Free DownloadNew Models and Methods in Dynamic Portfolio Optimization
English | 2025 | ISBN: 9811280568 | 342 Pages | PDF (True) | 7 MB
This book presents some new models and methods in the context of dynamical portfolio optimization. It encapsulates the authors’ recent progress in their research on several interesting, featured issues of dynamic portfolio optimization problems with default contagion, tracking benchmark, consumption habit, and reinforcement learning.
Free DownloadStatistical Quantitative Methods in Finance: From Theory to Quantitative Portfolio Management by Samit Ahlawat
English | January 23, 2025 | ISBN: 8868809613 | 312 pages | MOBI | 62 Mb
Statistical quantitative methods are vital for financial valuation models and benchmarking machine learning models in finance.
Free DownloadSequential Monte Carlo Methods in Practice by Arnaud Doucet, Nando Freitas, Neil Gordon
English | PDF (True) | 2001 | 590 Pages | ISBN : 0387951466 | 51.1 MB
Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modelling, neural networks,optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practicioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris- XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning.
Free DownloadMathematical Methods in Dynamical Systems by S. Chakraverty, Subrat Kumar Jena
English | May 19, 2023 | ISBN: 1032356863 | 392 pages | MOBI | 13 Mb
The art of applying mathematics to real-world dynamical problems such as structural dynamics, fluid dynamics, wave dynamics, robot dynamics, etc. can be extremely challenging. Various aspects of mathematical modelling that may include deterministic or uncertain (fuzzy, interval, or stochastic) scenarios, along with integer or fractional order, are vital to understanding these dynamical systems. Mathematical Methods in Dynamical Systems offers problem-solving techniques and includes different analytical, semi-analytical, numerical, and machine intelligence methods for finding exact and/or approximate solutions of governing equations arising in dynamical systems. It provides a singular source of computationally efficient methods to investigate these systems and includes coverage of various industrial applications in a simple yet comprehensive way.
Free DownloadArtificial Intelligence Methods Applied to Urban Remote Sensing and GIS by Chang-Wook Lee English | PDF | 2021 | 167 Pages | ISBN : 3036516042 | 142.7 MB
Free DownloadArne Gennerich, "Optical Tweezers: Methods and Protocols "
English | ISBN: 1071622285 | 2022 | 771 pages | EPUB | 105 MB
This detailed volume explores a wide variety of techniques involving optical tweezers, a technology that has become increasingly more accessible to a broad range of researchers. Beginning with recent technical advances, the book continues by covering the application of optical tweezers to study DNA-protein interactions and DNA motors, protocols to perform protein (un)folding experiments, the application of optical tweezers to study actin- and microtubule-associated motor proteins, and well as protocols for investigating the function and mechanical properties of microtubules and intermediate filaments, and more. Written for the highly successful Methods in Molecular Biology series, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Free DownloadNonlinear Equations: Numerical Methods for Solving
English | 2018 | ASIN: B07FL7JR1J | 111 pages | PDF | 6.41 MB
Nonlinear equations are found throughout science and engineering across a wide variety of disciplines. These are a significant part of applied mathematics and much effort has been devoted to their study and solution. We will consider single and multi-variable problems as well as real and complex numbers. Various theories will be presented, but always with a focus on what works best-that is, the most practical approaches. In the literature of applied mathematics, these are known as robust algorithms.
