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Optimizing the CVaR via sampling
 In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI
, 2015
"... Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation. Based on this formula, we propose a novel samplingbased estimator for the gradient of the ..."
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Cited by 1 (1 self)
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Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation. Based on this formula, we propose a novel samplingbased estimator for the gradient
Optimizing the CVaR via Sampling Supplementary Material
"... Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation. Based on this formula, we propose a novel samplingbased estimator for the CVaR gradient, i ..."
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Conditional Value at Risk (CVaR) is a prominent risk measure that is being used extensively in various domains. We develop a new formula for the gradient of the CVaR in the form of a conditional expectation. Based on this formula, we propose a novel samplingbased estimator for the CVaR gradient
Exact Matrix Completion via Convex Optimization
, 2008
"... We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M. Can we complete the matrix and recover the entries that we have not seen? We show that one can perfe ..."
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Cited by 860 (27 self)
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perfectly recover most lowrank matrices from what appears to be an incomplete set of entries. We prove that if the number m of sampled entries obeys m ≥ C n 1.2 r log n for some positive numerical constant C, then with very high probability, most n × n matrices of rank r can be perfectly recovered
STRESS TESTING FOR VaR AND CVaR
"... Practical use of the contamination technique in stress testing for risk measures ..."
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Practical use of the contamination technique in stress testing for risk measures
Compressive sampling
, 2006
"... Conventional wisdom and common practice in acquisition and reconstruction of images from frequency data follow the basic principle of the Nyquist density sampling theory. This principle states that to reconstruct an image, the number of Fourier samples we need to acquire must match the desired res ..."
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Cited by 1427 (15 self)
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Conventional wisdom and common practice in acquisition and reconstruction of images from frequency data follow the basic principle of the Nyquist density sampling theory. This principle states that to reconstruct an image, the number of Fourier samples we need to acquire must match the desired
Global Financial Risks, CVaR and Contagion Management
, 2008
"... Street, and many articles had been written on the changes in the global risk landscape that followed. However, there is scarcity of rigorous studies using empirical data and advanced econometric methods to verify such a change and the nature of such a change. In this paper, we provide rigorous analy ..."
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Street, and many articles had been written on the changes in the global risk landscape that followed. However, there is scarcity of rigorous studies using empirical data and advanced econometric methods to verify such a change and the nature of such a change. In this paper, we provide rigorous analyses of statistically significant changes in global financial risks and sharp increases in conditional ValueatRisk after September 2008. We perform statistical analyses using conditional distributions on the tail losses of equity portfolios constructed from the stock indexes of six major global financial markets. Employing the generalized marginal Pareto distribution and multivariate copula method, we provide strong empirical evidence to assert the prevalence of heightened global financial risks and its contagion effect across the globe. An important implication arising out of these conclusions is that banks under BASEL II and BASEL III and financial institutions in the nearfuture should not underestimate its Conditional ValueatRisk by using the normal distribution model since under stressed situations past September 2008, the portfolio return distributions have tails that simultaneously grow longer and thinner in the direction of the loss region. We also provide some thoughts for contagion management.
Adapting to unknown smoothness via wavelet shrinkage
 JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
, 1995
"... We attempt to recover a function of unknown smoothness from noisy, sampled data. We introduce a procedure, SureShrink, which suppresses noise by thresholding the empirical wavelet coefficients. The thresholding is adaptive: a threshold level is assigned to each dyadic resolution level by the princip ..."
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Cited by 990 (20 self)
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We attempt to recover a function of unknown smoothness from noisy, sampled data. We introduce a procedure, SureShrink, which suppresses noise by thresholding the empirical wavelet coefficients. The thresholding is adaptive: a threshold level is assigned to each dyadic resolution level
Results 1  10
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700,295