The impact of macroeconomic information releases on the smile shape

2016 ◽  
Vol 8 (1) ◽  
pp. 80-90 ◽  
Author(s):  
Hassan Tanha ◽  
Michael Dempsey
Keyword(s):  
Implied Volatility ◽  
Content Type ◽  
Macroeconomic Information ◽  
Macroeconomic Announcements ◽  
Pricing Errors ◽  
Black Scholes ◽  
Investor Behaviour ◽  
Volatility Function ◽  
S Model ◽  
The Impact

Purpose – The purpose of this paper is to assign fair values to options reduces to the attempt to attribute correct implied volatilities. Here, the authors extend the study by Tanha et al. (2014) to determine the impact of macro economic announcements on the option smile. Design/methodology/approach – First, the authors estimate the implied volatility function in terms of moneyness. The authors next analyse the impact of macroeconomic announcements on the estimated coefficients (b 0, b 1, b 2) by regressing the coefficients on the macroeconomic announcements. Findings – The authors find that in-the-money options are sensitive to such announcements, but that out-of-the money options are not. This is consistent with the interpretation of investor behaviour from prospect theory. Originality/value – The systematic pricing errors that have been documented using the Black-Scholes model have stimulated attempts to improve the model predictions. The approach uses DVF model to improve the B-S model.

Macroeconomic information and implied volatility: evidence from Australian index options

2014 ◽  
Vol 6 (1) ◽  
pp. 46-62 ◽  
Author(s):  
Hassan Tanha ◽  
Michael Dempsey ◽  
Terrence Hallahan
Keyword(s):  
Implied Volatility ◽  
Return Distribution ◽  
Index Options ◽  
Content Type ◽  
Market Participants ◽  
Macroeconomic Information ◽  
State Price ◽  
Macroeconomic Announcements ◽  
State Price Density ◽  
The Impact

Purpose – The purpose of this paper is to understand that option pricing is the response of option implied volatility (IV) to macroeconomic announcements. Design/methodology/approach – The authors use high-frequency data on ASX SPI 200 index options to examine the response of option IV, as well as higher moments of the underlying return distribution, to macroeconomic announcements. Additionally, the authors identify the response of the moments as a function of moneyness of the options. Findings – The findings suggest that in-the-money and out-of-the money options have difference characteristics in their responses, leading to the conclusion that heterogeneity in investor beliefs and preferences affect option IV through the state price density (SPD) function. Originality/value – The research contributes to the literature that examines whether IV captures the beliefs of market participants about the likelihood of future states together with the preferences of market participants towards these states. In particular, the authors relate changes in option IV to changes in macroeconomic announcements, through the impact of these announcements on the moments of the SPD function.

Performance of Black-Scholes model with TSRV estimates

2015 ◽  
Vol 41 (8) ◽  
pp. 857-870 ◽  
Author(s):  
Shivam Singh ◽  
Vipul .
Keyword(s):  
Risk Premium ◽  
Market Prices ◽  
Volatility Risk ◽  
Content Type ◽  
Forecasting Error ◽  
Ex Post ◽  
Tick Data ◽  
Black Scholes ◽  
Realised Volatility ◽  
S Model

Purpose – The purpose of this paper is to test the pricing performance of Black-Scholes (B-S) model, with the volatility of the underlying estimated with the two-scale realised volatility measure (TSRV) proposed by Zhang et al. (2005). Design/methodology/approach – The ex post TSRV is used as the volatility estimator to ensure efficient volatility estimation, without forecasting error. The B-S option prices, thus obtained, are compared with the market prices using four performance measures, for the options on NIFTY index, and three of its constituent stocks. The tick-by-tick data are used in this study for price comparisons. Findings – The B-S model shows significantly negative pricing bias for all the options, which is dependent on the moneyness of the option and the volatility of the underlying. Research limitations/implications – The negative pricing bias of B-S model, despite the use of the more efficient TSRV estimate, and post facto volatility values, confirms its inadequacy. It also points towards the possible existence of volatility risk premium in the Indian options market. Originality/value – The use of tick-by-tick data obviates the nonsynchronous error. TSRV, used for estimating the volatility, is a significantly improved estimate (in terms of efficiency and bias), as compared to the estimates based on closing data. The use of ex post realised volatility ensures that the forecasting error does not vitiate the test results. The sample is selected to be large and varied to ensure the robustness of the results.

