Nam Phueng
Nam Phueng
IT Professional and Forex Trader.
I am fond of statistical analysis.
shared author's Dmitriy Gizlyk article
Reversal patterns: Testing the Head and Shoulders pattern
Reversal patterns: Testing the Head and Shoulders pattern

This article is a follow-up to the previous one called "Reversal patterns: Testing the Double top/bottom pattern". Now we will have a look at another well-known reversal pattern called Head and Shoulders, compare the trading efficiency of the two patterns and make an attempt to combine them into a single trading system.

shared author's Vladimir Perervenko article
Deep Neural Networks (Part V). Bayesian optimization of DNN hyperparameters
Deep Neural Networks (Part V). Bayesian optimization of DNN hyperparameters

The article considers the possibility to apply Bayesian optimization to hyperparameters of deep neural networks, obtained by various training variants. The classification quality of a DNN with the optimal hyperparameters in different training variants is compared. Depth of effectiveness of the DNN optimal hyperparameters has been checked in forward tests. The possible directions for improving the classification quality have been determined.

shared author's Maxim Dmitrievsky article
Random Decision Forest in Reinforcement learning
Random Decision Forest in Reinforcement learning

Random Forest (RF) with the use of bagging is one of the most powerful machine learning methods, which is slightly inferior to gradient boosting. This article attempts to develop a self-learning trading system that makes decisions based on the experience gained from interaction with the market.

shared author's Alexander Dubovik article
Statistical Verification of the Labouchere Money Management System
Statistical Verification of the Labouchere Money Management System

In this article, we test the statistical properties of the Labouchere money management system. It is considered to be a less aggressive kind of Martingale, since bets are not doubled, but are raised by a certain amount instead.

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