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How candlestick features affect the performance of volatility forecasts: evidence from the stock market
Authors:Jung-Bin Su
Affiliation:1. Department of Finance, China University of Science and Technology, 245, Yen-Chiu-Yuan (Academia) Road, Sec3, Nankang, Taipei 11581, Taiwanjungbinsu@cc.cust.edu.twjungbinsu@gmail.com
Abstract:In this study, we used asymmetric GJR-X models to investigate how the return and volatility estimates in the stock market on any given day are affected by the features of the preceding day's candlestick. Empirical results show that, first, for symmetric volatility specification, the upper and lower shadows of yesterday can, respectively, lower and raise the return today, whereas both upper and lower shadows of yesterday can increase today's volatility. Notably, the upper and lower shadows elicited asymmetric responses in the sizes of the volatility and return increments. Conversely, for asymmetric volatility specification, leverage effect may affect the asymmetric response and prevent the upper shadow from influencing the return and volatility. Second, for symmetric volatility specification, the black and white real bodies of yesterday can, respectively, augment and abate today's return and volatility, indicating that the black real body produces a distinct type of leverage effect to influence volatility. Importantly, for asymmetric specification, the effects of the black and white real bodies appear the same as for the symmetric specification, but are less significant. Lastly, the real bodies (or, respectively, asymmetric volatility specification) influenced the accuracy of volatility forecasts more strongly than the upper and lower shadows (or, respectively, symmetric volatility specification).
Keywords:volatility  accuracy  candlestick  asymmetric GJR-X model  exogenous variables
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