MetaTrader Expert Advisors: The Set & Forget Myth [EAS-II]

EAs Metatrader: Le mythe du “tout automatique” [EAS-II]

25 February 2018

Voici le deuxième article de la série Expert Advisor MetaTrader – [EAS] que nous avons récemment démarré. Au cas où vous l’auriez manqué, voici un lien vers le premier post: Experts Advisors commerciaux: tout ce qui brille n’est pas or.   Si vous vous demandez ce que signifie “set & forget” (“branchez et laissez tourner”), c’est un slogan couramment […]

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 determine the relevance/importance of and correlation between strategy parameters respectively. Yet another technique we can use to estimate […]

LVQ and Machine Learning for Algorithmic Traders – Part 2

14 June 2017

    In LVQ and Machine Learning for Algorithmic Traders – Part 1, we discussed and demonstrated a technique (Linear Vector Quantization) to decipher the relevance and relative importance of each feature variable in the dataset under study. In doing so, algorithmic traders would be able to isolate which of a dataset’s features (read: strategy […]

LVQ and Machine Learning for Algorithmic Traders – Part 1

8 June 2017

Algorithmic traders across all spectra of asset classes, often face a rather daunting challenge. What are the best inputs for an algorithmic trading strategy’s parameter space? Different algorithmic trading strategies (whether manual or automated) will each have their own unique set of parameters that govern their behaviour. Granted.. Genetic and Walk-Forward Optimization will help algorithmic […]

Hidden Markov Models & Regime Change: DARWINs vs. S&P500

24 April 2017

In this post, we will employ a statistical time series approach using Hidden Markov Models (HMM), to firstly obtain visual evidence of regime change in the S&P500. We will then compare the index’ performance to a DARWIN Portfolio, between June 2014 and March 2017. Detecting significant, unforeseen changes in underlying market conditions (termed “market regimes“) […]

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 […]

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