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Financial modeling in Python

Financial modeling in Python (8회 대출)

자료유형
단행본
개인저자
Fletcher, Shayne. Gardner, Christopher.
서명 / 저자사항
Financial modeling in Python / Shayne Fletcher and Christopher Gardner.
발행사항
Chichester ;   Hoboken, NJ :   John Wiley & Sons ,   2009.  
형태사항
viii, 236 p. : ill. ; 25 cm. + 1 CD-ROM (4 3/4 in.).
총서사항
Wiley finance series
ISBN
0470987847 9780470987841 (cloth : alk. paper)
서지주기
Includes bibliographical references and index.
일반주제명
Finance -- Mathematical models -- Computer programs. Python (Computer program language)
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010 ▼a 2009019336
020 ▼a 0470987847
020 ▼a 9780470987841 (cloth : alk. paper)
035 ▼a (KERIS)REF000015301439
040 ▼a DLC ▼c DLC ▼d 211009
050 0 0 ▼a HG106 ▼b .F59 2009
082 0 0 ▼a 332.0285/5133 ▼2 22
090 ▼a 332.0285 ▼b F615f
100 1 ▼a Fletcher, Shayne.
245 1 0 ▼a Financial modeling in Python / ▼c Shayne Fletcher and Christopher Gardner.
260 ▼a Chichester ; ▼a Hoboken, NJ : ▼b John Wiley & Sons , ▼c 2009.
300 ▼a viii, 236 p. : ▼b ill. ; ▼c 25 cm. + ▼e 1 CD-ROM (4 3/4 in.).
490 1 ▼a Wiley finance series
504 ▼a Includes bibliographical references and index.
650 0 ▼a Finance ▼x Mathematical models ▼x Computer programs.
650 0 ▼a Python (Computer program language)
700 1 ▼a Gardner, Christopher.
830 0 ▼a Wiley finance series.
945 ▼a KINS

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
No. 1 소장처 과학도서관/Sci-Info(2층서고)/ 청구기호 332.0285 F615f 등록번호 121186151 도서상태 대출가능 반납예정일 예약 서비스 B M

컨텐츠정보

목차

1 Welcome to Python.

1.1 Why Python?

1.2 Common misconceptions about Python.

1.3 Roadmap for this book.

2 The PPF Package.

2.1 PPF topology.

2.2 Unit testing.

2.3 Building and installing PPF.

3 Extending Python from C++.

3.1 Boost.Date Time types.

3.2 Boost.MultiArray and special functions.

3.3 NumPy arrays.

4 Basic Mathematical Tools.

4.1 Random number generation.

4.2 N(.)

4.3 Interpolation.

4.4 Root finding.

4.5 Linear algebra.

4.6 Generalised linear least squares.

4.7 Quadratic and cubic roots.

4.8 Integration.

5 Market: Curves and Surfaces.

5.1 Curves.

5.2 Surfaces.

5.3 Environment.

6 Data Model.

6.1 Observables.

6.2 Flows.

6.3 Adjuvants.

6.4 Legs.

6.5 Exercises.

6.6 Trades.

6.7 Trade utilities.

7 Timeline: Events and Controller.

7.1 Events.

7.2 Timeline.

7.3 Controller.

8 The Hull–White Model.

8.1 A component-based design.

8.2 The model and model factories.

8.3 Concluding remarks.

9 Pricing using Numerical Methods.

9.1 A lattice pricing framework.

9.2 A Monte-Carlo pricing framework.

9.3 Concluding remarks.

10 Pricing Financial Structures in Hull–White.

10.1 Pricing a Bermudan.

10.2 Pricing a TARN.

10.3 Concluding remarks.

11 Hybrid Python/C++ Pricing Systems.

11.1 nth imm of year revisited.

11.2 Exercising nth imm of year from C++.

12 Python Excel Integration.

12.1 Black–scholes COM server.

12.2 Numerical pricing with PPF in Excel.

Appendices.

A Python.

A.1 Python interpreter modes.

A.2 Basic Python.

A.3 Conclusion.

B Boost.Python.

B.1 Hello world.

B.2 Classes, constructors and methods.

B.3 Inheritance.

B.4 Python operators.

B.5 Functions.

B.6 Enums.

B.7 Embedding.

B.8 Conclusion.

C Hull–White Model Mathematics.

D Pickup Value Regression.

Bibliography.

Index.


정보제공 : Aladin

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