Atjaunināt sīkdatņu piekrišanu

Introduction to Stochastic Finance with Market Examples 2nd edition [Hardback]

(Nanyang Technological University, Singapore)
  • Formāts: Hardback, 652 pages, height x width: 254x178 mm, weight: 1700 g, 16 Tables, black and white; 219 Line drawings, black and white; 219 Illustrations, black and white
  • Sērija : Chapman and Hall/CRC Financial Mathematics Series
  • Izdošanas datums: 13-Dec-2022
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-10: 1032288264
  • ISBN-13: 9781032288260
Citas grāmatas par šo tēmu:
  • Hardback
  • Cena: 130,13 €
  • Grāmatu piegādes laiks ir 3-4 nedēļas, ja grāmata ir uz vietas izdevniecības noliktavā. Ja izdevējam nepieciešams publicēt jaunu tirāžu, grāmatas piegāde var aizkavēties.
  • Daudzums:
  • Ielikt grozā
  • Piegādes laiks - 4-6 nedēļas
  • Pievienot vēlmju sarakstam
  • Bibliotēkām
Introduction to Stochastic Finance with Market Examples 2nd editionPalielināt
  • Formāts: Hardback, 652 pages, height x width: 254x178 mm, weight: 1700 g, 16 Tables, black and white; 219 Line drawings, black and white; 219 Illustrations, black and white
  • Sērija : Chapman and Hall/CRC Financial Mathematics Series
  • Izdošanas datums: 13-Dec-2022
  • Izdevniecība: Chapman & Hall/CRC
  • ISBN-10: 1032288264
  • ISBN-13: 9781032288260
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781032288260.html
Keywords:
Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods. It demonstrates both the power and limitations of mathematical models in finance, covering the basics of stochastic calculus for finance, and details the techniques required to model the time evolution of risky assets. The book discusses a wide range of classical topics including BlackScholes pricing, American options, derivatives, term structure modeling, and change of numéraire. It also builds up to special topics, such as exotic options, stochastic volatility, and jump processes.

New to this Edition





New chapters on Barrier Options, Lookback Options, Asian Options, Optimal Stopping Theorem, and Stochastic Volatility Contains over 235 exercises and 16 problems with complete solutions available online from the instructor resources Added over 150 graphs and figures, for more than 250 in total, to optimize presentation 57 R coding examples now integrated into the book for implementation of the methods



