Advances in quantitative analysis of finance and accounting. by Cheng-Few Lee

By Cheng-Few Lee

Advances in Quantitative research of Finance and Accounting is an annual booklet designed to disseminate advancements within the quantitative research of finance and accounting. The e-book is a discussion board for statistical and quantitative analyses of concerns in finance and accounting, in addition to purposes of quantitative easy methods to difficulties in monetary administration, monetary accounting, and company administration. the target is to advertise interplay among educational learn in finance and accounting and utilized study within the monetary group and accounting career. The chapters during this quantity hide quite a lot of very important issues, together with company finance and debt administration, gains administration, techniques and futures, fairness marketplace, and portfolio diversification. those issues are very priceless for either academicians and practitioners within the zone of finance.

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Care must be exercised that estimated regression coefficients more often than not, have some probability distributions, notably normal distribution. It remains an interesting topic in the future to incorporate stochastic programming in the marketing strategy model. That is, can normally distributed coefficients in the price equation give rise to a more systematic solution pattern in x’s? It seems that there is no theory in this regard to indicate a hard and fast answer. In the absence of an answer, a simulation approach has been recommended using plus and minus two standard errors.

Currency hedging with options and futures. European Economic Review, 47, 833–839. 6 Chapter 2 A Concave Quadratic Programming Marketing Strategy Model with Product Life Cycles Paul Y. Kim and Chin W. Yang Clarion University of Pennsylvania, USA Cindy Hsiao-Ping Peng Yu Da College of Business, Taiwan Ken Hung National Dong Hua University, Taiwan As a more general approach, the authors formulate a concave quadratic programming model of the marketing strategy (QPMS) problem. Due to some built-in limitations of its corresponding linear programming version, the development of the QPMS model is necessary to further improve the research effort of evaluating the profit and sales impact of alternative marketing strategies.

The generation of an empirical distribution of hedge returns provides the researcher with valuable incremental information about the candidate anomaly under study. Specifically, it locates the hedge returns obtained by a given researcher in the universe of hedge returns that would be obtained by researchers using the same data with different data selection criteria. These diagnostics are applied to the findings in two specific prior studies: the forecast-to-price anomaly documented by Elgers et al.

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