scholarly journals Patterns of 50 ETF Options Implied Volatility in China: On Implied Volatility Functions

2021 ◽  
Vol 24 (1) ◽  
pp. 135-145
Author(s):  
Pengshi Li ◽  
Yan Lin ◽  
Yuting Zhong
Keyword(s):  
Implied Volatility ◽  
Stock Exchange ◽  
Empirical Work ◽  
Ordinary Least Squares ◽  
Options Pricing ◽  
Options Market ◽  
European Options ◽  
Volatility Smile ◽  
Volatility Function ◽  
Better Than

The aim of this study is to examine the volatility smile based on the European options on Shanghai stock exchange 50 ETF. The data gives evidence of the existence of a well-known U-shaped implied volatility smile for the SSE 50 ETF options market in China. For those near-month options, the implied volatility smirk is also observed. And the implied volatility remains high for the short maturity and decreases as the maturity increases. The patterns of the implied volatility of SSE 50 ETF options indicate that in-the-money options and out-of-the-money options are more expensive relative to at-the-money options. This makes the use of at-the-money implied volatility for pricing out-of- or in-the-money options questionable. In order to investigate the implied volatility, the regression-based implied volatility functions model is considered employed to study the implied volatility in this study as this method is simple and easy to apply in practice. Several classical implied volatility functions are investigated in this paper to find whether some kind of implied volatility functions could lead to more accurate options pricing values. The potential determinants of implied volatility are the degree of moneyness and days left to expiration. The empirical work has been expressed by means of simple ordinary least squares framework. As the study shows, when valuing options, the results of using volatility functions are mixed. For far-month options, using at-the-money implied volatility performs better than other volatility functions in option valuation. For near-month options, the use of volatility functions can improve the valuation accuracy for deep in-the-money options or deep out-of-the-money options. However, no particular implied volatility function performs very well for options of all moneyness level and time to maturity.

Stylized patterns of implied volatility in India: a case study of NSE Nifty options

2014 ◽  
Vol 6 (3) ◽  
pp. 231-254 ◽  
Author(s):  
Imlak Shaikh ◽  
Puja Padhi
Keyword(s):  
Term Structure ◽  
Implied Volatility ◽  
Practical Implication ◽  
Empirical Work ◽  
Ordinary Least Squares ◽  
Options Market ◽  
Volatility Smile ◽  
Strike Price ◽  
Content Type ◽  
Option Pricing Model

Purpose – The aim of this study is to examine the “volatility smile” or/and “skew”, term structure and implied volatility surfaces based on those European options written in the standard and poor (S&P) Nifty equity index. The stochastic nature of implied volatility across strike price, time-to-expiration and moneyness violates the core assumption of the Black–Scholes option pricing model. Design/methodology/approach – The potential determinants of implied volatility are the degree of moneyness, time-to-expiration and the liquidity of the strikes. The empirical work has been expressed by means of a simple ordinary least squares (OLS) framework and presents the estimation results according to moneyness, time-to-expiration and liquidity of options. Findings – The options data give evidence of the existence of a classical U-shaped volatility smile for the Indian options market. Indeed, there is some evidence that the “volatility smirk” which pertains to 30-day options and also implied volatility remain higher for the shorter maturity options and decrease as the time-to-expiration increases. The results lead us to believe that in-the-money calls and out-of-the-money puts are of higher volatility than at-the-money options. Conclusion was drawn due to the persistence of the smile in the options market. Practical implications – The practical implication of studying stylized patterns of implied volatility is that it educates the volatility traders about how in-the-money and out-of-the-money options are priced in the options market, and provides an estimate of volatility for the pricing of future options. Originality/value – This study is an extension of previous work. The undertaking has been to examine the case of a more liquid and transparent options market, which is missing from the earlier work. The current study is more relevant because, since 2008, significant changes have been observed in the futures and options market in India.

APPLYING THE GENETIC-BASED NEURAL NETWORKS TO VOLATILITY TRADING

2005 ◽  
Vol 01 (02) ◽  
pp. 285-293
Author(s):  
SHINN-WEN WANG
Keyword(s):  
Theoretical Model ◽  
Implied Volatility ◽  
Options Pricing ◽  
Pricing Model ◽  
Options Markets ◽  
Volatility Smile ◽  
Two Phase ◽  
Enterprise Value ◽  
Black Scholes ◽  
Value Estimation

The Black-Scholes options pricing model is widely applied in various options contracts, including contract design, trading, assets evaluation, and enterprise value estimation, etc. Unfortunately, this theoretical model limited by the influences of many unexpected real world phenomena due to six unreasonable assumptions. If we were to soundly take these phenomena into account, the opportunity to gain an excess return would be created. This research therefore combines both the remarkable effects caused by the implied volatility smile (or skew) and the tick-jump discrepancy between the underlying and derivative prices to establish a two-phase options arbitrage model using a genetic-based neural network (GNN). Using evidence from the warrant market in Taiwan, it is shown that the GNN model with arbitrage operations is superior in terms of performance to the original Black-Scholes-based arbitrage model. The GNN model is found to be suitable for application to various options markets as the valuation factors are modified. This paper helps to integrate the theoretical model with important practical considerations.

scholarly journals Volatility Informed Trading in the Options Market: Evidence from India

2015 ◽  
Vol 17 (1) ◽  
pp. 13-22
Author(s):  
Rajesh Pathak
Keyword(s):  
Implied Volatility ◽  
Stock Exchange ◽  
Intrinsic Value ◽  
Emerging Market ◽  
Informed Trading ◽  
Options Market ◽  
Trading Activity ◽  
Market Trends ◽  
Vector Auto Regression ◽  
Auto Regression

