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

**Authors:** Jing-Chao Chen, Yu Zhou, Xi Wang  
**arXiv:** [1710.07470](https://arxiv.org/abs/1710.07470)  
**Date:** 2017-10-20  
**Summary page:** https://www.summarizepaper.com/en/paper/1710.07470v1/

## Key points

- Authors Jing-Chao Chen, Yu Zhou, and Xi Wang study the profitability of technical trading rules in financial markets.
- The authors convert Moving Average (MA), KDJ, and Bollinger Bands into stationary processes for analysis.
- High-frequency data (15s, 30s, and 60s intervals) from the CSI300 Stock Index Futures is used for the study.
- Various performance and risk measures are employed to evaluate the practical value of these trading rules.
- An Augmented Dickey-Fuller (ADF) test is used to verify stationarity, while a Superior Predictive Ability (SPA) test determines success factors.
- Significant parameter combinations are found for each indicator without transaction costs; however, profits disappear once transaction costs are considered.
- The study suggests a method to mitigate risks associated with technical trading rules.
- Stationarity and transaction costs play crucial roles in evaluating the profitability of technical trading strategies.

## Summary

In their study titled "Profitability of Simple Stationary Technical Trading Rules with High-Frequency Data of Chinese Index Futures," authors Jing-Chao Chen, Yu Zhou, and Xi Wang delve into the controversial realm of technical trading rules in financial markets. The profitability of such rules has long been debated, with little consideration given to the stationarity of the technical indicators used. To address this gap, the authors convert Moving Average (MA), KDJ, and Bollinger Bands into stationary processes and analyze their profitability using high-frequency data (15s, 30s, and 60s intervals) from the CSI300 Stock Index Futures spanning from January 4th, 2012 to December 31st, 2016. The research employs various performance and risk measures to evaluate the practical value of these trading rules directly. Additionally, an Augmented Dickey-Fuller (ADF) test is utilized to verify stationarity while a Superior Predictive Ability (SPA) test is conducted to determine whether the success of trading rules is attributed to inherent superiority or mere luck. The findings reveal several significant parameter combinations for each indicator when transaction costs are not factored in. However, once transaction costs are considered, any potential trading profits are completely eradicated. Furthermore, the study proposes a method to mitigate the risks associated with technical trading rules. Overall,this research sheds light on the complexities surrounding technical trading strategies in financial markets and underscores the importance of considering stationarity and transaction costs in evaluating their profitability.