Showing posts with label Mathematical. Show all posts
Showing posts with label Mathematical. Show all posts

Tuesday, June 21, 2016

Coursera - Mathematical Methods for Quantitative Finance by Dr. Kjell Konis (2016)




Coursera – Mathematical Methods for Quantitative Finance
WEBRip | English | MP4 | 960 x 540 | AVC ~63.8 kbps | 25 fps
AAC | 128 Kbps | 48.0 KHz | 2 channels | ~8 hours | 5.98 GB
Genre: eLearning Video / Maths, Economics & Finance


Mathematical Methods for Quantitative Finance covers topics from calculus and linear algebra that are fundamental for the study of mathematical finance. Students successfully completing this course will be mathematically well prepared to study quantitative finance at the graduate level.


The Mathematical Methods for Quantitative Finance course reviews the mathematical methods fundamental for the study of quantitative and computational finance. The areas of focus include calculus and multivariable calculus, constrained and unconstrained optimization, and linear algebra.


Topics covered include the following:

Functions and inverse functions


Limits, derivatives, partial derivatives, and chain rule


Integrals and multiple integrals, changing the order of differentiation and integration


Taylor series approximations


Newton’s method


Lagrange multiplier method


Vector and matrix arithmetic, determinants, eigenvalue-eigenvector decomposition, singular value decomposition


Numerical methods for optimization


Course goal:

Upon completion of the course students will know the fundamental mathematical concepts needed to effectively study quantitative finance areas such as fixed income, options and derivatives, portfolio optimization, and quantitative risk management.


Course Objectives: Upon completion of the course students will:

Understand the concept of a limit, differentiation, and integration;


Be able to compute partial derivatives and multiple integrals;


Understand the utility of matrix decompositions;


Be able to use Lagrange multipliers to solve constrained optimization problems; and


Apply the above methods to problems arising in finance.


also You can watch my other last: Coursera-posts



General
Complete name : Mathematical Methods for Quantitative Finance 8.1 W7.1.1 – Optimal Investment Portfolios (1732).mp4
Format : MPEG-4
Format profile : Base Media
Codec ID : isom
File size : 24.8 MiB
Duration : 17mn 32s
Overall bit rate mode : Variable
Overall bit rate : 198 Kbps
Movie name : MMfQF_W7_P1_Kjell_OptimalInvestmentPortfolios_FINAL
Composer : Jon Keib
Writing application : Lavf52.99.1
desc : This video is about MMfQF_W7_P1_Kjell_OptimalInvestmentPortfolios


Video
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Duration : 17mn 32s
Bit rate : 63.8 Kbps
Width : 960 pixels
Height : 540 pixels
Display aspect ratio : 16:9
Frame rate mode : Constant
Frame rate : 25.000 fps
Color space : YUV
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Scan type : Progressive
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Language : English


Audio
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Duration : 17mn 32s
Bit rate mode : Variable
Bit rate : 128 Kbps
Channel(s) : 2 channels
Channel positions : Front: L R
Sampling rate : 48.0 KHz
Compression mode : Lossy
Delay relative to video : -2ms
Stream size : 16.0 MiB (65%)
Language : English




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Sunday, June 19, 2016

Mathematical Theory of Nonequilibrium Steady States: On the Frontier of Probability and Dynamical Systems




Min Qian, Da-Quan Jiang, “Mathematical Theory of Nonequilibrium Steady States: On the Frontier of Probability and Dynamical Systems”
2004 | ISBN-10: 3540206116 | 296 pages | PDF | 1 MB


This volume provides a systematic mathematical exposition of the conceptual problems of nonequilibrium statistical physics, such as entropy production, irreversibility, and ordered phenomena. Markov chains, diffusion processes, and hyperbolic dynamical systems are used as mathematical models of physical systems. A measure-theoretic definition of entropy production rate and its formulae in various cases are given. It vanishes if and only if the stationary system is reversible and in equilibrium. Moreover, in the cases of Markov chains and diffusion processes on manifolds, it can be expressed in terms of circulations on directed cycles. Regarding entropy production fluctuations, the Gallavotti-Cohen fluctuation theorem is rigorously proved.



Tuesday, May 24, 2016

Mathematical Techniques in GIS (2nd edition) (Repost)




Mathematical Techniques in GIS (2nd edition) By Peter Dale
2014 | 359 Pages | ISBN: 146659554X | PDF | 8 MB



The second edition of a bestseller, Mathematical Techniques in GIS demystifies the mathematics used in the manipulation of spatially related data. The author takes a step-by-step approach through the basics of arithmetic, algebra, geometry, trigonometry and calculus that underpin the management of such data. He then explores the use of matrices, determinants and vectors in the handling of geographic information so that the data may be analyzed and displayed in two-dimensional form either in the visualization of the terrain or as map projections.
See What’s New in the Second Edition:
Summaries at the end of each chapter
Worked examples of techniques described
Additional material on matrices and vectors
Further material on map projections
New material on spatial correlation
A new section on global positioning systems
Written for those who need to make use geographic information systems but have a limited mathematical background, this book introduces the basic statistical techniques commonly used in geographic information systems and explains best-fit solutions and the mathematics behind satellite positioning. By understanding the mathematics behind the gathering, processing, and display of information, you can better advise others on the integrity of results, the quality of the information, and the safety of using it.