Do liquidity and sampling methods matter in constructing volatility indices? Empirical evidence from Taiwan

Tzang, Shyh-Weir; Hung, Chih-Hsing; Wang, Chou‐Wen; Shyu, David

doi:10.1016/j.iref.2010.06.008

Cited by 13 publications

(4 citation statements)

References 26 publications

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“…Serious illiquidity concerns lead Siriopoulos and Fassas (2012) to estimate the Greek implied volatility index at a daily frequency and to 2 See also the works by Tzang, Hung, Wang, and Shyu (2011) and Gonzalez-Perez and Novales (2011) for the introduction of implied volatility indices for Taiwan and Spain respectively.…”

Section: Option Price Q(k I ) and Index Calculation Frequencymentioning

confidence: 99%

“…In practice, active traders are mainly realized on nearby month options, and the trades of the second-nearby month options will become active only when nearby options are very close to expiry. If next-nearby month options are too illiquid, the estimation errors due to structural noises could be amplified in case the roll-over times are long (Tzang et al, 2011).…”

Section: Roll-over Timesmentioning

confidence: 99%

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Implied volatility indices: A review and extension in the Turkish case

Şensoy

Omole

2018

International Review of Financial Analysis

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We re-visit the model-free methodology of the new VIX, and review how its counterparts are estimated empirically across the world. Then, we modify its parameter selection procedure for it to be compatible with the microstructure characteristics of emerging derivatives markets. Applying this approach on Turkish market data, we introduce VBI; the implied volatility index of Borsa Istanbul. Accordingly, (i) VBI is a strong predictor of the future realized volatility, (ii) it is significantly correlated with Turkey's own financial indicators, but not with many global financial indicators, (iii) there is an implied volatility spillover from US equity market to Borsa Istanbul, but not the other way around.

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Section: Option Price Q(k I ) and Index Calculation Frequencymentioning

confidence: 99%

Section: Roll-over Timesmentioning

confidence: 99%

Implied volatility indices: A review and extension in the Turkish case

Şensoy

Omole

2018

International Review of Financial Analysis

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“…As the relative volatility of cash and futures prices increases, this option increases in value, which disconnects the cash market from the deliverable instrument in a futures contract. Tzang et al [95] found that liquidity and sampling methods affect the construction of volatility indices. Thus, the selection of futures contracts whose expiration dates do not match the reset dates and or dividend dates of indices can affect the accuracy and performance of the FTSE stablerisk indices.…”

Section: The Ftse Stablerisk Index Seriesmentioning

confidence: 99%

Sub-Additive Recursive "Matching" Noise and Biases in Risk-Weighted Index Calculation Methods in Incomplete Markets With Partially Observable Multi-Attribute Preferences

Nwogugu

2013

Discrete Math. Algorithm. Appl.

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While indices, index tracking funds and ETFs have grown in popularity during then last ten years, there are many structural problems, tracking errors and biases inherent in index calculation methodologies and the legal/economic structure of ETFs, which raise actionable issues of "suitability" and "fraud" under US securities laws. This article contributes to the existing literature by: (a) introducing and characterizing the errors and biases inherent in "risk-adjusted" index-weighting methods and the associated adverse effects; (b) showing how these biases/effects reduce social welfare, and can facilitate harmful arbitrage activities; (c) introducing new theorems. 1350020-1 Discrete Math. Algorithm. Appl. 2013.05. Downloaded from www.worldscientific.com by NANYANG TECHNOLOGICAL UNIVERSITY on 08/26/15. For personal use only. M. C. I. Nwogugu status. This perspective is consistent with institutional investors' focus on Information Ratio as the preferred measure of risk-adjusted returns. Reference [52] has documented various classes of recursive preferences within the context of volatility and markets.Nwogugu [69] showed that the Put-Call Parity Theorem is inaccurate even after making adjustments for taxes and transaction costs. References [101,123,43] and Bharadwaj and Wiggins (2001) empirically showed that the Put-Call Parity Theorem is often violated even after accounting for transaction costs. Poitras et al. [125] concluded that the Put-Call Parity Theorem is inaccurate, and that there are early exercise premia for both calls and puts. Brunetti and Torrieelli [117] found mixed evidence about the accuracy of the Put Call Parity Theorem.Arnott et al.[6] compared the major index weighting methods (cap-weighting; fundamental weighting; equal weighting; minimum-variance; minimum-beta; and risk-adjusted index weighting) and also analyzed historical returns and volatilities of such indices from analyzed the daily trading and portfolio configuration strategies of index and enhanced index equity funds, and concluded that passive funds benefit from employing less rigid rebalancing and investment strategies; and that during index revision periods, enhanced index funds commence portfolio rebalancing earlier than index funds, and employ more patient trading strategies (all of which results in higher returns and lower trading costs for enhanced index funds). Frino et al.[36] stated that where passive funds do not perfectly mimic the benchmark Index, passive funds are more likely to over-weight stocks that have greater liquidity, larger market capitalization and higher past performance; and that for non-index portfolio holdings, enhanced funds exhibit a greater propensity to hold 'winners' and sell 'losers'. Ang et al. [129] and Blitz and van Vilet [128] both concluded that lowvolatility stocks produced higher returns while high volatility stocks produce low returns, and that the effect could not be explained by size, book-to-market, momentum or liquidity. Daniel and Titman [21] noted that firm-characteristics (rather than t...

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“…The use of mid‐quote prices has an automatic liquidity/illiquidity impact in the VIX calculation—where the options prices are moving due to changes in the limit order book rather than a realized price from a transaction. This problem is prevalent in other emerging markets, and has implicitly driven an incorporation of liquidity considerations into VIX calculations (Tzang et al, ).…”

Section: Measurementmentioning

confidence: 99%

Liquidity Considerations in Estimating Implied Volatility

Grover

Thomas

2012

Journal of Futures Markets

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Option markets have significant variation in liquidity across different option series. Illiquidity reduces the informativeness of the price. Price information for illiquid options is more noisy, and thus the implied volatilities (IVs) based on these prices are more noisy. In this study, we propose weighting schemes to estimate IV, which reduce the importance attached to illiquid options. The two indexes using liquidity weights are SVIX, which is a spread‐adjusted volatility index, and TVVIX, which is a traded volume weighted VIX. We find SVIX outperforms TVVIX, the conventional schemes such as the traditional VXO, or vega weights, and volatility elasticity weights. © 2012 Wiley Periodicals, Inc. Jrl Fut Mark 32:714‐742, 2012

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Do liquidity and sampling methods matter in constructing volatility indices? Empirical evidence from Taiwan

Cited by 13 publications

References 26 publications

Implied volatility indices: A review and extension in the Turkish case

Implied volatility indices: A review and extension in the Turkish case

Sub-Additive Recursive "Matching" Noise and Biases in Risk-Weighted Index Calculation Methods in Incomplete Markets With Partially Observable Multi-Attribute Preferences

Liquidity Considerations in Estimating Implied Volatility

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