On Historical Value at Risk under Distribution Uncertainty
نویسندگان
چکیده
منابع مشابه
Quantile uncertainty and value-at-risk model risk.
This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly imp...
متن کاملThe impact of distribution on value-at-risk measures
Value at risk is a popular approach to aid financial risk management. Questions about the appropriateness of the measure have arisen since the related 2008 bubble collapses in some US housing markets and the global financial market. These questions include the presence of fat tails and their impact. This paper compares results based upon assumptions of normality and logistic distributions, comp...
متن کاملEvaluation of Value-at-Risk Models Using Historical Data
esearchers in the field of financial economics have long recognized the importance of measuring the risk of a portfolio of financial assets or securities. Indeed, concerns go back at least four decades, when Markowitz’s pioneering work on portfolio selection (1959) explored the appropriate definition and measurement of risk. In recent years, the growth of trading activity and instances of finan...
متن کاملA News-Based Approach for Computing Historical Value-at-Risk
Within the field of finance, Value-at-Risk (VaR) is a widely adopted tool to assess portfolio risk. When calculating VaR based on historical stock return data, the data could be sensitive to outliers caused by seldom occurring news events in the sampled period. Using a data set of news events, of which the irregular events are identified using a Poisson distribution, we research whether the VaR...
متن کاملRisk-Management Models Based on the Portfolio Theory Using Historical Data under Uncertainty
A mission in this chapter is to extend previous mathematical programming problems using historical data to stochastic and fuzzy programming problems under uncertainty, particularly considering the risk-management. In the practice decision making, it is necessary to take various constraints and assumptions into consideration as well as uncertainty, such as the probability derived from the statis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Mathematical Finance
سال: 2015
ISSN: 2162-2434,2162-2442
DOI: 10.4236/jmf.2015.52010