scholarly journals On Forecasting Taiwanese Stock Index Option Prices: The Role of Implied Volatility Index

2017 ◽  
Vol 9 (9) ◽  
pp. 133 ◽  
Author(s):  
Jying-Nan Wang ◽  
Hung-Chun Liu ◽  
Lu-Jui Chen
Keyword(s):  
Implied Volatility ◽  
Option Price ◽  
Garch Model ◽  
Predictive Performance ◽  
Stock Index ◽  
Additional Information ◽  
Volatility Index ◽  
Volatility Models ◽  
Rolling Window ◽  
The Garch Model

This paper aims to propose four volatility measures: The first is the GARCH model advocated by Bollerslev (1986); the second is the GARCHVIX model which extends the GARCH model by including the volatility index (VIX) as explanatory variable for volatility; the last two are HS20D and HS252D, which represent the historical volatilities generated by traditional rolling window technique with 20- and 252-day historical index returns data, respectively. We examine the price information on VIX to improve the predictive performance of GARCH model for valuing TAIEX stock index call options (TXO) over the period from January 2014 to May 2015. Empirical results firstly indicate that both the GARCH and GARCHVIX models consistently perform better than the historical volatility models for forecasting call value of TXO under different moneynesses. Secondly, the GARCHVIX model significantly outperforms the GARCH model for most cases, indicating that the GARCH-based option price forecasts can be effectively improved with the additional information contained in VIX. Finally, the use of GARCHVIX model can greatly reduce model mispricing especially for out-the-money TXO option case. Thus, volatility index is crucial for option traders to efficiently predict TXO option value with GARCH model.

Examining Contemporaneous Relationship between Return of Nifty Index and India VIX

2015 ◽  
Vol 5 (2) ◽  
Author(s):  
Prasenjit Chakrabarti
Keyword(s):  
Implied Volatility ◽  
Stock Index ◽  
Quadratic Effect ◽  
Asymmetric Building ◽  
Volatility Index ◽  
India Vix ◽  
The Relationship

The study examines the contemporaneous relationship between Nifty returns and India VIX returns. Literature documents that the relationship between them is negative and asymmetric. Building on this, the study considers the linear and quadratic effect of stock index return (CNX Nifty) and examines the changes in implied volatility index (India VIX). The study finds both linear and quadratic CNX Nifty index returns are significant for changes in the level of India VIX. Findings suggest that India VIX provides insurance both for downside market movement and size of the downside movement.

PRICING TIMER OPTIONS: SECOND-ORDER MULTISCALE STOCHASTIC VOLATILITY ASYMPTOTICS

2021 ◽  
pp. 1-19
Author(s):  
XUHUI WANG ◽  
SHENG-JHIH WU ◽  
XINGYE YUE
Keyword(s):  
Stochastic Volatility ◽  
Implied Volatility ◽  
Option Price ◽  
Second Order ◽  
Approximation Formula ◽  
Stochastic Volatility Models ◽  
Regular Perturbation ◽  
Volatility Models ◽  
Order Expansion ◽  
High Level

Abstract We study the pricing of timer options in a class of stochastic volatility models, where the volatility is driven by two diffusions—one fast mean-reverting and the other slowly varying. Employing singular and regular perturbation techniques, full second-order asymptotics of the option price are established. In addition, we investigate an implied volatility in terms of effective maturity for the timer options, and derive its second-order expansion based on our pricing asymptotics. A numerical experiment shows that the price approximation formula has a high level of accuracy, and the implied volatility in terms of its effective maturity is illustrated.

scholarly journals ANALYSIS OF MARKET VOLATILITY VIA A DYNAMICALLY PURIFIED OPTION PRICE PROCESS

2014 ◽  
Vol 09 (03) ◽  
pp. 1450006 ◽  
Author(s):  
CHUONG LUONG ◽  
NIKOLAI DOKUCHAEV
Keyword(s):  
Stock Price ◽  
Implied Volatility ◽  
Financial Time Series ◽  
Option Price ◽  
Option Prices ◽  
Price Process ◽  
Volatility Index ◽  
Quadratic Interpolation ◽  
Dynamic Estimation ◽  
The Impact

The paper studies methods of dynamic estimation of volatility for financial time series. We suggest to estimate the volatility as the implied volatility inferred from some artificial "dynamically purified" price process that in theory allows to eliminate the impact of the stock price movements. The complete elimination would be possible if the option prices were available for continuous sets of strike prices and expiration times. In practice, we have to use only finite sets of available prices. We discuss the construction of this process from the available option prices using different methods. In order to overcome the incompleteness of the available option prices, we suggests several interpolation approaches, including the first order Taylor series extrapolation and quadratic interpolation. We examine the potential of the implied volatility derived from this proposed process for forecasting of the future volatility, in comparison with the traditional implied volatility process such as the volatility index VIX.

Foreign Exchange Volatility Shifts and Futures Hedging: An ICSS-GARCH Approach

2007 ◽  
Vol 10 (03) ◽  
pp. 349-388 ◽  
Author(s):  
Iqbal Mansur ◽  
Steven J. Cochran ◽  
David Shaffer
Keyword(s):  
Garch Model ◽  
Volatility Persistence ◽  
Futures Hedging ◽  
Volatility Models ◽  
Out Of Sample ◽  
Competing Models ◽  
Foreign Exchange Volatility ◽  
The Garch Model ◽  
The Impact ◽  
Cumulative Sums

