Strategy Manager

We have created solution for market data collection for further data analysis in Python. This solution is our first step towards more algoritmic approach to trading. It consist of several statistical tool, management capability for investment ideas and algorithms developed by Strategy Quant.

27. 8. 2018 - added algorithmic indexes

Seasonality calculations

Access to 50 000 tickers across the world

Benchmarking theoretical and real trading performance

Aelnor database

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).

Upload strategies

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.

Strategies repository

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.

Strategy profile

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.

Performance comparism

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). We uses EAM manager for so with our own library.

Strategy parameters can be changed. Strategy can be deactivated, compiled and activated on remote access basis.

Portfolio management

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.


The overview tab displays information about several types of accounts and its performance, diversification of the portfolios and the distribution of the profits.

Information for management of the group and market news from selected channels are included as well.

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.

Seasonality calculations

Calculations of seasonality based on date and Day of the week are included for all tickers from Each seasonality chart also contains current development of the ticker.

Metrics and markets comparison

Compare markets to seasonality or markets to markets easily.

Algoritmic indexes

From any given tickers calculate the algorithmic index. Also predefined indexes smart and dumb are created. Those indexes follows the logic behind smart and dumb money investment.

Connection to data provider

We are connected to and uses their data as primary source of information. The number of accessible tickers for our calculations excess 50 000.


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.

Users management

The platform can have 3 different types of users – investor, data miner, portfolio manager. Investor sees overal performance and charting, data miner have access to upload function above the investor’s functionalities. Portfolio manager can start and stop trading strategies as the only user type.

Management of the group

Management includes creation and management of expenses, users, metatraders initial deposit, size of the MIKRO account and portfolio criterium that evaluates potential candidates for trading.

Connect to R Studio

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.

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High Risk Investment Warning
Trading foreign exchange and/or contracts for differences on margin carries a high level of risk, and may not be suitable for all investors. The possibility exists that you could sustain a loss in excess of your deposited funds and therefore, you should not speculate with capital that you cannot afford to lose. Information provided is only general advice that does not take into account your objectives, financial situation or needs. It must not be construed as personal advice.