Implied volatility and future portfolio returns

Banerjee, P.; Doran, James; Peterson, David R.

doi:10.1016/j.jbankfin.2006.12.007

Cited by 171 publications

(145 citation statements)

References 34 publications

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“…The VIX, the most well-known volatility index of the US market, plays a successful role as a market indicator and fear gauge measure. Numerous articles that examine the fitting and forecasting ability of the US' implied volatility index demonstrate its superiority over historical volatilities (Banerjee et al, 2007;Becker et al, 2007;Carr and Wu, 2006;Corrado and Miller, 2005;Frijns et al, 2010;Jiang and Tian, 2007;Konstantinidi et al, 2008;Simon, 2003). Some studies also investigate implied volatility indices for quantifying market risk and for risk management purposes (Giot, 2005;Kim and Ryu, 2015b).…”

Section: Introductionmentioning

confidence: 99%

Effects of the US Stock Market Return and Volatility on the VKOSPI

2015

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The KOSPI (Korea Composite Stock Price Index) 200 options are one of the most actively traded derivatives in the world. This paper empirically examines (a) the statistical properties of the Korea's representative implied volatility index (VKOSPI) derived from the KOSPI 200 options and (b) the macroeconomic and financial variables that can predict the implied volatility process of the index, using augmented heterogeneous autoregressive (HAR) models with exogenous covariates. The results suggest that the elaborate HAR framework is proficient at describing the dynamics of the VKOSPI and that some domestic macroeconomic variables explain the VKOSPI. More importantly, we find that the stock market return and implied volatility index of the US market (i.e., the S&P 500 spot return and the VIX from the S&P 500 options) play a key role in predicting the level of the VKOSPI and explaining its dynamics, and their explanatory power dominates that of domestic macro-finance variables. Further, while the domestic stock market return does not predict the VKOSPI, the US stock market return does so rather well. When two global factors, both the US stock market return and the US implied volatility index, are incorporated into the HAR framework, the model exhibits the best performance in terms of both in-sample fitting and out-of-sample forecasting ability. JEL C22 C50 G14 G15

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Section: Introductionmentioning

confidence: 99%

Effects of the US Stock Market Return and Volatility on the VKOSPI

2015

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“…Given that the KOSPI200 index options are top-tier options products due to their high trading volume and investor interest, there is good _________________________ 2 If we derive implied volatility from option pricing models, it contains some model bias, of which representative examples are volatility smiles or smirks of the Black-Scholes model. 3 See the recent studies of Giot (2005aGiot ( , 2005b, Banerjee, Doran, and Peterson (2007), Becker, Clements, andMcCelland (2009), andDuan andYeh (2010). 4 Some recent studies, such as Ryu (2008, 2010), Ryu (2011), and Kim and Ryu (2012), have begun to address the market microstructure issues of the KOSPI200 options market.…”

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confidence: 99%

Stock Returns and Implied Volatility: A New VAR Approach

Lee

Ryu

2013

Economics

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The authors re-examine the return-volatility relationship and its dynamics under a new vector autoregression (VAR) identification framework. By analyzing two model-free impliedvolatility indices -the well-established VIX (in the United States) and the recently published VKOSPI (in Korea) -and their stock market indices, the authors find an asymmetric volatility phenomenon in both the developed and emerging markets. However, the VKOSPI shows impulse response dynamics that are quite different from those of the VIX. This finding can be attributed to the unique characteristics of the KOSPI200 options market, which determine the dynamics of the VKOSPI. JEL G10 G15

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“…This is most likely a result of the well-documented mean reverting behavior of volatility indexes (see, for e.g., Dash and Moran, 2005), Zhu and Zhang (2007) and Banerjee, Doran and Peterson (2007). It is the mean reversion tendency that explains at least one of the reasons that sponsors of volatility products recommend a very short holding period.…”

Section: Resultsmentioning

confidence: 99%

Behind the Rejection of Alternative Measures of Implied Equity Volatility: A Note

Hancock¹

2013

JFRM

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This note evaluates the risk-adjusted performance of the implied volatility of the NASDAQ index (VXN), Russell 2000 (RVX) and Dow Jones Industrial Averages (VXD). The results are compared to the performance of the implied volatility of the S & P 500 (VIX) in order to identify the unique contribution of each volatility index. Futures and option contracts have been offered on the VXD, VXN and RVX with results so dismal that the contracts were eventually delisted. In May 2012 futures were once again offered on the VXN but there is little market interest as indicated by the low trading volume. This note finds that the equity index implied volatility measures on VXN, RVX and VXD do not offer sufficient benefits beyond what investors can achieve with VIX which may explain, in part, the rejection of derivatives written on those measures of tradable implied index volatility.

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Implied volatility and future portfolio returns

Cited by 171 publications

References 34 publications

Effects of the US Stock Market Return and Volatility on the VKOSPI

Effects of the US Stock Market Return and Volatility on the VKOSPI

Stock Returns and Implied Volatility: A New VAR Approach

Behind the Rejection of Alternative Measures of Implied Equity Volatility: A Note

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