Calculating Value-at-Risk Using Option Implied Probability Distribution of Asset Price

Wilmott ◽  
2012 ◽  
Vol 2012 (59) ◽  
pp. 56-61 ◽  
Author(s):  
Samit Ahlawat
Keyword(s):  
At Risk ◽  
Probability Distribution ◽  
Value At Risk ◽  
Asset Price

Return-Risk Evaluation of Investments

2020 ◽  
pp. 161-177
Author(s):  
Paul Weirich
Keyword(s):  
At Risk ◽  
Probability Distribution ◽  
Value At Risk ◽  
Risk Evaluation ◽  
Expected Return ◽  
Factors Affecting ◽  
Special Cases ◽  
Mean Risk

In finance, a common way of evaluating an investment uses the investment’s expected return and the investment’s risk, in the sense of the investment’s volatility, or exposure to chance. A version of this method derives from a general mean-risk evaluation of acts, under the assumption that only money, risk, and their sources matter. Although the method does not require a measure of risk, finance investigates measures of risks to assist evaluations of risks. An investment creates possible returns, and the variance of the probability distribution of their utilities is a measure of the investment’s risk. This measure neglects some factors affecting an investment’s risk, and so is satisfactory only in special cases. Another measure of risk is known as value-at-risk, or VAR. It also neglects some factors affecting an investment’s risk, and so should be restricted to special cases.

scholarly journals Higher dimensional probability of default in structural models

2021 ◽  
Author(s):  
Julie Ao
Keyword(s):  
At Risk ◽  
Probability Distribution ◽  
Value At Risk ◽  
Joint Probability ◽  
Tail Dependence ◽  
Three Dimensions ◽  
Joint Probability Distribution ◽  
Four Dimensions ◽  
Market Portfolio ◽  
Higher Dimensional

This thesis describes the joint probability distribution of defaults in two, three and four dimensions. In particular, default as defined by Merton and Black and Cox using analytical and simulated Monte Carlo approaches. Our analytical approach in a Merton setting, utilizes the multivariate normal to compute the joint probability distribution in any dimension. In a Black-Cox setting, analytical solutions are defined in specific dimensions, therefore we rely on a simulated approach. The precision of our simulated approaches are evaluated using 104, 107 and up to 107.5 paths 1. We use our results to compare the probability of defaults in both settings as well as tail dependence, portfolio value and value at risk. Tail dependence is evaluated in two and three dimensions with ρ=0.3 and ρ=0.9. We define covariance parameters in four dimensions; "normal" and "crisis" market conditions, to evaluate portfolio value in a credit and market portfolio and value at risk.

scholarly journals Asset Price Dynamics with Value-at-Risk Constrained Traders

2002 ◽  
Author(s):  
Jon Danielsson ◽  
Jean-Pierre Zigrand ◽  
Hyun Song Shin
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Asset Price ◽  
Price Dynamics

CoVaR

2016 ◽  
Vol 106 (7) ◽  
pp. 1705-1741 ◽  
Author(s):  
Tobias Adrian ◽  
Markus K. Brunnermeier
Keyword(s):  
At Risk ◽  
Financial Crisis ◽  
Systemic Risk ◽  
Value At Risk ◽  
Asset Price ◽  
Financial System ◽  
Maturity Mismatch ◽  
Out Of Sample ◽  
Forward Looking

We propose a measure of systemic risk, Δ CoVaR, defined as the change in the value at risk of the financial system conditional on an institution being under distress relative to its median state. Our estimates show that characteristics such as leverage, size, maturity mismatch, and asset price booms significantly predict Δ CoVaR. We also provide out-of-sample forecasts of a countercyclical, forward-looking measure of systemic risk, and show that the 2006:IV value of this measure would have predicted more than one-third of realized Δ CoVaR during the 2007–2009 financial crisis. (JEL C58, E32, G01, G12, G17, G20, G32)

scholarly journals Higher dimensional probability of default in structural models

2021 ◽  
Author(s):  
Julie Ao
Keyword(s):  
At Risk ◽  
Probability Distribution ◽  
Value At Risk ◽  
Joint Probability ◽  
Tail Dependence ◽  
Three Dimensions ◽  
Joint Probability Distribution ◽  
Four Dimensions ◽  
Market Portfolio ◽  
Higher Dimensional

This thesis describes the joint probability distribution of defaults in two, three and four dimensions. In particular, default as defined by Merton and Black and Cox using analytical and simulated Monte Carlo approaches. Our analytical approach in a Merton setting, utilizes the multivariate normal to compute the joint probability distribution in any dimension. In a Black-Cox setting, analytical solutions are defined in specific dimensions, therefore we rely on a simulated approach. The precision of our simulated approaches are evaluated using 104, 107 and up to 107.5 paths 1. We use our results to compare the probability of defaults in both settings as well as tail dependence, portfolio value and value at risk. Tail dependence is evaluated in two and three dimensions with ρ=0.3 and ρ=0.9. We define covariance parameters in four dimensions; "normal" and "crisis" market conditions, to evaluate portfolio value in a credit and market portfolio and value at risk.

Worst-case conditional value-at-risk based bidding strategy for wind-hydro hybrid systems under probability distribution uncertainties

2019 ◽  
Vol 256 ◽  
pp. 113918 ◽  
Author(s):  
Yangyang Liu ◽  
Zhongqi Shen ◽  
Xiaowei Tang ◽  
Hongbo Lian ◽  
Jiarui Li ◽  
...  
Keyword(s):  
At Risk ◽  
Probability Distribution ◽  
Hybrid Systems ◽  
Value At Risk ◽  
Conditional Value At Risk ◽  
Bidding Strategy ◽  
Worst Case

Extremwerttheorie und Value-at-Risk

2015 ◽  
Vol 44 (5) ◽  
pp. 259-267
Author(s):  
Frank Schuhmacher ◽  
Benjamin R. Auer
Keyword(s):  
At Risk ◽  
Value At Risk

Value at Risk

Controlling ◽  
2004 ◽  
Vol 16 (7) ◽  
pp. 425-426
Author(s):  
Mischa Seiter ◽  
Sven Eckert
Keyword(s):  
At Risk ◽  
Value At Risk
Sign in / Sign up

Export Citation Format

Share Document