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Abstract - The following research provides a thoughtful analysis regarding the use of machine learning techniques applied to algorithmic trading using common indexes such as the S&P500 and the Chicago Board Options Exchange Market Volatility Index (VIX). A trading simulation is carried out in order to test the efficiency of the algorithms in up trending and down trending periods. Statistical and economic performance measures are obtained and compared in order to discuss the most effective technique. The inputs used in the analysis are well-known quantitative indicators such as the Relative Strength Index and the Moving Average Convergence-Divergence. The relevance of the results lies in the use of separated training models for each kind of trend.
Keywords: Support Vector Machines, Quantitative trading, VIX, Machine learning, ADX, RSI.
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1Introduction
Trading is one of the most ancient ways of improving the personal economic situation, either by exchanging certain goods in favorable situations or using currency, by purchasing by a low amount, and selling by a higher one. Nowadays, trading system have become well-regulated and information is spread around the world, making it possible to gather the necessary data in order to perform the most successful operation [1]. However, the immense amount of information provided becomes unbearable by humans, who need to rely in computers in order to maximize the decision-making process. Using predefined systems in this process in order to avoid manual trading is called Algorithmic Trading.
There are many trading techniques which are suitable to be used in financial markets. From a global point of view, they can be classified in two main families, the technical trading and the fundamental trading. Fundamental analysis uses the social information as a source of knowledge in the decisionmaking process [2]. On the other hand, technical analysis relies in the price movements to forecast the future situation.
Algorithmic trading is especially useful in this kind of techniques, which are the ones that will be under use in this research. Regarding technical analysis, there will be two main group of techniques that will be discussed: quantitative techniques and machine learning. Quantitative techniques use fixed rules in order to trigger the purchases and sales operations, producing a solid system that, if well designed, can provide massive profit...