A comparative analysis of the predictive power of implied volatility indices and GARCH forecasted volatility

2015 ◽  
Vol 424 ◽  
pp. 105-112 ◽  
Author(s):  
Sónia R. Bentes
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 16 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Dean Diavatopoulos ◽  
Andy Fodor ◽  
Shawn Howton ◽  
Shelly Howton

1973 ◽  
Vol 10 (3) ◽  
pp. 262-269 ◽  
Author(s):  
Frank M. Bass ◽  
William L. Wilkie

A comparison of cross-sectional methods of analysis of multi-attribute attitude models indicates striking differences in predictive power. Importance weights do not detract from prediction, and correlations of attitude with preference compare favorably with attitude-affect correlations found in social psychology.


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

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

2017 ◽  
Vol 91 (8) ◽  
Author(s):  
Francesca Di Giallonardo ◽  
Timothy E. Schlub ◽  
Mang Shi ◽  
Edward C. Holmes

ABSTRACT Viruses use the cellular machinery of their hosts for replication. It has therefore been proposed that the nucleotide and dinucleotide compositions of viruses should match those of their host species. If this is upheld, it may then be possible to use dinucleotide composition to predict the true host species of viruses sampled in metagenomic surveys. However, it is also clear that different taxonomic groups of viruses tend to have distinctive patterns of dinucleotide composition that may be independent of host species. To determine the relative strength of the effect of host versus virus family in shaping dinucleotide composition, we performed a comparative analysis of 20 RNA virus families from 15 host groupings, spanning two animal phyla and more than 900 virus species. In particular, we determined the odds ratios for the 16 possible dinucleotides and performed a discriminant analysis to evaluate the capability of virus dinucleotide composition to predict the correct virus family or host taxon from which it was isolated. Notably, while 81% of the data analyzed here were predicted to the correct virus family, only 62% of these data were predicted to their correct subphylum/class host and a mere 32% to their correct mammalian order. Similarly, dinucleotide composition has a weak predictive power for different hosts within individual virus families. We therefore conclude that dinucleotide composition is generally uniform within a virus family but less well reflects that of its host species. This has obvious implications for attempts to accurately predict host species from virus genome sequences alone. IMPORTANCE Determining the processes that shape virus genomes is central to understanding virus evolution and emergence. One question of particular importance is why nucleotide and dinucleotide frequencies differ so markedly between viruses. In particular, it is currently unclear whether host species or virus family has the biggest impact on dinucleotide frequencies and whether dinucleotide composition can be used to accurately predict host species. Using a comparative analysis, we show that dinucleotide composition has a strong phylogenetic association across different RNA virus families, such that dinucleotide composition can predict the family from which a virus sequence has been isolated. Conversely, dinucleotide composition has a poorer predictive power for the different host species within a virus family and across different virus families, indicating that the host has a relatively small impact on the dinucleotide composition of a virus genome.


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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