Editorial Probability and Statistics with Applications in ...
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Editorial Probability and Statistics with Applications in Finance and Economics Sarah Brown 1 and Wing Keung Wong 2 1 Department of Economics, University of Sheffield, 9 Mappin Street, Sheffield S1 4DT, UK 2 Department of Economics, Hong Kong Baptist University, WLB, Shaw Campus, Kowloon Tong, Hong Kong Correspondence should be addressed to Wing Keung Wong; [email protected] Received 21 December 2014; Accepted 21 December 2014 Copyright © 2015 S. Brown and W. K. Wong. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Probability and statistics play a vital role in every field of human activity. In particular, they are quantitative tools widely used in the areas of economics and finance. Knowl- edge of modern probability and statistics is essential for the development of economic and finance theories and for the testing of their validity through robust analysis of real- world data. For example, probability and statistics could help to shape effective monetary and fiscal policies and to develop pricing models for financial assets such as equities, bonds, currencies, and derivative securities. e importance of developing robust methods for such empirical analysis has become particularly important following the recent global financial crisis in 2008, which has placed economic and finance theories under the spotlight. In this connection, this special issue has been co-edited by the following guest editors Sarah Brown (University of Sheffield), Terence Chong (e Chinese University of Hong Kong), Pulak Ghosh (Indian Institute of Management), Tai Zhong Hu (University of Science and Technology of China), Lu Lin (Shandong University), Wing-Keung Wong (Hong Kong Baptist University), and Zhijie Xiao (Boston College) brings together high quality papers that are relevant for academics and practitioners alike from a range of disciplines including economics, finance, and statistics. is special issue is devoted to advancements in the applications of probability and statistics in the areas of economics and finance bringing together practical, state-of-the-art applications of probability, and statistical techniques in economics and finance. We hope that the papers published in this special edition will stimulate further research in this area. e papers published in the special issue collectively make important contributions to a wide range of areas including contributions which enhance our understanding of financial and commodity markets as well as contributions to statistical theory, which may open up important avenues for applied analysis in the future. To be specific, with respect to finance applications, G. Hinterleitner et al. (2015) explore market structure at the opening of the trading day and its influence on subsequent trading. eir experimental framework compares a single continuous double auction and two complement markets with different call auction designs as opening mechanisms. eir findings indicate that a call auction not only improves market efficiency and liquidity at the beginning of the trading day when compared to the stand-alone continuous double auction, but also causes positive spillover effects on subsequent trading. On the other hand, G. M. Goerg (2014) presents a parametric, bijective transformation to generate heavy tail versions of arbitrary random variables. e Lambert W function is used to model and remove heavy tails from continuous random variables using a data-transformation approach. Motivated by the observation that financial data is frequently characterised by negative skewness and excess kurtosis, the simulations and applications to S&P 500 log-returns in this paper importantly demonstrate the usefulness of the introduced methodology. Given that natural gas has become an extremely important commodity for the global economy, a commodity which is characterised by an increasingly risky and volatile market, J. Tang et al. (2015) focus on estimating the risk of natural gas portfolios using a GARCH-EVT-copula model. e findings Hindawi Publishing Corporation e Scientific World Journal Volume 2015, Article ID 618785, 2 pages http://dx.doi.org/10.1155/2015/618785
Transcript of Editorial Probability and Statistics with Applications in ...
EditorialProbability and Statistics with Applications inFinance and Economics
Sarah Brown1 and Wing Keung Wong2
1Department of Economics, University of Sheffield, 9 Mappin Street, Sheffield S1 4DT, UK2Department of Economics, Hong Kong Baptist University, WLB, Shaw Campus, Kowloon Tong, Hong Kong
Correspondence should be addressed to Wing Keung Wong; [email protected]
Received 21 December 2014; Accepted 21 December 2014
Copyright © 2015 S. Brown and W. K. Wong. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.
Probability and statistics play a vital role in every field ofhuman activity. In particular, they are quantitative toolswidely used in the areas of economics and finance. Knowl-edge of modern probability and statistics is essential forthe development of economic and finance theories and forthe testing of their validity through robust analysis of real-world data. For example, probability and statistics couldhelp to shape effective monetary and fiscal policies and todevelop pricing models for financial assets such as equities,bonds, currencies, and derivative securities. The importanceof developing robust methods for such empirical analysis hasbecome particularly important following the recent globalfinancial crisis in 2008, which has placed economic andfinance theories under the spotlight.
In this connection, this special issue has been co-editedby the following guest editors Sarah Brown (University ofSheffield), Terence Chong (The Chinese University of HongKong), Pulak Ghosh (Indian Institute of Management), TaiZhong Hu (University of Science and Technology of China),Lu Lin (Shandong University), Wing-Keung Wong (HongKong Baptist University), and Zhijie Xiao (Boston College)brings together high quality papers that are relevant foracademics and practitioners alike from a range of disciplinesincluding economics, finance, and statistics.This special issueis devoted to advancements in the applications of probabilityand statistics in the areas of economics and finance bringingtogether practical, state-of-the-art applications of probability,and statistical techniques in economics and finance.We hopethat the papers published in this special edition will stimulatefurther research in this area.
The papers published in the special issue collectivelymake important contributions to a wide range of areasincluding contributions which enhance our understandingof financial and commodity markets as well as contributionsto statistical theory, which may open up important avenuesfor applied analysis in the future. To be specific, withrespect to finance applications, G. Hinterleitner et al. (2015)explore market structure at the opening of the trading dayand its influence on subsequent trading. Their experimentalframework compares a single continuous double auction andtwo complement markets with different call auction designsas opening mechanisms. Their findings indicate that a callauction not only improves market efficiency and liquidityat the beginning of the trading day when compared tothe stand-alone continuous double auction, but also causespositive spillover effects on subsequent trading. On the otherhand, G. M. Goerg (2014) presents a parametric, bijectivetransformation to generate heavy tail versions of arbitraryrandom variables. The Lambert W function is used to modeland remove heavy tails from continuous random variablesusing a data-transformation approach. Motivated by theobservation that financial data is frequently characterised bynegative skewness and excess kurtosis, the simulations andapplications to S&P 500 log-returns in this paper importantlydemonstrate the usefulness of the introduced methodology.Given that natural gas has become an extremely importantcommodity for the global economy, a commodity which ischaracterised by an increasingly risky and volatile market, J.Tang et al. (2015) focus on estimating the risk of natural gasportfolios using a GARCH-EVT-copula model. The findings
Hindawi Publishing Corporatione Scientific World JournalVolume 2015, Article ID 618785, 2 pageshttp://dx.doi.org/10.1155/2015/618785
2 The Scientific World Journal
indicate the importance of conducting further research ondependence structure in themarket for this critical commod-ity.
With respect to purely theoretical contributions, C.-W.Lin et al. (2014) demonstrate that, under suitable conditions,an almost sure central limit theorem for self-normalizedproducts of sums of partial sums holds under a fairly generalgrowth condition on the weight sequence, an importantstatistical result. Finally, C. Yin et al. (2014) focus on one ofthe key topics of actuarial science and finance, namely, theoptimal dividend problem. Specifically, they explore the opti-mal dividends problem for a company whose cash reservesfollow a general Levy process with certain positive jumpsand arbitrary negative jumps. In this interesting contribution,they present conditions under which the optimal dividendstrategy, among all admissible ones, takes the formof a barrierstrategy.
Sarah BrownWing Keung Wong
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