This is a preview. Log in through your library . Abstract In this paper four alternative quarterly econometric models of investment behavior are fitted to a common set of data for individual ...

Spatial econometrics addresses the challenges posed by spatially correlated data, enabling researchers to understand and quantify how economic phenomena in one location can influence those in ...

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

The Wharton Model is extrapolated for 24 quarters with appropriate assumptions. The problems involved in specifying a fresh model for long range forecasting are then outlined, including "endogenizing ...

The field of econometrics and statistical methods encompasses a suite of techniques designed to quantify economic relationships, test theories using real-world data, and forecast future trends. This ...

"Financial Econometrics," by Oliver Linton of Cambridge University, is written for master's degree students in finance and focuses on extending the path-breaking work presented in "The Econometrics of ...

The group is interested in theoretical and methodological developments in econometrics and statistics, with particular emphasis on applications in macroeconomics and finance. The research interests of ...

The global financial crisis, triggered by the subprime mortgage problem and resulting in the collapse of a major American investment bank in September 2008, has seriously affected the Japanese economy ...

Camelot Global commercial director Richard Bateson reminds us that econometric models are only as good as the data that goes into them, and more evidence is always needed to prove the return on ...