Results 11 to 20 of about 5,992 (265)
Computation, 2022 Tourism forecasting has garnered considerable interest. However, integrating tourism forecasting with volatility is significantly less typical. This study investigates the performance of both the single models and their combinations for forecasting the ...
Yuruixian Zhang +3 more
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Comparing various GARCH-type models in the estimation and forecasts of volatility of S&P 500 returns during Global Finance Crisis of 2008 and COVID-19 financial crisis [PDF]
SHS Web of Conferences, 2023 In this study, we utilize various GARCH-type models to estimate and forecast volatility on S&P 500 returns and compare the results between the two financial crises, the GFC of 2008 (Global Financial Crisis of 2008) and the COVID-19 financial crisis ...
Chen Xuanyu
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Forecasting Coherent Volatility Breakouts [PDF]
SSRN Electronic Journal, 2014 The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. The approach for computing fractal dimension using sequence of the minimal covers with decreasing scale (proposed in [1]) is used to decompose volatility into two0dynamic ...
Didenko, Alexander +2 more
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Global economic policy uncertainty and stock volatility: evidence from emerging economies
Journal of Applied Economics, 2021 We investigate the impact of the global economic policy uncertainty (GEPU) on stock volatility for nine emerging economies (Brazil, Russia, India, China, South Africa, Mexico, Indonesia, South Korea, and Turkey).
Xiaoling Yu, Yirong Huang, Kaitian Xiao
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Modeling and Forecasting the Volatility of NIFTY 50 Using GARCH and RNN Models
Economies, 2022 The stock market is constantly shifting and full of unknowns. In India in 2000, technological advancements led to significant growth in the Indian stock market, introducing online share trading via the internet and computers.
Vanshu Mahajan +2 more
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Journal of Forecasting, 2006 AbstractIn this paper, we investigate the time series properties of S&P 100 volatility and the forecasting performance of different volatility models. We consider several nonparametric and parametric volatility measures, such as implied, realized and model‐based volatility, and show that these volatility processes exhibit an extremely slow mean ...
Nikolay Gospodinov +2 more
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Investors’ perspective on forecasting crude oil return volatility: Where do we stand today?
Journal of Management Science and Engineering, 2022 In this paper, we review studies of oil volatility prediction from a new perspective: that of investors who require economic evaluations of forecasting performance.
Li Liu +3 more
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The Importance of the Volatility Risk Premium for Volatility Forecasting [PDF]
SSRN Electronic Journal, 2013 In this paper, we study the role of the volatility risk premium for the forecasting performance of implied volatility. We introduce a non-parametric and parsimonious approach to adjust the model-free implied volatility for the volatility risk premium and implement this methodology using more than 20 years of options and futures data on three major ...
Prokopczuk, Marcel, Wese Simen, Chardin
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Forecasting Volatility in Asian Stock Markets: Contributions of Local, Regional, and Global Factors
Asian Development Review, 2011 This paper examines volatility forecasting for the broad market indices of 12 Asian stock markets. After considering the long memory in volatility and volatility jumps, the paper incorporates local, regional, and global factors into a heterogeneous ...
Jianxin Wang
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Forecasting the Volatility of the Stock Index with Deep Learning Using Asymmetric Hurst Exponents
Fractal and Fractional, 2022 The prediction of the stock price index is a challenge even with advanced deep-learning technology. As a result, the analysis of volatility, which has been widely studied in traditional finance, has attracted attention among researchers.
Poongjin Cho, Minhyuk Lee
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