An introduction to the mathematics of financial derivatives:
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| Format: | Buch |
| Sprache: | English |
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San Diego [u.a.]
Acad. Press
[19]98
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| Ausgabe: | [Nachdr.] |
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XXI, 352 S. graph. Darst. |
| ISBN: | 0125153902 |
Internformat
MARC
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| 245 | 1 | 0 | |a An introduction to the mathematics of financial derivatives |c Salih N. Neftci |
| 250 | |a [Nachdr.] | ||
| 264 | 1 | |a San Diego [u.a.] |b Acad. Press |c [19]98 | |
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Datensatz im Suchindex
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|---|---|
| adam_text | An Introduction
to the
Mathematics of
Financial Derivatives
Salih N Neftci
CUNY Graduate Center
New York, New York
and
Graduate Institute of International Studies
Geneva, Switzerland
Academic Press
San Diego London Boston New York Sydney Tokyo Toronto
CONTENTS
PREFACE xv
INTRODUCTION
CHAPTER • 1 Financial Derivatives
A Brief Introduction
1 Introduction 1
2 Definitions 2
3 Types of Derivatives 2
3 1 Cash-and-Carry Markets 3
3 2 Price-Discovery Markets 4
3 3 Expiration Date 4
4 Forwards and Futures 5
4 1 Futures 6
5 Options 6
5 1 Some Notation 7
6 Swaps 9
61A Simple Interest Rate Swap 10
7 Conclusions 11
8 References 11
vi Contents
CHAPTER • 2 A Primer on the Arbitrage Theorem
1 Introduction 12
2 Notation 13
2 1 Asset Prices 14
2 2 States of the World 14
2 3 Returns and Payoffs 15
2 4 Portfolio 16
3 A Basic Example of Asset Pricing 16
31A First Glance at the Arbitrage Theorem 18
3 2 Relevance of the Arbitrage Theorem 19
3 3 The Use of Synthetic Probabilities 20
3 4 Martingales and Submartingales 23
3 5 Equalization of Rates of Return 23
4 A Numerical Example 24
4 1 Case 1: Arbitrage Possibilities 25
4 2 Case 2: Arbitrage-Free Prices 26
4 3 An Indeterminacy 26
5 An Application: Lattice Models 27
6 Some Generalizations 29
6 1 Time Index 29
6 2 States of the World 30
6 3 Discounting 30
7 Conclusions: A Methodology for Pricing
Assets 30
8 References 31
9 Appendix: Generalization of the Arbitrage
Theorem 31
CHAPTER • 3 Calculus in Deterministic and
Stochastic Environments
1 Introduction 35
1 1 Information Flows 36
1 2 Modeling Random Behavior 36
2 Some Tools of Standard Calculus 37
Contents vii
3 Functions 37
3 1 Random Functions 38
3 2 Examples of Functions 39
4 Convergence and Limit 42
4 1 The Derivative 42
4 2 The Chain Rule 47
4 3 The Integral 49
4 4 Integration by Parts 55
5 Partial Derivatives 56
5 1 Example 57
5 2 Total Differentials 57
5 3 Taylor Series Expansion 58
5 4 Ordinary Differential Equations 62
6 Conclusions 64
7 References 64
CHAPTER • 4 Pricing Derivatives
Models and Notation
1 Introduction 65
2 Pricing Functions 66
2 1 Forwards 66
2 2 Options 68
3 Application: Another Pricing Method 72
3 1 Example 73
4 The Problem 74
41A First Look at Ito s Lemma 74
4 2 Conclusions 76
5 References 77
CHAPTER • 5 Tools in Probability Theory
1 Introduction 78
2 Probability 78
2 1 Example 79
2 2 Random Variable 80
viii Contents
3 Moments 81
3 1 First Two Moments 81
3 2 Higher-Order Moments 82
4 Conditional Expectations 84
4 1 Conditional Probability 84
4-2 Properties of Conditional Expectations 86
5 Some Important Models 87
5 1 Binomial Distribution in Financial Markets 87
5 2 Limiting Properties 88
5 3 Moments 89
5 4 The Normal Distribution 90
5 5 The Poisson Distribution 94
6 Convergence of Random Variables 95
6 1 Types of Convergence and Their Uses 95
6 2 Weak Convergence 97
7 Conclusions 99
8 References 100
CHAPTER • 6 Martingales and Martingale
Representations
1 Introduction 101
2 Definitions 102
2 1 Notation 102
