International Journal of Modern Physics B · 2014 · 25 citations · 33 references
Social SciencesEconomicsFinanceEconometricsFinancial EconomicsTime Series AnalysisAsset Return ModelingCapital MarketsTemporal Dependence ModelingTime Series EconometricsTime Series ForecastingVolatility ModelingAutocorrelation FunctionCross-correlation AnalysisDependence In Asset ReturnsReturn Correlation AnalysisTime Scales
Recent studies confirm that weather affects the Chinese stock markets, based on a linear model. This paper revisits this topic using DCCA cross-correlation coefficient (ρ DCCA (n)), which is a nonlinear method, to determine if weather variables (i.e., temperature, humidity, wind and sunshine duration) affect the returns/volatilities of the Shanghai and Shenzhen stock markets. We propose an asymmetric ρ DCCA (n) by improving the traditional ρ DCCA (n) to determine if different cross-correlated properties exist when one time series trending is either positive or negative. Further, we improve a statistical test for the asymmetric ρ DCCA (n). We find that cross-correlation exists between weather variables and the stock markets on certain time scales and that the cross-correlation is asymmetric. We also analyze the cross-correlation at different intervals; that is, the relationship between weather variables and the stock markets at different intervals is not always the same as the relationship on the whole.
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Good Day Sunshine: Stock Returns and the Weather
David Hirshleifer, Tyler Shumway · The Journal of Finance · 2003 · 1.7K citations
Long-Term Memory in Stock Market Prices
Andrew W. Lo · Econometrica · 1991 · 1.7K citations · Full text
Social Sciences, Economics, Finance +17