SSRN Author: Cosimo MunariCosimo Munari SSRN Content
https://www.ssrn.com/author=1754159
https://www.ssrn.com/rss/en-usWed, 28 Nov 2018 01:01:09 GMTeditor@ssrn.com (Editor)Wed, 28 Nov 2018 01:01:09 GMTwebmaster@ssrn.com (WebMaster)SSRN RSS Generator 1.0REVISION: Risk Measures Based on Benchmark Loss DistributionsWe introduce a class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected Shortfall (ES), take into account both the frequency and the severity of losses. Under VaR a single confidence level is assigned regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key ingredient is a benchmark loss distribution (BLD), i.e.~a function that associates to each potential loss a maximal acceptable probability of occurrence. The corresponding risk measure, called Loss VaR (LVaR), determines the minimal capital injection that is required to align the loss distribution of a risky position to the target BLD. By design, one has full flexibility in the choice of the BLD profile and, therefore, in the range of relevant quantiles. Special attention is given to piecewise constant functions and to tail distributions of benchmark random losses, in which case the acceptability condition imposed by the ...
https://www.ssrn.com/abstract=3088423
https://www.ssrn.com/1742122.htmlTue, 27 Nov 2018 11:25:53 GMTREVISION: Risk Measures Based on Benchmark Loss DistributionsWe introduce a new class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected Shortfall (ES), take into account both the frequency and the severity of losses. Under VaR a single confidence level is assigned regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key ingredient is a benchmark loss distribution (BLD), i.e.~a function that associate to any potential loss a maximal acceptable probability of occurrence. The corresponding risk measure determines the minimal capital injection that is required to align the loss distribution of a risky position to the target BLD. By design, one has full flexibility in the choice of the BLD profile and, therefore, in the range of relevant quantiles. Special attention is given to piecewise constant functions and to tail distributions of benchmark random losses, in which case the acceptability condition imposed by the BLD boils down to ...
https://www.ssrn.com/abstract=3088423
https://www.ssrn.com/1704474.htmlTue, 03 Jul 2018 11:05:41 GMTREVISION: Risk Measures Based on Benchmark Loss DistributionsWe introduce a new class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected Shortfall (ES), take into account both the frequency and the severity of losses. Under VaR a single confidence level is assigned regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key ingredient is a benchmark loss distribution (BLD), i.e.~a function that associate to any potential loss a maximal acceptable probability of occurrence. The corresponding risk measure determines the minimal capital injection that is required to align the loss distribution of a risky position to the target BLD. By design, one has full flexibility in the choice of the BLD profile and, therefore, in the range of relevant quantiles. Special attention is given to piecewise constant functions and to tail distributions of benchmark random losses, in which case the acceptability condition imposed by the BLD boils down to ...
https://www.ssrn.com/abstract=3088423
https://www.ssrn.com/1704256.htmlMon, 02 Jul 2018 09:21:11 GMTREVISION: Risk Measures Based on Benchmark Loss DistributionsWe introduce a new class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected Shortfall (ES), take into account both the frequency and the severity of losses. Under VaR a single confidence level is assigned regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key ingredient is a benchmark loss distribution (BLD), i.e.~a function that associate to any potential loss a maximal acceptable probability of occurrence. The corresponding risk measure determines the minimal capital injection that is required to align the loss distribution of a risky position to the target BLD. By design, one has full flexibility in the choice of the BLD profile and, therefore, in the range of relevant quantiles. Special attention is given to piecewise constant functions and to tail distributions of benchmark random losses, in which case the acceptability condition imposed by the BLD boils down to ...
https://www.ssrn.com/abstract=3088423
https://www.ssrn.com/1674887.htmlSat, 10 Mar 2018 15:23:05 GMTREVISION: Risk Measures Based on Benchmark Loss DistributionsWe introduce a new class of quantile-based risk measures that generalize Value at Risk (VaR) and, likewise Expected Shortfall (ES), take into account both the frequency and the severity of losses. Under VaR a single confidence level is assigned regardless of the size of potential losses. We allow for a range of confidence levels that depend on the loss magnitude. The key ingredient is a benchmark loss distribution (BLD), i.e.~a function that associate to any potential loss a maximal acceptable probability of occurrence. The corresponding risk measure determines the minimal capital injection that is required to align the loss distribution of a risky position to the target BLD. By design, one has full flexibility in the choice of the BLD profile and, therefore, in the range of relevant quantiles. Special attention is given to piecewise constant functions and to tail distributions of benchmark random losses, in which case the acceptability condition imposed by the BLD boils down to ...
https://www.ssrn.com/abstract=3088423
https://www.ssrn.com/1652959.htmlTue, 19 Dec 2017 13:06:55 GMT