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A quantitative analyst or, in financial jargon, a quant is a person who specializes in the application of mathematical and statistical methods – such as numerical or quantitative techniques – to financial and risk management problems. Similar work of industrial mathematics is done in most other modern industries, but the work is not always called quantitative analysis.〔See Definition in the Society for Applied and Industrial Mathematics http://www.siam.org/about/pdf/brochure.pdf〕 Although the original quantitative analysts were "sell side quants" from market maker firms, concerned with derivatives pricing and risk management, the meaning of the term has expanded over time to include those individuals involved in almost any application of mathematics in finance, including the buy side.〔Derman, E. (2004). My life as a quant: reflections on physics and finance. John Wiley & Sons.〕 Examples include statistical arbitrage, quantitative investment management, algorithmic trading, and electronic market making. ==History== Quantitative finance started in 1900 with Louis Bachelier's doctoral thesis ''Theory of Speculation''. Harry Markowitz's 1952 Ph.D thesis "Portfolio Selection" and its published version〔Markowitz, H. (1952). Portfolio selection *. The journal of finance, 7(1), 77-91.〕 was one of the first efforts in economic journals to formally adapt mathematical concepts to finance. Markowitz formalized a notion of mean return and covariances for common stocks which allowed him to quantify the concept of "diversification" in a market. He showed how to compute the mean return and variance for a given portfolio and argued that investors should hold only those portfolios whose variance is minimal among all portfolios with a given mean return. Although the language of finance now involves Itō calculus, management of risk in a quantifiable manner underlies much of the modern theory. In 1965 Paul Samuelson introduced stochastic calculus into the study of finance.〔Samuelson, P.A. (1965), ‘‘Rational theory of warrant pricing’’, Industrial Management Review, Vol. 6 No. 2, pp. 13-32〕〔Henry McKean the co-founder of stochastic calculus (along with K Ito) wrote the appendix: see McKean, H.P. Jr (1965), ‘‘Appendix (to Samueson): a free boundary problem for the heat equation arising from a problem of mathematical economics’’, Industrial Management Review, Vol. 6 No. 2, pp. 32-9.〕 In 1969 Robert Merton promoted continuous stochastic calculus and continuous time processes. Merton was motivated by the desire to understand how prices are set in financial markets, which is the classical economics question of "equilibrium," and in later papers he used the machinery of stochastic calculus to begin investigation of this issue. At the same time as Merton's work and with Merton's assistance, Fischer Black and Myron Scholes developed the Black–Scholes model, which was awarded the 1997 Nobel Memorial Prize in Economic Sciences. It provided a solution for a practical problem, that of finding a fair price for a European call option, i.e., the right to buy one share of a given stock at a specified price and time. Such options are frequently purchased by investors as a risk-hedging device. In 1981, Harrison and Pliska used the general theory of continuous-time stochastic processes to put the Black–Scholes model on a solid theoretical basis, and showed how to price numerous other derivative securities.〔Harrison, J. Michael and Pliska, Stanley R., "Martingales and Stochastic Integrals in the Theory of Continuous Trading", in Stochastic Processes and their Applications, North Holland Publishing Company, 1981. (Harrison and Pliska paper )〕 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Quantitative analyst」の詳細全文を読む スポンサード リンク
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