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2016 | Buch

An Introduction to Mathematical Finance with Applications

Understanding and Building Financial Intuition

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Über dieses Buch

This textbook aims to fill the gap between those that offer a theoretical treatment without many applications and those that present and apply formulas without appropriately deriving them. The balance achieved will give readers a fundamental understanding of key financial ideas and tools that form the basis for building realistic models, including those that may become proprietary. Numerous carefully chosen examples and exercises reinforce the student’s conceptual understanding and facility with applications. The exercises are divided into conceptual, application-based, and theoretical problems, which probe the material deeper.

The book is aimed toward advanced undergraduates and first-year graduate students who are new to finance or want a more rigorous treatment of the mathematical models used within. While no background in finance is assumed, prerequisite math courses include multivariable calculus, probability, and linear algebra. The authors introduce additional mathematical tools as needed. The entire textbook is appropriate for a single year-long course on introductory mathematical finance. The self-contained design of the text allows for instructor flexibility in topics courses and those focusing on financial derivatives. Moreover, the text is useful for mathematicians, physicists, and engineers who want to learn finance via an approach that builds their financial intuition and is explicit about model building, as well as business school students who want a treatment of finance that is deeper but not overly theoretical.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Preliminaries on Financial Markets
Abstract
This chapter provides an intuitive understanding of how interest rates, financial markets and the financial system work from a practical standpoint. It introduces basic concepts about infrastructures of securities markets and market liquidity; and terminologies about a bewildering array of interest rates, money, credit/debt and leverage, as well as some economic indicators. These concepts and terminologies will be directly or indirectly needed in later chapters.
Arlie O. Petters, Xiaoying Dong
Chapter 2. The Time Value of Money
Abstract
You may have heard the expression, “A dollar today is worth more than a dollar tomorrow,” which is because a dollar today has more time to accumulate interest. The time value of money deals with this basic idea more broadly, whereby an amount of money at the present time may be worth more than in the future because of its earning potential. To be self-contained for readers new to finance, the chapter covers: interest rate and return rate; simple interest and compound interest, including a nonintegral number of periods, continuous compounding, and varying interest rates; the net present value and internal return rate; simple ordinary annuities, perpetuities, amortization theory, and annuities with varying payments and interest; applications of annuities; and applications to stock and bond valuation.
Arlie O. Petters, Xiaoying Dong
Chapter 3. Markowitz Portfolio Theory
Abstract
We introduce Harry Markowitz’s mathematical model for how to distribute an initial capital across a collection of risky securities to create an efficient portfolio, namely, one with the least risk given an expected return and largest expected return given a level of portfolio risk. This chapter covers: the set up of the Markowitz portfolio model, which includes modeling security returns, the issue of multivariate normality, weights, short selling, portfolio return, portfolio risk, and portfolio log returns; two-security portfolio theory; the efficient frontier for N securities with and without short selling; the global minimum-variance portfolio, diversified portfolio, and Mutual Fund Theorem; utility functions and utility maximization; and diversification.
Arlie O. Petters, Xiaoying Dong
Chapter 4. Capital Market Theory and Portfolio Risk Measures
Abstract
This chapter is a continuation and extension of modern portfolio theory presented in Chapter 3, with an emphasis on risk measures and risk management of a portfolio. It introduces the capital asset pricing model (CAPM), linear factor models, and several approaches to portfolio risk measures such as value-at-risk, conditional value-at-risk and the concept of coherent risk measures, as well as a variety of portfolio evaluation techniques such as the alpha and beta, the Sharpe ratio, the Sortino ratio and maximum drawdown. The introduction to factor models is brief and from intuitive perspective.
Arlie O. Petters, Xiaoying Dong
Chapter 5. Binomial Trees and Security Pricing Modeling
Abstract
We introduce a discrete-time model of a risky security’s future price using a binomial tree. By increasing the number of time-steps in the tree, the assumption is that one obtains a more and more accurate model of the random future price of a security. This chapter covers: the general binomial tree model of future security prices, the Cox-Ross-Rubinstein (CRR) tree in the real world and risk-neutral world, the Lindeberg Central Limit Theorem with applications to the continuous-time limit of the CRR tree, and statistical and probability formulas for continuous-time security prices.
Arlie O. Petters, Xiaoying Dong
Chapter 6. Stochastic Calculus and Geometric Brownian Motion Model
Abstract
This chapter provides a fundamental understanding of elementary stochastic calculus in relevance to modern finance, particularly to pricing financial derivatives. It introduces concepts such as conditional expectation with respect to a \(\sigma\)-algebra, filtrations, adapted processes, Brownian motion (BM), martingales, quadratic variation and covariation, the Itô integral with respect to BM, Itô’s lemma, Girsanov theorem for a single BM and geometric Brownian motion (GBM) model. GBM is used to model stock prices in the Black-Scholes-Merton model for option pricing. Options and option pricing will be discussed in later chapters. An important feature of this chapter is the balance between derivational approach and descriptive approach to abstract mathematical concepts.
Arlie O. Petters, Xiaoying Dong
Chapter 7. Derivatives: Forwards, Futures, Swaps, and Options
Abstract
Nowadays one cannot understand modern finance and financial markets without a solid understanding of derivatives. This chapter introduces the basic building blocks of derivatives: forwards, futures, swaps (a brief introduction only) and options with a balance of theoretical and practical perspectives. The approach focuses on understanding the contracts and strategies, with an emphasis on options. The pricing aspect will be discussed in the next chapter.
Arlie O. Petters, Xiaoying Dong
Chapter 8. The BSM Model and European Option Pricing
Abstract
The Black-Scholes-Merton (BSM) model, also known as the Black-Scholes model, is one of the pillars of finance, providing a powerful theoretical framework that is widely applicable in financial engineering and corporate finance. This chapter covers: the BSM model; derivation of the BSM p.d.e. using a self-financing, replicating portfolio; applications to pricing European calls and puts; application to pricing warrants; risk-neutral pricing and the fundamental theorems of asset pricing; binomial-tree pricing of European calls; delta hedging; option Greeks and managing portfolio risk; the BSM model versus market data, including jumps, skewness, kurtosis, and volatility skews; and the Merton jump-diffusion model and market incompleteness.
Arlie O. Petters, Xiaoying Dong
Backmatter
Metadaten
Titel
An Introduction to Mathematical Finance with Applications
verfasst von
Arlie O. Petters
Xiaoying Dong
Copyright-Jahr
2016
Verlag
Springer New York
Electronic ISBN
978-1-4939-3783-7
Print ISBN
978-1-4939-3781-3
DOI
https://doi.org/10.1007/978-1-4939-3783-7

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