We created Strategy management software specifically for investment algorithms developed by Strategy Quant. Database which Strategy manager uses can be further used for data collection and analysis and can be connected to R Studio.
30. 7. 2017. - project added to GitHub
R studio and StrateQyquant support
Automatic import data from Metatrader
Benchmarking theoretical and real trading performance
The shorter time when holding position in market the more random winning percentage in the trading. This fact lead us to focus on medium-term investment (2 - 14 days). For that prupose we created a tool consist of a database that helps us visualize large portions of data that we save for analysis. Strategy manager also includes portfolio management, support of execution in Metatarder and visualization trading data from strategies created by StrategyQuant, R studio and EAM manager. To our database algorithms writter in R can save data from TWS interactive brokers (this feature is in developement).
One of the methods of creation of investment algorithm is using existing software for data mining processes such as StrategyQuant.
Users can easily upload strategies from StrategyQuant for further management.
Bigger amount of strategies can be managed on one spot. Search engine is included.
Manually developed investment algorithms (for example in R studio) can use the same database to cooperate with those developed by StrategyQuant.
Every strategy has its own profile where all data related to that strategy are displayed.
Browsing strategies is easy as well as comparing to their backtest.
Comparism between DEMO, MIKRO and REAL accounts is clearly visualized and statsitics for all accounts where strategy was trading are recounted every 5 minutes.
Strategy can be downloaded, compiled and ready to trade in Metatrader (files .mg4).
Strategy parameters can be changed. Strategy can be deactivated, compiled and activated on remote access basis.
Portfolio managenent is build in function. It compares strategy average consequences losses and wins in backtest of the strategy to its performance on MIKRO trading account. If it exceed historical extremes, strategy shows itself to either increase or decrease its trading size. This depends on the type of extreme.
Overall statistics of Leading (REAL) and Lagging (MIKRO, DEMO account) portfolios are base on unique benchmarking. Our main benchmark is comparism between theoretical and practical performance of portfolio of strategies.
Aelnor database can be connected to R studio. This function is usefull when algorithms are written in R or C and needs to communicate with those who were created by StrategyQuant. By using R it is possible to save data from various resources do Aelnor database for further analysis. R studio is also possible to connect to TWS Interactive brokers.