Academic Trading Strategies
- The Encyclopaedia of Quantitative Trading Strategies
- Shows and explains more than 300 trading strategies derived from academic research (tens of thousands of financial research papers were investigated, most promising ideas are presented)
- Contains explicit trading rules in plain language, identified performance and risk characteristics and other attributes, links to source and related research papers
Sample pricing:
– $299 per 3-months period
– $499 per 12-months period
– $999 per 36-months period
Cool Backtesting Solutions
CERN QF-Lib is a Python library from the boys at CERN, which provides high quality tools for quantitative finance. Among the features, there are modules for portfolio construction, time series analysis, risk monitoring and diverse charting package. The library allows analyzing financial data in a convenient way, while providing a wide variety of tools for data processing and presentation of the results.
QF-Lib is a convenient environment for conducting your own analysis. The results will be presented in a practical form and include number of charts and statistical measures.
OpenQuant is a modern IDE integrated development environment for creating and testing computerized trading strategies. This is where the action is for human strategists as they create, develop, test and optimize new strategy candidates. It solves all the usual problems of importing market data, inspecting the data in table or chart form with built-in technical indicators, developing code, backtesting to evaluate performance, and visualizing trading behaviour with bar charts, equity curves, performance statistics, and portfolio trading logs.
OpenQuant is suitable for any style of investing, ranging from strategies driven by daily signals to high frequency trading utilizing the system’s ability to process up to one million events per second. The IDE uses C# on the Microsoft Windows .NET platform, and is fully user-extensible.