Short Term Trading Models Using Hurst Exponent and Machine Learning

16 Pages Posted: 12 Apr 2021

See all articles by Gursewak Singh Sidhu

Gursewak Singh Sidhu

WorldQuant LLC - WorldQuant University

Ali Ibrahim Ali Metwaly

WorldQuant LLC - WorldQuant University

Animesh Tiwari

WorldQuant LLC - WorldQuant University

Ritabrata Bhattacharyya

WorldQuant University

Date Written: April 11, 2021

Abstract

Predicting the direction of Stock Indices has always been an appealing topic which has motivated researchers over the years to develop better predictive models. Recently, Machine learning (ML) based models have been frequently deployed to forecast the direction of classic financial time series data. In the 1950s, Hurst Exponent was introduced as a statistical measure to classify various Time Series. This research analyzes the effectiveness of using Machine Learning and Hurst Exponent along with popular Technical Indicators for short term trading predictions. In this study we explore the use of Hurst Exponent to segment data for a short-term machine learning model in order to improve trading strategy. A comparative analysis has been carried out between the performance of a standalone short-term model, and a Segmented model (Segments based on hurst exponent cut off) in S&P 500, SSE Composite Indices, Gold SPDR Shares and Bitcoin. This new approach is being introduced in order to reach the optimum integration between Machine learning & Hurst Exponent.

Keywords: Short term trading models, Hurst Exponent, Technical Analysis, S&P500, Machine learning for finance, Financial time series, buy-and-hold, stop-loss, cryptocurrencies, Bitcoin, BTC-USD

JEL Classification: C13, C33, C38, G11

Suggested Citation

Sidhu, Gursewak Singh and Ibrahim Ali Metwaly, Ali and Tiwari, Animesh and Bhattacharyya, Ritabrata, Short Term Trading Models Using Hurst Exponent and Machine Learning (April 11, 2021). Available at SSRN: https://ssrn.com/abstract=3824032 or http://dx.doi.org/10.2139/ssrn.3824032

Gursewak Singh Sidhu (Contact Author)

WorldQuant LLC - WorldQuant University ( email )

Place St Charles
201 St Charles Ave #2500
New Orleans, LA 70170
United States

Ali Ibrahim Ali Metwaly

WorldQuant LLC - WorldQuant University ( email )

Place St Charles
201 St Charles Ave #2500
New Orleans, LA 70170
United States

Animesh Tiwari

WorldQuant LLC - WorldQuant University ( email )

Place St Charles
201 St Charles Ave #2500
New Orleans, LA 70170
United States

Ritabrata Bhattacharyya

WorldQuant University ( email )

Place St Charles
201 St Charles Ave #2500
New Orleans, LA 70170
United States

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