Beware: poor discussion of interest rate derivatives. Accessible introduction for physicists, but not sufficient on its own. Baxter and A. Rennie, Financial calculus. A very good and readable introduction to stochastic differential equations, martingale theory and option pricing. The emphasis complements Wilmott et al. Shimko, Finance in continuous time: A primer.
Lucid and crisp presentation of stochastic calculus with lots of examples on which to practice manipulations. Jorion, Value at Risk. An elementary introduction to modern day risk management and the concept of value-at-risk. Suggested reading. Here are some books that will give you a general background and are definitely worth reading if you intend to make this your career.
I know of at least one talented individual who was somewhat dazzled by Wall St, but eventually realised that it was not what he was looking for in life, and returned to academia as a result. Derman, My Life As a Quant. A personal memoir of one physicist's journey from academia into quantitative finance.
Derman's account is both a cautionary tale about the challenges of scientific and academic life and a realistic perspective about the "glamour" of Wall Street. Derman avoids superficial gloss and is refreshingly frank about the rewards and limitations of a career in quantitative finance. Recorded with equal candour are the author's limited successes in physics, the despair and loneliness of parts of his life, the invigourating success of parts of his work at Goldman, Sachs, and his dissatisfaction with some aspects of his career on Wall Street.
The book is particularly successful where it describes the physical intuition he used to develop his most substantial contributions to financial modeling: interest rate dynamics, and the volatility smile. I found this part skillfully written, particularly as it highlights the point I personally make in my own presentations: that the greatest value physicists can potentially provide to Wall Street is better modeling, rather than better and faster calculations on wrong or ill-founded models.
Another important lesson from the book is the value of listening to the "customer" in this case, traders , for whom an easy to use graphical interface is more important than all the math in the world. Derman's book is a must-read for would-be quants and academic physicists. The author is an authority on swaps, but in recent years has been something of a whistleblower " Like an ex-mobster turning state's witness Traders, Guns and Money describes all aspects of the financial derivatives world, at least as it existed prior to the credit crisis.
Unlike some of the other books below, this one is a warts-and-all account, and the picture that emerges is not a pleasant one. Many ex-physicists becoming quants will not necessarily understand the workings of the system as clearly as Das lays them out, and so this book is an excellent preparation for the realities of the world of Wall Street. Das writes very well, and has an excellent sense of humour which will appeal to those with a cynical bent.
Millman , The Vandal's Crown. A rather breathless account of the history of finance. Informative and easy to read. Bernstein, Capital Ideas.
A readable history of financial economics, from Markowitz, who developed the theory of portfolio optimization to the more recent growth of the derivatives markets. Frank Partnoy, F. A completely "gloves off" description of the dark side of Wall St, which has provoked predictable denials from the industry.
The author worked for several years on Wall St. Controversial, scurrilous, cynical, almost libellous, and amusingly written in parts. The narrative ends with the author leaving Wall St. The method combines two accurate … Expand. View 1 excerpt, cites background. Maximum-likelihood estimation for diffusion processes via closed-form density expansions. This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data.
A closed-form asymptotic expansion for … Expand. Empirical applications typically rely on some process … Expand. Bias in Estimating Multivariate and Univariate Diffusions. Multivariate continuous time models are now widely used in economics and finance. Empirical applications typically rely on some process of discretization so that the system may be estimated with … Expand.
We derive the asymptotics of the maximum likelihood estimators for diffusion models. The models considered in the paper are very general, including both stationary and nonstationary diffusions. For … Expand. This paper develops a maximum likelihood ML method to estimate partially observed diffusion models based on data sampled at discrete times. The method combines two techniques recently proposed in … Expand.
In this chapter we develop and implement a method for maximum simulated likelihood estimation of the continuous time stochastic volatility model with the constant elasticity of volatility. The … Expand. Parameter estimation and bias correction for diffusion processes. This paper considers parameter estimation for continuous-time diffusion processes which are commonly used to model dynamics of financial securities including interest rates. To understand why the … Expand.
Highly Influenced. View 4 excerpts, cites background and methods. Empirical applications typically rely on some process of discretization so that the system may be … Expand.
View 2 excerpts, cites results. Stochastic differential equations often provide a convenient way to describe the dynamics of economic and financial data, and a great deal of effort has been expended searching for efficient ways to … Expand. Front Matter Pages Stochastic Environment. State Space Notation. Filtering Algorithms. Parameter Estimation. Valuation Model. First Empirical Results.
Implications for Investment Strategies. Summary and Conclusions. Term Structure Model.
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