Statistical Arbitrage Options Trading Strategy Based On Volatility Term Structure

Statistical arbitrage is a two-way trading hedging strategy that does not depend on market trends,that is,a market-neutral strategy.The basic principle is that the product used to construct the asset portfolio maintains a relatively stable relationship over a long period of time,that is,the price trend of the trading asset is consistent for a long time or the spread sequence is in equilibrium for a long time.Investors can use these two properties to temporarily deviate To make a profit.The implementation of the strategy requires a short-selling mechanism in the market and a mean regression characteristic of the spread of trading assets.By using the mean regression characteristic of the spread,the asset portfolio of long and short positions is constructed to obtain investment returns.Its origins date back to the matching transactions conducted by Morgan Stanley in the 1980s.In the following ten years,it was enthusiastically sought after by major securities firms and investment institutions,and brought them huge profits.As a more mature quantitative trading strategy,statistical arbitrage strategies have long been applied to investments in developed capital markets.The introduction of stock index options makes the shorting mechanism possible in China,and provides an effective tool for the implementation of statistical arbitrage strategies in China.In recent years,due to changes in the market structure,the development of statistical arbitrage in the later stages has incorporated a variety of factors,including trading experience,empirical observations,experimental analysis,and so on.With the gradual development of time series analysis theory,the use of spread time series to analyze statistical arbitrage in the capital market is becoming more and more perfect.Chinese scholars have also done research on statistical arbitrage,and paid more attention to the construction of arbitrage models.This article starts with the implied volatility of options.Unlike traditional statistical arbitrage,which focuses on the spread,it focuses on the volatility difference,that is,the option's volatility trading.Volatility trading of options is based on the judgment of the option's implied volatility and the direction of change,and profit from changes in implied volatility.Due to the characteristics of the volatility term structure,the implied volatility difference between the target and the contract with the same execution price has the characteristic of mean regression,which is why this article chooses the volatility term structure as the transaction design.This article expands from two parts,theory and strategy.The first half focuses on theory.It mainly discusses the implicit volatility term structure,related theories of statistical arbitrage,trading strategies and models,including co-integration theory,stability testing,and GARCH model.The second half takes the SSE 50ETF option data of China's options market as an example to conduct strategy tests and analyze statistical arbitrage performance.In the theoretical part,two aspects are discussed in detail:the first is the selection of paired assets,a qualitative analysis of the term structure of implied volatility,and a quantitative analysis of statistical cointegration tests to determine the difference in the volatility of the paired asset structure sequence.Structure 2 is to fit the term structure of volatility,using AR(1),AR(1)-GARCH,AR(1)-EGARCH models for fitting,and finally AR(1)-EGARCH models for data fitting The degree is better.In the strategy part,empirical tests show that statistical arbitrage is still effective in the Chinese market.The strategy using the standard deviation of the EGARCH model as a trading signal performs well.Although there have been losses during the period,the annual return rate is still as high as 18%.This is a good choice for large-scale investment institutions.