Advances In Quantitative Analysis Of Finance And Accounting Vol. 6

Advances in Quantitative Analysis of Finance and Accounting is an annual publication designed to disseminate developments in the quantitative analysis of finance and accounting. The publication is a forum for statistical and quantitative analyses of issues in finance and accounting, as well as applications of quantitative methods to problems in financial management, financial accounting, and business management. The objective is to promote interaction between academic research in finance and accounting and applied research in the financial community and accounting profession. The chapters in this volume cover a wide range of important topics, including corporate finance and debt management, earnings management, options and futures, equity market, and portfolio diversification. These topics are very useful for both academicians and practitioners in the area of finance. Contents: Collateral Constraints, Debt Management, and Investment Incentives (E Agliardi & R Andergassen); A Concave Quadratic Programming Marketing Strategy Model with Product Life Cycles (P Y Kim et al.); Evaluating the Robustness of Market Anomaly Evidence (W D Brown, Jr et al.); Why is the Value Relevance of Earnings Lower for High-Tech Firms? (B B Lee et al.); Thirty Years of Canadian Evidence on Stock Splits, Reverse Stock Splits, and Stock Dividends (V Jog & P C Zhu); Intraday Volume Volatility Relation of the DOW: A Behavioral Interpretation (A F Darrat et al.); The Pricing of Initial Public Offerings: An Option Approach (S Liu et al.); Determinants of Winner Loser Effects in National Stock Markets (M-S Pan); Earnings Management in Corporate Voting: Evidence from Antitakeover Charter Amendments (C-K Hoi et al.); Deterministic Portfolio Selection Models, Selection Bias, and an Unlikely Hero (H E Phillips); Corporate Capital Structure and Firm Value: A Panel Data Evidence from Australia s Dividend Imputation Tax System (A T Mollik); The Momentum and Mean Reversion of Nikkei Index Futures: A Markov Chain Analysis (K Peng & S Wang).