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J. Risk Financial Manag., Volume 6, Issue 1 (December 2013), Pages 1-61

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Editorial

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Open AccessEditorial The Journal of Risk and Financial Management in Open Access
J. Risk Financial Manag. 2013, 6(1), 1-3; doi:10.3390/jrfm6010001
Received: 19 September 2013 / Accepted: 20 September 2013 / Published: 1 October 2013
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Abstract
Financial economics and econometrics have advanced rapidly in recent years, in terms of coverage of topics, the creation of new data sources, the availability of existing high frequency and ultra-high frequency tick data, the growing importance of international financial analysis, the technicality [...] Read more.
Financial economics and econometrics have advanced rapidly in recent years, in terms of coverage of topics, the creation of new data sources, the availability of existing high frequency and ultra-high frequency tick data, the growing importance of international financial analysis, the technicality of research topics, and the number of papers and journals publishing such theoretical and practical research. [...] Full article
Open AccessEditorial Publisher’s Note: Journal of Risk and Financial Management
J. Risk Financial Manag. 2013, 6(1), 4-5; doi:10.3390/jrfm6010004
Received: 2 October 2013 / Accepted: 2 October 2013 / Published: 3 October 2013
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Abstract
The Journal of Risk and Financial Management (JRFM) is published in full open access by MDPI as of 1 October 2013, when MDPI took over the ownership of the journal. So far, this journal has been published elsewhere in yearly volumes (one [...] Read more.
The Journal of Risk and Financial Management (JRFM) is published in full open access by MDPI as of 1 October 2013, when MDPI took over the ownership of the journal. So far, this journal has been published elsewhere in yearly volumes (one issue per yearly volume) since 2008, with a total of 25 papers released up to this moment [1]. Starting from 1 January 2014, the journal will be published in quarterly issues. [...] Full article

Research

Jump to: Editorial

Open AccessArticle A Non-Parametric and Entropy Based Analysis of the Relationship between the VIX and S&P 500
J. Risk Financial Manag. 2013, 6(1), 6-30; doi:10.3390/jrfm6010006
Received: 3 October 2013 / Revised: 7 October 2013 / Accepted: 8 October 2013 / Published: 21 October 2013
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Abstract
This paper features an analysis of the relationship between the S&P 500 Index and the VIX using daily data obtained from the CBOE website and SIRCA (The Securities Industry Research Centre of the Asia Pacific). We explore the relationship between the S&P [...] Read more.
This paper features an analysis of the relationship between the S&P 500 Index and the VIX using daily data obtained from the CBOE website and SIRCA (The Securities Industry Research Centre of the Asia Pacific). We explore the relationship between the S&P 500 daily return series and a similar series for the VIX in terms of a long sample drawn from the CBOE from 1990 to mid 2011 and a set of returns from SIRCA’s TRTH datasets from March 2005 to-date. This shorter sample, which captures the behavior of the new VIX, introduced in 2003, is divided into four sub-samples which permit the exploration of the impact of the Global Financial Crisis. We apply a series of non-parametric based tests utilizing entropy based metrics. These suggest that the PDFs and CDFs of these two return distributions change shape in various subsample periods. The entropy and MI statistics suggest that the degree of uncertainty attached to these distributions changes through time and using the S&P 500 return as the dependent variable, that the amount of information obtained from the VIX changes with time and reaches a relative maximum in the most recent period from 2011 to 2012. The entropy based non-parametric tests of the equivalence of the two distributions and their symmetry all strongly reject their respective nulls. The results suggest that parametric techniques do not adequately capture the complexities displayed in the behavior of these series. This has practical implications for hedging utilizing derivatives written on the VIX. Full article
Open AccessArticle Testing for a Single-Factor Stochastic Volatility in Bivariate Series
J. Risk Financial Manag. 2013, 6(1), 31-61; doi:10.3390/jrfm6010031
Received: 4 October 2013 / Revised: 25 November 2013 / Accepted: 12 December 2013 / Published: 19 December 2013
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Abstract
This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the [...] Read more.
This paper proposes the Lagrange multiplier test for the null hypothesis thatthe bivariate time series has only a single common stochastic volatility factor and noidiosyncratic volatility factor. The test statistic is derived by representing the model in alinear state-space form under the assumption that the log of squared measurement error isnormally distributed. The empirical size and power of the test are examined in Monte Carloexperiments. We apply the test to the Asian stock market indices. Full article

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