The Predictive Power of REIT Implied Volatility and Implied Idiosyncratic Volatility

2010 ◽  
Vol 16 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Dean Diavatopoulos ◽  
Andy Fodor ◽  
Shawn Howton ◽  
Shelly Howton
2016 ◽  
Vol 8 (1) ◽  
pp. 58
Author(s):  
Chikashi Tsuji

This paper empirically examines the forecast power of the previous day’s US implied volatility for large declines of the Nikkei by using several versions of quantile regression models. All our empirical results suggest that the previous day’s US S&P 500 implied volatility has forecast power for large price drops of the Nikkei 225 in Japan. Since we repeatedly and carefully tested the several left tail risks in price changes of the Nikkei and we also tested by using some different versions of quantile regression models, our evidence of the predictive power of the S&P 500 implied volatility for downside risk of the Nikkei is very robust.


2010 ◽  
Vol 34 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Wayne W. Yu ◽  
Evans C.K. Lui ◽  
Jacqueline W. Wang

2014 ◽  
Vol 17 (02) ◽  
pp. 1450010 ◽  
Author(s):  
Nusret Cakici ◽  
Kudret Topyan ◽  
Chia-Jane Wang

This paper provides an analysis of the effectiveness of certain return predictors in Taiwan Stock Exchange (TWSE) from January 1990 to December 2011 by employing both portfolio method and cross-sectional regressions. While we found no statistically significant predictive power of beta, total volatility, and idiosyncratic volatility the two cheapness variables, book-to-market (BKMT) and cash-flow-to-price (FPR) ratios showed strong consistent economically and statistically significant predictive powers. In addition, our multiple regressions found predictive power in total volatility, short-term reversal (STREV), and market capitalization in the set of small stocks, while our all stock set showed predictive power only in total volatility and STREV.


2020 ◽  
Author(s):  
Najmi Ismail Murad Samsudin ◽  
Azhar Mohamad ◽  
Imtiaz Sifat ◽  
Zarinah Hamid

Author(s):  
Najmi Ismail Murad Samsudin ◽  
Azhar Mohamad ◽  
Imtiaz Mohammad Sifat ◽  
Zarinah Hamid

2015 ◽  
Vol 13 (4) ◽  
pp. 571
Author(s):  
Luis Fernando Pereira Azevedo ◽  
Pedro L. Valls Pereira

VIX - Volatility Index - emerged as an alternative calculation of implied volatility in order to mitigate some problems encountered in models of the Black-Scholes. This kind of volatility is seen as the best predictor of future volatility, given that option traders' expectations are embedded in their values. In this paper we test whether the VIX has more predictive power for future volatility and contains relevant information not found in time series models time for non-negative variables, treated by multiplicative error model. The results indicate that the VIX has greater predictive power in periods of economic stability, but does not contain relevant information to the realized volatility which here is considered as the "true volatility". In periods of economic crisis the result changes, with the VIX presenting the same explanatory power, but contains relevant information in the short term.


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