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  Investors and traders may find useful material such as lecture notes on asset pricing and portfolio theory. There is a rich literature for option traders such as material ranging from stochastic calculus to option pricing under non-normal distributions.

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Showing posts with label Probability. Show all posts
Showing posts with label Probability. Show all posts

Sunday, July 17, 2011

An Introduction to Mathematical Analysis for Economic Theory and Econometrics

Authors: Dean Corbae, Max Stinchcombe and Juraj Zeman
Type: e-book (final manuscript)
Level: Advanced Undergraduate (Math), MSc(Math. Fin), Ph.D.(Econ, Fin)

A manuscript (final, 2008) by Dean Corbae, Max Stinchcombe, and Juraj Zeman. After chapter 1 which briefly deals with the concept of logic, the authors cover set theory in chapter 2. In chapter 3 introduces the "Space of Real Numbers". You can read about the basic properties of rationals, the concept of distance, Cauchy sequences, supremum and infimum and the commpleteness of the Real Numbers. You can also find applications to economics. Chapter 4 is devoted to Metric Spaces $R^l,$ $l=1,2,...$ The basic definitions of Metric Spaces are introduced. You can also read about normed vector spaces, compacteness, completeness, closure, convergence and separability. Continuous functions on $R^l$ and Lipschitz and uniform continuity are covered next. There are also some applications to economic concepts. Convex analysis in $R^l$ is the topic of chapter 5 where you can read about convexity, the dual space of $R^l$, concave and convex functions, and the Hahn-Banach theorem. There are also many related to economics and optimization concepts such as the Kuhn-Tucker Theorem, Lagrange multipliers and fixed point theorems. Metric spaces is the subject of chapter 6. In chapter 7 the authors cover measure spaces and probability. There you can find the necessary background if you want to study stochastic calculus and option pricing. Measurable sets, probabilities, random variables, limit theorems, and convergence are just a small subset of the content. Chapter 8 is a little more technical and covers the $L^p(\Omega,\mathcal{F},P)$ and $l^p$ spaces, $p\in[1,\infty]$. There are applications to game theory and optimization. Chapters 9, 10 and 11 cover more advanced and technical concepts that a phd student in mathematical economics may find useful.

You can download the file using the link below

Thursday, July 14, 2011

Stochastic Calculus, Filtering, and Stochastic Control

Author: Ramon van Handel
Type: Study Notes, Lecture Notes, e-book
Level: MSc(Math. Fin), Ph.D.(Fin)

These lecture notes for the course "Stochastic Calculus and Stochastic Control" from Ramon van Handel are an excellent coverage of the topic. The notes are very intuitive and thus are appropriate for readers with major other than mathematics. The lecture notes provide the necessary background, probability theory, stochastic processes, martingales, the wiener process (Brownian motion). Stochastic integrals, Itō's lemma and stochastic differential equatios (SDEs) are covered in later chapters. After the necessary background, optimal control and filtering theory are covered next. Optimal stopping is discussed in the final chapter.

You can download Ramon van Handel's "Stochastic Calculus, Filtering, and Stochastic Control" using the following link

An Introduction to Stochastic Differential Equations

Author: Lawrence Evans
Type: Study Notes, Lecture Notes
Type: Advanced Undergraduate(Math), MSc(Math. Fin), Ph.D.(Fin)

These lecture notes for the course "An Introduction to Stochastic Differential Equations" from Lawrence Evans are a not-so-long introduction to stochastic differential equations (SDEs). The lecture notes start with "A crash course in basic probability theory". After the necessary background, Brownian motion and stochastic processes follow. Stochastic integrals and Itō's lemma are covered next with SDEs to follow. Finally, there are some applications such as optimal stopping and Options Pricing.

You can download Lawrence Evans' "An Introduction to Stochastic Differential Equations" using the link that follows