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Computational Finance

Computational Finance : An Introductory Course with R

 Arratia, Argimiro
 Atlantis Press, 2014 ISBN: 9789462390690
 Paris : X, 301 p. : ill. ; 29 cm. English
MacroeconomicsComputer simulationMáy tínhTài chínhPhân tích dữ liệuKhoa Quản trị kinh doanh và du lịch
Mô tả biểu ghi
ID:69671
DDC 003.3
Tác giả CN Arratia, Argimiro
Nhan đề Computational Finance : An Introductory Course with R / Argimiro Arratia
Thông tin xuất bản Paris : Atlantis Press, 2014
Mô tả vật lý X, 301 p. : ill. ; 29 cm.
Tóm tắt The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.
Thuật ngữ chủ đề Macroeconomics
Thuật ngữ chủ đề Computer simulation
Thuật ngữ chủ đề Máy tính-Phân tích dữ liệu
Từ khóa tự do Tài chính
Từ khóa tự do Máy tính
Từ khóa tự do Phân tích dữ liệu
Môn học Khoa Quản trị kinh doanh và du lịch
Địa chỉ 100TK_Tài liệu môn học-MH516029(2): 000140948-9
Tệp tin điện tử http://lib.hanu.vn/kiposdata1/bookcover/tailieumonhoc/000140948thumbimage.jpg
MARC
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260[ ] |a Paris : |b Atlantis Press, |c 2014
300[ ] |a X, 301 p. : |b ill. ; |c 29 cm.
520[ ] |a The book covers a wide range of topics, yet essential, in Computational Finance (CF), understood as a mix of Finance, Computational Statistics, and Mathematics of Finance. In that regard it is unique in its kind, for it touches upon the basic principles of all three main components of CF, with hands-on examples for programming models in R. Thus, the first chapter gives an introduction to the Principles of Corporate Finance: the markets of stock and options, valuation and economic theory, framed within Computation and Information Theory (e.g. the famous Efficient Market Hypothesis is stated in terms of computational complexity, a new perspective). Chapters 2 and 3 give the necessary tools of Statistics for analyzing financial time series, it also goes in depth into the concepts of correlation, causality and clustering. Chapters 4 and 5 review the most important discrete and continuous models for financial time series. Each model is provided with an example program in R. Chapter 6 covers the essentials of Technical Analysis (TA) and Fundamental Analysis. This chapter is suitable for people outside academics and into the world of financial investments, as a primer in the methods of charting and analysis of value for stocks, as it is done in the financial industry. Moreover, a mathematical foundation to the seemly ad-hoc methods of TA is given, and this is new in a presentation of TA. Chapter 7 reviews the most important heuristics for optimization: simulated annealing, genetic programming, and ant colonies (swarm intelligence) which is material to feed the computer savvy readers. Chapter 8 gives the basic principles of portfolio management, through the mean-variance model, and optimization under different constraints which is a topic of current research in computation, due to its complexity. One important aspect of this chapter is that it teaches how to use the powerful tools for portfolio analysis from the RMetrics R-package. Chapter 9 is a natural continuation of chapter 8 into the new area of research of online portfolio selection. The basic model of the universal portfolio of Cover and approximate methods to compute are also described.
650[0 0] |a Macroeconomics
650[0 0] |a Computer simulation
650[1 7] |a Máy tính |x Phân tích dữ liệu
653[0 ] |a Tài chính
653[0 ] |a Máy tính
653[0 ] |a Phân tích dữ liệu
690[ ] |a Khoa Quản trị kinh doanh và du lịch
691[ ] |a Công nghệ tài chính (Fintech)
692[ ] |a Khai thác và phân tích dữ liệu tài chính
693[ ] |a Giáo trình
852[ ] |a 100 |b TK_Tài liệu môn học-MH |c 516029 |j (2): 000140948-9
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