Stochastic Process Finance

Fertility Decline and Background Independence: Applying a Reaction-Diffusion System as a Stochastic Process

Fertility Decline and Background Independence: Applying a Reaction-Diffusion System as a Stochastic Process By Shuichirou Ike
2015 | 120 Pages | ISBN: 4431551506 | PDF | 3 MB
Real Options Valuation: The Importance of Stochastic Process Choice in Commodity Price Modelling

Max Schöne, "Real Options Valuation: The Importance of Stochastic Process Choice in Commodity Price Modelling"
2014 | ISBN-10: 3658074922 | 120 pages | PDF | 2 MB

Bayesian Analysis of Stochastic Process Models  

Posted by fdts at Oct. 29, 2014
Bayesian Analysis of Stochastic Process Models

Bayesian Analysis of Stochastic Process Models
by David Insua, Fabrizio Ruggeri, Mike Wiper
English | 2012 | ISBN: 0470744537 | 332 pages | PDF | 6.1 MB
Stochastic Process Variation in Deep-Submicron CMOS: Circuits and Algorithms

Stochastic Process Variation in Deep-Submicron CMOS: Circuits and Algorithms by Amir Zjajo
English | 2013 | ISBN: 9400777809 | 200 pages | PDF | 4,9 MB

One of the most notable features of nanometer scale CMOS technology is the increasing magnitude of variability of the key device parameters affecting performance of integrated circuits.

Stochastic Analysis for Finance with Simulations  eBooks & eLearning

Posted by Underaglassmoon at July 20, 2016
Stochastic Analysis for Finance with Simulations

Stochastic Analysis for Finance with Simulations
Springer | Mathematics | August 14, 2016 | ISBN-10: 3319255878 | 657 pages | pdf | 11.96 mb

Authors: Choe, Geon Ho
Presents the mathematical methods required for pricing financial derivatives
Encourages hands-on experience and builds intuition by explaining theoretical concepts with computer simulations
Covers mathematical prerequisites, including measure theory, ordinary differential equations, and partial differential equations

Probability and Statistics for Finance (Repost)  

Posted by manamba13 at Feb. 26, 2015
Probability and Statistics for Finance (Repost)

Probability and Statistics for Finance by Svetlozar T. Rachev
English | 2010 | ISBN: 0470400935 | 654 Pages | PDF | 8 MB

A comprehensive look at how probability and statistics is applied to the investment process Finance has become increasingly more quantitative, drawing on techniques in probability
A Practical Guide To Quantitative Finance Interviews (repost)

A Practical Guide To Quantitative Finance Interviews by Xinfeng Zhou
CreateSpace Independent Publishing Platform; 14th Edition | April 9, 2008 | English | ISBN: 1438236662 | 210 pages | PDF | 12 MB

This book will prepare you for quantitative finance interviews by helping you zero in on the key concepts that are frequently tested in such interviews. In this book we analyze solutions to more than 200 real interview problems and provide valuable insights into how to ace quantitative interviews. The book covers a variety of topics that you are likely to encounter in quantitative interviews: brain teasers, calculus, linear algebra, probability, stochastic processes and stochastic calculus, finance and programming.

Stochastic Modelling for Systems Biology (repost)  

Posted by interes at Nov. 17, 2013
Stochastic Modelling for Systems Biology (repost)

Darren J. Wilkinson, "Stochastic Modelling for Systems Biology"
English | 2006 | ISBN: 1584885408 | 280 pages | PDF | 28,2 MB

Although stochastic kinetic models are increasingly accepted as the best way to represent and simulate genetic and biochemical networks, most researchers in the field have limited knowledge of stochastic process theory.
The Elements of Stochastic Processes with Applications to the Natural Sciences (repost)

Norman T. J. Bailey, "The Elements of Stochastic Processes with Applications to the Natural Sciences"
English | 2000 | ISBN: 0471041653 | 249 pages | PDF | 8 MB

Develops an introductory and relatively simple account of the theory and application of the evolutionary type of stochastic process. Professor Bailey adopts the heuristic approach of applied mathematics and develops both theoretical principles and applied techniques simultaneously.
Optimization in Economics and Finance: Some Advances in Non-Linear, Dynamic, Multi-Criteria and Stochastic Models

Bruce D. Craven, Sardar M. N. Islam, «Optimization in Economics and Finance: Some Advances in Non-Linear, Dynamic, Multi-Criteria and Stochastic Models»
Springer | ISBN 0387242791 | August 2005 | PDF | 176 Pages | 3,50 Mb

Many optimization questions arise in economics and finance; an important example of this is the society's choice of the optimum state of the economy (the social choice problem). Optimization in Economics and Finance extends and improves the usual optimization techniques, in a form that may be adopted for modeling social choice problems. Problems discussed include: when is an optimum reached; when is it unique; relaxation of the conventional convex (or concave) assumptions on an economic model; associated mathematical concepts such as invex and quasimax; multiobjective optimal control models; and related computational methods and programs. These techniques are applied to economic growth models (including small stochastic perturbations), finance and financial investment models (and the interaction between financial and production variables), modeling sustainability over long time horizons, boundary (transversality) conditions, and models with several conflicting objectives.