Kent Centre for Finance

A recent research paper authored by Ekaterini Panopoulou of Kent Business School (joint with L. Meligkotsidou, I. Vrontos and S. Vrontos) entitled ‘Out-of-sample equity premium prediction: A complete subset quantile regression approach’ has ranked among the TOP 10 most downloaded papers in its category within days of it being uploaded onto the Social Science Research Network (SSRN).

The paper focuses on the issue of forecasting equity returns, which is one of the most widely discussed topics in the finance literature mainly due to its central role in asset pricing, portfolio allocation and evaluation of investment managers. The authors propose a new forecasting approach based on complete subset quantile regressions. Their quantile regression approach to equity premium prediction allows them to cope with the non-linearity and non-normality patterns that are evident in the relationship between stock returns and potential predictors. Moreover, by employing quantile forecast combinations, they reduce model uncertainty and parameter instability. Finally, employing complete subset quantile regressions induces shrinkage to the respective estimates and further helps reduce the effect of parameter estimation error. A further contribution of this paper is the development of a recursive algorithm for selecting the best subset in real time, based on the past history of excess returns and predictive variables. The proposed algorithm is a likelihood-based method that chooses the best complete subset for a given quantile and is flexible enough to allow for variability of the selected value across quantiles. Their approach delivers statistically and economically significant out-of-sample US equity premium forecasts relative to both the historical average benchmark and the complete subset mean regression approach. More importantly, the economic evaluation results suggest that an investor that adopts this framework can gain sizable benefits which range from 3.91% to an impressive 6.27% per year relative to a naïve strategy based on the historical benchmark performance.

For more details, the paper is available from the following link: http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2335084

Dr. Ekaterini Panopoulou is organizing an exciting session on “Recent advances in forecasting financial time series” at the 7th International Conference on Computational and Financial Econometrics (CFE 2013) which will take place at the Senate House, University of London, UK, 14-16 December 2013.

For more information – http://cfenetwork.org/CFE2013/full_programme.php

Kent Business School’s Dr. Ekaterini Panopoulou has been elected on the board of Methods in International Finance Network.

The Methods in International Finance Network (MIFN) aims at promoting research in the domain of international finance. It provides a platform for researchers and advanced PhD students to exchange research ideas and share new research findings with an emphasis on the interactions between econometric methods and economic theory. The Network activities include annual meeting/conference, exchange of PhD students between participating universities, and applications for European or National grants.

A recent research paper co-authored by Dr Silvia Stanescu and Prof Radu Tunaru, entitled ‘Investment Strategies with VIX and VSTOXX Futures’ has ranked among the TOP 10 most downloaded papers in its category within days of it being uploaded onto the Social Science Research Network (SSRN).

The paper discusses one of the hottest topics in financial markets at the moment, namely volatility derivatives, which have experienced an exponential growth in the aftermath of the subprime crisis. In the first part of the paper, the authors have analysed the performance of various portfolios mixing equity with bonds but also considering volatility futures. The analysis was carried out comparatively for US using VIX futures and also for Euro zone where VSTOXX futures were employed. The results point out that the best portfolio will contain a large proportion of equity, a smaller proportion of bonds and also of volatility index futures. The key finding here is that bonds will help investors in periods of liquidity pressure while volatility futures will help to insulate the portfolio against temporary market crashes and systemic shock events. In the second part of the paper the authors identify a statistical arbitrage opportunity between the VIX futures and VSTOXX futures markets. For the first time in the literature they analyse the synchronous daily time-series of the differences between the VIX futures and VSTOXX futures. This is a unique dataset that was compiled with the great help from Eurex Deutsche Borse. The in-sample results show that the difference VIX-VSTOXX (futures) is significantly negative, in effect that there was more volatility in the Euro zone than in US. This relationship may change in the future but the statistical methodology presented in the paper along with the proposed trading strategies can be applied the same way.

For more details, the paper is available from the following link:
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2351427