Profitability of simple stationary technical trading rules with high-frequency data of Chinese Index Futures

TL;DR

This study converts popular technical trading rules into stationary processes and evaluates their profitability on high-frequency Chinese Index Futures data, finding that transaction costs negate profits but risk reduction methods are possible.

Contribution

It introduces a method to transform technical indicators into stationary processes and assesses their profitability with high-frequency data, considering transaction costs and risk reduction.

Findings

Profitability disappears after accounting for transaction costs.

Certain parameter combinations yield significant profits without costs.

Risk reduction methods can mitigate trading risks.

Abstract

Technical trading rules have been widely used by practitioners in financial markets for a long time. The profitability remains controversial and few consider the stationarity of technical indicators used in trading rules. We convert MA, KDJ and Bollinger bands into stationary processes and investigate the profitability of these trading rules by using 3 high-frequency data(15s,30s and 60s) of CSI300 Stock Index Futures from January 4th 2012 to December 31st 2016. Several performance and risk measures are adopted to assess the practical value of all trading rules directly while ADF-test is used to verify the stationarity and SPA test to check whether trading rules perform well due to intrinsic superiority or pure luck. The results show that there are several significant combinations of parameters for each indicator when transaction costs are not taken into consideration. Once transaction costs are included, trading profits will be eliminated completely. We also propose a method to reduce the risk of technical trading rules.