In this study, the impact of volatility regime shifts on volatility persistence and hedge ratio estimation is determined for four major currencies using an iterated cumulative sums of squares (ICSS)-GARCH model. Employing a standard GARCH (1,1) model as the benchmark, within-sample results demonstrate that the inclusion of volatility shifts substantially reduces volatility persistence and the significance of the ARCH and GARCH coefficients. In terms of hedging effectiveness, the ICSS-GARCH model outperforms the standard GARCH model for all four currencies. In comparison to two constant volatility models, the standard GARCH model yields the lowest performance, whereas the ICSS-GARCH model performs at least as well as these models. In out-of-sample analysis, the GARCH model provides substantial variance reductions relative to the constant volatility models. Moreover, the ICSS-GARCH model yields positive variance reductions relative to all competing models, including the standard GARCH model. The results suggest that in cases where dynamic hedging is important, sudden shifts in volatility should not be ignored.

scholarly journals Option Price Decomposition in Spot-Dependent Volatility Models and Some Applications

2017 ◽  
Vol 2017 ◽  
pp. 1-16
Author(s):  
Raúl Merino ◽  
Josep Vives
Keyword(s):  
Implied Volatility ◽  
Option Price ◽  
Model Parameters ◽  
Numerical Comparison ◽  
Cev Model ◽  
Volatility Models ◽  
Local Volatility Model ◽  
Volatility Model ◽  
Volatility Surface ◽  
Price Decomposition

We obtain a Hull and White type option price decomposition for a general local volatility model. We apply the obtained formula to CEV model. As an application we give an approximated closed formula for the call option price under a CEV model and an approximated short term implied volatility surface. These approximated formulas are used to estimate model parameters. Numerical comparison is performed for our new method with exact and approximated formulas existing in the literature.

scholarly journals Accessing the Equity Return Volatility Effect of East and South Asian Nations: The Econometrics Modelling Method

2019 ◽  
Vol 8 (3S) ◽  
pp. 594-603
Keyword(s):  
Stock Market ◽  
South Asian ◽  
Market News ◽  
Institutional Investors ◽  
Garch Model ◽  
Equity Market ◽  
Stock Index ◽  
Critical Element ◽  
Market Returns ◽  
The Garch Model

In financial management, the equity market performance is the critical element of equity market returns volatility wherever the shareholder’s resilience around the instability subsists. The data is collected from the authenticated secondary sources for the analysis. This paper shows that the 2008economicpredicament, as well as the effect above proceeding developing financial prudence of the globe, is found in the equity return instability connation of developing financial prudence (2004-2015). By the GARCH model, it can be examined that as the information from the U.S.A. stock market news has an essential consequences on the earnings of the S&P 500 stock market index, the indices of the east, as well as south Asian nations, has also influenced by the news of U.S.A. The GARCH model is estimated for the U.S.A. stock market news has a substantial effect or not on East and South Asian nation's daily share market returns. The outcomes show that market earnings in the equity market in east and south Asian nations are incredibly reliant on their historical earnings. It is found that Tokyo Topic (4.8929) is a highly volatile stock index among the East and South Asian stock returns, and the low volatile stock index is DSEX (0.0068). The news of the U.S.A. stock market has affected the equity market of India, Japan, China, and Korea, which are included in the East and South Asian stock market. In all the country’s share markets, found most significant variance in the equity income instability. This study is essential for the shareholders looking for the diversification in the portfolio, domestic institutional investors and foreign institutional investors

CONVERGENCE SPEED OF GARCH OPTION PRICE TO DIFFUSION OPTION PRICE

2009 ◽  
Vol 12 (03) ◽  
pp. 359-391 ◽  
Author(s):  
JIN-CHUAN DUAN ◽  
YAZHEN WANG ◽  
JIAN ZOU
Keyword(s):  
Discrete Time ◽  
Option Price ◽  
Garch Model ◽  
Convergence Speed ◽  
Time Interval ◽  
Square Root ◽  
Option Prices ◽  
European Option ◽  
The Garch Model

It is well known that as the time interval between two consecutive observations shrinks to zero, a properly constructed GARCH model will weakly converge to a bivariate diffusion. Naturally the European option price under the GARCH model will also converge to its bivariate diffusion counterpart. This paper investigates the convergence speed of the GARCH option price. We show that the European option prices under the two corresponding models are equal up to an order near the square root of the length of discrete time interval.

scholarly journals Linkage between India Implied Volatility Index and Stock Index Returns

2017 ◽  
Vol 07 (04) ◽  
pp. 929-938
Author(s):  
Palamalai Srinivasan ◽  
R. D. Vasudevan
Keyword(s):  
Implied Volatility ◽  
Stock Index ◽  
Volatility Index ◽  
Stock Index Returns

Do High-Frequency Volatility Methods Improve the Accuracies of Risk Forecasts? Evidence from Stock Indexes and Portfolio

2020 ◽  
pp. 2150032
Author(s):  
Siqi Xu ◽  
Kun Yang ◽  
Yifeng Zhang ◽  
Bo Li
Keyword(s):  
High Frequency ◽  
Value At Risk ◽  
Financial Risk ◽  
Low Frequency ◽  
Stock Index ◽  
Extreme Risk ◽  
Volatility Models ◽  
Risk Forecasting ◽  
The Garch Model ◽  
Stock Indexes

Though the high-frequency volatility approaches are increasingly introduced to forecast financial risk in recent years, whether they can improve the accuracies of risk forecasts remains controversial. This paper compares the risk forecasting abilities of four pairs of low- and high-frequency volatility models, by calculating and evaluating the downside and upside value-at-risk and expected shortfall of stock indexes and portfolio. The empirical results show that, first, all the volatility models can well filter the serial dependence in the extremes, and the conditional standard deviation obtained from the GARCH model performs best in filtering the dependence. Secondly, the backtesting results of stock index and portfolio risk forecasts are consistent. More specifically, the traditional low-frequency volatility models produce more accurate risk forecasts in most cases, whereas the high-frequency volatility methods also manifest some advantages in the upside extreme risk forecasting.

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