The forecasting performance of implied volatility index: evidence from India VIX

Shaikh, Imlak; Padhi, Puja

doi:10.1007/s10644-014-9149-z

Cited by 19 publications

(10 citation statements)

References 49 publications

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“…Other studies focus on volatility indices in less‐developed or emerging markets. So for instance, Huang et al () study the information spill‐over effects of the Taiwan stock index futures, options trading volume and Taiwan VIX; Shaikh and Padhi () examine the forecasting performance of implied volatility for Indian markets; Ryu () and Lee and Ryu () investigate the properties of the Korean volatility index VKOSPI; Siriopoulos and Fassas () propose a model‐free Greek implied volatility index; and Lee () explores the relationship between the changes in the Japanese volatility index and Nikkei 225 returns.…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Trading and Investing in Volatility Products

2015

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Since the banking crisis the market for volatility exchange-traded products has developed rapidly as it opens to clients beyond the large institutional investor pool.Speculation is driven by increasingly complex leveraged and inverse exposures including those that attempt to trade on significant roll costs in volatility futures curves.Longer-term investors use these products for the purposes of equity diversification, driven by fears of an ongoing Eurozone crisis. We survey the burgeoning academic literature in this area and present a comprehensive and up-to-date comparison of the market and statistical characteristics of European and US exchange-traded volatility products.JEL classification: G12, G15, G23

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Section: Introduction and Literature Reviewmentioning

confidence: 99%

Trading and Investing in Volatility Products

2015

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“…In the more current research, another study of Frijns et al (2010) (Cheng & Fung, 2012;Ryu, 2012;Shaikh & Padhi, 2014). The superior forecast ability of VIX has been demonstrated in the majority of later research (Ammann et al, 2009;Frijns et al, 2010;Ryu, 2012).…”

Section: Implied Volatility Forecasting Volatilitymentioning

confidence: 88%

“…The predictive ability testing focuses mainly on the leading stock indices and foreign exchange rates. For stock and stock indexes, numerical analyses report that IVs provide a better forecast of future volatility than those based on historical data, but they are biased (Beckers, 1981;Cheng & Fung, 2012;Latane & Rendleman, 1976;Ryu, 2012;Schmalensee & Trippi, 1978;Shaikh & Padhi, 2014). Moreover, IV provides better forecasts at the monthly horizon.…”

Section: Discussionmentioning

confidence: 99%

Analysing Intraday Implied Volatility for Pricing Currency Options

Le¹

2021

Contributions to Finance and Accounting

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This research analyses the intraday implied volatility (IV) for pricing currency options. It conducts analyses in three steps. First, estimates at-the-money IV using the price of options with one-month, two-month, and three-month maturity during the opening, midday, and closing period of a trading day. Second, the Mincer-Zarnowitz regression test assessing the performance of IV to forecast the volatility of the underlying currency of options for the withinweek, one-week, and one-month forecast horizon. Third, mean absolute error (MAE), mean squared error (MSE), and root mean squared error (RMSE) measures evaluating the performance of IV to estimate the price of currency options for the within-week, one-week, and one-month estimate horizon. It employs Australian dollar, British pound, Canadian dollar, Euro, and Swiss franc options trading from 01 January 2010 to 31 December 2017. This study reveals four critical findings. First, three-month maturity IV does not contain useful information about future volatility of the underlying currency and pricing currency options.Second, IV incorporates all information is not relevant to compute the price of currency options for less than a week estimate horizon. Third, IV of the closing period on Monday or Tuesday subsumes most of the essential information compared to other periods of a trading day and other days of a week to forecast volatility of the underlying currency and estimate the value of currency options. Fourth, the shorter (longer) maturity IV holds vital information to price currency options for the shorter (longer) estimate horizon. The overall research findings imply that the information content embedded in one-month and two-month maturity IV is appropriate to calculate the currency options price for the one-week and one-month estimate horizon, respectively. The intraday IV approach adds a new dimension to obtain the unobservable volatility in pricing currency options accurately for the researchers and practitioners. v

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“…The methods like conditional volatility framework, RiskMetrics, VaR and stochastic volatility model (e.g. Lehar et al, 2002;Poon and Granger, 2003;Shaikh and Padhi, 2014c) performs better in explaining and forecasting the stock market volatility.…”

Section: Notesmentioning

confidence: 99%

On the relationship between implied volatility index and equity index returns

Shaikh

Padhi

2016

Journal of Economic Studies

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Purpose – The purpose of this paper is to analyze the asymmetric contemporaneous relationship between implied volatility index (India VIX) and Equity Index (S & P CNX Nifty Index). In addition, the study also analyzes the seasonality of implied volatility index in the form of day-of-the-week effects and option expiration cycle. Design/methodology/approach – This study employs simple OLS estimation to analyze the contemporaneous relationship among the volatility index and stock index. In order to obtain robust results, the analysis has been presented for the calendar years and sub-periods. Moreover, the international evidenced presented for other Asian markets (Japan and China). Findings – The empirical evidences reveal a strong persistence of asymmetry among the India VIX and Nifty stock index, at the same time the magnitude of asymmetry is not identical. The results show that the changes in India VIX occur bigger for the negative return shocks than the positive returns shocks. The similar kinds of results are recorded for the Japan and China volatility index. Particularly, the analysis also supports that India VIX holds seasonality, on the market opening VIX observed to be at its high level, and on the subsequent days it remains low. The results on the options expiration unfold the facts that India VIX remains more normal on the day of expiration. Practical implications – The asymmetric relation and seasonal patterns are quite useful to the volatility traders to price the financial assets when market trades in the high- and low-volatility periods. Originality/value – There is a lack of studies of this kind in the context of emerging markets like India; hence, this is an attempt in this direction. The study provides an insight to the NSE to launch some derivative products (i.e. F & Os) on India VIX that can generate more liquidity in the market for the volatility traders.

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The forecasting performance of implied volatility index: evidence from India VIX

Cited by 19 publications

References 49 publications

Trading and Investing in Volatility Products

Trading and Investing in Volatility Products

Analysing Intraday Implied Volatility for Pricing Currency Options

On the relationship between implied volatility index and equity index returns

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