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Links to Free Computer, Mathematics, Technical Books all over the World



Data Science for Economics and Finance: Methodologies & Apps
This book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance.

Mathematics of Economics and Business (Frank Werner, et al.)
For all students who wish to understand current economic and business literature, knowledge of mathematical methods has become a prerequisite. Clear and concise, with precise definitions and theorems, this book covers all the major topics required.

Financial Mathematics: Concepts and Computational Methods
This text serves as a primer in financial mathematics with a focus on conceptual understanding of models and problem solving. It includes the mathematical background needed for risk management, such as probability theory, optimization, and the like.

Financial Mathematics (C.H. Richardson, et al.)
Covering the theories of interest rates, with applications to the evaluation of cash flows, the pricing of fixed income securities and the management of bonds, this textbook also contains numerous examples and exercises of financial calculation.

Financial Numerical Recipes in C++: Applications in Finance
This book provides a good deal of useful examples and algorithms for people working within the field of finance, in C++. All the routines have been made to confirm to the new ISO/ANSI C++ standard, using namespaces and the standard template library.

Mathematical Methods for Economic Theory (Martin J. Osborne)
This book covers the basic mathematical tools used in economic theory. It emphasizes techniques rather than abstract theory. However, the conditions under which each technique is applicable are stated precisely.

Using Python for Introductory Econometrics (Florian Heiss, et al.)
This book introduces the popular, powerful and free programming language and software package Python, focuses on implementation of standard tools and methods used in econometrics.

Python for Econometrics, Statistics, and Data Analysis
This book is designed for someone new to statistical computing wishing to develop a set of skills necessary to perform original research for econometrics, statistics or general numerical analysis using Python.

Python Programming for Economics and Finance
Looking to enhance your skills in Economics and Finance? Dive into Python programming! With libraries like Pandas, NumPy, and Matplotlib, you can analyze data, build models, and visualize trends like never before.

Using R for Introductory Econometrics (Florian Heiss)
This book introduces the popular, powerful and free programming language and software package R, focuses on implementation of standard tools and methods used in econometrics.

Panel Data Econometrics with R (Yves Croissant, et al.)
This book provides a tutorial for using R in the field of Panel Data econometrics. Illustrated throughout with examples, it presents classic methodology and applications including error component models, spatial panels and dynamic models.

Introduction to Python for Finance (Trenton McKinney)
Unlock the full potential of Python in the world of finance. This comprehensive guide is your gateway to mastering the powerful capabilities of Python to revolutionize financial analysis and investment strategies.

Financial Machine Learning (Bryan T. Kelly, et al.)
This book is designed for both financial economists interested in grasping machine learning tools, as well as for statisticians and machine learners seeking interesting financial contexts where advanced methods may be deployed.

Games, Fixed Points and Mathematical Economics (C. Ewald)
This book gives the reader access to the mathematical techniques involved and goes on to apply fixed point theorems to proving the existence of equilibria for economics and for cooperative and noncooperative games.

Statistical Foundations of Actuarial Learning and its Applications
This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future.

A Basic Course in the Theory of Interest and Derivatives Markets
This book is designed for an introductory course in the theory of interest and annuity. Each section contains the embedded examples with answer keys. It is suitable for a junior level course in the mathematics of finance.

Innovations in Derivatives Markets (Kathrin Glau, et al)
Pricing and hedging in fixedincome markets and multicurve interestrate modeling. Recent developments concerning contingent convertible bonds, the measuring of basis spreads, and the modeling of implied correlations.

Numerical Methods for Finance (Maciej J. Capinski)
This book explores new and relevant numerical methods in C++ for the solution of practical problems in finance. It is one of the few books entirely devoted to numerical methods as applied to the financial field.

Blockchain and Crypto Currency: Marketplace for Crypto Data
This book contributes to the creation of a cyber ecosystem supported by Blockchain technology in which technology and people can coexist in harmony. The decentralization of the recording process is expected to significantly economize the cost of transactions.

Global Fintech: Financial Innovation in the Connected World
The book offers accessible explanations of Blockchain and Distributed Ledger technology and explores big data analytics. It considers, among other things, open banking, platformbased strategies for banks, and digital financial services.

Math for Trades: Volume 1 (Chad Flinn, et al.)
This volume represents the building blocks for math training. The goal of this volume is to get students prepared for the more advanced topics that they will encounter during their trades math education.

Math for Trades: Volume 2 (Chad Flinn, et al.)
This volume continues where the Volume 1 left off. Volume 2 increases the challenge with topics such as converting units and working with equations, perimeter, area, and volume. Once again the material is presented from a trades perspective.

Stochastic Differential Equations: Models and Numerics
The goal of this book is to give useful understanding for solving problems formulated by stochastic differential equations models in science, engineering and mathematical finance. Typically, these problems require numerical methods to obtain a solution.

Financial Accounting (University of Minnesota)
This book is intended for an undergraduate or MBA level Financial Accounting course. It covers the standard topics in a standard sequence, utilizing the Socratic method of asking and answering questions.

Applied Quantitative Finance: Theory and Computational Tools
This book presents solutions, theoretical developments and method proliferation for many practical problems in quantitative finance. The combination of practice and theory supported by computational tools is reflected in the selection of topics.

