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Performance of the multifractal model of asset returns (MMAR) : evidence from emerging stock markets
Günay, Samet - In: International Journal of Financial Studies : open … 4 (2016) 2, pp. 1-17
In this study, the performance of the Multifractal Model of Asset Returns (MMAR) was examined for stock index returns … of four emerging markets. The MMAR, which takes into account stylized facts of financial time series, such as long memory … consists of two sections. In the first section, we estimated the parameters of GARCH, EGARCH, FIGARCH, MRS-GARCH and MMAR for …
Persistent link: https://www.econbiz.de/10011474619
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Fractal structure of the stock markets of leading asian countries
Günay, Samet - In: Journal of East Asian economic integration 18 (2014) 4, pp. 367-394
In this study, we examined the fractal structure of the Nikkei225, HangSeng, Shanghai Stock Exchange and Straits Times Index of Singapore. Empirical analysis was performed via non-parametric, semi-parametric long memory tests and also fractal dimension calculations. In order to avoid spurious...
Persistent link: https://www.econbiz.de/10011568388
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A multifractal model of asset (in)variances
Grobys, Klaus - In: Journal of international financial markets, … 85 (2023), pp. 1-37
Persistent link: https://www.econbiz.de/10014433281
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The Information Content of High-Frequency Data for Estimating Equity Return Models and Forecasting Risk
Dobrev, Dobrislav - 2011
We demonstrate that the parameters controlling skewness and kurtosis in popular equity return models estimated at daily frequency can be obtained almost as precisely as if volatility is observable by simply incorporating the strong information content of realized volatility measures extracted...
Persistent link: https://www.econbiz.de/10013128339
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A Simple Nonlinear Predictive Model for Stock Returns
Cai, Biqing - 2017
In this paper, we propose a simple approach to testing and modelling nonlinear predictability of stock returns using Hermite Functions. The proposed test suggests that there exists a kind of nonlinear predictability for the dividend yield. Furthermore, the out-of-sample evaluation results...
Persistent link: https://www.econbiz.de/10012945869
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Jump variation estimation with noisy high frequency financial data via wavelets
Zhang, Xin; Kim, Donggyu; Wang, Yazhen - In: Econometrics : open access journal 4 (2016) 3, pp. 1-26
This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...
Persistent link: https://www.econbiz.de/10011568279
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Multi-step non- and semi-parametric predictive regressions for short and long horizon stock return prediction
Cheng, Tingting; Gao, Jiti; Linton, Oliver - 2018
In this paper, we propose three new predictive models: the multi-step nonparametric predictive regression model and the multi-step additive predictive regression model, in which the predictive variables are locally stationary time series; and the multi-step time-varying coefficient predictive...
Persistent link: https://www.econbiz.de/10011775136
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Local Predictability of Stock Returns and Cash Flows
Yu, Deshui; Chen, Li - 2023
Motivated by the present-value framework, this article proposes a novel and flexible semiparametric time-varying model to examine the so-called `pockets of predictability,' i.e., stock returns or cash flows are significantly predictable in a given local period. We apply a semiparametric profile...
Persistent link: https://www.econbiz.de/10014257232
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Time-Varying Predictability of the Long Horizon Equity Premium Based on Semiparametric Regressions
Yu, Deshui; Li, Chen; Li, Luyang - 2023
This paper proposes a novel semiparametric time-varying model for long-horizon predictive regressions in which the coefficients are allowed to change over time with unspecified functional forms. A linear projection method is employed to deal with the embedded endogeneity issue. We pursue an...
Persistent link: https://www.econbiz.de/10014258471
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A Comparison of Conditional Volatility Estimators for the ISE National 100 Index Returns
Köksal, Bülent - 2009
We compare more than 1000 different volatility models in terms of their fit to the historical ISE-100 Index data and their forecasting performance of the conditional variance in an out-of-sample setting. Exponential GARCH model of Nelson (1991) with “constant mean, t-distribution, one lag...
Persistent link: https://www.econbiz.de/10013159436