The Impact of Macroeconomic Announcements on Implied Volatility

2011 ◽  
Author(s):  
Roland Füss ◽  
Ferdinand Mager ◽  
Holger Wohlenberg ◽  
Lu Zhao
Keyword(s):  
Implied Volatility ◽  
Macroeconomic Announcements ◽  
The Impact

Who predicts dollar-rupee volatility better? A tale of two options markets

2019 ◽  
Vol 45 (9) ◽  
pp. 1292-1308
Author(s):  
Aparna Prasad Bhat
Keyword(s):  
Implied Volatility ◽  
Realized Volatility ◽  
Informational Efficiency ◽  
Significant Information ◽  
Content Type ◽  
Merton Model ◽  
Model Free ◽  
Ex Post ◽  
Black Scholes ◽  
Practical Implications

Purpose The purpose of this paper is to examine whether volatility implied from dollar-rupee options is an unbiased and efficient predictor of ex post volatility, and to determine which options market is a better predictor of future realized volatility and to ascertain whether the model-free measure of implied volatility outperforms the traditional measure derived from the Black–Scholes–Merton model. Design/methodology/approach The information content of exchange-traded implied volatility and that of quoted implied volatility for OTC options is compared with that of historical volatility and a GARCH(1, 1)-based volatility. Ordinary least squares regression is used to examine the unbiasedness and informational efficiency of implied volatility. Robustness of the results is tested by using two specifications of implied volatility and realized volatility and comparison across two markets. Findings Implied volatility from both OTC and exchange-traded options is found to contain significant information for predicting ex post volatility, but is neither unbiased nor informationally efficient. The implied volatility of at-the-money options derived using the Black–Scholes–Merton model is found to outperform the model-free implied volatility (MFIV) across both markets. MFIV from OTC options is found to be a better predictor of realized volatility than MFIV from exchange-traded options. Practical implications This study throws light on the predictive power of currency options in India and has strong practical implications for market practitioners. Efficient currency option markets can serve as effective vehicles both for hedging and speculation and can convey useful information to the regulators regarding the market participants’ expectations of future volatility. Originality/value This study is a comprehensive study of the informational efficiency of options on an emerging currency such as the Indian rupee. To the author’s knowledge, this is one of the first studies to compare the predictive ability of the exchange-traded and OTC markets and also to compare traditional model-dependent volatility with MFIV.

The impact of macroeconomic announcements on implied volatility

2011 ◽  
Vol 21 (21) ◽  
pp. 1571-1580 ◽  
Author(s):  
Roland Füss ◽  
Ferdinand Mager ◽  
Holger Wohlenberg ◽  
Lu Zhao
Keyword(s):  
Implied Volatility ◽  
Macroeconomic Announcements ◽  
The Impact

Investor sentiments and pricing errors

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rahul Verma ◽  
Priti Verma
Keyword(s):  
Risk Factors ◽  
Institutional Investors ◽  
Stock Prices ◽  
Institutional Investor ◽  
Content Type ◽  
Valuation Model ◽  
Intrinsic Values ◽  
Pricing Errors ◽  
Investor Sentiments ◽  
The Impact

PurposeThis paper computes the pricing errors of S&P 500 index by employing the valuation model developed by Doran et al. (2009) and investigates its response to individual and institutional investor sentiments. This study contributes to the literature by looking at both rational and quasi-rational sentiments and how noise trading and investments based on fundamentals affect pricing errors.Design/methodology/approachThis paper computes the pricing errors of S&P 500 index by employing the valuation model developed by Doran et al. (2009) and investigates its response to individual and institutional investor sentiments.FindingsResults show that pricing errors are persistent and stock prices systematically deviate from their intrinsic values. The authors also find that both individuals and institutional investors form their expectations based on risk factors as well as noise; however, institutional investors seems to be more driven by rational factors. The findings also suggest that institutional investors have a significant power to cause pricing errors due to unpredictable changes in their sentiments while small investors lack such ability to move stock prices away from their intrinsic values. Additionally, this paper finds that quasi-rational (rational) investor sentiments have positive (negative) impact on pricing errors suggesting that trading based on noise is an important determinant of pricing errors while investors' expectations stemming from fundamentals play an important role in improving market efficiency.Research limitations/implicationsThe impact of rational outlook due to changes in fundamentals seems to be greater than that of noise on the pricing errors, consistent with both risk-based and behavioral models of the asset pricing literature.Originality/valueOur study contributes to the existing literature in the following ways: first, the authors employ most recent data to compute mispricing for the market index and investigate if it is persistent and systematic. Second, the authors decompose sentiment variables into rational and quasi-rational components and trace their dynamics to better understand the role of risk factors and noise in the formation of sentiments. Third, the authors investigate the relative impact of individual and institutional investor sentiments on mispricing. Lastly, the authors examine the response of pricing errors to both rational and quasi-rational sentiments of individual and institutional investors.

