Build Your First Trading Strategy Portfolio

Trader Libor: Building the first portfolio

Building your first portfolio of algorithmic trading strategies is one of the most important steps on your journey to consistent profits. In previous articles, we created and tested three types of strategies and their variants: Simple breakout strategy, Breakout limit strategy, and Buying dips strategy. Today we will combine them into our first small portfolio.

Why Building Your First Portfolio Is the Real “Holy Grail”

Regardless of what our individual strategies look like — whether they have a perfect equity curve or not — our future trading success will never depend on the performance of individual strategies, but on the overall portfolio of many uncorrelated strategies. As I once read, the only “holy grail” in trading is the diversification of strategies in the portfolio.

Only a portfolio composed of different strategies will protect your investments even in periods when individual strategies fail. Building your first portfolio is like assembling a hockey team at the World Cup — individuals can be great, but if they don’t play together as a team, they have no chance of winning.

Risk Normalization Before Building the First Portfolio

First, we test all strategies again with a different money management. The aim is to normalize the risk so that all strategies have the same starting position.

As a reminder: we have 10 strategies with different logic and different exits — namely Breakout (4x), BreakoutLimit (3x) and BuyDip (3x). The total starting capital is $100,000, with each strategy being assigned a risk of 10% of the account. We then retest the strategies one by one.

Creating a Gross Portfolio: Correlation Analysis

Once we have the strategies tested, we create a rough portfolio to visually assess the similarity of the strategies and calculate their correlation. This is a critical step when building your first portfolio.

We look at the correlation between the strategies on a monthly basis (Correlation by Month) and separately analyze their correlation at losses (Correlation by Loss). I only use Loss because I don’t mind similar gains, but I don’t want to have similar losses.

The correlation table looks like this:

Portfolio Optimization: Eliminating Correlated Strategies

From the correlation table we can see that there is a high correlation between Breakout_var03, Breakout_var04, BreakoutLimit_var03A and BreakoutLimit_var03B. It is quite logical, because for these two Breakout strategies we only changed the number of traded shares and for the BreakoutLimit strategies we only changed the entry price.

So we eliminate two strategies — e.g. Breakout_var03 and BreakoutLimit_var03A — and create a new portfolio.

Upon further analysis, we find that there is still a high correlation between BreakoutLimit_var03B and Breakout_var04. Since we have more breakout strategies in the portfolio, we remove Breakout_var04 and create a new portfolio.

The table already looks beautifully green. We could still eliminate one BuyDip type strategy where correlation is higher than 0.3. Finally, we eliminate BuyDip_var02 and create the last 4th portfolio.

In the end, we eliminated four of the original 10 strategies and created a final portfolio with low correlations. The graph of the individual strategies in the portfolio:

Statistics of the final portfolio:

Benchmark Comparison: First Portfolio vs S&P 500

The final comparison shows a clear difference between passive investing (holding SPY for 40 years) and active trading with our portfolio. The table on the right shows the statistics of both the portfolio and the benchmark at the same % drawdown — and our first portfolio clearly wins.

Summary: Your First Portfolio Is Just the Beginning

Building your first portfolio is like selecting players for the World Cup. The best strikers, defenders and great goalkeepers must be selected. Everyone has a different role in the team, but overall they have to form a strong invincible team.

And it is the same with the selection of strategies for the portfolio. We choose a different strategy for each market deviation so that the overall portfolio is strong, robust, and resistant to large market fluctuations.

We have completed the basic structure. Next time we will focus on fine-tuning money management and then deploying the portfolio to a test account.

Libor Štěpán