2 2 Continuous-Time Martingales 103
3 The Use of Martingales in Asset Pricing 104
4 Relevance of Martingales in Stochastic
Modeling 106
4 1 An Example 108
5 Properties of Martingale Trajectories 110
6 Examples of Martingales 113
6 1 Example 1: Brownian Motion 113
6 2 Example 2: A Squared Process 114
6 3 Example 3: An Exponential Process 115
6 4 Example 4: Right Continuous Martingales 116
Contents is
7 Martingale Representations 116
7 1 An Example 117
7 2 Doob-Meyer Decomposition 120
8 The First Stochastic Integral 123
8 1 Application to Finance: Trading Gains 124
9 Conclusions 125
10 References 126
CHAPTER • 7 Differentiation in Stochastic
Environments
1 Introduction 127
2 Motivation 128
3 A Framework for Discussing
Differentiation 132
4 The Size of Incremental Errors 135
5 One Implication 139
6 Putting the Results Together 140
6 1 Stochastic Differentials 142
7 Conclusions 142
8 References 143
CHAPTER * 8 The Wiener Process and Rare
Events in Financial Markets
1 Introduction 144
1 1 Relevance of the Discussion 145
2 Two Generic Models 146
2 1 The Wiener Process 147
2 2 The Poisson Process 149
2 3 Examples 151
2 4 Back to Rare Events 153
3 SDE in Discrete Intervals, Again 154
4 Characterizing Rare and Normal Events 155
4-1 Normal Events 158
4 2 Rare Events 160
5 A Model for Rare Events 161
x Contents
6 Moments That Matter 164
7 Conclusions 166
8 References 167
CHAPTER • 9 Integration in Stochastic
Environments
The Ito Integral
1 Introduction 168
1 1 The Ito Integral and SDEs 170
1 2 The Practical Relevance of the Ito Integral 171
2 The Ito Integral 172
2 1 The Riemann-Stieltjes Integral 173
2 2 Stochastic Integration and Riemann Sums 175
2 3 Definition: The Ito Integral 177
2 4 An Expository Example 179
3 Properties of the Ito Integral 185
3 1 The Ito Integral Is a Martingale 185
3 2 Pathwise Integrals 189
4 Other Properties of the Ito Integral 190
4 1 Existence 190
4 2 Correlation Properties 191
4 3 Addition 191
5 Integrals with Respect to Jump Processes 192
6 Conclusions 192
7 References 193
CHAPTER • 10 Ito s Lemma
1 Introduction 194
2 Types of Derivatives 194
2 1 Example 196
3 Ito s Lemma 196
3 1 The Notion of Size in Stochastic Calculus 199
3 2 First-Order Terms 201
3 3 Second-Order Terms 202
Contents xi
3 4 Terms Involving Cross Products 203
3 5 Terms in the Remainder 204
4 The Ito Formula 204
5 Uses of Ito s Lemma 205
5 1 Ito s Formula as a Chain Rule 205
5 2 Ito s Formula as an Integration Tool 206
6 Integral Form of Ito s Lemma 208
7 Ito s Formula in More Complex Settings 209
7 1 Multivariate Case 209
7 2 Ito s Formula and Jumps 212
8 Conclusions 214
9 References 215
CHAPTER • 11 The Dynamics of Derivative Prices
Stochastic Differential Equations
1 Introduction 216
1 1 Conditions on a, and r, 217
2 A Geometric Description of Paths Implied by
SDEs 218
3 Solution of SDEs 219
3 1 What Does a Solution Mean? 219
3 2 Types of Solutions 220
3 3 Which Solution Is To Be Preferred? 222
34A Discussion of Strong Solutions 222
3 5 Verification of Solutions to SDEs 225
3 6 An Important Example 226
4 Major Models of SDEs 229
4-1 Linear Constant Coefficient SDEs 230
4 2 Geometric SDEs 231
4 3 Square Root Process 233
4 4 Mean Reverting Process 234
4 5 Ornstein-Uhlenbeck Process 235
5 Stochastic Volatility 235
6 Conclusions 236
7 References 236
Contents
CHAPTER • 12 Pricing Derivative Products
Partial Differential Equations
1 Introduction 237
2 Forming Risk-Free Portfolios 238
3 Partial Differential Equations 241
3 1 Why Is the PDE an Equation? 242
3 2 What Is the Boundary Condition? 242
4 Classification of PDEs 243
4 1 Example 1: Linear, First-Order PDE 244
4 2 Example 2: Linear, Second-Order PDE 247
5 A Reminder: Bivariate, Second-Degree
Equations 249
5 1 Circle 249
5 2 Ellipse 250
5 3 Parabola 251
5 4 Hyperbola 251
6 Types of PDEs 251