Stochastic Calculus and Finance (Steven E. Shreve)
The book gives both precise statements of results, plausibility arguments, and even some proofs, but more importantly intuitive explanations developed and refine through classroom experience with this material are provided.

Mathematical Models in Portfolio Analysis (Farida Kachapova)
This book explains portfolio modelling in financial mathematics as a consistent mathematical theory with all steps justified. The topics include meanvariance portfolio analysis and capital market theory. The book contains many examples with solutions.

Introduction to Mathematical Finance (Kaisa Taipale)
This textbook on the basics of option pricing is accessible to readers with limited mathematical training. It is for both professional traders and undergraduates studying the basics of finance. Assuming no prior knowledge of probability.

Price Theory: An Intermediate Text (David D. Friedman)
This book was designed to develop the reader's understanding of the economic way of thinking by first providing verbal, intuitive explanations of concepts, then illustrating them with graphs and/or calculus..

Mastering Bitcoin: Programming the Open Blockchain
This book is your guide through the seemingly complex world of Bitcoin, providing the knowledge you need to participate in the internet of money. It will help you engineer money. You're about to unlock the API to a new economy. This book is your key.

Bitcoin and Cryptocurrency Technologies (Arvind Narayanan, ...)
It provides a comprehensive introduction to the revolutionary yet often misunderstood new technologies of digital currency. This authoritative and selfcontained book tells you everything you need to know about the new global money for the Internet age.

Portfolio Theory and Financial Analyses (Robert Alan Hill)
This book connects each of the major categories of techniques and practices to the unifying and seminal conceptual developments of modern portfolio theory, whether these involve measuring the return on a portfolio, analysing portfolio risk or evaluating the quality of the portfolio management process.

Financial Applications using Excel Addin in C/C++ (Steve Dalton)
This book is a mustbuy book for any serious Excel developer, the only complete howto guide and reference book for the creation of high performance addins for Excel in C and C++ for users in the finance industry.

Statistics Using Excel® Succinctly (Charles Zaiontz)
This book illustrates the capabilities of Microsoft Excel to teach applied statistics effectively. It is a stepbystep exercisedriven guide for students and practitioners who need to master Excel to solve practical statistical problems

CFI Excel® Book for Finance (CFI Education)
This book walks through all the most important and useful Excel functionalities that will advance your career in financial services. From logical functions to calculating the yield of a bond, it provides you with numerous examples and key shortcuts!

Stochastic Processes for Finance (Patrick Roger)
It describes the most important stochastic processes used in finance in a pedagogical way, especially Markov chains, Brownian motion and martingales. It also shows how mathematical tools like filtrations, Ito's lemma or Girsanov theorem should be understood in the framework of financial models.

Python for Econometrics, Statistics and Data Analysis
This book provides an introduction to Python for a beginning programmer. They may also be useful for an experienced Python programmer interested in using NumPy, SciPy, and matplotlib for numerical and statistical analaysis.

Probability for Finance (Patrick Roger)
This book provides technical support for students in finance. It reviews the main probabilistic tools used in financial models in a pedagogical way, starting from simple concepts like random variables and tribes and going to more sophisticated ones like conditional expectations and limit theorems.

From Algorithms to ZScores: Probabilistic and Statistical Modeling
This is a textbook for a course in mathematical probability and statistics for computer science students.

Basic Data Analysis and More  A Guided Tour Using Python
In this book, a selection of frequently required statistical tools will be introduced and illustrated.

A Beautiful Math: John Nash, Game Theory, and a Code of Nature
At the time of Nash's early work, game theory was briefly popular among some mathematicians and Cold War analysts.

The Pure Logic Of Choice (Richard D. Fuerle)
This book presents a general theory of economics based on free will. The laws of economics are deduced from the premise that people have free will and can change physical things in an attempt to achieve their chosen values.

Accounting Succinctly: A Developer's Guide (Joe Booth)
This book is a developer's guide to basic accounting. Written with business app development in mind, it discusses some of the most common accounting processes, including assets, multiple accounts, journaling, posting, inventory, and payroll.

DevOps for Finance (Jim Bird)
Aims to debunk that myth by showing how the finance industry can benefit from DevOps practices and perform a greater degree of automation by implementing DevOps properly. It explains DevOps benefits that are far more important for the financial services industry.

Mathematics for Finance: An Introduction to Financial Engineering
This book is an excellent introduction to Mathematical Finance. Armed with a knowledge of basic calculus and probability a student can use this book to learn about derivatives, interest rates and their term structure and portfolio management.

Statistical Tools for Finance and Insurance (Pavel Cizek, et al)
Presents readytouse solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance, offers a unique combination of topics from which every market analyst and risk manager will benefit.

Statistics of Financial Markets: An Introduction (Jürgen Franke)
The focus is both on fundamentals of mathematical finance and financial time series analysis and on applications to given problems of financial markets.

Strategic Foundations of General Equilibrium: Bargaining Games
Making use of insights from game theory, search theory and bargaining theory, the author develops a model to explain what actually goes on in markets and how a competitive general equilibrium is achieved.

Inventory Analytics: A Practicable, PythonDriven Approach
This book provides a comprehensive and accessible introduction to the theory and practice of Inventory Control – a significant research area central to supply chain planning. It adopts a practicable, Pythondriven approach to illustrating theories and concepts.
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