A strategy can be statistically profitable, with positive mathematical expectancy, an adequate Sharpe ratio and controlled drawdowns, and an investor in it can still lose money. The cause is usually not the algorithm. It is the timing and the behaviour of the investor.
The strategy’s own return and the return an investor actually earns are two different numbers. The first is measured over the whole period. The second depends on the day the money arrived, the day it left and what happened in between. This article sets out the six mistakes that most often separate the two.
1. A horizon shorter than the strategy’s cycle
Algorithmic strategies, trend-following and multi-system ones in particular, earn their return over a long period. They also have stretches of stagnation, sideways markets and drawdowns, and these are a normal part of the process.
An investor who arrives with a horizon of three to six months and expects a steady, linear return will be disappointed when the market enters an unfavourable phase. Algotoria publishes a minimum investment horizon of one year, so that the strategy can pass through a full range of market conditions. A horizon shorter than the strategy’s statistical cycle judges a long-run process on a short sample.
2. Entering after the best run
The classic mistake is to invest after seeing a strong equity curve. A strategy has an excellent year, attention builds, money arrives at a local peak, a natural correction or drawdown follows, and the investor sees a loss within weeks of entering.
The pattern is a behavioural one: past returns are extrapolated into the future, although markets move in cycles. The investor in effect buys the strategy at its peak price.
3. Leaving during a drawdown
Drawdowns are part of any systematic trading. Psychology works against the investor here: greed on the way up, fear on the way down.
An investor who leaves at the point of maximum discomfort locks in the loss at the moment when the expectancy of the strategy begins to improve. The strategy then recovers without that investor. The Risk Disclosure Notice sets out the drawdowns that Algotoria’s strategies can produce.
4. Switching between strategies
Another common pattern is repeated switching. Strategy A is in a drawdown, so the investor moves to Strategy B, which has just done well. A few months later the cycle repeats.
The result is a systematic sale of the drawdown and purchase of the past performance. Over several cycles this is an effective way to erode capital, because every switch crystallises a loss and restarts the clock.
5. Misreading the risk and return profile
Many investors look only at the average return. The profile also includes the depth and duration of drawdowns, volatility, the frequency of negative months and the correlation with the wider market.
A strategy can have positive expectancy and an uneven return profile at the same time. An investor who is not prepared for that equity curve will find it hard to stay invested through it.
6. No plan and no rules
A professional approach needs four things in place before the first deposit: a predefined horizon, a clear understanding of the acceptable drawdown, fixed rules for adding and withdrawing capital, and diversification across strategies.
Without them, an account under professional management turns into emotional trading carried out through an intermediary. The frequently asked questions explain how the drawdown budget works and what redemption involves, which are the two parameters a plan should fix first.
The conclusion
In algorithmic strategies, the part that fails is more often the investor’s behaviour than the model. A strategy asks for time, discipline, patience and an understanding of the statistics behind it.
If the investor cannot hold through the normal phases of the market, even a profitable algorithm will not protect the capital. Behavioural resilience is therefore part of the long-run result, alongside the code.