Volatility Informed Trading in the Options Market: Evidence from India (original) (raw)
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Efficiency of Indian Option Market: Estimation of Future Market Volatility Using Implied Volatility
SDMIMD Journal of Management, 2019
Forecasting volatility is a key process in pricing stock and index options. Accurate forecasting of future volatility would facilitate the traders and investors to make an informed decision. The study examines the market efficiency of exchange traded index options in India. We investigate the predictive power of implied volatility of Nifty index options in forecasting the future stock market volatility. The efficient market hypothesis believes that the implied contains all past information, thereby making it a superior volatility forecast for the underlying asset. Our study is based on the implied volatility of Nifty index options for the years between 2010 and 2018. In this paper, we compare the accuracy of expected future volatility using implied volatility concerning historical volatility. We study the implied volatility for Nifty 50 index option over the last seven years and compare the results against the ARMA model and historical forecasts to re-establish the superiority of implied volatility and efficiency of the Indian option market.
Social Science Research Network, 2004
This study empirically investigates the impact of some non-price variables viz., open interest and trading volume from option market in predicting the price index viz. Nifty Index in underlying cash market in India. This study applies open interest and volume based predictors for both call and put option, as suggested by Bhuyan and Yan (2002) to empirically investigate the hypothesis that the above non-price variables in option market can not be used to predict the future price index in underlying cash market. Daily data for both price as well as non-price variables, for two different sub periods, have been employed in order to explore whether there is any significant change in the above relationship in two different periods. The empirical findings confirm that the open interest based predictors are significant in predicting the spot price index in underlying cash market in both the periods, just after the initiation of the index option in the market and in the later sub period. But, as far as the volume based predictors are concerned, it shows some changing evidence. Though being
Forecasting Volatility and Pricing Option: An Empirical Evaluation of Indian Stock Market
IOSR Journal of Business and Management, 2017
The present study empirically investigates and examine seven models of volatility forecasting, namely unconditional standard deviation (also written as Long Term Moving Volatility), Standard GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, GJR-GARCH model, Exponential GARCH model (eGARCH), Asymmetric Power GARCH model (apGARCH), Component Standard GARCH model (csGARCH) , and Option Implied Volatility model to gauge the most appropriate model of volatility forecasting in Nifty constituent companies. The assessment of risk and determination of price of the asset class is primarily dependent on the volatility calculated for the class of asset. In view of obtaining precision in the process of determining the price of the option and making hedging most effective, it's imperative to have the most appropriate method of calculating the volatility. The present study finds option implied volatility as the best performing model except in few categories of option data where VIX outperformed. Similarly on empirical performance of Black-Scholes (BS) model the present study finds that performance is not same across various maturities which indicate volatility is not constant as assumed by BS model during the tenure of the study in Indian market.
Characterization of Volatilities in the Nigerian Stock Exchange: Prospects for Options Trading
This paper examined the characteristics of volatilities in the Nigerian stock exchange (NSE) and their prospects for option trading. Also, the paper tested the information efficiency of the historical volatilities of the NSE All Share Index (ASI) and NSE30 Index equities using Variance Ratio Wild Bootstrap Joint Tests. The study found that one equity has a long left tail distribution, while others were positively skewed. Three equities have kurtosis and Jarque Bera probability statistics that approximate that of a normal distribution. All other stocks including the NSE ASI are leptokurtic and have Jarque Bera statistics that indicate strong conditional heteroscedasticity. The standard deviation statistics show that the degree of volatility vary among the NSE30 index equities. The Variance Ratio Wild Bootstrap Joint Tests based on the Chow-Denning maximum |z| statistic show that for the monthly volatilities, eight equities and the NSE ASI generally reject the null hypothesis that they are martingales. The three month moving volatilities, shows that three stocks strongly reject the null of a martingale while the NSE ASI and the rest of the NSE30 Index equities failed to reject the null hypothesis. Given the standard deviation of the NSE30 Index equities monthly and three month moving volatilities, option traders may be better off writing/buying options on these equities than the NSE ASI which is comparably the least volatile. As for whether investors can rely on past volatility information on the NSE ASI and NSE30 Index equities, the results are mixed and therefore depends on the particular asset of interest.
