In the previous article on event-driven backtesting we considered how to construct a Strategy class hierarchy. Strategies, as defined here, are used to generate signals,… ( Read More )
Event-Driven Backtesting with Python - Part IV
The discussion of the event-driven backtesting implementation has previously considered the event-loop, the event class hierarchy and the data handling component. In this article a… ( Read More )
Event-Driven Backtesting with Python - Part III
In the previous two articles of the series we discussed what an event-driven backtesting system is and the class hierarchy for the Event object. In… ( Read More )
Event-Driven Backtesting with Python - Part II
In the last article we described the concept of an event-driven backtester. The remainder of this series of articles will concentrate on each of the… ( Read More )
Event-Driven Backtesting with Python - Part I
We've spent the last couple of months on QuantStart backtesting various trading strategies utilising Python and pandas. The vectorised nature of pandas ensures that certain… ( Read More )
Successful Backtesting of Algorithmic Trading Strategies - Part II
In the first article on successful backtesting we discussed statistical and behavioural biases that affect our backtest performance. We also discussed software packages for backtesting,… ( Read More )
Successful Backtesting of Algorithmic Trading Strategies - Part I
This article continues the series on quantitative trading, which started with the Beginner's Guide and Strategy Identification. Both of these longer, more involved articles have… ( Read More )
Value at Risk (VaR) for Algorithmic Trading Risk Management
Value at Risk (VaR) for Algorithmic Trading Risk Management Estimating the risk of loss to an algorithmic trading strategy, or portfolio of strategies, is of… ( Read More )
Should You Build Your Own Backtester?
About This Post The post is suitable for those who are beginning quantitative trading as well as those who have had some experience with the… ( Read More )