A young scholar tells the story of the physicists and mathematicians who created the models that have become the basis of modern finance and argues that these models are the "solution" to--not the source of--our current economic woes.

Provides graduate students and practitioners in physics and economics with a better understanding of stochastic processes.

In My Life as a Quant, Emanuel Derman relives his exciting journey as one of the first high-energy particle physicists to migrate to Wall Street. Page by page, Derman details his adventures in this field—analyzing the incompatible personas of traders and quants, and discussing the dissimilar nature of knowledge in physics and finance. Throughout this tale, he also reflects on the appropriate way to apply the refined methods of physics to the hurly-burly world of markets.

In this book, Dr Mak views the financial market from a scientific perspective. The book attempts to provide a realistic description of what the market is, and how future research should be developed. The market is a complex phenomenon, and can be forecasted only with errors — if that particular market can be forecasted at all.The book reviews the scientific literatures on the financial market and describes mathematical procedures which demonstrate that some markets are non-random. How the markets are modeled — phenomenologically and from first principle — is explained.It discusses indicators, which are quite objective, rather than price patterns, which are rather subjective. Similarities between indicators in market trading and operators in mathematics are noted, and particularly, between oscillator indicators and derivatives in Calculus. It illustrates why some indicators, e.g., Stochastics, have limited usage. Several new indicators are designed and tested on theoretical waveforms to check their validity and applicability. The indicators have a minimal time lag, which is significant for trading purposes. Common market behaviors like divergences between price and momentum are explained. A skipped convolution technique is introduced to allow traders to pick up market movements at an earlier time. The market is treated as a nonlinear phenomenon. Forecasting of when the market is going to turn is emphasized.

A careful examination of the interaction between physics and finance. It takes a look at the 100-year-long history of co-operation between the two fields and goes on to provide new research results on capital markets - taken from the field of statistical physics. The random walk model, well known in physics, is one good example of where the two disciplines meet. In the world of finance it is the basic model upon which the Black-Scholes theory of option pricing and hedging has been built. The underlying assumptions are discussed using empirical financial data and analogies to physical models such as fluid flows, turbulence, or superdiffusion. On this basis, new theories of derivative pricing and risk control can be formulated.

Positive feedback--when A produces B, which in turn produces even more A--drives not only abrupt climate changes, but also disruptive events in economics and finance, from asset bubbles to debt crises, bank runs, even corporate corruption. But economists, with few exceptions, have ignored this reality for fifty years, holding on to the unreasonable belief in the wisdom of the market. It's past time to be asking how markets really work. Can we replace economic magical thinking with a better means of predicting what the financial future holds, in order to prepare for--or even avoid--the next extreme economic event? Here, physicist and acclaimed science writer Mark Buchanan answers these questions and more in a master lesson on a smarter economics, which accepts that markets act much like weather. Market instability is as natural--and dangerous--as a prairie twister. With Buchanan's help, perhaps we can better govern the markets and weather their storms.

Risk control and derivative pricing have become of major concern to financial institutions, and there is a real need for adequate statistical tools to measure and anticipate the amplitude of the potential moves of the financial markets. Summarising theoretical developments in the field, this 2003 second edition has been substantially expanded. Additional chapters now cover stochastic processes, Monte-Carlo methods, Black-Scholes theory, the theory of the yield curve, and Minority Game. There are discussions on aspects of data analysis, financial products, non-linear correlations, and herding, feedback and agent based models. This book has become a classic reference for graduate students and researchers working in econophysics and mathematical finance, and for quantitative analysts working on risk management, derivative pricing and quantitative trading strategies.