6 1 Example: Parabolic PDE 252
7 Conclusions 253
8 References 253
CHAPTER • 13 The Black-Scholes PDE
An Application
1 Introduction 254
2 The Black-Scholes PDE 254
21A Geometric Look at the Black-Scholes Formula 256
3 PDEs in Asset Pricing 258
31A Second Factor 258
4 Exotic Options 263
4-1 Lookback Options 264
4 2 Ladder Options 264
4 3 Trigger or Knock-in Options 264
4 4 Knock-out Options 264
4 5 Other Exotics 265
4 6 The Relevant PDEs 265
Contents xiii
5 Solving PDEs in Practice 266
5 1 Closed-Form Solutions 266
5 2 Numerical Solutions 268
6 Conclusions 272
7 References 272
CHAPTER • 14 Pricing Derivative Products
Equivalent Martingale Measures
1 Translations of Probabilities 273
1 1 Probability as Measure 273
2 Changing Means 277
2 1 Method 1: Operating on Possible Values 278
2 2 Method 2: Operating on Probabilities 282
3 The Girsanov Theorem 283
31A Normally Distributed Random Variable 284
32A Normally Distributed Vector 286
3 3 The Radon-Nikodym Derivative 288
3 4 Equivalent Measures 289
4 Statement of the Girsanov Theorem 290
5 A Discussion of the Girsanov Theorem 292
5 1 Application to SDEs 293
6 Conclusions 295
7 References 296
CHAPTER • 15 Equivalent Martingale Measures
Applications
1 Introduction 297
2 A Martingale Measure 298
2 1 The Moment-Generating Function 298
2 2 Conditional Expectation of Geometric Processes 300
3 Converting Asset Prices into Martingales 301
3 1 Determining P 302
3 2 The Implied SDEs 304
4 Application: The Black-Scholes Formula 305
4 1 Calculation 308
xiv Contents
5 Comparing Martingale and PDE
Approaches 3 1 0
5 1 Equivalence of the Two Approaches 311
5 2 Critical Steps of the Derivation 315
5 3 Integral Form of the Ito Formula 316
6 Conclusions 317
7 References 318
CHAPTER • 16 Tools for Complicated Derivative
Structures
1 Introduction 319
2 New Tools 320
2 1 Interest Rate Derivatives 321
3 Term Structure of Interest Rates 322
3 1 Relating rs and RJ1 325
4 Characterization of Expectations Using
PDEs 326
4 1 Risk-Neutral Bond Pricing 327
5 Random Discount Factors and PDEs 328
5 1 Ito Diffusions 329
5 2 The Markov Property 329
5 3 Generator of an Ito Diffusion 330
54A Representation for A 330
5 5 Kolmogorov s Backward Equation 332
5 6 The Feyman-Kac Formula 334
6 American Securities 336
6 1 Stopping Times 336
6 2 Use of Stopping Times 337
7 Extending the Results to Stopping Times 338
7 1 Martingales 338
7 2 Dynkin s Formula 339
8 Conclusions 339
9 References 3 3 9
BIBLIOGRAPHY 341
INDEX 345
|
| adam_txt |
An Introduction
to the
Mathematics of
Financial Derivatives
Salih N Neftci
CUNY Graduate Center
New York, New York
and
Graduate Institute of International Studies
Geneva, Switzerland
Academic Press
San Diego London Boston New York Sydney Tokyo Toronto
CONTENTS
PREFACE xv
INTRODUCTION
CHAPTER • 1 Financial Derivatives
A Brief Introduction
1 Introduction 1
2 Definitions 2
3 Types of Derivatives 2
3 1 Cash-and-Carry Markets 3
3 2 Price-Discovery Markets 4
3 3 Expiration Date 4
4 Forwards and Futures 5
4 1 Futures 6
5 Options 6
5 1 Some Notation 7
6 Swaps 9
61A Simple Interest Rate Swap 10
7 Conclusions 11
8 References 11
vi Contents
CHAPTER • 2 A Primer on the Arbitrage Theorem
1 Introduction 12
2 Notation 13
2 1 Asset Prices 14
2 2 States of the World 14
2 3 Returns and Payoffs 15
2 4 Portfolio 16
3 A Basic Example of Asset Pricing 16
31A First Glance at the Arbitrage Theorem 18
3 2 Relevance of the Arbitrage Theorem 19
3 3 The Use of Synthetic Probabilities ' 20
3 4 Martingales and Submartingales 23
3 5 Equalization of Rates of Return 23
4 A Numerical Example 24
4 1 Case 1: Arbitrage Possibilities 25
4 2 Case 2: Arbitrage-Free Prices 26
4 3 An Indeterminacy 26
5 An Application: Lattice Models 27
6 Some Generalizations 29
6 1 Time Index 29
6 2 States of the World 30
6 3 Discounting 30
