Search Results - subject:"Probability distribution"

Chen, Kan; Cheng, Tuoyuan - 2022

Value-at-Risk (VaR) and Expected Shortfall (ES) are common high quantile- based risk measures adopted in financial regulations and risk management. In this paper, we propose a tail risk measure based on the most probable maximum size of risk events (MPMR) that can occur over a length of time....

Persistent link: https://www.econbiz.de/10014238744

Tail Risk Forecasting Using Bayesian Realized Egarch Models

Tendenan, Vica; Gerlach, Richard H.; Wang, Chao - 2022

This paper develops a Bayesian framework for the realized exponential generalized autoregressive conditional heteroskedasticity (realized EGARCH) model and adopts a standardized Student-t and a standardized skewed Student-t distributions for the return equation. The Bayesian estimators show more...

Persistent link: https://www.econbiz.de/10014239179

Probability Distribution in Volatility and Value-at-Risk Forecasting for Cryptocurrency

Chen, Qihao; Huang, Zhuo; Liang, Fang - 2022

This study investigates the role of probability distribution in forecasting volatility and Value-at-Risk (VaR). We use … the Realized GARCH model and high-frequency data from the cryptocurrency market and show that the role of probability … distribution varies across different situations. A skewed-t distribution contributes to better performance in forecasting the VaR …

Persistent link: https://www.econbiz.de/10014239198

Quantum Binomial Tree, an effective method for probability distribution loading for derivative pricing

Pracht, Rafał - 2022

In the paper, I propose a new effective approach to the probability distribution loading for derivative pricing. The …

Persistent link: https://www.econbiz.de/10014239333

From Knothe-Rosenblatt Rearrangement to Distribution Mapping for Gaussian Fixed-Income Models

Henry-Labordere, Pierre; Monedero, Tiphaine - 2022

The so-called distribution mapping is a technique, commonly used by practitioners in fixed-income, that allows to tweak model 1D-dis\-tri\-bu\-tions into market $1$D-distributions. This technique is intended to overcome the shortcomings of standard fixed-income diffusion models which do not...

Persistent link: https://www.econbiz.de/10014239408

Commodity Tail Risks

Ammann, Manuel; Mörke, Mathis; Prokopczuk, Marcel; … - 2022

In this study, we investigate the cross-section of option implied tail risks in commodity markets. In contrast to findings from equity markets, left and right tail risk implied by option markets are both large. Commodity specific variables exert the largest influence on tail risk, while there is...

Persistent link: https://www.econbiz.de/10014239679

Tail Approximations for Sum of Randomly Weighted Dependent Random Variables with Applications

Roozegar, Rasool; Toghdori, Abdolsaleh - 2022

There has been much work on the approximation of independent or dependent random variables. But we are not aware of any work giving exact results for the approximation of the sum of randomly weighted random variables. In this paper, we derive results for the randomly weighted sum of dependent...

Persistent link: https://www.econbiz.de/10014240361

What is the Predictive Value of SPF Point and Density Forecasts?

Clark, Todd E.; Ganics, Gergely; Mertens, Elmar - 2022

This paper presents a new approach to combining the information in point and density forecasts from the Survey of Professional Forecasters (SPF) and assesses the incremental value of the density forecasts. Our starting point is a model, developed in companion work, that constructs quarterly term...

Persistent link: https://www.econbiz.de/10014240770

Recipes and Economic Growth : A Combinatorial March Down an Exponential Tail

Jones, Charles I. - 2022

max extreme value to the number of draws and the shape of the tail for any continuous probability distribution …

Persistent link: https://www.econbiz.de/10014240910

Finite-Sample Performance of the T- and W-Estimators for the Pareto Tail Index under Data Truncation and Censoring

Poudyal, Chudamani; Brazauskas, Vytaras - 2022

A single-parameter Pareto model, Pareto I, arises in many areas of application such as pricing of insurance risks, measuring income or wealth inequality in economics, or modeling lengths of telephone calls in telecommunications. In insurance, for example, it is common to work with data that are...

Persistent link: https://www.econbiz.de/10014241162