We have found 42 entries for " algorithmic trading "
Quantitative Trader

Why Quantitative? – Serious Algorithmic Trading Series (Part 2)

20 March 2017

In case you haven’t already, you may wish to read the first two posts of the Serious Algorithmic Trading Series, here and here. Many individual traders will often hear the term “Quant” and may visualize either: A sharply dressed City trader working in a hedge fund, sat in front of his Bloomberg or Thomson Reuters […]

Advantages of Trading $DWC vs. Other Listed Assets

Serious Algorithmic Trading Series – Part 1

16 March 2017

Can individual traders really compete with large institutions?   This post is the first of a four-part “Serious Algorithmic Trading” series, introduced here. A trader will at one point or another, question how practical it is to compete with large institutions in the same markets. After all, it is “big money” at the end of […]

Serious Algorithmic Trading

Serious Algorithmic Trading Series – Introduction

13 March 2017

You’ll learn how algorithmic trading differs substantially from “automated trading using technical analysis”. The two are in fact entirely different disciplines, as this series will demonstrate. You’ll also learn that contrary to popular opinion, algorithmic trading is not synonymous with “automated trading”, though a large percentage of algorithmic trading systems today are indeed automated. We’ll […]

Setting up a DARWIN Data Science Environment

How To Identify Overfit Trading Strategies

15 November 2017

In this post, we describe the main features and behaviours of overfit trading strategies, and the risks they pose to both traders and DARWIN investors. Overfit trading strategies typically perform well in backtesting environments, creating the illusion that they exploit the market inefficiency being targeted, really well. However, when deployed in a live trading environment, […]

MetaTrader 4 Backtesting

MetaTrader Backtesting – Best Practices for Algorithmic Traders

16 October 2017

MetaTrader backtesting can be tricky business for algorithmic traders. Follow these best practices to engineer robust, reliable trading strategies. Watch the full video tutorial here (36 minutes). Simulating a strategy’s historical performance correctly, increases the probability of it generalizing well to unseen market data in future. As such, it’s important that all backtesting be conducted […]

LVQ and Machine Learning for Algorithmic Traders – Part 3

17 June 2017

In the last two posts, LVQ and Machine Learning for Algorithmic Traders – Part 1, and LVQ and Machine Learning for Algorithmic Traders – Part 2, we demonstrated how to use: Linear Vector Quantization Correlation testing ..to determine the relevance/importance of and correlation between strategy parameters respectively. Yet another technique we can use to estimate […]

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