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Asymmetry in Stock Comovements : An Entropy Approach
Jiang, Lei - 2020
return. This approach yields a model-free test for stock return asymmetry, generalizing the correlation-based test proposed …
Persistent link: https://www.econbiz.de/10012856552
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Correlated information consumption and comovement in the stock market
Tan, Selin Duz - In: Borsa Istanbul Review 22 (2022) 4, pp. 812-827
This study shows how correlated information consumption (CIC) of retail investors relates to comovement in stock market outcomes. We construct clusters of stocks with CIC by employing network analysis on Google co-search data. We predict significant comovement in returns and liquidity of stocks...
Persistent link: https://www.econbiz.de/10013334839
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Testing and Support Recovery of Correlation Structures for Matrix-Valued Observations with an Application to Stock Market Data
Chen, Xin; Yang, Dan; Xu, Yan; Xia, Yin; Wang, Dong; … - 2021
Estimation of the covariance matrix of asset returns is crucial to portfolio construction. As suggested by economic … theories, the correlation structure among assets differs between emerging markets and developed countries. It is therefore … imperative to make rigorous statistical inference on correlation matrix equality between the two groups of countries. However, if …
Persistent link: https://www.econbiz.de/10013314503
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Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2021 - This version: June 2021
recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the … unconditional correlation matrix. In this paper, we show how performance can be increased further by using open/high/low/close (OHLC …
Persistent link: https://www.econbiz.de/10012584099
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Covariance Forecasting in Equity Markets
Symitsi, Efthymia - 2018
We compare the performance of popular covariance forecasting models in the context of a portfolio of major European equity indices. We find that models based on high-frequency data offer a clear advantage in terms of statistical accuracy. They also yield more theoretically consistent predictions...
Persistent link: https://www.econbiz.de/10012915984
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Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2022 - This version: January 2022
recent DCC-NL model of Engle et al. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the … unconditional correlation matrix. In this paper, we show how performance can be increased further by using open/high/low/close (OHLC …
Persistent link: https://www.econbiz.de/10013040932
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Large dynamic covariance matrices: enhancements based on intraday data
De Nard, Gianluca; Engle, Robert F.; Ledoit, Olivier; … - 2020
. (2019) is able to overcome this curse via nonlinear shrinkage estimation of the unconditional correlation matrix. In this …
Persistent link: https://www.econbiz.de/10012253083
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CoAnomaly : Correlation Risk in Stock Market Anomalies
Guo, James Tengyu - 2019
pairwise correlation among 34 anomalies, which helps to explain both the time-series and the cross-sectional anomaly return …, CoAnomaly carries a negative price of risk. These return patterns suggest that arbitrageurs take the time-varying correlation …
Persistent link: https://www.econbiz.de/10012900148
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Forecasting Stock Market Volatility and Application to Volatility Timing Portfolios
Chun, Dohyun; Cho, Hoon; Ryu, Doojin - 2022
This study predicts stock market volatility and applies them to the standard problem in finance, namely, asset allocation. Based on machine learning and model averaging approaches, we integrate the drivers’ predictive information to forecast market volatilities. Using various evaluation...
Persistent link: https://www.econbiz.de/10013404229
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Option-implied information and predictability of extreme returns
Vilkovz, Grigory; Xiaox, Yan - 2013 - This version: January 28, 2013
We study whether prices of traded options contain information about future extreme market events. Our option-implied conditional expectation of market loss due to tail events, or tail loss measure, predicts future market returns, magnitude, and probability of the market crashes, beyond and above...
Persistent link: https://www.econbiz.de/10010226098