A Study Of Quantitative Investment Strategy Based On Multifractal

The introduction of the fractal market hypothesis in the 1990 s posed a powerful challenge to efficient markets and their normal assumptions.The fractal market has obvious non-linear characteristics,such as self-similarity,scale invariance,long-range correlation,etc.,and multifractal is the promotion and supplement of single fractal.Previous studies have made some attempts to characterize the fractal characteristics of the financial market and use single fractals to quantify transactions.Based on the daily closing price data of the Shanghai Composite Index and Shenzhen Component Index,this paper uses the KS test and JB statistics to demonstrate the non-normality of the two market return series,and then describes the internal dynamics of the Chinese capital market from the perspective of fractal According to the characteristics of multi-fractal detrending flutuation analysis(MF-DFA),the multi-fractal characteristics of Shanghai and Shenzhen stock markets were verified,and the multi-fractal spectrum was calculated.The existence of multi-fractal spectrum and its asymmetrical nature both explain the multi-fractal characteristics of financial time series,reflect the inherent laws of capital market fluctuations,and describe the size and frequency of fluctuations in detail.Taking advantage of this important property of financial time series,this paper builds a simple trend strategy based on momentum effect,a Hurst index strategy based on single fractal,and an improved timing strategy with multi-fractal spectrum parameters and comparative analysis.The addition of parameters enables quantitative trading strategies to achieve good results in the period of intense financial market volatility,able to withstand market risks and obtain excess returns.Finally,using the bootstrap method in the statistical test,this article finds that there is still room for improvement in the real predictive power of quantitative trading strategies.