Trading system design and optimization

Usually, the formation of a trading system needs to go through three stages. The first is the generation of trading ideas, which can be a complex theory, a simple technique, or any other idea that you think can be profitable. The second is to transform the idea into a corresponding strategy, specifically to clarify the core operation arrangements such as entry, stop loss, and take profit that are suitable for the strategy. Finally, the formation of a complete system, that is, on the basis of the above, all elements are solidified into clear trading rules, forming a replicable trading system. The so-called replicable means that anyone who operates according to the signals of this system has no difference in performance.

The most crucial sign of a successful trading system is that its performance is generally large profits and small losses over a long period of time, at least to be able to pass the test of historical conditions. However, the author believes that this is far from enough, and further important analysis of the trading system in four dimensions is required to determine the profitability of the trading system and identify future improvement directions.

The first dimension is the winning rate of the trading system, that is, the proportion of the number of profitable transactions and the number of losing transactions in the total number of transactions.

The second dimension is the profit-loss ratio of the system, which is the ratio of the average amount of money won each time to the average amount lost each time.

The third dimension is the friction rate of the system. Everyone knows that futures are zero-sum transactions, and each transaction requires payment of various fees, including handling fees. No matter whether the transaction is profitable or lossy, it cannot be avoided. This cost rate is the friction rate.

The fourth dimension is frequency, which refers to the average number of trading signals issued by the system over a period of time, such as a year.

Now we can analyze the correlation between the above four dimensions and the profitability of the trading system.

First of all, is a high win rate necessarily profitable? Not necessarily. In extreme cases, such as 99 consecutive 100% profits, as long as you encounter a 100% loss, even if you have a 99% win rate, the final result will still be zero.

Secondly, does a high profit-to-loss ratio necessarily make a profit? Not necessarily, such as an average win of 3 and a loss of 2, but if an average win is accompanied by 2 losses, it is still a loss after offset. Therefore, the winning rate must be combined with the profit-to-loss ratio to form a common mathematical expression of the trading system, namely: total profit = number of profits × average profit amount - number of losses × average loss amount.

Once again, there is the friction rate, which is the amount of money that each transaction costs. This is an absolute consumption, so of course, the less the better.

Finally, there is frequency, which is how long it takes to make a trade on average. If a profitable trading system takes one to two years to capture a trading opportunity, it is by no means a good trading system.

Next, let's analyze two basic types of trading systems using a four-dimensional evaluation method.

The author believes that there are two basic types of trading systems, one is an oscillatory trading system based on oscillating market conditions, and the other is a trend trading system based on trending market conditions.

Oscillator trading systems strive to maximize profits in volatile markets, while at the same time trying to avoid possible losses in the event of a trend, which is the opposite of trend trading.

From the above four dimensions, we will find that compared with trend trading systems, oscillatory trading systems usually require a higher winning rate, generally greater than 50%; a relatively loose profit-loss ratio, which can be below 1; due to the high trading frequency, a very low friction rate is required, that is, this type of system needs to accumulate profits through a large number of transactions, and extreme cases such as intraday speculation require minimization of friction losses; correspondingly, the capital curve of oscillatory trading systems is relatively smooth, with fewer retracements. Trend trading, on the other hand, usually requires only a low win rate, which can be less than 50% or even lower, but it must have a high profit-loss ratio, such as 3, 2, or even 1, or higher, and a relatively loose friction rate. Because the trading frequency is relatively low, the transaction cost is higher, and the capital curve may have a large retracement of a certain proportion. If someone wants to ask, is it possible to design a trading system that combines the two, I think it can be achieved, but the structure is more complicated.

We know that parameter optimization and fund management are two important ways to improve the performance of trading systems. Next, we will explore the key points of performance improvement by combining the characteristics of the two basic types of trading systems.

The first is the relationship between system profitability and parameter optimization. Even if a system passes the historical market test under certain parameter conditions, it may not be profitable in reality. The problem is most likely to lie in two links. One is that the prior cannot be realized, which means that the idealization of the test transaction cannot be fully realized in reality. For example, the position squaring in the test may be a stop in reality, or it is related to the specificity of the market selected in the test period. The second is that the posterior cannot be realized, which means that the test transaction requires very precise operation discipline, but the actual implementation cannot be fully mechanized due to the operator's reasons, resulting in the profit system becoming a loss. The first case can be optimized mainly by adjusting the parameters, while the second case requires adjusting the system to achieve harmony between the human and the system. For the same strategy, different parameters may determine the profit and loss of the same system, and parameter optimization plays a very important role.

Secondly, the relationship between system profitability and fund management, where fund management mainly refers to position control. Because the oscillatory trading method mainly accumulates profits through multiple small profits, it requires a large position at the beginning in most cases, and the stop loss control is very strict when the trend may come, so the focus is on parameter optimization for oscillatory trading systems. Trend trading can tolerate more trial and error, the purpose is to make profits run, so relatively speaking, fund management or position management has more room to play in trend trading systems.

The author believes that for the trend trading system, on the one hand, it is necessary to improve the winning rate of the transaction through parameter optimization, and then improve the profit margin of the system. In particular, each variety may have different optimal parameters, and sometimes the market for a period of time will also have special optimal parameters. Therefore, it is necessary to carry out appropriate optimization; on the other hand, it is also necessary to improve the profit margin of the system by improving the profit-loss ratio. Sometimes the role of fund management, that is, position management, is even more important than parameter optimization. The key lies in whether the operator can distinguish which situations in the trend trading system are more likely to have strong trends, and which transactions will be stopped by the system. Only by deeply understanding their trading system and making corresponding improvements can the performance of the trading system be continuously improved.