7 Conclusions: A Methodology for Pricing
Assets 30
8 References 31
9 Appendix: Generalization of the Arbitrage
Theorem 31
CHAPTER • 3 Calculus in Deterministic and
Stochastic Environments
1 Introduction 35
1 1 Information Flows 36
1 2 Modeling Random Behavior 36
2 Some Tools of Standard Calculus 37
Contents vii
3 Functions 37
3 1 Random Functions 38
3 2 Examples of Functions 39
4 Convergence and Limit 42
4 1 The Derivative 42
4 2 The Chain Rule 47
4 3 The Integral 49
4 4 Integration by Parts 55
5 Partial Derivatives 56
5 1 Example 57
5 2 Total Differentials 57
5 3 Taylor Series Expansion 58
5 4 Ordinary Differential Equations 62
6 Conclusions 64
7 References 64
CHAPTER • 4 Pricing Derivatives
Models and Notation
1 Introduction 65
2 Pricing Functions 66
2 1 Forwards 66
2 2 Options 68
3 Application: Another Pricing Method 72
3 1 Example 73
4 The Problem 74
41A First Look at Ito's Lemma 74
4 2 Conclusions 76
5 References 77
CHAPTER • 5 Tools in Probability Theory
1 Introduction 78
2 Probability 78
2 1 Example 79
2 2 Random Variable 80
viii Contents
3 Moments 81
3 1 First Two Moments 81
3 2 Higher-Order Moments 82
4 Conditional Expectations 84
4 1 Conditional Probability 84
4-2 Properties of Conditional Expectations 86
5 Some Important Models 87
5 1 Binomial Distribution in Financial Markets 87
5 2 Limiting Properties 88
5 3 Moments 89
5 4 The Normal Distribution 90
5 5 The Poisson Distribution 94
6 Convergence of Random Variables 95
6 1 Types of Convergence and Their Uses 95
6 2 Weak Convergence 97
7 Conclusions 99
8 References 100
CHAPTER • 6 Martingales and Martingale
Representations
1 Introduction 101
2 Definitions 102
2 1 Notation 102
2 2 Continuous-Time Martingales 103
3 The Use of Martingales in Asset Pricing 104
4 Relevance of Martingales in Stochastic
Modeling 106
4 1 An Example 108
5 Properties of Martingale Trajectories 110
6 Examples of Martingales 113
6 1 Example 1: Brownian Motion 113
6 2 Example 2: A Squared Process 114
6 3 Example 3: An Exponential Process 115
6 4 Example 4: Right Continuous Martingales 116
Contents is
7 Martingale Representations 116
7 1 An Example 117
7 2 Doob-Meyer Decomposition 120
8 The First Stochastic Integral 123
8 1 Application to Finance: Trading Gains 124
9 Conclusions 125
10 References 126
CHAPTER • 7 Differentiation in Stochastic
Environments
1 Introduction 127
2 Motivation 128
3 A Framework for Discussing
Differentiation 132
4 The Size of Incremental Errors 135
5 One Implication 139
6 Putting the Results Together 140
6 1 Stochastic Differentials 142
7 Conclusions 142
8 References 143
CHAPTER * 8 The Wiener Process and Rare
Events in Financial Markets
1 Introduction 144
1 1 Relevance of the Discussion 145
2 Two Generic Models 146
2 1 The Wiener Process 147
2 2 The Poisson Process 149
2 3 Examples 151
2 4 Back to Rare Events 153
3 SDE in Discrete Intervals, Again 154
4 Characterizing Rare and Normal Events 155
4-1 Normal Events 158
4 2 Rare Events 160
5 A Model for Rare Events 161
x Contents
6 Moments That Matter 164
7 Conclusions 166
8 References 167
CHAPTER • 9 Integration in Stochastic
Environments
The Ito Integral
1 Introduction 168
1 1 The Ito Integral and SDEs 170
1 2 The Practical Relevance of the Ito Integral 171
2 The Ito Integral 172
2 1 The Riemann-Stieltjes Integral 173
2 2 Stochastic Integration and Riemann Sums 175
2 3 Definition: The Ito Integral 177
2 4 An Expository Example 179
3 Properties of the Ito Integral 185
3 1 The Ito Integral Is a Martingale 185
3 2 Pathwise Integrals 189
4 Other Properties of the Ito Integral 190
4 1 Existence 190
4 2 Correlation Properties 191
4 3 Addition 191
5 Integrals with Respect to Jump Processes 192
6 Conclusions 192
7 References 193
CHAPTER • 10 Ito's Lemma
1 Introduction 194
2 Types of Derivatives 194
2 1 Example 196
3 Ito's Lemma 196
