Volume 20, Number 3 Print ISSN: 1096-3685 Online ISSN: 1528-2635 ACADEMY OF ACCOUNTING AND FINANCIAL STUDIES JOURNAL Marianne James California State University, Los Angeles Editor The Academy of Accounting and Financial Studies Journal is owned and published by Jordan Whitney Enterprises, Inc. Editorial content is under the control of the Allied Academies, Inc., a non-profit association of scholars, whose purpose is to support and encourage research and the sharing and exchange of ideas and insights throughout the world. Authors execute a publication permission agreement and assume all liabilities. Neither Jordan Whitney Enterprises nor Allied Academies is responsible for the content of the individual manuscripts. Any omissions or errors are the sole responsibility of the authors. The Editorial Board is responsible for the selection of manuscripts for publication from among those submitted for consideration. The Publishers accept final manuscripts in digital form and make adjustments solely for the purposes of pagination and organization. The Academy of Accounting and Financial Studies Journal is owned and published by Jordan Whitney Enterprises, Inc., PO Box 1032, Weaverville, NC 28787 USA. Those interested in communicating with the Journal, should contact the Executive Director of the Allied Academies at [email protected] Copyright 2016 by Jordan Whitney Enterprises, Inc., Weaverville, NC, USA EDITORIAL REVIEW BOARD MEMBERS Robert Marley Liang Song University of Tampa Michigan Technological University Robert Graber Steve Moss University of Arkansas – Monticello Georgia Southern University Michael Grayson Chris Harris Brooklyn College Elon University Sudip Ghosh Atul K. Saxena Pennn State University, Berks campus Georgia Gwinnett College Rufo R. Mendoza Anthony Yanxiang Gu Certified Public Accountant State University of New York Alkali Yusuf Hema Rao Universiti Utara Malaysia SUNY Osweg Junaid M. Shaikh Marek Gruszczynski Curtin University of Technology Warsaw School of Economics Douglass Linda Bressler Natalie Tatiana Churyk University of Houston Downtown Northern Illinois University Suzanne Pinac Ward Dan Ward University of Louisiana at Lafayette University of Louisiana at Lafayette Eugene Calvasina Ron Stunda Southern University Valdosta State University P.N. Saksena Martha Sale Indiana University South Bend Sam Houston State University Askar Choudhury Rafik Z. Elias Illinois State University California State University, Los Angeles Harold Little Dawn Mead Hukai Western Kentucky University University of Wisconsin, River Falls James A. DiGabriele Desti Kannaiah Montclair State University Middlesex University London, Dubai Campus Philip H. Siegel Treba Marsh Augusta State University Stephen F. Austin State University Frank Plewa Mukunthan Santhanakrishnan Idaho State University Idaho State University Jan L. Williams Martha G. Suez-Sales University of Baltimore University of Guam Table of Contents A HYBRID NEURO-FUZZY MODEL FOR FOREIGN EXCHANGE RATE PREDICTION………………………………....…1 Hari Sharma, Virginia State University Dinesh K. Sharma, University of Maryland Eastern Shore Hari S. Hota, Bilaspur University VALUE RELEVANCE OF HISTORICAL INFORMATION AND FORECAST INFORMATION IN CHINA: EMPIRICAL EVIDENCE BASED ON THE OHLSON AND FELTHAM–OHLSON MODELS………………………………………......….14 Xiaobai Zhang, Nagoya University ESTIMATING THE VOLATILITY REDUCING HEDGE RATIOS USING OLS: EVIDENCE FROM THE SPOT AND SILVER FUTURES MARKET…………………………………………………………….……………………………........……28 Alan Harper, Gwynedd Mercy University Zhenhu Jin, Valparaiso University Raufu Sokunle, J.P. Morgan THE REGULATOR’S VIEW OF AUDIT QUALITY: A FOCUS ON IAASB’S PROPOSED FRAMEWORK FROM THE PERSPECTIVE OF INSTITUTIONAL THEORY……………………………………………………………………..…….....…37 Hu Dan Semba, Nagoya University WHAT IS YOUR EPS? ISSUES IN COMPUTING AND INTERPRETING EARNINGS PER SHARE……………….…….....48 Jeffrey J. Jewell, Lipscomb University Jeffrey A. Mankin, Lipscomb University INFLUENCE OF THE AUDIT MARKET SHIFT FROM BIG 4 TO BIG 3 ON AUDIT FIRMS’ INDUSTRY SPECIALIZATION AND AUDIT QUALITY: EVIDENCE FROM JAPAN………………………………….........................…62 Ryo Kato, Keio University Hu Dan Semba, Nagoya University Frendy, Nagoya University EARNINGS MANAGEMENT, EXECUTIVE COMPENSATION AND LAYOFFS…………………………………….…..….84 Chialing Hsieh, The University of Texas at Tyler Yi Ren, Illinois State University Roger Lirely, The University of Texas at Tyler CEO CHARACTERISTICS, COMPENSATION AND REAL ACTIVITY MANAGEMENT IN MANUFACTURING COMPANIES…………………………………………………………………...…………………………………………...……103 Linda M. Lovata, Southern Illinois University Edwardsville Timothy S. Schoenecker, Southern Illinois University Edwardsville Michael L. Costigan, Southern Illinois University Edwardsville UNETHICAL BUSINESS BEHAVIOR AND STOCK PERFORMANCE…………………………………........................