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$ d5 f' {! s/ j i/ j An insightful book on financial modeling and Monte Carlo simulation with the No.1 software name in the business, Crystal Ball, and its lead educator.
# c# C1 z. Y5 C( p% T8 w 内容简介% ~2 y3 U, |/ f8 N
Need to apply risk analysis, financial modeling, and simulation to your work? Answer: Use Crystal Ball to make better decisions.Financial Modeling with Crystal Ball provides tools and techniques you to need know to perform spreadsheet simulation, and answers the essential question of why risk analysis is vital to the decision-making process, whatever the problem you are facing in finance and investment.After reviewing the basics, this book covers how to define and refine probability distributions in financial modeling, and exhaustively reviews the concepts behind the simulation modeling process.It discusses simulation controls and analysis of simulation results.Exercises models help you apply risk analysis to such areas as derivative pricing, cost estimation, portfolio allocation and optimization, design analysis, and cash flow analysis.The tools and techniques reviewed are designed to make anyone expert in financial modeling and simulation.They will help you immediately develop essential skills in the areas of areas of valuation, pricing, hedging, trading, risk management, project evaluation and portfolio management.) C+ H/ L6 ^3 }4 n% Q! W
作者简介, p9 {+ c0 \& X3 k+ e% W
Dr.John Charnes (Lawrence, KS) is Director of the Finance, Economics, and Decision Sciences Area in the University of Kansas School of Business.His specialty is the application of computer simulation and statistical methods for identifying and solving business problems, and his most current research involves using simulation for option pricing and hedging with derivatives to comply with Financial Accounting Standard (FAS) 133.Prof.Charnes has taught courses in computer simulation, statistics, operations, quality management, and finance in the business schools of the University of Miami (Florida), University of Washington (Seattle), University of Minnesota (Minneapolis), and Hamline University (St.Paul).He has published papers on simulation, statistics, and other topics in Financial Analysts Journal, The American Statistician, Management Science, Decision Sciences, Computers and Operation Research, Journal of the Operational Research Society, Journal of Business Logistics, and Proceedings of the Winter Simulation Conference.Prof.Charnes has performed research, consulting and executive education for more than 50 corporations and other organizations.Prof.Charnes holds the Ph. MBA, and Bachelor of Civil Engineering degrees from the University of Minnesota.Crystal Ball is a full suite of Microsoft Excel-based applications for Monte Carlo simulation, time-series forecasting, optimization and real options analysis.Crystal Ball applications transform basic spreadsheets into dynamic models that solve almost any problem involving uncertainty, variability and risk.7 R6 c5 U* h1 z* y9 _
目录
6 x" I0 L J. c1 [( x9 O2 ] Cover+ F. X3 {5 V* R2 V/ j2 r! U4 p1 c
Contents" @4 }3 Q- m% T1 m, |7 Q
Title
1 J, C, ]* \9 E6 p/ { Copyright. n- Q9 x0 Z" L) r8 v; W5 \5 g
Dedication
) U7 V* D$ r5 z! }+ u' w1 h" Y Preface
. o6 k' T% h r! _3 k+ _ Acknowledgments
! g2 e, W( e/ x6 h9 j# e% S About the Author
* s. v4 z% X6 l8 [; q Chapter 1: Introduction |3 _; ^, x& \) u, e# w, c
Financial Modeling# u6 K+ U6 [" p
Risk Analysis
8 W5 Q: I/ i7 q* I Monte Carlo Simulation
8 { X4 n+ l1 l$ O, U; m Risk Management
' F. L2 Q- A @9 b Benefits and Limitations of Using Crystal Ball3 m/ |& f0 ^& Z
Chapter 2: Analyzing Crystal Ball Forecasts/ I7 b& X V3 e+ [: s0 |' \' [
