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Credit cycles and macro fundamentals
Koopman, Siem Jan; Kräussl, Roman; Lucas, André; … - 2006
We study the relation between the credit cycle and macro-economic fundamentals in an intensity-based framework. Using … the credit cycle from the micro rating data. We relate this cycle to the business cycle, bank lending conditions, and … financial market variables. In line with earlier studies, these variables appear to explain part of the credit cycle. As our …
Persistent link: https://www.econbiz.de/10011348707
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Improving Portfolio Allocation Through Covariance Matrix Filtering
Golden, Daron - 2017
The sample covariance matrix is known to contain substantial statistical noise, making it inappropriate for use in financial decision making. Leading researchers have proposed various filtering methods that attempt to reduce the level of noise in the covariance matrix estimator. In most cases,...
Persistent link: https://www.econbiz.de/10012965654
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Black-Litterman in Continuous Time : The Case for Filtering
Davis, Mark - 2013
In this article, we extend the Black-Litterman approach to a continuous time setting. We model analyst views jointly with asset prices to estimate the unobservable factors driving asset returns. The key in our approach is that the filtering problem and the stochastic control problem are...
Persistent link: https://www.econbiz.de/10013082305
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Dynamic Volatility Management : From Conditional Volatility to Realized Volatility
Zhang, Rongju - 2019
The volatility of concern in conventional volatility-managed strategies such as volatility-targeting strategy and mean-variance optimization is the expected conditional volatility. However for investors, it is the realized volatility that is important, because there is only one realization in...
Persistent link: https://www.econbiz.de/10012890272
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Large Dimensional Time-Varying GMM Estimation : A New Approach
Cui, Liyuan; Hong, Yongmiao; Wang, Junhui - 2021
We develop a novel machine learning method to estimate large dimensional time-varying GMM models via our newly designed ridge fusion regularization scheme. Our method is a one-step procedure and allows for abrupt, smooth and dual type time variation with a fast rate of convergence. It...
Persistent link: https://www.econbiz.de/10013234588
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Unrestricted Maximum Likelihood Estimation of Multivariate Realized Volatility Models
Vogler, Jan; Golosnoy, Vasyl - 2022
The popular conditional autoregressive Wishart (CAW) model for dynamics of realized covariance matrices provides a flexible parametrisation. However, the number of parameters grows quadratically with the number of assets, which causes enormous computational difficulties in higher dimensions....
Persistent link: https://www.econbiz.de/10013292096
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Filtering Noise from Correlation Matrices : Paper 3 in a Series 'Uncovering Hidden Dependencies'
Izmailov, Alexander - 2014
of random matrix theory, a branch of probability theory; and an introduction of the Shannon entropy as a measure of noise …
Persistent link: https://www.econbiz.de/10013062134
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'Extraordinary Stability of Noise-Filtered Correlation Matrices' : Paper 4 in a Series 'Uncovering Hidden Dependencies'
Izmailov, Alexander - 2014
Alexander Izmailov, Ph.D (theoretical physics) and Brian Shay, Ph.D (mathematics), of Market Memory Trading, L.L.C., present in a series of nine (9) white papers, aspects of a revolutionary advance in uncovering hidden dependencies via filtering noise from correlation matrices developed by the...
Persistent link: https://www.econbiz.de/10013062136
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Portfolio rebalancing based on time series momentum and downside risk
Guo, Xiaoshi; Ryan, Sarah - 2021
To examine the familiar tradeoff between risk and return in financial investments, we use a rolling two-stage stochastic program to compare mean-risk optimization models with time series momentum strategies. In a backtest of allocating investment between a market index and a risk-free asset, we...
Persistent link: https://www.econbiz.de/10013247805
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CHICAGO: a fast and accurate method for portfolio risk calculation
Broda, Simon A.; Paolella, Marc S. - 2008
The estimation of multivariate GARCH models remains a challenging task, even in modern computer environments. This manuscript shows how Independent Component Analysis can be used to estimate the Generalized Orthogonal GARCH model in a fraction of the time otherwise required. The proposed method...
Persistent link: https://www.econbiz.de/10003961455