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Obtaining and Predicting the Bounds of Realized Correlations
Grossmass, Lidan - 2013
The problem of estimation of realized correlation, which is analogous to realized covariance, is compounded by effects … point identification of realized correlation difficult, but identification bounds in the spirit of Manski (1995) can be … derived. These identification bounds allow for a more robust approach to inference, especially when the realized correlation …
Persistent link: https://www.econbiz.de/10013082359
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A Structural Approach for Predicting Default Correlation
Liu, Sheen - 2013
Default correlation is a critical concept in risk management for fixed income investment, bank management, and …-firm environment and predict the default correlation between two firms by directly simulating the calibrate model based on the observed … equity data (1990-2010) for various ratings. Using our empirical default correlation estimation as the benchmark, our …
Persistent link: https://www.econbiz.de/10013090295
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Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?
Bali, Turan G. - 2014
We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...
Persistent link: https://www.econbiz.de/10013066429
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Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?
Bali, Turan G. - 2014
We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...
Persistent link: https://www.econbiz.de/10013066748
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Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?
Bali, Turan G. - 2014
We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...
Persistent link: https://www.econbiz.de/10013067174
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Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?
Bali, Turan G. - 2014
We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...
Persistent link: https://www.econbiz.de/10013067280
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Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?
Bali, Turan G. - 2014
We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...
Persistent link: https://www.econbiz.de/10013067331
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Forecasting Covariance Matrices : A Mixed Frequency Approach
Halbleib, Roxana - 2015
model and forecast daily realized volatilities combined with low-frequency (daily) data as input to the correlation model …
Persistent link: https://www.econbiz.de/10013038331
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Hybrid Tail Risk and Expected Stock Returns : When Does the Tail Wag the Dog?
Bali, Turan G. - 2013
We introduce a new, hybrid measure of stock return tail covariance risk, motivated by the under-diversified portfolio holdings of individual investors, and investigate its cross-sectional predictive power. Our key innovation is that this covariance is measured across the left tail states of the...
Persistent link: https://www.econbiz.de/10013075854
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Incorporating Time-Dependent Covariates into BG-NBD Model for Churn Prediction in Non-Contractual Settings
Babkin, Andrey - 2017
Nowadays, churn prediction models in non-contractual settings are gaining increasing interest. In a non-contractual setting the exact moment of customers dropout is unknown. The popular approach to identify active customers is to fit parametric probability model and then infer the probability of...
Persistent link: https://www.econbiz.de/10012964742