scholarly journals Examination of Market Risk Estimation Models via DEA Approach Modelling

2017 ◽  
Vol 65 (2) ◽  
pp. 161-178
Author(s):  
Aleš Kresta ◽  
Tomáš Tichý ◽  
Mehdi Toloo
Keyword(s):  
Risk Estimation ◽  
Market Risk ◽  
Dea Approach ◽  
Estimation Models

The use of risk estimation models for the induction of secondary cancers following radiotherapy

2005 ◽  
Vol 44 (4) ◽  
pp. 339-347 ◽  
Author(s):  
Alexandru Daşu ◽  
Iuliana Toma-Daşu ◽  
Jörgen Olofsson ◽  
Mikael Karlsson
Keyword(s):  
Risk Estimation ◽  
Secondary Cancers ◽  
Estimation Models

489 The use of carcinogenesis risk estimation models for radiotherapy

2005 ◽  
Vol 76 ◽  
pp. S210
Author(s):  
A. Dasu ◽  
I. Toma-Daşu ◽  
J. Olofsson ◽  
M. Karlsson
Keyword(s):  
Risk Estimation ◽  
Estimation Models

scholarly journals MARKET RISK ESTIMATION IN (T+)-TRANSACTIONS

2016 ◽  
Vol 7 (2(26)) ◽  
pp. 224-233 ◽  
Author(s):  
Radik B. Begov ◽  
Michael N. Prokofyev ◽  
Alexander S. Trusov
Keyword(s):  
Risk Estimation ◽  
Market Risk

scholarly journals Value-at-Risk Estimation of Equity Market Risk in India

2021 ◽  
Vol 9 (1) ◽  
pp. 1-24
Author(s):  
Jitender
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Moving Average ◽  
Equity Market ◽  
Market Risk ◽  
Financial Instrument ◽  
Historical Simulation ◽  
Distributed Models

Abstract The value-at-risk (Va) method in market risk management is becoming a benchmark for measuring “market risk” for any financial instrument. The present study aims at examining which VaR model best describes the risk arising out of the Indian equity market (Bombay Stock Exchange (BSE) Sensex). Using data from 2006 to 2015, the VaR figures associated with parametric (variance–covariance, Exponentially Weighted Moving Average, Generalized Autoregressive Conditional Heteroskedasticity) and non-parametric (historical simulation and Monte Carlo simulation) methods have been calculated. The study concludes that VaR models based on the assumption of normality underestimate the risk when returns are non-normally distributed. Models that capture fat-tailed behaviour of financial returns (historical simulation) are better able to capture the risk arising out of the financial instrument.

Comparison of market risk models with respect to suggested changes of Basel Accord

2014 ◽  
Vol 64 (Supplement-2) ◽  
pp. 257-274
Author(s):  
Eliška Stiborová ◽  
Barbora Sznapková ◽  
Tomáš Tichý
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Risk Estimation ◽  
Market Risk ◽  
Capital Requirements ◽  
Internal Models ◽  
Conditional Value At Risk ◽  
Risk Capital ◽  
Basel Accord ◽  
Capital Charge

The market risk capital charge of financial institutions has been mostly calculated by internal models based on integrated Value at Risk (VaR) approach, since the introduction of the Amendment to Basel Accord in 1996. The internal models should fulfil several quantitative and qualitative criteria. Besides others, it is the so called backtesting procedure, which was one of the main reasons why the alternative approach to market risk estimation — conditional Value at Risk or Expected Shortfall (ES) — were not applicable for the purpose of capital charge calculation. However, it is supposed that this approach will be incorporated into Basel III. In this paper we provide an extensive simulation study using various sets of market data to show potential impact of ES on capital requirements.

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