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Uncertainty due to infectious diseases and stock-bond correlation
Gillas, Konstantinos Gkillas; Konstantatos, Christoforos; … - In: Econometrics : open access journal 9 (2021) 2, pp. 1-18
We study the non-linear causal relation between uncertainty-due-to-infectious-diseases and stock-bond correlation. To … this end, we use high-frequency 1-min data to compute daily realized measures of correlation and jumps, and then, we employ … this type of uncertainty on realized stock-bond correlation and jumps. Our findings reveal that uncertainty …
Persistent link: https://www.econbiz.de/10012504028
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The factor-spline-GARCH model for high and low frequency correlations
Rangel, Jose Gonzalo; Engle, Robert F. - 2009
that characterize long-term correlation patterns. We associate such term behavior with low frequency economic variables … improves the empirical fit of equity correlations in the US and correlation forecasts at long horizons. -- Factor models ; Low … frequency volatilities and correlations ; Dynamic conditional correlation ; Spline-GARCH ; Idiosyncratic volatility ; Long …
Persistent link: https://www.econbiz.de/10003821063
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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
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(Presentation Slides) Investor Overconfidence, Covariance Risk, and Predictors of Securities Returns
Daniel, Kent D. - 2018
Presentation Slides for "Overconfidence, Arbitrage, and Equilibrium Asset Pricing" This paper offers a model in which asset prices reflect both covariance risk and misperceptions of firmsapos prospects, and in which arbitrageurs trade against mispricing. In equilibrium, expected returns are...
Persistent link: https://www.econbiz.de/10012918741
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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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Efficient Markets and the Law : A Predictable Past and an Uncertain Future
Hu, Henry T. C. - 2012
This article analyzes the manifold situations in which the efficient-market hypothesis (EMH) has influenced — or has failed to influence — federal securities regulation and state corporate law, and the prospective roles for the EMH in these contexts. In federal securities regulation, the EMH...
Persistent link: https://www.econbiz.de/10013100915
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International tail risk and world fear
Nguyen, Duc Binh Benno; Prokopczuk, Marcel; Wese Simen, … - 2017
We examine the pricing of tail risk in international stock markets. We find that the tail risk of different countries is highly integrated. Introducing a new World Fear index, we find that local and global aggregate market returns are mainly driven by global tail risk rather than local tail...
Persistent link: https://www.econbiz.de/10011751251
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The time-varying relation between stock returns and monetary variables
McMillan, David G. - In: Journal of risk and financial management : JRFM 15 (2022) 1, pp. 1-17
shifting the pattern of behaviour. We show a change in the correlation between each of the three variables with stock returns …. Notably, a predominantly negative correlation with bond yields and inflation becomes positive, while the opposite is true for …. Results of predictive regressions for stock returns also indicate a switch in behaviour. Predominantly negative predictive …
Persistent link: https://www.econbiz.de/10012813273
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A Machine Learning Approach to Estimating Large Positive Definite Covariance Matrix of High Frequency Data
Cui, Liyuan - 2019
This paper proposes a novel covariance estimator via a machine learning approach when both the sampling frequency and covariance dimension are large. Assuming that a large covariance matrix can be decomposed into low rank and sparse components, our method simultaneously provides a consistent...
Persistent link: https://www.econbiz.de/10012867396
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An analysis of systematic risk in worldwide econonomic sentiment indices
Luu, Duc Thi; Yanovski, Boyan; Lux, Thomas - 2018 - Ver. January 2, 2018
In this paper, we investigate the temporal dynamics of correlations between sentiment indices worldwide. Employing the tools of Random Matrix Theory (RMT) and Principal Component Analysis (PCA), our paper aims to extract latent information embedded in the interactions between economic and...
Persistent link: https://www.econbiz.de/10011790790