Indicates that there is no predictable relationship between the performance of the two strategies. Their movements are largely independent of each other.
How to view the correlation matrix?
To access the correlation matrix for your portfolio, please follow the simple steps given below.
- First, you should backtest a portfolio. To do this, go to the portfolio section and click on the "Run Portfolio" button, as shown in the image below.
- Now, scroll down and click on the "Show Correlation Matrix" button located below the backtest report, as shown in the image below.
- It will display the correlation matrix as shown in the image below. You can click on the "Show only checked" button to display the correlation matrix only for the selected strategies in the portfolio.
How to Analyse a Correlation Matrix?
Understanding the correlation matrix is crucial for building a well-diversified portfolio. Using the correlation matrix, you can create a portfolio that can provide good rewards with less risk. Let's understand how the correlation matrix works.
Matrix Layout:
Each cell in the matrix represents the correlation coefficient between two strategies. The diagonal elements are always 1, indicating a perfect correlation of the strategy with itself.
Understanding the Values:
0 to 1
As the value increases from 0 to 1, the correlation between two strategies also increases. This means that the higher the value, the more related the strategies are to each other. A high correlation value indicates that if one strategy is making a profit or a loss, the other will also likely to make a profit or a loss on the same day.
-1 to 0
As the value decreases from 0 to -1, the correlation between two strategies also decreases. This means that the strategies are highly unrelated to each other. If one strategy is making profit or loss on a day, then the other strategy will likely do the opposite, i.e. it will make a loss or profit for that day.
0 correlation
Zero correlation means there is no relationship between the strategies. Their movements will be largely independent of each other.
Identifying Relationships:
Look for strategies with lower positive correlations or negative correlations. For example, in the image below, you will see a strategy named “finnifty youtube” that has a correlation of 0.03 with a strategy named “finnifty expiry: Afcp1”. This means that these two strategies are not very closely related to each other, which is beneficial for portfolio diversification.
In the image below, you can observe that the strategy named "Finnifty Exp: maf" has a negative correlation of -0.15 with the strategy named "Finnifty Exp: Afcp1". Therefore, it would be a beneficial strategy to add to our portfolio for diversification.
So what does this mean?
Correlations are dynamic and change with the market environment. One major implication here is that the historical profitability of your backtests could be implicitly dependent on this historical correlation. And if future correlation is different from historical correlation, you run the risk of losses.
Furthermore, correlations between strategies can change over time. So any diversification benefit you may derive from these (un)correlated strategies can disappear pretty quickly as the correlation coefficient changes!
Here is a tweet thread that highlights this point:
https://twitter.com/rogue_hft/status/1507712462438641665
History
In fact, one of the greatest blowups in trading history can be attributed to precisely this breakdown of historical correlation. Here is a quote from the wikipedia article I archived sometime back:
The profits from LTCM’s trading strategies were generally not correlated with each other and thus normally LTCM’s highly leveraged portfolio benefited from diversification. However, the general flight to liquidity in the late summer of 1998 led to a marketwide repricing of all risk leading these positions to all move in the same direction. As the correlation of LTCM’s positions increased, the diversified aspect of LTCM’s portfolio vanished and large losses to its equity value occurred. Thus the primary lesson of 1998 and the collapse of LTCM for Value at Risk (VaR) users is not a liquidity one, but more fundamentally that the underlying Covariance matrix used in VaR analysis is not static but changes over time.
Demo
Finally, here is a video we just released demonstrating the portfolio feature. In this video, we will backtest multiple strategies together using our portfolio feature.
https://youtu.be/0lfx8NtK0cQ