The purpose of this paper is to investigate the trading activity in options market based on information about expected future volatility in spot market. We employ Common Implied Volatility as a measure of expected volatility and options volume and changes in Open Interests as measures of options trading activity. We first test for simultaneous information flow in the two markets using multiple regression technique. Next, we test for information based or hedge based use of options using Trivariate Vector-auto Regression framework. We further consider the classes of options moneyness and the market trends in our analysis to examine if the trader’s preference of options changes with change in description of options intrinsic value and market environment. We use daily closing data of S&P CNX Nifty Index options traded on National Stock Exchange, India. We, for the most part, find negative and significant relationship in contemporaneous regression suggesting active trading by arbitrageurs. A feedback relationship is observed in vector auto regression analysis suggesting that options are traded in India for both information based trading and hedging purposes. We also observe the relationship to be varying when market trends and classes of options moneyness are considered. This indicates that traders are not indifferent in their choice of trading venue when market conditions and factors change. The results of this study are helpful for traders in managing the risk and return of their portfolio based on volatility forecast. This study is distinctive as it examines the scarcely researched area of volatility informed trading in an emerging market set up.

scholarly journals A mean bound financial model and options pricing

2017 ◽  
Vol 04 (04) ◽  
pp. 1750047 ◽  
Author(s):  
Yu Li
Keyword(s):  
Implied Volatility ◽  
Heavy Tails ◽  
Asset Returns ◽  
Mathematical Explanation ◽  
Options Pricing ◽  
Fat Tails ◽  
Volatility Smile ◽  
Financial Model ◽  
Black Scholes Model ◽  
Black Scholes

Most of financial models, including the famous Black–Scholes–Merton options pricing model, rely upon the assumption that asset returns follow a normal distribution. However, this assumption is not justified by empirical data. To be more concrete, the empirical observations exhibit fat tails or heavy tails and implied volatilities against the strike prices demonstrate U-shaped curve resembling a smile, which is the famous volatility smile. In this paper we present a mean bound financial model and show that asset returns per time unit are Pareto distributed and assets are log Gamma distributed under this model. Based on this we study the sensitivity of the options prices to a change in underlying parameters, which are commonly called the Greeks, and derive options pricing formulas. Finally, we reveal the relation between correct volatility and implied volatility in Black–Scholes model and provide a mathematical explanation of volatility smile.

The economic determinants of the implied volatility function for currency options

2018 ◽  
Vol 13 (6) ◽  
pp. 1798-1819
Author(s):  
Aparna Prasad Bhat
Keyword(s):  
Exchange Rate ◽  
Implied Volatility ◽  
Emerging Market ◽  
Volatility Smile ◽  
Currency Options ◽  
Content Type ◽  
Indian Rupee ◽  
The Exchange Rate ◽  
Volatility Function ◽  
Practical Implications

Purpose The purpose of this paper is to ascertain the pattern of the implied volatility function for currency options traded on the National Stock Exchange of India (NSE), identify its potential determinants and to investigate any seasonality in the pattern. Design/methodology/approach The paper examines four different specifications for the implied volatility smile of exchange-traded dollar-rupee options. These specifications are tested by running Ordinary Least Squares (OLS) regressions on a daily basis for all options over the entire sample period. Seven potential determinants for the shape of the volatility function are identified. Contemporaneous and lead-lag relationships between these determinants and the shape of the volatility function are examined using OLS and multivariate VAR. Impulse response functions are employed to test the strength and persistence of the lead-lag relations. Seasonality of the smile pattern is tested using OLS. Findings The study shows that the implied volatility function for dollar-rupee options is asymmetric and varies with the time to maturity of the option. Historical volatility, momentum and jumps in the exchange rate, time to maturity, traded volume of options and volatility in the stock market appear to Granger-cause the shape of the volatility smile. Feedback causality is observed from the shape of the smile to the volatility, momentum and jumps in the exchange rate and trading volume of currency options. A weak day-of-the-week effect is observed in the pattern of the volatility smile. Practical implications The study sheds light on the potential determinants of the smile and highlights the predictive power of the smile which findings can be useful to market practitioners for pricing and hedging of dollar-rupee options. The study has strong practical implications during a period of increased volatility in the dollar-rupee pair. Originality/value Most of the existing literature regarding implied volatility smiles has focused either on the volatility smile of US equity index options or that of major liquid currencies. There is a need for such studies in the context of options on emerging market currencies such as the Indian rupee which are characterized by thin trading and frequent central bank intervention and signaling. To the best of the author’s knowledge this study is the first to focus on the volatility smile of exchange-traded options on the US dollar–Indian rupee.

scholarly journals Implied Volatility Prediction Based on Different Term Structures: An Empirical Study of the SSE 50 ETF Options Market from High-Frequency Data

2021 ◽  
Vol 235 ◽  
pp. 02043
Author(s):  
Wenqi Yang ◽  
Jingkun Ma
Keyword(s):  
High Frequency ◽  
Implied Volatility ◽  
Model Fitting ◽  
Garch Model ◽  
High Frequency Data ◽  
Time Varying ◽  
Options Market ◽  
Term Structures ◽  
Typical Time ◽  
Better Than

This article focuses on the implied volatility forecast of the SSE 50 ETF options market from June 1, 2017, to August 30, 2019, and constructs AR (1) model and ARMA-GARCH model based on liquidity characteristics to compare and analyze the prediction effect of implied volatility on different option types and term structures. The results show that, during the sample period of the SSE 50 ETF options market, the effect of model fitting of the ARMA-GARCH model is significantly better than the AR (1) model; the fitting sequences predicted by the two models have typical time-varying and synchronization characteristics, and the prediction effect of the ARMA-GARCH model in the whole period is significantly better than the AR (1) model.

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