3 1 The Notion of Size in Stochastic Calculus 199
3 2 First-Order Terms 201
3 3 Second-Order Terms 202
Contents xi
3 4 Terms Involving Cross Products 203
3 5 Terms in the Remainder 204
4 The Ito Formula 204
5 Uses of Ito's Lemma 205
5 1 Ito's Formula as a Chain Rule 205
5 2 Ito's Formula as an Integration Tool 206
6 Integral Form of Ito's Lemma 208
7 Ito's Formula in More Complex Settings 209
7 1 Multivariate Case 209
7 2 Ito's Formula and Jumps 212
8 Conclusions 214
9 References 215
CHAPTER • 11 The Dynamics of Derivative Prices
Stochastic Differential Equations
1 Introduction 216
1 1 Conditions on a, and r, 217
2 A Geometric Description of Paths Implied by
SDEs 218
3 Solution of SDEs 219
3 1 What Does a Solution Mean? 219
3 2 Types of Solutions 220
3 3 Which Solution Is To Be Preferred? 222
34A Discussion of Strong Solutions 222
3 5 Verification of Solutions to SDEs 225
3 6 An Important Example 226
4 Major Models of SDEs 229
4-1 Linear Constant Coefficient SDEs 230
4 2 Geometric SDEs 231
4 3 Square Root Process 233
4 4 Mean Reverting Process 234
4 5 Ornstein-Uhlenbeck Process 235
5 Stochastic Volatility 235
6 Conclusions 236
7 References 236
Contents
CHAPTER • 12 Pricing Derivative Products
Partial Differential Equations
1 Introduction 237
2 Forming Risk-Free Portfolios 238
3 Partial Differential Equations 241
3 1 Why Is the PDE an Equation? 242
3 2 What Is the Boundary Condition? 242
4 Classification of PDEs 243
4 1 Example 1: Linear, First-Order PDE 244
4 2 Example 2: Linear, Second-Order PDE 247
5 A Reminder: Bivariate, Second-Degree
Equations 249
5 1 Circle 249
5 2 Ellipse 250
5 3 Parabola 251
5 4 Hyperbola 251
6 Types of PDEs 251
6 1 Example: Parabolic PDE 252
7 Conclusions 253
8 References 253
CHAPTER • 13 The Black-Scholes PDE
An Application
1 Introduction 254
2 The Black-Scholes PDE 254
21A Geometric Look at the Black-Scholes Formula 256
3 PDEs in Asset Pricing 258
31A Second Factor 258
4 Exotic Options 263
4-1 Lookback Options 264
4 2 Ladder Options 264
4 3 Trigger or Knock-in Options 264
4 4 Knock-out Options 264
4 5 Other Exotics 265
4 6 The Relevant PDEs 265
Contents xiii
5 Solving PDEs in Practice 266
5 1 Closed-Form Solutions 266
5 2 Numerical Solutions 268
6 Conclusions 272
7 References 272
CHAPTER • 14 Pricing Derivative Products
Equivalent Martingale Measures
1 Translations of Probabilities 273
1 1 Probability as Measure 273
2 Changing Means 277
2 1 Method 1: Operating on Possible Values 278
2 2 Method 2: Operating on Probabilities 282
3 The Girsanov Theorem 283
31A Normally Distributed Random Variable 284
32A Normally Distributed Vector 286
3 3 The Radon-Nikodym Derivative 288
3 4 Equivalent Measures 289
4 Statement of the Girsanov Theorem 290
5 A Discussion of the Girsanov Theorem 292
5 1 Application to SDEs 293
6 Conclusions 295
7 References 296
CHAPTER • 15 Equivalent Martingale Measures
Applications
1 Introduction 297
2 A Martingale Measure 298
2 1 The Moment-Generating Function 298
2 2 Conditional Expectation of Geometric Processes 300
3 Converting Asset Prices into Martingales 301
3 1 Determining P 302
3 2 The Implied SDEs 304
4 Application: The Black-Scholes Formula 305
4 1 Calculation 308
xiv Contents
5 Comparing Martingale and PDE
Approaches 3 1 0
5 1 Equivalence of the Two Approaches 311
5 2 Critical Steps of the Derivation 315
5 3 Integral Form of the Ito Formula 316
6 Conclusions 317
7 References 318
CHAPTER • 16 Tools for Complicated Derivative
Structures
1 Introduction 319
2 New Tools 320
2 1 Interest Rate Derivatives 321
3 Term Structure of Interest Rates 322
3 1 Relating rs and RJ1 325
4 Characterization of Expectations Using
PDEs 326
4 1 Risk-Neutral Bond Pricing 327
5 Random Discount Factors and PDEs 328
5 1 Ito Diffusions 329
5 2 The Markov Property 329
5 3 Generator of an Ito Diffusion 330