Simulating A 50 - 50 Portfolio
/ W& z2 h% g& r( `: w Varying the Allocations; S z1 a1 ` t- D$ q X
Presenting the Results
7 _: I3 y6 |4 e! T+ N/ @ Chapter 3: Building a Crystal Ball Model1 g6 ?; c# _; X7 \% O; I3 W
Simulation Modeling Process
: S. T) N8 K, _7 X( V n4 k2 B' p Defining Crystal Ball Assumptions
: c$ O; ]/ w7 L5 _9 Z Running Crystal Ball Q, K; f* M1 V4 T4 j6 p. N
Sources of Error7 q( e- ]( F5 O2 j- C1 b
Controlling Model Error% A$ i. H1 u( t* m+ a. d
Chapter 4: Selecting Crystal Ball Assumptions
! D5 O' f& _" ~4 B/ J# V Crystal Ball's Basic Distributions
A7 B! u* a& O" s( L$ }! f, q/ R; a Using Historical Data to Choose Distributions* w! y6 W* T6 ]7 @1 G- A+ `
Specifying Correlations, v$ R! C3 c, L, h8 D b
Chapter 5: Using Decision Variables
. l2 p' d8 w* k: i5 z0 Y Defining Decision Variables# D' q3 U2 ?+ i3 T! J" H. J! N
Decision Table with One Decision Variable2 k( U c( P- u# [: [3 ^
Decision Table with Two Decision Variables
+ }+ S/ `+ [4 H+ u$ y Using OptQuest
+ m* B; o7 b9 ]" ?; M- n7 W Chapter 6: Selecting Run Preferences$ T* v( H6 d G R$ ]/ n( J
Trials8 K: t) b+ D2 W$ S* C# E/ ]- D
Sampling
9 Q5 g+ W& X/ t! a( f5 b' | Speed
# {* v, S( Y# m3 e& P8 S6 g Options
% h8 C! e6 d" H0 r$ a Statistics- i6 A, t2 @+ f. l0 @# D6 ^; B
Chapter 7: Net Present Value and Internal Rate of Return
) Y4 {& y, W: e" I- {1 |6 U, @ Deterministic NPV and IRR& j: p1 ?: u2 m" ?/ F
Simulating NPV and IRR& n. z- f4 h' @/ S; N3 ~
Capital Budgeting
9 A" ~! G& n5 D# n x Customer Net Present Value
6 q3 X2 b5 Q( E' e Chapter 8: Modeling Financial Statements1 r3 Z, o; E! I. N5 |+ C
Deterministic Model) m/ `; x* q2 m$ K
Tornado Chart and Sensitivity Analysis6 Y# o: e! ]% a
Crystal Ball Sensitivity Chart
" \0 F5 k; z* k9 b$ }# i Conclusion u: l# r+ w# V2 E: ~
Chapter 9: Portfolio Models
2 C: V0 G* Q5 O5 J, M/ }; X Single-Period Crystal Ball Model+ p" n" s) K6 h# S; h- ?. V
Single-Period Analytical Solution" H" \- }, i" B- [7 P Y* G
Multiperiod Crystal Ball Model
+ b p, @+ W0 V! v6 G1 k5 u Chapter 10: Value at Risk
0 O4 Y/ I0 Z$ Y VaR
8 m. b2 V: L/ G) Y Shortcomings of VaR
0 H, l$ t. J) z5 b; m2 [0 h! ^+ d CVaR
+ F3 j7 d- b9 N, t+ |4 I! A Chapter 11: Simulating Financial Time Series
3 f; x2 t. }+ g) u% b White Noise
' D5 u5 ]- _2 F: U Random Walk7 R$ R: b7 D% P' ~" ~* t A# t
Autocorrelation' Z1 u* {" w7 j. `8 e Z# O0 O/ y
Additive Random Walk with Drift9 F2 P) r* N) _: L, V3 f
Multiplicative Random Walk Model$ J: b8 m4 }( r( h# P8 a
Geometric Brownian Motion Model
( A0 \; _/ e) v& d7 G" G6 y3 {8 a+ e Mean-Reverting Model
' I- y, S+ p2 l* Z' U# U Chapter 12: Financial Options
& C6 ~/ {' n( N4 F: ~# l Types of Options
* v$ H: F% I1 \1 T, m7 A Risk-Neutral Pricing and the Black-Scholes Model2 _$ K3 H" t- i9 C. b
Portfolio Insurance
2 h4 J3 Y8 U }0 o+ O$ | American Option Pricing) B0 m& W+ M( o( G$ s- @
Exotic Option Pricing
4 _# f1 `' a! A0 | N Bull Spread
8 b2 ]9 b# w5 K! R& j8 [/ | Principal-Protected Instrument/ Z- z2 g# ~+ Q- C. ^' n8 K
Chapter 13: Real Options4 |! M) a6 Q' R9 @5 A* r
Financial Options and Real Options: g' M. @0 ^. I# o! ]
Applications of ROA4 }) m/ Q# F- K3 O# j) |
Black-Scholes Real Options Insights
2 w! w% H/ h1 o3 ] ROV Tool
( k/ g! v* Y! V" j Summary: E$ o7 R" s3 I! z1 B: J M
Appendix A: Crystal Ball's Probability Distributions5 }! W p) g& v- g' K9 Y
Appendix B: Generating Assumption Values2 a8 q; y9 h& \$ n* F; b. ]
Appendix C: Variance Reduction Techniques
3 {$ V0 ]. N" A/ ?# i( | Appendix D: About the Download
; h) ]$ Y! p v$ d3 m Glossary! Z0 ~9 J3 \7 u+ ~( V6 ~' B
References
7 u9 Z a6 M& O; w Index1 O, Z. a* x) G4 F7 _; Z. |0 M$ z
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