What is Quantitative Finance?
Quantitative finance deals with financial mathematics and statistical analysis to determine the risk associated with an investment portfolio or asset class. This is done by analyzing historical data over a long period of time, which allows the individual to determine the potential for loss and gain. In financial mathematics, quantitative finance is a substantial branch of pure and applied mathematics. It plays a role in the process of investment decision-making. Although the field deals with “mathematical models and tools” related to investment decisions, it is more than just using numbers to make financial decisions. Since its inception in the early 1970’s, financial mathematics has expanded far beyond the use of linear models and solutions in finance. Mathematical models in finance make up a vital part of solving problems in decision-making and risk management for investors and managers of capital markets.
The field of quantitative finance covers a wide range of topics from the fundamentals of mathematics to advanced mathematics, statistics and computation. Quantitative finance is used almost everywhere from hedge funds to investment banks as well as large corporations. In the 1990’s as the popularity of hedge funds grew many firms started adding more ‘quants’ into their investment processes.
Why Should Investors Consider Quantitative Finance?
Investors have long been using quantitative tools in their financial decisions, but recently they have been doing so more often and with a greater variety of tools than usual. Why has this happened? The short answer is that many investors have realized that they can use mathematical models to help fine tune their investment strategies and reduce overall risk. They are more frequently turning to quantitative finance tools to help execute their trades.
Investors are increasingly relying on financial data to make decisions, but they are also realizing that the financial data alone is not enough. The key is using the appropriate mathematical models in conjunction with financial data. Investors who don’t understand the underlying concepts behind quantitative finance may not be able to properly interpret the resulting data and use it in making investment decisions.
What Are Some Common Pitfalls of Investors Who Are Using Mathematical Models?
The field of quantitative finance relies heavily on special functions known as stochastic processes which are used to model random variables or risk factors in mathematical methods of analysis or optimization of systems under uncertainty. In many instances, financial mathematics is applied to calculating the probability of risk factors as a result of a financial decision.
The most common mistakes investors make when dealing with mathematical models are those described in the following.
Confusing Models With Mathematics: Mathematical models are models used to represent real-world processes, systems, and/or objects. They differ from mathematical laws in that they can be used as a means of understanding a system subject to random events. Models often have logical relationships that represent logical relationships between processes or systems which may or may not exist in reality. As with any models, they must be tested against reality to ensure the correctness of their assumptions and conclusions drawn from their results.
Mismatching Models To The Objective: There are many types of mathematical models in financial markets. Investors must consider what type of model will work best for the specific objective they are trying to accomplish. For example, traders who want to be real-time price risk managers might use a stochastic volatility model while investors who want to hedge market risk would use an option pricing model.
Insufficient Understanding Of Model Assumptions And Initial Conditions: All mathematical models have certain assumptions which are used in deriving their results. The accuracy of the results is dependent on how well the assumptions reflect reality. Before applying any mathematical models investors should thoroughly understand the assumptions and initial conditions used in any analysis or optimization implemented using mathematical models.
Conclusion
The field of quantitative finance is growing rapidly alongside the growth of financial markets. It is used in nearly every aspect of financial decision-making and risk management. It is important that investors who manage capital consider the use of quantitative finance tools to guide their investment decisions. As with any investment decisions, they should thoroughly understand the investment strategies, risks, and possible rewards involved in using these tools. Where investors and managers lack in knowledge, they are advised to not cut corners but reach out to consultants to get the necessary help required. Fintalent, the hiring and collaborative platform for tier-1 Strategy and M&A consultants, has a pool of world class finance experts skilled in all aspects of quantitative an financial analysis available to help out investors and managers that require professional assistance.
