Empirical Performance of Option Pricing Models: Evidence from India

Singh, Vipul Kumar

doi:10.5539/ijef.v5n2p141

Cited by 8 publications

(6 citation statements)

References 17 publications

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“…Moneyness is measured as the ratio of spot price to strike price (S/K), and the data are grouped into five different moneyness categories in line with Bakshi et al . (1997), Kim and Kim (2003), Singh (2013) and many others: deep-out-of-the-money (DOTM: S/K < 0.91), out-of-the-money (OTM: S/K ≥ 0.91 and < 0.97), at-the-money (ATM: S/K ≥ 0.97 and < 1.03), in-the-money (ITM: S/K ≥ 1.03 and < 1.09) and deep-in-the-money (DITM: S/K ≥ 1.09). The option price data are segregated into three categories of maturity: short-term (≤22 days), medium-term (between 22 and 60 days) and long-term (>60 days).…”

Section: Methodsmentioning

confidence: 99%

“…Empirical studies of the performance of alternative option-pricing models in the Indian context include Singh and Ahmed (2011), Singh (2013) and Singh (2015) who concluded that no single model could completely eliminate the pricing bias, although the AHBS model, the Heston model and the jump-diffusion models showed smaller pricing errors than the BSM model. Singh and Vipul (2015) found mispricing by the BSM model to persist despite the use of a realized volatility measure.…”

Section: Literature Reviewmentioning

confidence: 99%

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An empirical exploration of the performance of alternative option pricing models

Bhat¹

2019

JIBR

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Purpose The purpose of this paper is to ascertain the effectiveness of major deterministic and stochastic volatility-based option pricing models in pricing and hedging exchange-traded dollar–rupee options over a five-year period since the launch of these options in India. Design/methodology/approach The paper examines the pricing and hedging performance of five different models, namely, the Black–Scholes–Merton model (BSM), skewness- and kurtosis-adjusted BSM, NGARCH model of Duan, Heston’s stochastic volatility model and an ad hoc Black–Scholes (AHBS) model. Risk-neutral structural parameters are extracted by calibrating each model to the prices of traded dollar–rupee call options. These parameters are used to generate out-of-sample model option prices and to construct a delta-neutral hedge for a short option position. Out-of-sample pricing errors and hedging errors are compared to identify the best-performing model. Robustness is tested by comparing the performance of all models separately over turbulent and tranquil periods. Findings The study finds that relatively simpler models fare better than more mathematically complex models in pricing and hedging dollar–rupee options during the sample period. This superior performance is observed to persist even when comparisons are made separately over volatile periods and tranquil periods. However the more sophisticated models reveal a lower moneyness-maturity bias as compared to the BSM model. Practical implications The study concludes that incorporation of skewness and kurtosis in the BSM model as well as the practitioners’ approach of using a moneyness-maturity-based volatility within the BSM model (AHBS model) results in better pricing and hedging effectiveness for dollar–rupee options. This conclusion has strong practical implications for market practitioners, hedgers and regulators in the light of increased volatility in the dollar–rupee pair. Originality/value Existing literature on this topic has largely centered around either US equity index options or options on major liquid currencies. While many studies have solely focused on the pricing performance of option pricing models, this paper examines both the pricing and hedging performance of competing models in the context of Indian currency options. Robustness of findings is tested by comparing model performance across periods of stress and tranquility. To the best of the author’s knowledge, this paper is one of the first comprehensive studies to focus on an emerging market currency pair such as the dollar–rupee.

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

An empirical exploration of the performance of alternative option pricing models

Bhat¹

2019

JIBR

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“…Since then there have been a few empirical studies to test the B-S model in the Indian derivatives market. Nagendran and Vadivel (2005), Kakati (2006), Singh (2013) and Nagendran and Venkateswar (2014) confirm the mispricing of the B-S model in the Indian options market. But, these studies have been conducted using the daily closing data, which entails nonsynchronous trading error.…”

Section: Introductionmentioning

confidence: 91%

Performance of Black-Scholes model with TSRV estimates

Singh

Vipul

2015

Managerial Finance

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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.

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“…Empirical evidence supports this prediction. Singh (2013) found that practitioner Black-Scholes model, Gram-Charliers model, Hull-white uncorrelated stochastic volatility model and Hestom model are all not able to eliminate bias completely.…”

Section: Arbitrage Profit Exists In the Real Worldmentioning

confidence: 98%

Insurance Economics and Theory of Option Pricing: A Proposal

Ting¹

2014

IJEF

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Probability and maximum expected utility under risk aversion are corner stone of the contemporary insurance economics. Since economists use arbitrage assumption and riskless portfolio to construct the modern theory of option pricing, probability plays no role to determine option price under uncertainty. It is wrong that the contemporary insurance economics and the modern theory of option pricing are irrelevant and opposite because all prices of substitute products (e.g., portfolio insurance and option) should be explained by the same independent variables. Since option pricing is supposed to be similar to insurance pricing, the purpose of this paper is to propose a single price theory that explains both the premium of portfolio insurance and option price.

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Empirical Performance of Option Pricing Models: Evidence from India

Cited by 8 publications

References 17 publications

An empirical exploration of the performance of alternative option pricing models

An empirical exploration of the performance of alternative option pricing models

Performance of Black-Scholes model with TSRV estimates

Insurance Economics and Theory of Option Pricing: A Proposal

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