John B. Guerard, JR. - Böcker

Financial forecasting is an integral element to creating effective financial management and portfolio selection decision-making. In this volume, the authors report financial modelling results to corporate financial policies of forecasting sales and earnings, which are key inputs to dividend policy, capital investment, stock buybacks, and optimal debt policy. Financial forecasts of earnings enhance portfolio selection in US, Japanese, global, and emerging market portfolios. The book reports how the financial forecasting models of Clive Granger and David Hendry, and their associates, can be employed to effectively implement the portfolio selection models of Harry Markowitz, Bill Sharpe, and Martin Gruber, and Ed Elton.

Financial forecasting is an integral element to creating effective financial management and portfolio selection decision-making. In this volume, the authors report financial modelling results to corporate financial policies of forecasting sales and earnings, which are key inputs to dividend policy, capital investment, stock buybacks, and optimal debt policy. Financial forecasts of earnings enhance portfolio selection in US, Japanese, global, and emerging market portfolios. The book reports how the financial forecasting models of Clive Granger and David Hendry, and their associates, can be employed to effectively implement the portfolio selection models of Harry Markowitz, Bill Sharpe, and Martin Gruber, and Ed Elton.

Covering a wide spectrum of topics, including portfolio selection, data mining tests, and multi-factor risk models, the book presents a comprehensive approach to portfolio construction tools, models, frameworks, and analyses, with both practical and theoretical implications.

Quantitative Corporate Finance is designed to be an advanced graduate corporate financial management textbook. The book will address several problems in contemporary corporate finance: optimal capital structure, both in the US and in the G7 economies, the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Model (APT) and the implications for the cost of capital, dividend policy, sales forecasting and pro forma statement analysis, leverage and bankruptcy, and mergers and acquisitions.

Quantitative Corporate Finance is designed to be an advanced graduate corporate financial management textbook. The book will address several problems in contemporary corporate finance: optimal capital structure, both in the US and in the G7 economies, the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Model (APT) and the implications for the cost of capital, dividend policy, sales forecasting and pro forma statement analysis, leverage and bankruptcy, and mergers and acquisitions.

Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.

Covering a wide spectrum of topics, including portfolio selection, data mining tests, and multi-factor risk models, the book presents a comprehensive approach to portfolio construction tools, models, frameworks, and analyses, with both practical and theoretical implications.

Forecasting—the art and science of predicting future outcomes—has become a crucial skill in business and economic analysis. This volume introduces the reader to the tools, methods, and techniques of forecasting, specifically as they apply to financial and investing decisions. With an emphasis on "earnings per share" (eps), the author presents a data-oriented text on financial forecasting, understanding financial data, assessing firm financial strategies (such as share buybacks and R&D spending), creating efficient portfolios, and hedging stock portfolios with financial futures. The opening chapters explain how to understand economic fluctuations and how the stock market leads the general economic trend; introduce the concept of portfolio construction and how movements in the economy influence stock price movements; and introduce the reader to the forecasting process, including exponential smoothing and time series model estimations. Subsequent chapters examine the composite index of leading economic indicators (LEI); review financial statement analysis and mean-variance efficient portfolios; and assess the effectiveness of analysts’ earnings forecasts. Using data from such firms as Intel, General Electric, and Hitachi, Guerard demonstrates how forecasting tools can be applied to understand the business cycle, evaluate market risk, and demonstrate the impact of global stock selection modeling and portfolio construction.

This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds.Now in its second edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance.New to the second edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.

This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds.Now in its third edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance.New to the third edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.

This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds.Now in its third edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance.New to the third edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.

This volume, inspired by and dedicated to the work of pioneering investment analyst, Jack Treynor, addresses the issues of portfolio risk and return and how investment portfolios are measured.

This volume, inspired by and dedicated to the work of pioneering investment analyst, Jack Treynor, addresses the issues of portfolio risk and return and how investment portfolios are measured.

This book introduces the readers to the rapidly growing literature and latest results on financial, fundamental and seasonal anomalies, stock selection modeling and portfolio management. Fifty years ago, finance professors taught the Efficient Markets Hypothesis which states that the average investor could not outperform the stock market based on technical, seasonal and fundamental data. Many, if not most faculty and investors, no longer share that opinion. In this book, the authors report original empirical evidence that applied investment research can produce statistically significant stock selection and excess portfolio returns in the US, and larger excess returns in international and emerging markets.