54A Representation for A 330
5 5 Kolmogorov's Backward Equation 332
5 6 The Feyman-Kac Formula 334
6 American Securities 336
6 1 Stopping Times 336
6 2 Use of Stopping Times 337
7 Extending the Results to Stopping Times 338
7 1 Martingales 338
7 2 Dynkin's Formula 339
8 Conclusions 339
9 References 3 3 9
BIBLIOGRAPHY 341
INDEX 345 |
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| author | Neftci, Salih N. |
| author_facet | Neftci, Salih N. |
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| author_sort | Neftci, Salih N. |
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| building | Verbundindex |
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| callnumber-search | HG6024.A3N44 1996 |
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| callnumber-subject | HG - Finance |
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| ctrlnum | (OCoLC)245806020 (DE-599)BVBBV023519391 |
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| dewey-ones | 332 - Financial economics |
| dewey-raw | 332.63/2 20 |
| dewey-search | 332.63/2 20 |
| dewey-sort | 3332.63 12 220 |
| dewey-tens | 330 - Economics |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| edition | [Nachdr.] |
| format | Book |
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| id | DE-604.BV023519391 |
| illustrated | Illustrated |
| index_date | 2024-07-02T22:32:33Z |
| indexdate | 2024-07-09T21:23:45Z |
| institution | BVB |
| isbn | 0125153902 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016839711 |
| oclc_num | 245806020 |
| open_access_boolean | |
| owner | DE-521 |
| owner_facet | DE-521 |
| physical | XXI, 352 S. graph. Darst. |
| publishDate | 1998 |
| publishDateSearch | 1998 |
| publishDateSort | 1998 |
| publisher | Acad. Press |
| record_format | marc |
| spelling | Neftci, Salih N. Verfasser aut An introduction to the mathematics of financial derivatives Salih N. Neftci [Nachdr.] San Diego [u.a.] Acad. Press [19]98 XXI, 352 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Mathematik Derivative securities -- Mathematics Derivat Wertpapier (DE-588)4381572-8 gnd rswk-swf Finanzmathematik (DE-588)4017195-4 gnd rswk-swf Finanzmathematik (DE-588)4017195-4 s Derivat Wertpapier (DE-588)4381572-8 s DE-604 HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016839711&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Neftci, Salih N. An introduction to the mathematics of financial derivatives Mathematik Derivative securities -- Mathematics Derivat Wertpapier (DE-588)4381572-8 gnd Finanzmathematik (DE-588)4017195-4 gnd |
| subject_GND | (DE-588)4381572-8 (DE-588)4017195-4 |
| title | An introduction to the mathematics of financial derivatives |
| title_auth | An introduction to the mathematics of financial derivatives |
| title_exact_search | An introduction to the mathematics of financial derivatives |
| title_exact_search_txtP | An introduction to the mathematics of financial derivatives |
| title_full | An introduction to the mathematics of financial derivatives Salih N. Neftci |
| title_fullStr | An introduction to the mathematics of financial derivatives Salih N. Neftci |
| title_full_unstemmed | An introduction to the mathematics of financial derivatives Salih N. Neftci |
| title_short | An introduction to the mathematics of financial derivatives |
| title_sort | an introduction to the mathematics of financial derivatives |
| topic | Mathematik Derivative securities -- Mathematics Derivat Wertpapier (DE-588)4381572-8 gnd Finanzmathematik (DE-588)4017195-4 gnd |
| topic_facet | Mathematik Derivative securities -- Mathematics Derivat Wertpapier Finanzmathematik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016839711&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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