Summary A complete strategy is actually a set of rules that traders give themselves. It includes all aspects of the trading, and does not leave a little room for subjective imagination. Every choic

Summary A complete quantitative trading life cycle is more than just the trading strategy itself. It consists of at least six parts, including: strategy design, model building, backtesting tuning,

Summary Many people think complex trading strategies as a starting point when discussing quantitative trading, and inadvertently put a layer of mystery on quantitative trading. In this section, we

Summary As a product of the combination of science and machine, quantitative trading is changing the pattern of modern financial markets. Many investors have turned their attention to this field. H

Quantitative trading quick start Content Part 1, the basis of quantitative trading 1. What is quantitative trading? 2. Why choose quantitative trading

MACD is a popularly used technical indicator in trading stocks, currencies, cryptocurrencies, etc. Basics of MACD MACD is used and discussed in many different trading circles. Moving Average Conve

In trading, a single transaction result with win or loss is not the focus of quantitative traders, so what are they most concerned about? The answer is the result of trading the system after 800 or 10

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 and Ba

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 Foreca

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 without k

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 use of two Ex

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 Movi

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 worked for a

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

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, which are used by a portfolio

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 Strategy class hier

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 this article we are going to consider how market dat