Discussion of article "Custom presentation of trading history and creation of report diagrams"
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New article Custom presentation of trading history and creation of report diagrams has been published:
The article describes custom methods for assessing the trading history. Two classes have been written for downloading and analyzing history. The first of them collects the trading history and represents it as a summary table. The second one deals with statistics: it calculates a number of variables and builds charts for a more efficient evaluation of trading results.
The core piece of any trading activity is the trading algorithm which forms the Profit/Loss curve. Such an algorithm can be compared with a synthetic asset, the value of which is formed relative to the underlying asset (i.e. the traded instrument). For example, in options trading the Black-Scholes model formula is used for calculating such a synthetic asset based on the underlying asset price. But there is no such formula for a trading algorithm. Accordingly, launch of an algorithm can be compared to a long position of a synthetic symbol, the PL curve of which is formed by the algorithm's programmed logic. Profit formed by this "asset" can be unstable in different time periods. Even if it can be evaluated by some econometric model, this model cannot be unified. But how to track this asset and our trading stages? One of the suitable solutions is to monitor the algorithm trading retrospective and detect deviations from expected results.
I will not give advice on how to analyze algorithms, but will only provide a set of methods, which allow the presentation of the complete picture of your trading history. Based on data obtained, you will be able to build complex econometric models, calculate probability characteristics and make various conclusions.
This article will be divided into 2 chapters. In the first (technical) part, I will describe methods for generating trading reports based on the bulk of information, which is stored in your terminals. This chapter deals with the source data used for analysis. In the second part, we will deal with the main values, by which we will evaluate the trading retrospective on the selected data. Data sampling can be varied: all assets or a selected symbol, for the entire available history or for a certain period of time. The analysis results will be presented in a separate file and briefly visualized in the terminal.
I used data from my real trading history for the analysis examples. Code implementation examples were prepared using a testing period, which I intentionally accumulated by trading on a demo account.
Author: Andrey Azatskiy