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Archive for April, 2012

Vix futures: why the most hideous forecasting record?

23 Apr

Article by: Izabella Kaminska
Published by: Financial Times
Date: 24 Feb 2012

“It’s official – volatility is back. The Vix index, which is derived from the value of S&P 500 options, posted its biggest two-day increase in nine months on Wednesday following a sharp fall in S&P 500 equities.

“All of which is good news for the CBOE, the keeper of the Vix futures contract.

“The product is viewed by the option specialist as one of its key growth areas, contributing to the bulk of the group’s performance over the past year.

“What is interesting though is that the biggest increase in Vix futures volumes happened over the course of last year when volatility was largely low.”

Full article (requires subscription): Link

 
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Posted in Implied volatility

 

Vix products are not for rational investors

17 Apr

Article by: John Dizard
Published by: Financial Times
Date: 15 Apr 2012

“If the public behaved rationally, casinos would be out of business and there would be little if any trading in Vix (Chicago’s volatility index) futures and options. Yet supposedly sophisticated investors, who would laugh off the notion that you can beat the house playing slot machines, have turned the Vix products into one of the greatest marketing successes in the history of financial products.”

Full article (requires subscription): Link

 
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Posted in Implied volatility

 

Is the Potential for International Diversification Disappearing?

04 Apr

Article by: Peter Christoffersen, Vihang Errunza, Kris Jacobs, Hugues Langloi
Published by: 16th Annual Global Investment Conference
Date: 16 Mar 2010

“Since understanding and quantifying the evolution of security co-movements is critical for asset pricing and portfolio allocation, we investigate patterns and trends in correlations over time using weekly returns for large systems of developed markets (DMs) and emerging markets (EMs) during the period 1973-2009. We use the DECO, DCC, and BEKK correlation models, and develop a novel dynamic t-copula which generalizes the normal copula, to allow for dynamic tail dependence. We demonstrate that it is possible to overcome the well known dimensionality problems and compute correlation and tail dependence in international markets using large samples, without relying on factor models. Our results suggest that correlations have been significantly trending upward for both the DMs and EMs. Further, the evidence clearly contradicts the decoupling hypothesis. Although the tail dependence is increasing through time for both EMs and DMs, the level of the tail dependence is still very low at the end of our sample period for EMs as compared to DMs. Therefore, while the correlation analysis suggests that the diversification potential of EMs has largely disappeared, this is contradicted by our findings on tail dependence. Thus, even though diversification benefits might have lessened in the case of DMs, the case for EMs remains intact.”

Full article (PDF): Link

 
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Posted in Investing ideas

 

Parametric and nonparametric volatility measurement

01 Apr

Article by: Torben G. Andersen, Tim Bollerslev, and Francis X. Diebold
Published by: Wharton School, Univ. of Penn.
Date: Jul 2002

“Volatility has been one of the most active areas of research in empirical finance and time series econometrics during the past decade. This chapter provides a unified continuous-time, frictionless, no-arbitrage framework for systematically categorizing the various volatility concepts, measurement procedures, and modeling procedures. We define three different volatility concepts: (i) the notional volatility corresponding to the ex-post sample-path return variability over a fixed time interval, (ii) the ex-ante expected volatility over a fixed time interval, and (iii) the instantaneous volatility corresponding to the strength of the volatility process at a point in time. The parametric procedures rely on explicit functional form assumptions regarding the expected and/or instantaneous volatility. In the discrete-time ARCH class of models, the expectations are formulated in terms of directly observable variables, while the discrete- and continuous-time stochastic volatility models involve latent state variable(s). The nonparametric procedures are generally free from such functional form assumptions and hence afford estimates of notional volatility that are flexible yet consistent (as the sampling frequency of the underlying returns increases). The nonparametric procedures include ARCH filters and smoothers designed to measure the volatility over infinitesimally short horizons, as well as the recently-popularized realized volatility measures for (non-trivial) fixed-length time intervals.”

Full article (PDF): Link

 
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Posted in Implied volatility, Realized volatility