The Behavior of Option’s Implied Volatility Index: a Case of India VIX
Verslas: Teorija ir Praktika, 2015
The aim of this paper is to investigate the behavior of implied volatility in the form of day-of-the-week, year-of-the-month and surround the expiration of options. The persistence of volatility is modeled in ARCH/GARCH type framework. The empirical results have shown significant effects of the day-of-the-week, month-of-the-year and day of options expiration. The positive significant Monday effect explains that India VIX rises significantly on the initial days of the market opening, and the significant negative Wednesday effect shows that expected stock market volatility fall through Wednesday-Friday. Moreover, the study reveals the fact on options expiration, the evidence shows that India VIX fall significantly on the day of expiration of European call and put options. The March and December months have reported significant negative impact on the volatility index. Certainly, this kind of results holds practical implication for volatility traders, and helps to the market participant...
Modeling information linkages in the stock and options markets
Chan, F., Marinova, D. and Anderssen, R.S. (eds) MODSIM2011, 19th International Congress on Modelling and Simulation., 2011
When markets are assumed to be complete, option trading should not contain new information for market participants, as options derive their prices from the underlying stocks. However, if markets are incomplete, then this unidirectional relationship may not be true, because informed traders may prefer to trade options instead of the underlying stocks for several reasons: one, option trading involves lower transaction costs and higher financial leverage; and two, investors who have private information about stock price volatility can only make their bet on volatility in the option market. Compared with the research on the relationship between options trading activity and stock prices, there is little analysis on the information embodied in option transactions volume for stock market volatility, which undoubtedly is an important variable for risk management and portfolio allocation. This study focuses on the dynamic linkages between option trading volume and stock market volatility. We compare the significance of option trading activity in explaining the volatilities of the underlying stocks with that of stock market volume by selecting 15 New York Stock Exchange (NYSE) stocks that are most actively traded in the option markets during the period from December 11 2002 to August 31 2006. Our approach implies the following two distinctive features: • instead of the put/call volume ratio conventionally used in the literature, we measure the influence of option volume on stock market volatility by constructing the relative put (RPUT) and relative call (RCALL) ratios. • our approach also allows us to quantify the impact of option volume on the existence of persistence and asymmetry in stock market volatility. Instead of the usual generalized autoregressive conditional heteroskedasticity (GARCH) model that is commonly used to analyze the stock volume-volatility relation, we adopt Nelson's (1991) exponential GARCH (EGARCH) approach in this study. For each stock, it is noted that the trading activities in the put and call options markets have significant explanatory power for stock market volatility. In addition, the results indicate that the call options trading activity has a stronger impact on stock volatility compared with that of the put options. Our results demonstrate that information and sentiment in the option market is useful for the estimation of stock market volatility. Also, the significance of the effects of option trading activity on stock price volatility is observed to be comparable to that of stock market trading activity. Furthermore, the persistence and asymmetric effects in the volatility of some stocks tend to disappear once option trading activity is taken into account.
The Effects of Option Trading Behavior on Option Prices
Journal of Risk and Financial Management
This paper investigates the relationship between option trading behavior and option pricing patterns. We argue that greater active trading in the options market due to investor overconfidence leads to higher volatility and larger discrepancies in option pricing, which may be captured by implied volatility spread and implied volatility skewness. Using two different measures of excess option trading, we find that trading activities are correlated in different ways with volatility, volatility spread, and volatility skewness. We also find that these relationships exist both over time and cross-sectionally. We suggest that options investors tend to chase “hot” stocks, as we find evidence of a positive relationship between option trading activities and past underlying equity returns. Heavier trading in the options market also tends to make out-of-the-money call options more (less) expensive than the at-the-money counterparts over time (cross-sectionally). Because trading activities do not...
Informed trading in the index option market: The case of KOSPI 200 options
Journal of Futures Markets, 2008
This study examines if informed trading is present in the index option market by analyzing the KOSPI 200 options, the most actively traded derivative product in the world. The spread decomposition model developed by is utilized and the adverse-selection cost component of the spread estimated by the model is then used as a proxy for the degree of informed trading. We find that adverse-selection costs constitute a nontrivial portion of the transaction costs in index options trading. Approximately one-third of the spread can be accounted for by information asymmetry costs. A further analysis indicates that adverse-selection costs are positively related with option delta. Our regression analysis shows that option-related variables are significantly associated with estimated information asymmetry costs, even when controlling for proxies for informed trading in the index futures market. Finally, we find the evidence that foreign investors are better informed compared to domestic investors and that domestic institutions have an edge in terms of information over domestic individuals.
