VAR As a Tool to Assess the Market Risk of Trading Positions of a Commercial Bank

2016 ◽  
Vol 4 (2) ◽  
pp. 58-64
Author(s):  
Попова ◽  
Anna Popova
Keyword(s):  
At Risk ◽  
Exchange Rates ◽  
Commercial Bank ◽  
Value At Risk ◽  
Market Value ◽  
Market Risk ◽  
Foreign Exchange Rates ◽  
Financial Instruments ◽  
Short Period ◽  
The Common

Forecasting of any risk is the crucial activity for any commercial bank. In current situation market risk is an important element needed to be analyzed. The probability of this type of risk may be affected by the change in the market value of financial instruments and by the volatility of foreign exchange rates. Nowadays in Russia each organization should conduct proper risk-management and be able to predict possible losses. The article presents the assessment of the market risk by the example of the price of the common share of the Bank of Moscow. Forecasting is implemented by three models: ARIMA, Value-at-Risk and VAR. Scientific novelty of this article is in comparison of the prediction procedures of above mentioned methods. The result obtained during the analysis shows, that the model Value-at-Risk is efficient for a short period of forecasting and should be combined with others models in order to get more accurate results.

scholarly journals Using HMM Approach for Assessing Quality of Value at Risk Estimation: Evidence from PSE Listed Company

2017 ◽  
Vol 65 (5) ◽  
pp. 1687-1694
Author(s):  
Tomáš Konderla ◽  
Václav Klepáč
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange ◽  
Risk Estimation ◽  
Listed Company ◽  
Mixture Distribution ◽  
Normal Mixture ◽  
Development Characteristic ◽  
The Common

The article points out the possibilities of using Hidden Markov model (abbrev. HMM) for estimation of Value at Risk metrics (abbrev. VaR) in sample. For the illustration we use data of the company listed on Prague Stock Exchange in range from January 2011 to June 2016. HMM approach allows us to classify time series into different states based on their development characteristic. Due to a deeper shortage of existing domestic results or comparison studies with advanced volatility governed VaR forecasts we tested HMM with univariate ARMA‑GARCH model based VaR estimates. The common testing via Kupiec and Christoffersen procedures offer generalization that HMM model performs better that volatility based VaR estimation technique in terms of accuracy, even with the simpler HMM with normal‑mixture distribution against previously used GARCH with many types of non‑normal innovations.

Optimal Reciprocal Reinsurance under VaR or TVaR Constraint

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Hung-Hsi Huang ◽  
Ching-Ping Wang
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Moral Hazard ◽  
Value At Risk ◽  
Incentive Compatibility ◽  
Regular Form ◽  
Optimal Reinsurance ◽  
The Common ◽  
Risk Constraint ◽  
Management Requirement

Abstract Most existing researches on optimal reinsurance contract are based on an insurer’s viewpoint. However, the optimal reinsurance contract for an insurer is not necessarily to be optimal for a reinsurer. Hence, this study aims to develop the optimal reciprocal reinsurance which satisfies the benefits of both the insurer and reinsurer. Additionally, due to legislative restriction or risk management requirement, the wealth of insurer and reinsurer are frequently imposed upon a VaR (Value-at-Risk) or TVaR (Tail Value-at-Risk) constraint. Therefore, this study develops an optimal reciprocal reinsurance contract which maximizes the common benefits (evaluated by weighted addition of expected utilities) of the insurer and reinsurer subject to their VaR or TVaR constraints. Furthermore, for avoiding moral hazard problem, the developed contract is additionally restricted to a regular form or incentive compatibility (both indemnity schedule and retained loss schedule are continuously nondecreasing).

MEASURING THE MARKET RISK OF FREIGHT RATES: A VALUE-AT-RISK APPROACH

2008 ◽  
Vol 11 (05) ◽  
pp. 447-469 ◽  
Author(s):  
TIMOTHEOS ANGELIDIS ◽  
GEORGE SKIADOPOULOS
Keyword(s):  
At Risk ◽  
Hedge Funds ◽  
Value At Risk ◽  
Statistical Tests ◽  
Market Risk ◽  
Freight Rate ◽  
Freight Rates ◽  
Rate Risk ◽  
Risk Approach ◽  
Non Parametric

The fluctuation of shipping freight rates (freight rate risk) is an important source of market risk for all participants in the freight markets including hedge funds, commodity and energy producers. We measure the freight rate risk by the Value-at-Risk (VaR) approach. A range of parametric and non-parametric VaR methods is applied to various popular freight markets for dry and wet cargoes. Backtesting is conducted in two stages by means of statistical tests and a subjective loss function that uses the Expected Shortfall, respectively. We find that the simplest non-parametric methods should be used to measure freight rate risk. In addition, freight rate risk is greater in the wet cargoes markets. The margins in the growing freight derivatives markets should be set accordingly.

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