TRA CỨU
  • Sách
  • 003.3 ARR
    Computational Finance :
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
Khoa Khoa Quản trị kinh doanh và du lịch
Chuyên ngành Công nghệ tài chính (Fintech)
Môn học Khai thác và phân tích dữ liệu tài chính
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0410 |aeng
044 |afr
08204|a003.3|bARR
1001 |aArratia, Argimiro
24510|aComputational Finance :|bAn Introductory Course with R / |cArgimiro Arratia
260 |aParis : |bAtlantis Press, |c2014
300 |aX, 301 p. : |bill. ; |c29 cm.
520 |aThe 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.
65000|aMacroeconomics
65000|aComputer simulation
65017|aMáy tính|xPhân tích dữ liệu
6530 |aTài chính
6530 |aMáy tính
6530 |aPhân tích dữ liệu
690 |aKhoa Quản trị kinh doanh và du lịch
691 |aCông nghệ tài chính (Fintech)
692 |aKhai thác và phân tích dữ liệu tài chính
693 |aGiáo trình
852|a100|bTK_Tài liệu môn học-MH|c516029|j(2): 000140948-9
8561|uhttp://lib.hanu.vn/kiposdata1/bookcover/tailieumonhoc/000140948thumbimage.jpg
890|a2|b0|c0|d0
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1 000140949 TK_Tài liệu môn học-MH MH FT 003.3 ARR Tài liệu Môn học 1 Tài liệu chỉ đọc tại Thư viện ebook
2 000140948 TK_Tài liệu môn học-MH MH FT 003.3 ARR Tài liệu Môn học 2 Tài liệu chỉ đọc tại Thư viện ebook

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