……..115 D. Michael Long, University of Tennessee of Tennessee – Chattanooga Christi Wann, University of Tennessee of Tennessee – Chattanooga Christopher Brockman, University of Tennessee of Tennessee – Chattanooga DOES BOOK-TAX DIFFERENCE INFLUENCE THE VALUE RELEVANCE OF BOOK INCOME? EMPIRICAL EVIDENCE FROM JAPAN………………………………………………………………………………………………..……..123 Akihiro Yamada, Chuo University BUDGETARY SLACK: EXPLORING THE EFFECT OF DIFFERENT TYPES, DIRECTIONS, AND REPEATED ATTEMPTS OF INFLUENCE TACTICS ON PADDING A BUDGET…………………………………………………...……147 Sean M. Andre, West Chester University of Pennsylvania Marco Lam, Western Carolina University Mark O’Donnell, York College of Pennsylvania AN EXPERIMENTAL TESTING OF FACTORS ASSOCIATED WITH FINANCIAL STATEMENT FRAUD.....................167 Darryl J. Woolley, University of Idaho Academy of Accounting and Financial Studies Journal Volume 20, Number 3, 2016 A HYBRID NEURO-FUZZY MODEL FOR FOREIGN EXCHANGE RATE PREDICTION Hari Sharma, Virginia State University Dinesh K. Sharma, University of Maryland Eastern Shore Hari S. Hota, Bilaspur University ABSTRACT Foreign exchange (FX) rate movements depend on several factors such as economic conditions and the foreign policy of a country. Therefore, it is important to monitor the economic conditions of a country as well as its foreign policy to assess the impact on exchange rates. Since the FX rate has a nonlinear relationship with its predicting factors, researchers are designing and developing sophisticated models to accommodate the complex relationships between the foreign exchange rates and the predictive variables that are considered the most influential on the currency exchange rates in the short term. Recent research reveals that predictive models developed using Artificial Neural Network (ANN) captures nonlinear trends better than traditional forecasting techniques. Therefore, the focus of this research is to design and develop models that have better predictive power in real time. The authors have accomplished this goal by applying a hybrid of ANN and fuzzy logic in an Adaptive Neuro-Fuzzy Inference System (ANFIS) that can be implemented successfully with non-linear data prediction. This research paper utilizes ANFIS to develop a rule based model with one input and one output variable to predict the FX rates of three Asian countries: China, India, and Japan with respect to the US dollar. Recent time series datasets of five financial years of Chinese Yuan Renminbi/US Dollar (CNY/USD), Indian Rupees/US Dollar (INR/USD) and Japanese Yen /US Dollar (JPY/USD) were obtained and preprocessed to ANFIS for our predictions. A rule based model developed through ANFIS was utilized further for testing of the data. The results are obtained in terms of Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Root Mean Square Error (RMSE) and compared with ANN, which showed that the daily CNY/USD exchange rates has the least MAPE as compared to the other two exchange rates predictions. Thus, the prediction for the daily CNY/USD was more precise than the other two predictions (INR/USD and JPY/USD). Keywords: Adaptive Neuro-Fuzzy Inference System (ANFIS), Foreign Exchange (FX) Rate. INTRODUCTION The fluctuations in currency exchange rates require continuous monitoring of the economic and financial variables of a country. The exchange rates of a country’s currency with the US dollar depends primarily on the demand of the currency which is determined primarily by the net export position in a given period as well as the accumulated trade deficit (Sharma et al., 2014). The countries selected for the study are close competitors and have demonstrated the demand for their products in the US Market. Since the net export from China to the USA has increased during the period of study, the currency exchange rates of China have remained strong to the US dollar. On the other hand, due to the global economic slowdown and other internal and external factors, the exchange rates of India and Japan did not perform as well. Therefore, we are 1 Academy of Accounting and Financial Studies Journal Volume 20, Number 3, 2016 interested in testing the predictive power of Artificial Neural Network (ANN) integrated models for these currencies. Since the collapse of the Bretton-Woods system in 1973, researchers have focused on designing and developing sophisticated models to predict foreign exchange (FX) rates using computational intelligence, signal processing, and econometrics. The forecast of FX rates is important as the currency exchange rates are one of the most significant economic indices which needs ongoing attention in the international monetary markets. The FX market is the largest