Rajandran R Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, USDINR and High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in)

Computational Finance : The Quants Heaven

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If you have an aptitude in Computer Programming, Mathematics and Finance then you are looking for the term known as Computational Finance or Financial Engineering. Computational Finance helps in making investment, trading and hedging decisions using Computer Intelligence, mathematical-numerical analysis and simulations. Generally, individuals who fill positions in computational finance are known as “quants”, referring to the quantitative skills necessary to perform the job. The main aim of Computational Finance is to calculate the financial risk of any financial problem by modeling it using computer intelligence and mathematical analysis.

Computational Finance uses the mathematical tools like Probability Distribution, Calculus, Differential Equations, Numerical analysis etc. to set up a model for a financial problem. One of the very famous models is the Black-Scholes model which is used for Option Pricing model. The model develops partial differential equations whose solution, the Black–Scholes formula, is widely used in the pricing of European-style options. For a detailed information of the model refer to [3].

Computational finance is a wide umbrella of disciplines — mathematical science, and the use of computer simulations to explore the potential risks as well as the probable outcomes of trading, hedging and investment decisions. Applications of Computational finance are used in the fields of investment banking, financial risk management, options pricing, strategic planning and so on. Concepts such as Monte-Carlo simulations, portfolio selection & optimization and high frequency data analysis are the basic topics in computational finance

Some of the current work going on in this field are :-

1) Agent-Based Artificial Markets

2) Derivatives trading

3) Investment Banking

4) Forecasting

5) Security Trading

The 10 Quant schools are Carnegie Mellon University, Columbia University, Cornell University, New York University, Princeton University, Rutgers University, Stanford University, University of California at Berkeley, University of Chicago and University of Michigan as per the report from advanced trading

References

[1] Computational Finance, Edward P.K. Tsang and Serafin Martinez-Jaramillo, Centre for Computational Finance and Economic Agents (CCFEA)

[2] http://en.wikipedia.org/wiki/Computational_finance

[3] http://en.wikipedia.org/wiki/Black–Scholes

Rajandran R Telecom Engineer turned Full-time Derivative Trader. Mostly Trading Nifty, Banknifty, USDINR and High Liquid Stock Derivatives. Trading the Markets Since 2006 onwards. Using Market Profile and Orderflow for more than a decade. Designed and published 100+ open source trading systems on various trading tools. Strongly believe that market understanding and robust trading frameworks are the key to the trading success. Writing about Markets, Trading System Design, Market Sentiment, Trading Softwares & Trading Nuances since 2007 onwards. Author of Marketcalls.in)

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