Over the last few years we’ve looked at various tools to help us identify exploitable patterns in asset prices. In particular we have considered basic econometrics, statistical machine learning ...
Mature Python libraries such as matplotlib, pandas and scikit-learn also reduce the necessity to write boilerplate code or come up with our own implementations of well known algorithms. The Forecastin...
No matter how much time, effort, and money you put into an investment, if you don’t have a predetermined exit strategy, everything can be gone. For this reason, investment guru never invests wit...
Institutional asset managers specialize in a particular asset class, style, sector, or geography, based on their expertise or domain knowledge. This is reflected in the investment products they offer ...
In this article we are going to consider our first intraday trading strategy. It will be using a classic trading idea, that of “trading pairs”. In this instance we are going to be making u...
In this article we will make use of the machinery we introduced to carry out research on an actual strategy, namely the Moving Average Crossover on AAPL. Moving Average Crossover Strategy The Moving A...
In this article I want to introduce you to the methods by which I myself identify profitable algorithmic trading strategies. Our goal today is to understand in detail how to find, evaluate and select ...
It’s been a while since we’ve considered the event-driven backtester, which we began discussing in this article. In Part VI I described how to code a stand-in ExecutionHandler model that w...
In the last article on the Event-Driven Backtester series we considered a basic ExecutionHandler hierarchy. In this article we are going to discuss how to assess the performance of a strategy post-bac...
This article continues the discussion of event-driven backtesters in Python. In the previous article we considered a portfolio class hierarchy that handled current positions, generated trading orders ...