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|a DLC
|c DLC
|d BAKER
|d MUQ
|d NLGGC
|d UKM
|d BTCTA
|d YDXCP
|d SINLB
|d DEBSZ
|d IG#
|d DEBBG
|d ILU
|d TULIB
|d BDX
|d OCLCF
|d I8M
|d OCLCQ
|d OCLCA
|d OCLCQ
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|d DCHUA
|d OCLCO
|d CPS
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|a 332.64/5/0151828
|2 22
|
| 100 |
1 |
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|a McLeish, D. L.
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| 245 |
1 |
0 |
|a Monte Carlo simulation and finance /
|c Don L. McLeish.
|
| 260 |
|
|
|a Hoboken, NJ :
|b John Wiley & Sons,
|c 2005.
|
| 300 |
|
|
|a xi, 387 p. :
|b il. ;
|c 24 cm.
|
| 490 |
1 |
|
|a Wiley finance series
|
| 504 |
|
|
|a Incluye referencias bibliográficas (p. 375-381) e índice.
|
| 505 |
0 |
|
|a 1. Introduction -- 2. Some basic theory of finance: Introduction to pricing: single period models ; Multiperiod models ; Determining the process Bt ; Minimum variance portfolios and the Capital Asset Pricing Model ; Entropy: choosing a Q measure ; Models in continuous time ; Problems -- 3. Basic Monte Carlo methods: Uniform random number generation ; Apparent randomness of pseudo-random number generators ; Generating random numbers from non-uniform continuous distributions ; Generating random numbers from discrete distributions ; Random samples associated with Markov chains ; Simulating stochastic partial differential equations ; Problems -- 4. Variance reduction techniques: Introduction ; Variance reduction for one-dimensional Monte-Carlo integration ; Problems -- 5. Simulating the value of options: Asian options ; Pricing a call option under stochastic interest rates ; Simulating barrier and lookback options ; Survivorship bias ; Problems -- 6. Quasi-Monte Carlo multiple integration: Introduction ; Theory of low discrepancy sequences ; Examples of low discrepancy sequences ; Problems -- 7. Estimation and calibration: Introduction ; Finding a root ; Maximization of functions ; Maximum likelihood estimation ; Using historical data to estimate the parameters in diffusion models ; Estimating volatility ; Estimating Hedge ratios and correlation coefficients ; Problems -- 8. Sensitivity analysis, estimating derivatives and the Greeks: Estimating derivatives ; Infinitesimal perturbation analysis: pathwise differentiation ; Calibrating a model using simulations ; Problems -- 9. Other directions and conclusions: Alternative models ; ARCH and GARCH ; Conclusions.
|
| 520 |
|
|
|a ""Monte Carlo simulation and finance" provides financial engineers, researchers, and students with today's most detailed and application-based examination of Monte Carlo modeling techniques. It is filled with valuable insights and methodologies for formulating the problem at hand; setting specific objectives; choosing and implementing the most applicable model; determining parameters; running the simulation; and documenting results and conclusions in light of the simulation results. Monte Carlo Simulation and Finance is an essential reference for anyone, professional or academic, looking to design and implement accurate models for securities pricing and risk management. Further theoretical and mathematical information supporting the concepts discussed throughout this book also appear in an online appendix." --Descripción del editor.
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| 650 |
|
0 |
|a Financial futures.
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| 650 |
|
0 |
|a Monte Carlo method.
|
| 650 |
|
0 |
|a Options (Finance)
|
| 650 |
|
7 |
|a Futuros financieros.
|2 UDESA
|
| 650 |
|
7 |
|a Monte Carlo, Método de.
|2 UDESA
|
| 650 |
|
7 |
|a Opciones (Finanzas)
|2 UDESA
|
| 830 |
|
0 |
|a Wiley finance series
|