566 research outputs found
Forecasting Value-at-Risk using block structure multivariate stochastic volatility models
No full textMost multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with milder restrictions, whose purpose is to combine the need for interpretability and efficiency faced by model users with the computational problems that may emerge when the number of assets can be very large. A contribution to this strand of the literature including a block-type parameterization for multivariate stochastic volatility models is provided. The empirical analysis on stock returns on the US market shows that 1% and 5% Value-at-Risk thresholds based on one-step-ahead forecasts of covariances by the new specification are satisfactory for the period including the Global Financial Crisis
Comprehensive diagnosis of bacterial infection associated with acute cholecystitis using metagenomics approach
No full text主査 : 舘田一博 / タイトル : Comprehensive diagnosis of bacterial infection associated with acute cholecystitis using metagenomics approach /著者 : Manabu Kujiraoka, Makoto Kuroda, Koji Asai, Tsuyoshi Sekizuka, Kengo Kato, Manabu Watanabe, Hiroshi Matsukiyo, Tomoaki Saito, Tomotaka Ishii, Natsuya Katada, Yoshihisa Saida, Shinya Kusachi /掲載誌 : Frontiers in Microbiology /巻号・発行年等 : 8:685, 201
Comprehensive diagnosis of bacterial infection associated with acute cholecystitis using metagenomics approach
No full text主査 : 舘田一博 / タイトル : Comprehensive diagnosis of bacterial infection associated with acute cholecystitis using metagenomics approach /著者 : Manabu Kujiraoka, Makoto Kuroda, Koji Asai, Tsuyoshi Sekizuka, Kengo Kato, Manabu Watanabe, Hiroshi Matsukiyo, Tomoaki Saito, Tomotaka Ishii, Natsuya Katada, Yoshihisa Saida, Shinya Kusachi /掲載誌 : Frontiers in Microbiology /巻号・発行年等 : 8:685, 201
Supplemental material for A novel protocol for three-dimensional rotational venography with low-dose contrast media in preoperative angiography of brain tumours
No full textSupplemental Material for A novel protocol for three-dimensional rotational venography with low-dose contrast media in preoperative angiography of brain tumours by Kimiaki Kashimoto, Katsunori Asai, Manabu Kinoshita, Yoshiko Okita, Shogo Tanabe, Yasuhiko Yamane, Minoru Kawamata, Akitoshi Yoneda and Katsuyuki Nakanishi in The Neuroradiology Journal</p
Asymptotic Theory for Robust Autocorrelation Test under Stochastic Volatility
No full textWooldridge (1991) suggest a robust test for autocorrelations of the disturbances of regression models, under misspecified conditional heteroskedastic model. Although stochastic volatility (SV) models allow unconditional time-varying variance, the Monte Carlo results of Asai (2000) indicate that the test of Wooldridge (1991) is robust under the SV process. This paper shows that the test statistic has asymptotic χ2 distribution under the null hypothesis of no serial
correlation, even when the underlying process has stochastic volatility.departmental bulletin pape
Dynamic Conditional Correlations for Asymmetric Processes
No full textThe paper develops two Dynamic Conditional Correlation (DCC) models, namely the Wishart DCC (wDCC) model. The paper applies the wDCC approach to the exponential GARCH (EGARCH) and GJR models to propose asymmetric DCC models. We use the standardized multivariate t-distribution to accommodate heavy-tailed errors. The paper presents an empirical example using the trivariate data of the Nikkei 225, Hang Seng and Straits Times Indices for estimating and forecasting the wDCC-EGARCH and wDCC-GJR models, and compares the performance with the asymmetric BEKK model. The empirical results show that AIC and BIC favour the wDCC-EGARCH model to the wDCC-GJR, asymmetric BEKK and alternative conventional DCC models. Moreover, the empirical results indicate that the wDCC-EGARCH-t model produces reasonable VaR threshold forecasts, which are very close to the nominal 1% to 3% values.Dynamic conditional correlations, Wishart process, EGARCH, GJR, asymmetric BEKK, heavy-tailed errors.
Alternative Asymmetric Stochastic Volatility Models
No full textThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.Stochastic volatility; asymmetric effects; leverage; threshold; indicator function; importance sampling; numerical simulations
Dynamic Conditional Correlations for Asymmetric Processes
No full textThe paper develops two Dynamic Conditional Correlation (DCC) models, namely the Wishart DCC (WDCC) model and the Matrix-Exponential Conditional Correlation (MECC) model. The paper applies the WDCC approach to the exponential GARCH (EGARCH) and GJR models to propose asymmetric DCC models. We use the standardized multivariate t-distribution to accommodate heavy-tailed errors. The paper presents an empirical example using the trivariate data of the Nikkei 225, Hang Seng and Straits Times Indices for estimating and forecasting the WDCC-EGARCH and WDCC-GJR models, and compares the performance with the asymmetric BEKK model. The empirical results show that AIC and BIC favour the WDCC-EGARCH model to the WDCC-GJR and asymmetric BEKK models. Moreover, the empirical results indicate that the WDCC-EGARCH-t model produces reasonable VaR threshold forecasts, which are very close to the nominal 1% to 3% values.
"Alternative Asymmetric Stochastic Volatility Models"
No full textThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is insignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.
Alternative Asymmetric Stochastic Volatility Models
No full textThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is a generalization of the exponential GARCH (EGARCH) model of Nelson (1991). We consider categories for asymmetric effects, which describes the difference among the asymmetric effect of the EGARCH model, the threshold effects indicator function of Glosten, Jagannathan and Runkle (1992), and the negative correlation between the innovations in returns and volatility. The new model is estimated by the efficient importance sampling method of Liesenfeld and Richard (2003), and the finite sample properties of the estimator are investigated using numerical simulations. Four financial time series are used to estimate the alternative asymmetric SV models, with empirical asymmetric effects found to be statistically significant in each case. The empirical results for S&P 500 and Yen/USD returns indicate that the leverage and size effects are significant, supporting the general model. For TOPIX and USD/AUD returns, the size effect is nsignificant, favoring the negative correlation between the innovations in returns and volatility. We also consider standardized t distribution for capturing the tail behavior. The results for Yen/USD returns show that the model is correctly specified, while the results for three other data sets suggest there is scope for improvement.
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