scholarly journals The Impact of Liquidity on GARCH Option Pricing Error during Financial Crisis

2017 ◽  
Vol 4 (4) ◽  
pp. 160
Author(s):  
Han Ching Huang ◽  
Yong Chern Su ◽  
Wei-Shen Chen
Keyword(s):  
Financial Crisis ◽  
Option Pricing ◽  
Garch Model ◽  
Black Scholes Model ◽  
Pricing Errors ◽  
Black Scholes ◽  
Out Of Sample ◽  
Pricing Error ◽  
The Impact ◽  
The Relationship

In this paper, we explore the valuation performance of Heston and Nandi GARCH (HN GARCH) model on the pricing of options of financial stocks listed for AMEX during pre and post financial crisis periods. We find that the GARCH pricing model presents better performance than the traditional Black-Scholes model for the out-of-sample option pricing, no matter what the moneyness and the time-to-maturity. Specifically, the models show the effects of liquidity is not significant. Intuitionally, smaller liquidity tends to exhibit more pricing errors, especially for longer mature options. Unfortunately, we cannot get the expected outcomes, which is that the period of post financial crisis tend to have larger pricing errors. In sum, except more computational convenience, the HN GARCH model offers another vision of the relationship between liquidity and its effect on pricing errors.

An Empirical Test of the Black-Scholes Option Pricing Model and the Implied Variance: A Confidence Interval Approach

1987 ◽  
Vol 2 (4) ◽  
pp. 355-369 ◽  
Author(s):  
Haim Levy ◽  
Young Hoon Byun
Keyword(s):  
Confidence Interval ◽  
Option Pricing ◽  
Implied Volatility ◽  
Empirical Test ◽  
Market Price ◽  
Pricing Model ◽  
Black Scholes ◽  
Option Pricing Model ◽  
S Model ◽  
Over Time

The empirical studies on the Black-Scholes (B-S) option pricing model have reported that the model tends to exhibit systematic biases with respect to the exercise price, time to expiration, and the stock's volatility. This paper attempts to test the B-S model with a new approach: derive the confidence interval of the model call option value based on the confidence interval of the. estimated variance. The test reports that even when the variance's confidence interval is considered, a systematic deviation between the theoretical “range” of the option price values and the observed market price still exist. If the stock variance is constant over time, the interpretation of the results is that the B-S model is wrong. However, if stock variance changes over time, the interpretation of the results is that the implied volatility in options market prices had a tendency to be significantly higher than the estimate that could have been obtained from historical data.

Australian market response to COVID-19 as moderated by social media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vinicius Mothé Maia ◽  
Roberto Tommasetti ◽  
Marcelo Alvaro da Silva Macedo
Keyword(s):  
Social Media ◽  
Stock Market ◽  
Global Economy ◽  
Time Series Regression ◽  
Content Type ◽  
Market Participants ◽  
Stock Market Performance ◽  
User Attention ◽  
Investor Behaviour ◽  
The Impact

Purpose Emerging as a black swan event that stifled the global economy, COVID-19 is the first social media (SM) pandemic. In an unsocial age due to social distancing, SM relevance is intuitively magnified during a pandemic. This study aims to investigate the direct and moderating impact of Twitter on the Australian stock market during the COVID-19 info-pandemic. Design/methodology/approach As a natural experiment, a time-series regression measures the effect of the COVID-19 virus, proxied by the active cases and the marginal impact of SM user attention and sentiment on the Australian stock market. Findings Results show that SM user attention and sentiment to COVID-19 related fear topics are significant in explaining market returns and in predicting their volatility. It demonstrates that SM plays a role between COVID-19 and Australian stock market performance by amplifying the pandemic impact. Originality The study goes beyond a purely empirical investigation of the catalyst (i.e. the pandemic), thus contributing to current theoretical debates on the impact of SM on investor behaviour. Practical implications Policymakers and market participants could benefit from the empirical findings of this research in the case of analogous epidemics.

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.

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