Yin Hwang; Eric Lefebvre; Michaela Pejcochova; Uta Rahmann-Steinert; Hildegard Rui Jiang; Kira Samosyuk; Clarissa Vo Spee Dietrich Reimer (2017) Pehmeäkantinen kirja
Junlan Wang (ed.); Bonnie Antoun (ed.); Eric Brown (ed.); Weinong Chen (ed.); Ioannis Chasiotis (ed.); Em Huskins-Retzlaff Springer (2017) Kovakantinen kirja
Shouyi Wang; Vicky Yamamoto; Jianzhong Su; Yang Yang; Erick Jones; Leon Iasemidis; Tom Mitchell Springer Nature Switzerland AG (2018) Pehmeäkantinen kirja
Springer-Verlag New York Inc. Sivumäärä: 998 sivua Asu: Pehmeäkantinen kirja Painos: 2nd ed. 2006 Julkaisuvuosi: 2005, 08.12.2005 (lisätietoa) Kieli: Englanti
The field of financial econometrics has exploded over the last decade. This book represents an integration of theory, methods, and examples using the S-PLUS statistical modeling language and the S+FinMetrics module to facilitate the practice of financial econometrics. This is the first book to show the power of S-PLUS for the analysis of time series data. It is written for researchers and practitioners in the finance industry, academic researchers in economics and finance, and advanced MBA and graduate students in economics and finance. Readers are assumed to have a basic knowledge of S-PLUS and a solid grounding in basic statistics and time series concepts.
This second edition is updated to cover S+FinMetrics 2.0 and includes new chapters on copulas, nonlinear regime switching models, continuous-time financial models, generalized method of moments, semi-nonparametric conditional density models, and the efficient method of moments.
From the reviews of the second edition:
"It provides theoretical and empirical discussions on exhaustive topics in modern financial econometrics, statistics and time series. … it is definitely a good reference book for use in studying and/or researching in modern empirical finance … ." (T. S. Wirjanto, Short Book Reviews, Vol. 26 (1), 2006)
"...It is a pleasure to strongly recommend this text, and to include statisticians such as myself among the pleased audience." (Thomas L. Burr for Techommetrics, Vol. 49, No. 1, February 2007)
