scholarly journals MENAKSIR VALUE AT RISK (VAR) PORTOFOLIO PADA INDEKS SAHAM DENGAN METODE PENDUGA VOLATILITAS GARCH

2013 ◽  
Vol 2 (1) ◽  
pp. 14
Author(s):  
INTAN AWYA WAHARIKA ◽  
KOMANG DHARMAWAN ◽  
NI MADE ASIH
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Stock Exchange ◽  
Stock Index ◽  
Financial Loss

Value at Risk (VaR) is a concept which was used to measure a risk on risk management. VaR explained the worst amount of financial loss in a financial product with the horizon and certain degree of believe. In the calculation of VaR, it was needed a prediction in volality, volality from a series of time which can be homokedasticity (constant) or heterokedasticity (ever changed). Changed volality can be found on the stock and stock index. One of the method which was done in modeling of changed volality was GARCH. In this research, GARCH was used to estimate VaR’s Value from IHSG and LQ45 to be sold in Jakarta Stock Exchange on 4 January to 23 August 2012 (650 observations) VaR can be calculated with a periode of horizon, 1 day, 10 days, and 22 days with the degree of believe 95%

scholarly journals Asymmetric Volatility Effects in Risk Management: An Empirical Analysis using a Stock Index Futures

2020 ◽  
Author(s):  
Guillermo Benavides
Keyword(s):  
Risk Management ◽  
Empirical Analysis ◽  
Value At Risk ◽  
Stock Exchange ◽  
Stock Index ◽  
Futures Contracts ◽  
Stock Index Futures ◽  
Index Futures ◽  
Minimum Capital ◽  
The Empirical Analysis

In this research paper ARCH-type models and option implied volatilities (IV) are applied in order to estimate the Value-at-Risk (VaR) of a stock index futures portfolio for several time horizons. The relevance of the asymmetries in the estimated volatility estimation is considered. The empirical analysis is performed on futures contracts of both the Standard and Poors 500 Index and the Mexican Stock Exchange. According to the results, the IV model is superior in terms of precision compared to the ARCH-type models. Under both methodologies there are relevant statistical gains when asymmetries are included. The referred gains range from 4 to around 150 basis points of minimum capital risk requirements. This research documents the importance of taking asymmetric effects (leverage effects) into account in volatility forecasts when it comes to risk management analysis.

scholarly journals Asymmetric Volatility Relevance in Risk Management: An Empirical Analysis using Stock Index Futures

2021 ◽  
Vol 16 (TNEA) ◽  
pp. 1-18
Author(s):  
Guillermo Benavides
Keyword(s):  
Risk Management ◽  
Empirical Analysis ◽  
Value At Risk ◽  
Stock Exchange ◽  
Research Work ◽  
Stock Index ◽  
Futures Contracts ◽  
Stock Index Futures ◽  
Index Futures ◽  
Minimum Capital

The objective of this research work is to show the relevance of asymmetries in estimating volatility. The methodology consists in the application of ARCH-type models and implied volatilities of options (IV) to estimate Value-at-Risk (VaR). These for a portfolio of stock index futures for various time horizons. The empirical analysis is carried out for the futures contracts for the Standard and Poors 500 and Mexican Stock Exchange Indices. According to the results, the IV model is superior in terms of precision compared to the ARCH-type models. It is recommended to use the relevant statistical gains when asymmetries are included with respect to when asymmetries are not used. The referred gains range from 4 to 150 basis points of minimum capital risk requirements. The originality of the present work consists of showing the importance of considering the asymmetric effects with IV and ARCH-type models in volatility forecasts within risk management analysis. It is concluded that the methodology means gains in monetary terms.

Volatility Forecast by Volatility Index and Its Use as a Risk Management Tool Under a Value-at-Risk Approach

2018 ◽  
Vol 21 (02) ◽  
pp. 1850010 ◽  
Author(s):  
Yam Wing Siu
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Risk Premium ◽  
Value At Risk ◽  
Realized Volatility ◽  
Management Tool ◽  
Spot Price ◽  
Pricing Options ◽  
Significance Levels ◽  
Risk Approach

This paper examines the predicting power of the volatility indexes of VIX and VHSI on the future volatilities (or called realized volatility, [Formula: see text] of their respective underlying indexes of S&P500 Index, SPX and Hang Seng Index, HSI. It is found that volatilities indexes of VIX and VHSI, on average, are numerically greater than the realized volatilities of SPX and HSI, respectively. Further analysis indicates that realized volatility, if used for pricing options, would, on some occasions, result in greatest losses of 2.21% and 1.91% of the spot price of SPX and HSI, respectively while the greatest profits are 2.56% and 2.93% of the spot price of SPX and HSI, respectively, making it not an ideal benchmark for validating volatility forecasting techniques in relation to option pricing. Hence, a new benchmark (fair volatility, [Formula: see text] that considers the premium of option and the cost of dynamic hedging the position is proposed accordingly. It reveals that, on average, options priced by volatility indexes contain a risk premium demanded by the option sellers. However, the options could, on some occasions, result in greatest losses of 4.85% and 3.60% of the spot price of SPX and HSI, respectively while the greatest profits are 4.60% and 5.49% of the spot price of SPX and HSI, respectively. Nevertheless, it can still be a valuable tool for risk management. [Formula: see text]-values of various significance levels for value-at-risk and conditional value-at-value have been statistically determined for US, Hong Kong, Australia, India, Japan and Korea markets.

scholarly journals Value at risk: Evidence from Pakistan Stock Exchange

2011 ◽  
Vol 5 (17) ◽  
pp. 7474-7480 ◽  
Author(s):  
Nawaz Faisal ◽  
Afzal Muhammad
Keyword(s):  
At Risk ◽  
Value At Risk ◽  
Stock Exchange

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.

scholarly journals Risk management of risk under the Basel Accord: forecasting value‐at‐risk of VIX futures

2011 ◽  
Vol 37 (11) ◽  
pp. 1088-1106 ◽  
Author(s):  
Chia‐lin Chang ◽  
Juan‐Ángel Jiménez‐Martín ◽  
Michael McAleer ◽  
Teodosio Pérez‐Amaral
Keyword(s):  
At Risk ◽  
Risk Management ◽  
Value At Risk ◽  
Basel Accord ◽  
Vix Futures ◽  
Management Of Risk

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).

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