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 25 of october Profiting from U.S. presidential elections might just be the ultimate form of democratic capitalism. So when the media spin surrounding the 2004 elections started gaining momentum, I decided to join the politically inspired pollsters and bumper sticker peddlers in finding and exploiting the inefficiencies resulting from predicting election results. I suppose it should not have been surprising that the time tested Arbitrage Pricing Theorem was equally applicable in the political arena...
Learn more about Presidential Arbitrage and how you can profit from it.
- 4 of november
Quantitative finance is a challenging subject. However, financial practitioners don't exactly go out of their way to make the topic more accessible to outsiders. One problem is the language barrier, separating quants from the rest of the world. The following article makes light of a profession that has a tendency to take itself too seriously.
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Introductory Mathematics Textbooks
Modern finance requires a solid command of mathematics. Many problems in finance require knowledge of calculus, differential equations, linear algebra, probability, stochastic processes, and statistics. The books in this category cover said areas of mathematics; for introductory texts on stochastic calculus please refer to the titles listed in the finance and educational sections of this website.
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Advanced Calculus with Applications in Statistics (Andre Khuri) -- This underrated book summarizes key findings of single- and multi-variable calculus as they relate to statistics. I recommend this book as a refresher of Newtonian calculus and an introduction to its applications in probability and statistics. The math presentation is very clean and many of the proofs are quite elegant. |
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Introduction to Numerical Analysis (F. B. Hildebrand) -- It is often handy to have access to a good reference on numerical analysis. This text is slightly dated but it has served me quite well. |
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Optimization Theory With Applications (Donald Pierre) -- Numerical optimization is another area of interest to finance professionals. Most institutions use commercial software packages to perform optimizations. However, it is useful to have at least a high-level understanding of the algorithms deployed in these applications. |
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Stochastic Processes: An Introduction (P. W. Jones et al) -- This is one of the least painful introductions to elementary stochastic processes. Recommended to students. |
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Probability and Random Processes (Geoffrey R. Grimmett et al) -- The same authors have also released a companion guide named One Thousand Exercises in Probability. Together, they form a pretty good introduction to probability. |
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Stochastic Differential Equations (Bernt Oksendal et al) -- This book is frequently recommended to students of quantitative finance. I agree it is a good book but probably a bit difficult as an introduction. |
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Mathematical Techniques (D. W. Jordan et al) -- With the exception of stochastic processes, all of the areas mentioned in the introduction of this page are cataloged in this book. Note that the intended target audience of this text is engineers and not mathematicians. Nice reference. |
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