I decided to write a short series on how to do the monitoring of your trading performance. This was originally developed for algorithmic trading of futures, but can also be used for other trading stiles.

After this article series you will know how to monitor your trading on strategy and portfolio level and how to analyze the data. This will enable you to know whether your strategies are working well and your portfolio is developing as it should according to your back tests.

The series will contain the following articles:

  • Monitoring trading performance of individual strategies
  • Additional statistics (maxQL and ITuW)
  • Monte Carlo drawdown
  • Monitoring the trading performance of a portfolio of strategies
  • How to handle strategies that are not IDD (independent and identically distributed) or have autocorrelation

The basics – documentation of your trading performance

Before you can analyze the data of your trading you first need to document it. This can be done either automatically or manually. I currently trade 15 day and swing trading strategies. Thus, on average I have 10 orders (exit or entry) filled in a day. Since this is still a small number and I like to check the trading performance every day, I still do this by hand.

You need to note down two numbers for each trade: (1) the filled price of the trade, and (2) the back-tested price of the same trade. In case you use Tradestation you can get the filled price from the TradeManager – Orders Tab. For an example let’s take the strategy that runs on the Japanese Yen (JYZ20), there the Filled Price was 0.95280.

Tradestation - TradeManager - Orders

In addition, you should note down the back-tested price. In Tradestation you get this from your performance report. Go to the Trade List tab and note down the Price of the same trade. In our example this was 0.95275.

In addition, you should also note down your position size, so that you know the total Net Profit of the trade.

Tradestation - Performance Report - Trade List

Controlling the slippage

If you do this for your entry and also for your exit order, you can calculate the trade profit and more importantly also the slippage. The slippage is the difference in theoretical and actual filling price for your order. This number is very important for your trading performance, since a high slippage may ruin your algorithmic trading strategy. Normally a certain slippage is already included in the backtest, but if the actual slippage gets much higher than the one you planned for you may get into trouble.

In our case the slippage was 1 Tick or $6.25 which is normal for this market. If you build an average of slippages of all your live trades you get a good benchmark. In my case the average slippage over 70 trades (entry and exit) is $2.57 compared to an assumption for the back test of $6.25. Thus, everything is fine and I am on the save side in my development assumptions.

Comparing live trading to the expected one

Documenting the actual performance including the slippage is not enough to know whether the trading performance of your strategy is in line with expectations. With the help of statistics, you can calculate whether everything is all right.

To do so you need to know the Average Trade and its Standard Deviation of the back test. In Tradestation you can get this from the performance report in the Trade Analysis tab.

Tradestation - Trade Analysis

In our example the Avg. Trade Net Profit is $476.62 and the 1 Std. Deviation is $3,331.60.

Statistics now tells us that our profit/loss should remain within a well-defined cone which can be calculated by the following equation:

NP = mu * t +/- Z_alpha * sigma * SQRT(t)

Here the terms have the following meaning:

  • NP = Net Profit
  • mu = Avg. Trade Net Profit
  • t = number of trades from start of live trading
  • Z_alpha = a statistical parameter that relates to the probability of being within our outside of the cone
  • sigma = 1 Std. Deviation

I do not want to bore you with equations, but show you the result in action. Here the trading performance of the Japanese Yen strategy as a graph:

Monitoring trading performance

What you see here is the following. The upper (green) and lower (orange) cones are the calculated borders for the Net Profit. The outer dark cone is for a probability of 99% and the lighter one for 98% probability. Thus, with a 99% or 98% probability your Net Profit (without position sizing = blue line) should be within these boundaries. If they it is not you should be alarmed. Your strategy is either performing above expectations or below.

Summary and outlook

We now know how to collect actual and plan data to measure our trading performance. We also learned how to check whether your slippage is in line with expectations and whether your strategy performs within some probability cone.

In the next article you will learn about additional statistical indicators which will help you to determine whether your strategy is performing well.