Narrow search
Showing 1 - 10 of 1,550
Cover Image
Energy contagion in the COVID-19 crisis
Heinlein, Reinhold; Legrenzi, Gabriella; Mahadeo, Scott … - 2020
time of the COVID-19 pandemic. We provide evidence in favour of energy contagion, in term of significantly higher …
Persistent link: https://www.econbiz.de/10012226706
Cover Image
Quantile Spectral Beta : A Tale of Tail Risks, Investment Horizons, and Asset Prices
Baruník, Jozef - 2019
We examine how extreme market risks are priced in the cross-section of asset returns at various horizons. Based on the decomposition of covariance between indicator functions capturing fluctuations of different parts of return distributions over various frequencies, we define a \textit{quantile...
Persistent link: https://www.econbiz.de/10012899016
Cover Image
Tail risks, asset prices, and investment horizons
Baruník, Jozef; Nevrla, Matěj - 2019
We examine how extreme market risks are priced in the cross-section of asset returns at various horizons. Based on the frequency decomposition of covariance between indicator functions, we define the quantile cross-spectral beta of an asset capturing tail-specific as well as horizon-, or...
Persistent link: https://www.econbiz.de/10012009758
Cover Image
Testing for Stock Market Contagion : A Quantile Regression Approach
Park, Sungyong - 2015
Regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile … contagion test allows us to investigate the stock market contagion at various quantiles, not only at the mean. We show that the … quantile contagion test can detect a contagion effect that is possibly ignored by correlation-based tests. A wide range of …
Persistent link: https://www.econbiz.de/10013025474
Cover Image
Expected Returns and Large Language Models
Jiang, Jingwen; Kelly, Bryan T.; Xiu, Dacheng - 2023
We extract contextualized representations of news text to predict returns using the state-of-the-art large language models in natural language processing. Unlike the traditional bag-of-words approach, the contextualized representation captures both the syntax and semantics of text, thus...
Persistent link: https://www.econbiz.de/10014351081
Cover Image
Asset Pricing and Deep Learning
Zhang, Chen - 2022
Traditional machine learning methods have been widely studied in financial innovation. My study focuses on the application of deep learning methods on asset pricing.I investigate various deep learning methods for asset pricing, especially for risk premia measurement. All models take the same set...
Persistent link: https://www.econbiz.de/10014236793
Cover Image
Testing for stock market contagion : a quantile regression approach
Park, Sungyong; Wang, Wendun; Huang, Naijing - 2015 - This version: March 25, 2015
Regarding the asymmetric and leptokurtic behavior of financial data, we propose a new contagion test in the quantile … contagion test allows us to investigate the stock market contagion at various quantiles, not only at the mean. We show that the … quantile contagion test can detect a contagion effect that is possibly ignored by correlation-based tests. A wide range of …
Persistent link: https://www.econbiz.de/10010504111
Cover Image
Asset market linkages in crisis periods
Hartmann, Philipp; Straetmans, Stefan; Vries, Casper G. de - 2001
is particularly important. For example, our data show that stock-bond contagion is approximately as frequent as flight to …
Persistent link: https://www.econbiz.de/10011317457
Cover Image
On the Evaluation of Marginal Expected Shortfall
Caporin, Massimiliano - 2010
In the analysis of systemic risk, Marginal Expected Shortfall may be considered to evaluate the marginal impact of a single stock on the market Expected Shortfall. These quantities are generally computed using log-returns, in particular when there is also a focus on returns conditional...
Persistent link: https://www.econbiz.de/10013136975
Cover Image
Extreme Dependence in Investor Attention and Stock Returns - Consequences for Forecasting Stock Returns and Measuring Systemic Risk
Scheffer, Marcus - 2019
We characterize co-movements in investor attention by modeling multivariate internet search volume data. Using a variety of copula models that can capture both asymmetric and skewed dependence, we find empirical evidence of strong non-linear and asymmetric dependence in the attention investors...
Persistent link: https://www.econbiz.de/10012868542