Stochastic Processes and Calculus: An Elementary Introduction with Applications

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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.

Author(s): Uwe Hassler
Series: Springer Texts in Business and Economics
Edition: 1
Publisher: Springer
Year: 2015

Language: English
Pages: 391
Tags: Economic Theory/Quantitative Economics/Mathematical Methods; Statistics for Business/Economics/Mathematical Finance/Insurance; Quantitative Finance; Macroeconomics/Monetary Economics//Financial Economics; Econometrics; Game Theory, Econo

Front Matter....Pages i-xviii
Introduction....Pages 1-10
Front Matter....Pages 11-11
Basic Concepts from Probability Theory....Pages 13-43
Autoregressive Moving Average Processes (ARMA)....Pages 45-75
Spectra of Stationary Processes....Pages 77-101
Long Memory and Fractional Integration....Pages 103-126
Processes with Autoregressive Conditional Heteroskedasticity (ARCH)....Pages 127-148
Front Matter....Pages 149-149
Wiener Processes (WP)....Pages 151-177
Riemann Integrals....Pages 179-197
Stieltjes Integrals....Pages 199-211
Ito Integrals....Pages 213-237
Ito’s Lemma....Pages 239-258
Front Matter....Pages 259-259
Stochastic Differential Equations (SDE)....Pages 261-283
Interest Rate Models....Pages 285-302
Asymptotics of Integrated Processes....Pages 303-330
Trends, Integration Tests and Nonsense Regressions....Pages 331-352
Cointegration Analysis....Pages 353-382
Back Matter....Pages 383-391