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Machine learning for predicting stock return volatility

Filipović, Damir; Khalilzadeh, Amir - 2021

We use machine learning methods to predict stock return volatility. Our out-of-sample prediction of realised volatility for a large cross-section of US stocks over the sample period from 1992 to 2016 is on average 44.1% against the actual realised volatility of 43.8% with an R2 being as high as...

Persistent link: https://www.econbiz.de/10012800743

News augmented GARCH(1,1) model for volatility prediction

Sadik, Zryan A.; Date, Paresh M.; Mitra, Gautam - In: IMA journal of management mathematics 30 (2019) 2, pp. 165-185

Persistent link: https://www.econbiz.de/10012057108

Stock market manipulation detection using feature modelling with hybrid recurrent neural networks

Sridhar, Sashank; Mootha, Siddartha - In: International journal of networking and virtual … 26 (2022) 1/2, pp. 47-79

Persistent link: https://www.econbiz.de/10013256819

Asymmetric volatility effects in risk management: An empirical analysis using a stock index futures

Benavides, Guillermo - 2020

In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical...

Persistent link: https://www.econbiz.de/10012616403

What Exactly is "Bad News" in Foreign Exchange Markets? Evidence from Latin American Markets

Maya, Cecilia; Gómez, Karoll - In: Latin American Journal of Economics-formerly Cuadernos … 45 (2008) 132, pp. 161-183

This paper asks whether the ‘leverage effect’ –as defined by Black (1976) for stock markets– is also a characteristic of foreign exchange markets. The study focuses on five Latin American emerging markets which have adopted a floating exchange regime. It

Persistent link: https://www.econbiz.de/10005510150

Bad environments, good environments: A non-Gaussian asymmetric volatility model

Bekaert, Geert; Engstrom, Eric; Ermolov, Andrey - In: Journal of Econometrics 186 (2015) 1, pp. 258-275

heteroskedasticity (GARCH) class that admits conditional non-Gaussianities in a tractable fashion. Our “bad environment–good environment …-order moments. In an empirical application to stock returns, the BEGE model outperforms asymmetric GARCH and regime-switching models …

Persistent link: https://www.econbiz.de/10011209276

Asymmetric Volatility and Risk-return Relationship in the Indian Stock Market

Karmakar, Madhusudan - In: South Asia Economic Journal 8 (2007) 1, pp. 99-116

This article investigates the heteroscedastic behaviour of the Indian stock market using different GARCH models. First …, the standard GARCH approach is used to investigate whether stock return volatility changes over time and if so, whether it …) GARCH in the mean extension has been tried to examine the relation between market risk and expected return. The …

Persistent link: https://www.econbiz.de/10010784330

The dynamics in the spot, futures, and call options with basis asymmetries: an intraday analysis in a generalized multivariate GARCH-M MSKST framework

Wang, Kai-Li; Chen, Mei-Ling - In: Review of Quantitative Finance and Accounting 29 (2007) 4, pp. 371-394

Persistent link: https://www.econbiz.de/10005701339

Exchange rate exposure of stock returns at firm level

Premaratne, Gamini; Jayasinghe, Prabhath - EconWPA - 2005

direct and indirect exchange rate exposure effects. In this paper, we suggest an orthogonalized GJR-GARCH-t version of …

Persistent link: https://www.econbiz.de/10005119493

Measuring Asymmetry and Persistence in Conditional Volatility in Real Output : Evidence from Three East Asian Tigers Using a Multivariate GARCH approach

Hai, Vu Thanh; Tsuia, Albert K.; Zhang, Zhaoyong - East Asian Bureau of Economic Research (EABER) - 2009

: Singapore, Hong Kong and Taiwan. The widely accepted exponential GARCH-type model is used to capture the existence of asymmetric …

Persistent link: https://www.econbiz.de/10009363459