Trading Strategy Design In SSE 50ETF Options Market

Financial derivatives trading strategy research is closely related to its own pricing.From the perspective of risk-free arbitrage theory,when the market is fully effective and the pricing is completely reasonable,the market price should reflect all information in a timely and sufficient manner.The price competition mechanism will maintain the price balance between the various contracts.However,since the actual market is not fully effective,theoretical prices and market prices tend to deviate,resulting in a breakdown of the price balance between contracts.At this point,there will be a risk-free arbitrage opportunity,which can obtain positive excess returns.This is the basic principle of the derivatives pricing theory.Only a more accurate pricing can find the deviation between the theoretical price and the actual market price,and provide a guiding reference for subsequent trading behavior.In the classic pricing method,the Monte Carlo simulation method divides the duration of an option into several time intervals.The simulated price changes and motion paths are extracted from the distribution samples,and the averaging is used to derive the benefits of the T time.Option prices are obtained by discounting them at risk-free rates.The obvious drawback is that it relies too much on the number of simulations.The Black-Scholes option pricing model requires five parameters(base asset spot price,underlying asset volatility,optionexecution price,option duration relative days,market risk-free rate),except for the underlying asset volatility.Variables can be observed directly in the market.For investors,it is more convenient to use the formula directly,which is the main reason why the B-S formula can be widely used.The volatility parameter in the formula reflects the intrinsic profitability of the option and is the core variable that determines the price of the option.Since there are no existing indicators,it is necessary to take some mathematical methods and measurement models to estimate the volatility.Whether the pricing is accurate determines whether market participants can make better investment strategies.Therefore,to grasp the trend of option prices,the prediction of volatility becomes a very important task.In this paper,the traditional GARCH method and the machine learning support vector machine SVR method are used to predict the volatility,substitute the B-S formula pricing and backward testing the corresponding trading strategy,compare and determine the more accurate pricing method,and then provide reference for investors to formulate trading strategies.