Substantially class-tested, so ideal for course use or self-study





With abundant exercises, problems with complete solutions, graphs and figures, and R coding examples, the book is primarily aimed at advanced undergraduate and graduate students in applied mathematics, financial engineering, and economics. It could be used as a course text or for self-study and would also be a comprehensive and accessible reference for researchers and practitioners in the field.
Preface ix
Introduction 1(14)
1 Assets, Portfolios, and Arbitrage
15(24)
1.1 Portfolio Allocation and Short Selling
15(2)
1.2 Arbitrage
17(4)
1.3 Risk-Neutral Probability Measures
21(4)
1.4 Hedging of Contingent Claims
25(2)
1.5 Market Completeness
27(1)
1.6 Example: Binary Market
27(12)
Exercises
34(5)
2 Discrete-Time Market Model
39(26)
2.1 Discrete-Time Compounding
39(2)
2.2 Arbitrage and Self-Financing Portfolios
41(6)
2.3 Contingent Claims
47(3)
2.4 Martingales and Conditional Expectations
50(4)
2.5 Market Completeness and Risk-Neutral Measures
54(2)
2.6 The Cox-Ross-Rubinstein (CRR) Market Model
56(9)
Exercises
60(5)
3 Pricing and Hedging in Discrete Time
65(48)
3.1 Pricing Contingent Claims
65(4)
3.2 Pricing Vanilla Options in the CRR Model
69(5)
3.3 Hedging Contingent Claims
74(1)
3.4 Hedging Vanilla Options
75(8)
3.5 Hedging Exotic Options
83(6)
3.6 Convergence of the CRR Model
89(24)
Exercises
94(19)
4 Brownian Motion and Stochastic Calculus
113(40)
4.1 Brownian Motion
113(2)
4.2 Three Constructions of Brownian Motion
115(3)
4.3 Wiener Stochastic Integral
118(8)
4.4 Ito Stochastic Integral
126(6)
4.5 Stochastic Calculus
132(21)
Exercises
142(11)
5 Continuous-Time Market Model
153(20)
5.1 Asset Price Modeling
153(1)
5.2 Arbitrage and Risk-Neutral Measures
154(2)
5.3 Self-Financing Portfolio Strategies
156(3)
5.4 Two-Asset Portfolio Model
159(5)
5.5 Geometric Brownian Motion
164(9)
Exercises
167(6)
6 Black-Scholes Pricing and Hedging
173(34)
6.1 The Black-Scholes PDE
173(4)
6.2 European Call Options
177(6)
6.3 European Put Options
183(4)
6.4 Market Terms and Data
187(3)
6.5 The Heat Equation
190(4)
6.6 Solution of the Black-Scholes PDE
194(13)
Exercises
197(10)
7 Martingale Approach to Pricing and Hedging
207(42)
7.1 Martingale Property of the Ito Integral
207(4)
7.2 Risk-Neutral Probability Measures
211(4)
7.3 Change of Measure and the Girsanov Theorem
215(2)
7.4 Pricing by the Martingale Method
217(6)
7.5 Hedging by the Martingale Method
223(26)
Exercises
228(21)
8 Stochastic Volatility
249(28)
8.1 Stochastic Volatility Models
249(3)
8.2 Realized Variance Swaps
252(4)
8.3 Realized Variance Options
256(7)
8.4 European Options - PDE Method
263(6)
8.5 Perturbation Analysis
269(8)
Exercises
273(4)
9 Volatility Estimation
277(22)
9.1 Historical Volatility
277(2)
9.2 Implied Volatility
279(6)
9.3 Local Volatility
285(5)
9.4 The VLX® Index
290(9)
Exercises
295(4)
10 Maximum of Brownian Motion
299(24)
10.1 Running Maximum of Brownian Motion
299(1)
10.2 The Reflection Principle
300(4)
10.3 Density of the Maximum of Brownian Motion
304(9)
10.4 Average of Geometric Brownian Extrema
313(10)
Exercises
320(3)
11 Barrier Options
323(26)
11.1 Options on Extrema
323(4)
11.2 Knock-Out Barrier
327(10)
11.3 Knock-In Barrier
337(3)
11.4 PDE Method
340(4)
11.5 Hedging Barrier Options
344(5)
Exercises
345(4)
12 Lookback Options
349(22)
12.1 The Lookback Put Option
349(2)
12.2 PDE Method
351(5)
12.3 The Lookback Call Option
356(7)
12.4 Delta Hedging for Lookback Options
363(8)
Exercises
368(3)
13 Asian Options
371(30)
13.1 Bounds on Asian Option Prices
371(6)
13.2 Hartman-Watson Distribution
377(3)
13.3 Laplace Transform Method
380(1)
13.4 Moment Matching Approximations
380(6)
13.5 PDE Method
386(15)
Exercises
395(6)
14 Optimal Stopping Theorem
401(18)
14.1 Filtrations and Information Flow
401(1)
14.2 Submartingales and Supermartingales
401(3)
14.3 Optimal Stopping Theorem
404(6)
14.4 Drifted Brownian Motion
410(9)
Exercises
415(4)
15 American Options
419(30)
15.1 Perpetual American Put Options
419(5)
15.2 PDE Method for Perpetual Put Options
424(4)
15.3 Perpetual American Call Options
428(3)
15.4 Finite Expiration American Options
431(3)
15.5 PDE Method with Finite Expiration
434(15)
Exercises
438(11)
16 Change of Numeraire and Forward Measures
449(30)
16.1 Notion of Numeraire
449(2)
16.2 Change of Numeraire
451(9)
16.3 Foreign Exchange
460(7)
16.4 Pricing Exchange Options
467(2)
16.5 Hedging by Change of Numeraire
469(10)
Exercises
472(7)
17 Short Rates and Bond Pricing
479(34)
17.1 Vasicek Model
479(6)
17.2 Affine Short Rate Models
485(3)
17.3 Zero-Coupon and Coupon Bonds
488(3)
17.4 Bond Pricing PDE
491(22)
Exercises
503(10)
18 Forward Rates
513(30)
18.1 Construction of Forward Rates
513(9)
18.2 LIBOR/SOFR Swap Rates
522(4)
18.3 The HJM Model
526(4)
18.4 Yield Curve Modeling
530(4)
18.5 Two-Factor Model
534(3)
18.6 The BGM Model
537(6)
Exercises
538(5)
19 Pricing of Interest Rate Derivatives
543(22)
19.1 Forward Measures and Tenor Structure
543(3)
19.2 Bond Options
546(2)
19.3 Caplet Pricing
548(5)
19.4 Forward Swap Measures
553(2)
19.5 Swaption Pricing
555(10)
Exercises
560(5)
20 Stochastic Calculus for Jump Processes
565(36)
20.1 The Poisson Process
565(6)
20.2 Compound Poisson Process
571(5)
20.3 Stochastic Integrals and Ito Formula with Jumps
576(9)
20.4 Stochastic Differential Equations with Jumps
585(4)
20.5 Girsanov Theorem for Jump Processes
589(12)
Exercises
595(6)
21 Pricing and Hedging in Jump Models
601(22)
21.1 Fitting the Distribution of Market Returns
601(7)
21.2 Risk-Neutral Probability Measures
608(1)
21.3 Pricing in Jump Models
609(2)
21.4 Exponential Levy Models
611(3)
21.5 Black-Scholes PDE with Jumps
614(2)
21.6 Mean-Variance Hedging with Jumps
616(7)
Exercises
619(4)
22 Basic Numerical Methods
623(8)
22.1 Discretized Heat Equation
623(3)
22.2 Discretized Black-Scholes PDE
626(2)
22.3 Euler Discretization
628(1)
22.4 Milshtein Discretization
629(2)
Exercises
630(1)
Bibliography 631(12)
Index 643
Nicolas Privault received a PhD degree from the University of Paris VI, France. He was with the University of Evry, France, the University of La Rochelle, France, and the University of Poitiers, France. He is currently a Professor with the School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore. His research interests are in the areas of stochastic analysis and its applications.