The Journal of Finance, 1998
This study investigates the intertemporal relation between daily stock index change and volume turnover of four countries. The results show that, in the sample period 1996-2000, the pricevolume relations are differential across countries. Index change leads volume turnover for US stock market. When daily stock prices go up (down) strongly, subsequent volume turnover fall (rise). On the other hand, stock prices do not exhibit a clear pattern after a significant change in volume turnover. Moreover, UK and Japanese markets exhibit a comtemporary or independent relation while Taiwanese market shows a causal relation between index change and volume. The distinct relations across countries are ascribed to the behavior of market participant structure. Since unconditional volume cannot help forecast prices, we characterize volume by time-series models to measure abnormal volume. We show that abnormal volume have weak predictable power on prices. An Investigation on the Intertemporal Relation between Stock Index and Volume Financial academicians and practitioners are leaned to believe that trading volume contain important information. A number of research shed light on the role of volume played in price determination (e.g., Karpoff (1987), Gallant, Rossi, and Tauchen (1992), and Lo and Wang (2000) among others). Nevertheless, the price-volume relation is not crystal yet and has an extensive room to explore. The complexity of financial market behavior makes the price-volume relation sophisticated (discussed in section I). Hiemstra and Jones (1994), for example, conclude a nonlinear causal relation between price and volume. It may imply that many factors, macro and micro, known or unknown, may simultaneously affect either of both of price and volume. Thus the price-volume relation could vary over time and is difficult to examine. The purpose of this paper is to investigate the intertemporal relation between stock index change and aggregate volume turnover. There have been a number of studies related to the pricevolume relations of individual stocks, while research of aggregate price and volume are not plenty. This topic is important for explaining market behavior. If past volume lead prices, it contributes to the predictability on stock price. On the other hand, if past prices can predict volume, it reflects that investors mainly respond to price changes. Lagged prices, therefore, should be modeled in current volume. In contrast to Hiemstra and Jones' (1994) nonlinear relation, we postulate that the indexvolume relation is linear but not strictly stationary. In other words, we allow the price-volume relation to vary over time. This framework is simple but intuitive. We conjecture that there should be some kind of unconditional time-series relation between index and volume in normal periods while some other relations during certain particular periods. Specifically, we conduct the nested causal tests developed by Chen and Lee (1990). These tests employ several hypotheses to identify the relation between variables and are consistent with nonlinear tests. The results show that five of six indices have no causality from volume to prices. We then assume that "abnormal volume" have a significant impact on price. Technically, we employ the ARMA model with three types of outliers, namely, additive, temporal-change, and level-shift outliers to characterize volume. We use the difference between the actual and forecasted volume by the ARMA-outlier model to be an "abnormal volume" proxy. The results show that past "abnormal volume" have some predicted power on index change. The remainder of this paper is structured as follows. Section I reviews the price-volume relations. Section II discusses the data sample. Section III summarizes the causality tests of Chen and Lee (1990). Section IV introduces the abnormal volume model. Section V reports the empirical results. Finally, section VI concludes the findings.
Empirical Performance of Option Pricing Models: Evidence from India
International Journal of Economics and Finance, 2013
This paper empirically investigates the comparative competitiveness of the family of option pricing models categorized as deterministic and stochastic. Forecasting effectiveness of the models is judged on the basis of pricing accuracy of the models. For same this paper categorically examine the out-of-sample moneyness-maturity forecasting performance of models. Data set of Nifty index options of India is especially chosen for analyzing the effectiveness of models. Pricing imperfections of models is compare and contrasted with the market price of the options. Cross competitiveness of the models is empirically testifies with the benchmark Black-Scholes but relative to market using well-known technique of error metrics. Expected price of the models inferred analytically by estimating the parameters of the models continuously, almost every day. The models are inter-pass through the recent waves of financial upheavals and has been put into a practical implication of fastest descending movement of Indian capital market. We found that the Practitioner Black-Scholes and Heston model has smaller out of sample valuation errors in pricing Nifty Index options than the Constant Elasticity of Variance, Gram-Charlier, and Hull & Whit models, but no models eliminates price bias completely.