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This textbook gives a comprehensive introduction to stochastic processes and calculus in the fields of finance and economics, more specifically mathematical finance and time series econometrics. Over the past decades stochastic calculus and processes have gained great importance, because they play a decisive role in the modeling of financial markets and as a basis for modern time series econometrics. Mathematical theory is applied to solve stochastic differential equations and to derive limiting results for statistical inference on nonstationary processes.
This introduction is elementary and rigorous at the same time. On the one hand it gives a basic and illustrative presentation of the relevant topics without using many technical derivations. On the other hand many of the procedures are presented at a technically advanced level: for a thorough understanding, they are to be proven. In order to meet both requirements jointly, the present book is equipped with a lot of challenging problems at the end of each chapter as well as with the corresponding detailed solutions. Thus the virtual text - augmented with more than 60 basic examples and 40 illustrative figures - is rather easy to read while a part of the technical arguments is transferred to the exercise problems and their solutions.
Uwe Hassler studied mathematics and economics at Freie Universität Berlin and specialized in statistics and econometrics at the London School of Economics. He completed his doctoral studies in 1993 at Freie Universität. Hassler published in leading field journals such as Econometric Theory, Journal of Econometrics and Journal of Time Series Analysis. His main research interests are within the field of time series analysis. Since 2003 he is Professor of Statistics and Econometric Methods at Goethe University Frankfurt, Germany. Prior to joining Goethe University he held permanent or visiting positions at leading universities in Darmstadt, Munich and Muenster (Germany), and in Madrid (Spain). He has been teaching stochastic processes and calculus for 15 years.
Introduction.- Part I Time Series Modeling.- Basic Concepts from Probability Theory.- Autoregressive Moving Average Processes (ARMA).- Spectra of Stationary Processes.- Long Memory and Fractional Integration.- Processes with Autoregressive Conditional Heteroskedasticity (ARCH).- Part II Stochastic Integrals.- Wiener Processes (WP).- Riemann Integrals.- Stieltjes Integrals.- Ito Integrals.- Ito's Lemma.- Part III Applications.- Stochastic Differential Equations (SDE).- Interest Rate Models.- Asymptotics of Integrated Processes.- Trends, Integration Tests and Nonsense Regressions.- Cointegration Analysis.
Show moreThis textbook gives a comprehensive introduction to stochastic processes and calculus in the fields of finance and economics, more specifically mathematical finance and time series econometrics. Over the past decades stochastic calculus and processes have gained great importance, because they play a decisive role in the modeling of financial markets and as a basis for modern time series econometrics. Mathematical theory is applied to solve stochastic differential equations and to derive limiting results for statistical inference on nonstationary processes.
This introduction is elementary and rigorous at the same time. On the one hand it gives a basic and illustrative presentation of the relevant topics without using many technical derivations. On the other hand many of the procedures are presented at a technically advanced level: for a thorough understanding, they are to be proven. In order to meet both requirements jointly, the present book is equipped with a lot of challenging problems at the end of each chapter as well as with the corresponding detailed solutions. Thus the virtual text - augmented with more than 60 basic examples and 40 illustrative figures - is rather easy to read while a part of the technical arguments is transferred to the exercise problems and their solutions.
Uwe Hassler studied mathematics and economics at Freie Universität Berlin and specialized in statistics and econometrics at the London School of Economics. He completed his doctoral studies in 1993 at Freie Universität. Hassler published in leading field journals such as Econometric Theory, Journal of Econometrics and Journal of Time Series Analysis. His main research interests are within the field of time series analysis. Since 2003 he is Professor of Statistics and Econometric Methods at Goethe University Frankfurt, Germany. Prior to joining Goethe University he held permanent or visiting positions at leading universities in Darmstadt, Munich and Muenster (Germany), and in Madrid (Spain). He has been teaching stochastic processes and calculus for 15 years.
Introduction.- Part I Time Series Modeling.- Basic Concepts from Probability Theory.- Autoregressive Moving Average Processes (ARMA).- Spectra of Stationary Processes.- Long Memory and Fractional Integration.- Processes with Autoregressive Conditional Heteroskedasticity (ARCH).- Part II Stochastic Integrals.- Wiener Processes (WP).- Riemann Integrals.- Stieltjes Integrals.- Ito Integrals.- Ito's Lemma.- Part III Applications.- Stochastic Differential Equations (SDE).- Interest Rate Models.- Asymptotics of Integrated Processes.- Trends, Integration Tests and Nonsense Regressions.- Cointegration Analysis.
Show moreIntroduction.- Part I Time Series Modeling.- Basic Concepts from Probability Theory.- Autoregressive Moving Average Processes (ARMA).- Spectra of Stationary Processes.- Long Memory and Fractional Integration.- Processes with Autoregressive Conditional Heteroskedasticity (ARCH).- Part II Stochastic Integrals.- Wiener Processes (WP).- Riemann Integrals.- Stieltjes Integrals.- Ito Integrals.- Ito’s Lemma.- Part III Applications.- Stochastic Differential Equations (SDE).- Interest Rate Models.- Asymptotics of Integrated Processes.- Trends, Integration Tests and Nonsense Regressions.- Cointegration Analysis.
Uwe Hassler studied mathematics and economics at Freie Universität Berlin and specialized in statistics and econometrics at the London School of Economics. He completed his doctoral studies in 1993 at Freie Universität. Hassler published in leading field journals such as Econometric Theory, Journal of Econometrics and Journal of Time Series Analysis. His main research interests are within the field of time series analysis. Since 2003 he is Professor of Statistics and Econometric Methods at Goethe University Frankfurt, Germany. Prior to joining Goethe University he held permanent or visiting positions at leading universities in Darmstadt, Munich and Muenster (Germany), and in Madrid (Spain). He has been teaching stochastic processes and calculus for 15 years.
“The book is quite readable and can be used as a textbook for the
application of mathematical theory in the area of econometrics.
Also, a mathematician might benefit from an intuitive exposition of
some different and specific types of integration appearing in the
theory of stochastic processes. The book might then serve as
starting point for a more detailed study of the mathematical
foundation of the topics presented.” (Ludger Overback, Mathematical
Reviews, October, 2016)“The book covers both discrete and
continuous time stochastic processes, and it is of course in the
second area where mathematical intricacies abound. … All this is
very much up to date and provides a most useful introduction to
modern time series methods for anybody wishing to understand the
mechanics without having to dig too deep into the mathematical
foundations.” (Walter Krämer, Statistics Papers, Vol. 57, 2016)“The
construction of this book is based on the author experience of 15
years of teaching stochastic processes and calculus. … book is
therefore a very successful work on the task of providing the
largest number of readers an introduction to stochastic processes
and calculus simultaneously accessible and rigorous, with a wide
exemplification of applications in various fields. Very important
for readers in the fields of mathematics, finance and econometrics
and also in biology, engineering or physics, but not only.” (Prof.
Dr. Manuel Alberto M. Ferreira, Acta Scientiae et Intellectus, Vol.
2 (2), 2016)
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