On last week’s post (here) we discussed a new random forest based model that I created for the prediction of out-of-sample (OS) returns in our price-action based trading system repository at Asirikuy. This is the last from a series of currently 7 different models used for OS predictions in our community. Thinking about how I […]
Posts Tagged ‘machine learning’
- 2017: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
- 2016: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
- 2015: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
- 2014: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
- 2013: Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
November 2017
- When are non-zero return thresholds a good idea for OS performance classification?
- The effect of return thresholds on ML models for trading system OS predictions
- A new RF classifier for continuous OS return predictions in our PA repository
September 2017
August 2017
July 2017
- Building "the switch" using machine learning
- Predicting trading system out-of-sample success using chaos properties of financial time series
June 2017
April 2017
December 2016
November 2016
- Introducing pKantuRL: GPU enabled mining for reinforcement learning based systems
- Are a stoploss or takeprofit really necessary? Analyzing ideal trading mechanics
- Reinforcement Learning: Implementing a flexible approach to prepare for GPU mining
- Reinforcement learning in trading: What about random data?
- Reinforcement learning and degrees of freedom in Forex trading
- Reinforcement learning and trading: Approaching the markets like a game
- My experience with Udacity’s Machine Learning Engineering Nanodegree: Part two
- My experience with Udacity's Machine Learning Engineering Nanodegree: Part one
October 2016
September 2016
- Looking at a Regressor for Out-of-sample predictions
- Building a model for continuous out-of-sample performance prediction
- The Numerai hedge fund: Paying anyone who can lend a crystal ball
- The nature of success: A closer look at our IS/OS classifier
- Hidden consequences of classification model overfitting in Random Forests
August 2016
- Improving our Random Forest IS/OS classification method
- A current picture of our machine learning based mining and trading system portfolio
- Finally an out-of-sample performance predicting model that works (a bit)
- Making Random Forests cheap enough for machine learning mining
June 2016
- Some interesting results from our machine learning system repository
- Our Forex machine learning system repository is alive again!
May 2016
- Using R in trading: Building a Random Forest model to predict out of sample results
- The big possibilities of machine learning ensembles
April 2016
- First pKantuML results: Starting the building of a machine learning repository
- Small computers: Getting pyOpenCL to run on the ODROID-XU4
March 2016
- Rethinking machine learning in trading: Let's mine using the GPU!
- Machine Learning in Forex Trading: Choosing a machine learning library
- Dissecting the performance of our Forex machine learning strategies
February 2016
- Machine Learning in Forex Trading: First results from shifted timeframes
- Machine Learning in Forex: Different input options, Part 1
- Machine Learning in FX Trading: Measuring the quality of Input/Output structures
January 2016
- Machine Learning in Trading: What about lower timeframes?
- Machine Learning in Trading: Using Heiken-Ashi returns as inputs
- Machine Learning in Trading: Exploring multiple trade outcome predictions on the EUR/USD
- Machine learning in trading: Predicting multiple trade outcomes using a linear regression model
December 2015
- Creating Successful Machine Learning Systems: My journey in the world of self-adapting strategies, part 2
- Creating Successful Machine Learning Systems: My journey in the world of self-adapting strategies, part 1
- Neural Networks Using Technical Indicators: Exploring Commodity Channel Index (CCI) based systems
November 2015
- Neural Networks Using Technical Indicators: RSI system results on multiple pairs
- Neural Networks Using Technical Indicators: exploring single period RSI algorithms
- Neural Networks Using Technical Indicators: a Machine learning algo using the RSI
September 2015
June 2015
May 2015
- Generating a methodology for the creation and trading of machine learning strategies
- Machine Learning in Forex Trading: Why many academics are doing it all wrong
September 2014
- Machine Learning in Forex: Data quality, broker dependency and trading systems
- Using R in Algorithmic Trading: Back-testing a machine learning strategy that retrains every day
- Using R in Algorithmic Trading: Building and testing a machine learning model
August 2014
- Building a Machine Learning Library for Forex Trading: Creating a toolbox of input/output generators
