Answers are grounded in this paper and cite their sources.
Quantitative investment trading is becoming more and more popular due to the gradual integration of computer technology, mathematics, and statistics. It is of great practical significance to develop a multi-species portfolio investment model that takes into account various transaction costs and conforms to live trading. In this paper, we use the free software R to program the Bollinger Bands trading strategy and test it on the historical data of the Chinese futures market. Through in-sample optimization, out-of-sample testing and correlation test, the varieties with good back testing effect are selected for risky investment portfolio to provide investors involved in the Chinese futures market with specific trading strategies that can be used for reference, and at the same time to provide investors with a way of thinking to develop quantitative investment portfolio models. JEL classification numbers: C60.
No takes yet. Share an insight, caveat, or question.
Zhang et al. (2023) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: