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Quantitative finance is a multidisciplinary field that relies on mathematical finance, statistics, numerical methods, and computer simulations to perform risk management in decisions involving trading, hedging and investment. Quantitative finance is also known as computational finance. It is closely related to financial engineering. The only distinction between quantitative finance and financial engineering is that financial engineering focuses on the applications of quantitative finance by building tools that will implement the results of the financial models. The primary purpose of financial engineering is to establish the financial risk that certain financial instruments create precisely. The professionals who study and practice quantitative finance are known as quants. They work in the financial markets to develop mathematical models to assist traders and risk management activities in banks and large corporate institutions.
To become a quant, one needs to have a strong background in mathematical finance, engineering or computer science. Quantitative financial analysts often have advanced degrees such as Masters or Ph. D's in the fields of economics, finance, and math. Typically, the study of quantitative finance focuses on;
- Algorithms
- Differential equations
- Linear algebra
- Multi-variable calculus
- Probability theories
- Statistical analysis
- Programming
Quantitative analysts are in such high demand that special actuarial courses and Master's and Ph.D. programs have since been created for students to develop quants. These programs include financial engineering, computational finance, financial reinsurance, operations research, computational statistics, machine learning, and financial analysis.
Types of quantitative finance
Quantitative investment management
Quants in this division become asset managers that use extensive statistical and mathematical modeling methods to develop investment products for financial institutions like banks and insurance companies. They are sometimes hired by clients/investors to become portfolio managers to maintain client accounts.
Front office quantitative analyst
These are quants that work in sales and trading to determine prices, manage risk and identify profitable opportunities for companies. They use algorithmic trading where they develop models to determine trends in value and pricing of investment products and offer information that enables companies to make informed investment decisions.
Library quantitative analysis
Companies hire quantitative finance specialists to develop for them calculated methods of evaluating prices and risk. They use computer programming usually in Java or C++ languages, incorporating finite differential methods in mathematics to predict infinitesimal changes in value in the market of products so that companies can capitalize on them and make profits.
Algorithmic trading quantitative analyst
These are often the highest paid quantitative analysts. This is because of the complexity of the tasks they handle. They use principles of signal processing, game theory, econometrics, and time series analysis to develop sequential models called algorithms that automate the process of predicting trends in financial markets for investment.
Risk managers
Risk managers use mathematical and statistical methods to evaluate the amount of risks in making certain investment decisions. They can also be used by financial institutions as credit evaluators to determine the risks involved in issuing loans to individuals and businesses.
Model validation
Model validation is the analysis of the methods and models developed by other quantitative analysis processes to determine their correctness. Model validators are superior quantitative operation professionals in financial institutions because they always have to deal with the most recent and advanced models and trading techniques across the company.
Quantitative developer
Quantitative developers are computer programmers that assist in implementing and maintaining the different quantitative modes that have been developed. They require advanced knowledge in econometrics and are highly trained in machine language and technology. They act as a bridge between quantitative analysts and software developers.
Quantitative finance draws its techniques from various topics of statistics, probability, and calculus that revolve around differential equations, linear algebra, discrete mathematics, and econometrics. They combine these techniques with computer science, physics, and computer engineering to be able to develop automated models that perform analysis and economic forecasts.
A common task in mathematically oriented quantitative finance would be to develop a model for deciding which stocks are relatively expensive and which stocks are relatively costly in the financial market. The model will comprise of the company's book value to price ratio, the trailing earnings to price ratio, and other different accounting variables. The investment manager will implement the analysis by buying the underpriced stock or selling the overpriced stock to get the maximum value for money of investment.
Career options for quants
Quants are in high demand in the financial sector, and a qualified quantitative finance specialist will be set up for a career in one of the following fields.
Trading strategy development
Quantitative analysts use their techniques specifically to develop methods of maximizing profits when trading in the financial markets.
Portfolio optimization
Portfolio optimization involves the management and maintenance of investments made by individuals or companies in terms of stocks in the financial markets.
Risk management
They are concerned with minimizing the risks involved in making financial decisions by companies.
Asset pricing and liability management
Quants in asset pricing analyze the value and change in value; appreciation and depreciation, of assets to determine their price and value over time.
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