VALUE AT RISK WITH STOCHASTIC VOLATILITY PERTURBED BY HURST PARAMETER

We explore the class of second-order weak approximation schemes (cubature methods) for the numerical simulation of joint default probabilities in credit portfolios where the firm's asset value processes are assumed to follow the multivariate Heston stochastic volatility model. Correlation between firms' asset processes is reflected by the dependence on a common set of underlying risk factors. In particular, we consider the Ninomiya–Victoir algorithm and we study the application of this method for the computation of value-at-risk and expected shortfall. Numerical simulations for these quantities for some exogenous portfolios demonstrate the numerical efficiency of the method.

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Value at risk estimation under stochastic volatility models using adaptive PMCMC methods

Communications in Statistics - Simulation and Computation ◽

10.1080/03610918.2016.1235188 ◽

2017 ◽

Vol 46 (9) ◽

pp. 7221-7237 ◽

Cited By ~ 1

Author(s):

Xinxia Yang ◽

Ratthachat Chatpatanasiri ◽

Pairote Sattayatham

Keyword(s):

At Risk ◽

Stochastic Volatility ◽

Value At Risk ◽

Risk Estimation ◽

Stochastic Volatility Models ◽

Volatility Models

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ESTIMASI VALUE AT RISK MENGGUNAKAN VOLATILITAS DISPLACED DIFFUSION

E-Jurnal Matematika ◽

10.24843/mtk.2019.v08.i04.p268 ◽

2019 ◽

Vol 8 (4) ◽

pp. 298

Author(s):

MIRANDA NOVI MARA DEWI ◽

KOMANG DHARMAWAN ◽

KARTIKA SARI

Keyword(s):

At Risk ◽

Stochastic Process ◽

Stochastic Volatility ◽

Diffusion Model ◽

Stock Prices ◽

Value At Risk ◽

Implied Volatility ◽

Stochastic Volatility Model ◽

Financial Asset ◽

Volatility Model

Value at Risk (VaR) is a measure of risk that is able to calculate the worst possible loss that can occurs to stock prices with a certain level of confidence and within a certain period of time. The purpose of this study was to determine the VaR estimate from PT. Indonesian Telecommunications by using Displaced Diffusion volatility. The Displaced Diffusion Model is a stochastic volatility model that describes changes in a financial asset assuming volatility is not constant, but follows a stochastic process. Displaced Diffusion model are capable of modelling skewed implied volatility structures and frequently applied by interest rate quants. Based on the estimation of Displaced Diffusion volatility, it is found that volatility for PT. Indonesian Telecommunications is 0.010168 and VaR estimation using Displaced Diffusion volatility with a confidence level of 95 percent of 1.63%.

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VaR/CVaR ESTIMATION UNDER STOCHASTIC VOLATILITY MODELS

International Journal of Theoretical and Applied Finance ◽

10.1142/s0219024914500095 ◽

2014 ◽

Vol 17 (02) ◽

pp. 1450009 ◽

Cited By ~ 7

Author(s):

CHUAN-HSIANG HAN ◽

WEI-HAN LIU ◽

TZU-YING CHEN

Keyword(s):

At Risk ◽

Stochastic Volatility ◽

Value At Risk ◽

Extreme Event ◽

Stochastic Volatility Model ◽

Conditional Value At Risk ◽

Transform Method ◽

Historical Simulation ◽

Volatility Models ◽

Volatility Model

This paper proposes an improved procedure for stochastic volatility model estimation with an application to Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) estimation. This improved procedure is composed of the following instrumental components: Fourier transform method for volatility estimation, and importance sampling for extreme event probability estimation. The empirical analysis is based on several foreign exchange series and the S&P 500 index data. In comparison with empirical results by RiskMetrics, historical simulation, and the GARCH(1,1) model, our improved procedure outperforms on average.

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PERHITUNGAN VALUE AT RISK DENGAN PENDUGA VOLATILITAS STOKASTIK HESTON

E-Jurnal Matematika ◽

10.24843/mtk.2018.v07.i04.p220 ◽

2018 ◽

Vol 7 (4) ◽

pp. 317

Author(s):

DESAK PUTU DEVI DAMIYANTI ◽

KOMANG DHARMAWAN ◽

LUH PUTU IDA HARINI

Keyword(s):

At Risk ◽

Stochastic Process ◽

Stochastic Volatility ◽

Value At Risk ◽

Financial Risk ◽

Stochastic Volatility Model ◽

Heston Model ◽

Volatility Model ◽

The Mean ◽

Simulation Results

Value at risk is a method that measures financial risk of an security or portfolio. The aims of the research is to find out the value at risk of an exchange rate using the Heston stochastic volatility model. Heston model is a strochastic volatility model that assumes that volatility of the security follow stochastic process and consider the mean reversion. Based on simulation results, the value of volatility using Heston volatility estimastor is 0.2887, and the value of Heston VaR with 95 percent confident level is 0.0297. Based on result of backtesting, there are 48 violations obtained VaR using Heston model, while historical VaR there are 2 violations. Thus, VaR using Heston model is more strict in estimating risk.

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