The terms financial mathematics and financial economics are often interchanged and thought of as the same discipline. Financial analysis is a different discipline all-together that uses elements from financial mathematics and financial economics in doing an in-depth analysis of the targeted firm regarding its financial sustainability. Let’s compare and see how they differ.
What is Financial Mathematics?
Financial mathematics can be understood as the field that is concerned with mathematical applications in finance. Solving financial problems using mathematical methods is the main focus of financial mathematics. Financial mathematics is alternatively termed as quantitative finance and computational finance. The major applications of quantitative mathematics are in the field of securities valuation, risk management, and portfolio structuring, etc. by financial institutions like investment banks, hedge funds, and insurance companies. Financial mathematics also plays a crucial role in commodities-based industries. The valuation of various financial instruments requires mathematical modelling of financial markets.
What is Financial Analysis?
Financial analysis can be defined as the process of evaluating a business or a project using different techniques such as ratio analysis that helps to ascertain the suitability and viability of the business. Major applications of financial analysis are in evaluating economic trends, building financial policy, etc. The results obtained after a rigorous financial analysis help different stakeholders in decision making. Internally conducted financial analysis helps managers to make an informed decision or study successful historical trends. Financial analysis is further classified into two parts -fundamental analysis and technical analysis, let’s delve into the details of both the techniques.
Fundamental analysis uses the approach of evaluating securities and conducting financial analysis by measuring the intrinsic value of the security. Fundamental analysis takes a more comprehensive view of the organisation and considers different factors such as economic conditions, industry outlook, management of the company, etc. It also evaluates the company on account of assets, liabilities, expenses, income generated, etc.
Technical analysis is different from the fundamental analysis technique for evaluating the viability of the company. It has only two inputs in the whole evaluation method. The two elements of this technique are stock prices and volume. It assumes that stock prices reflect other important fundamentals of the company. This method uses stock charts and other tools to predict the future trends of the stock.
What is Financial Economics?
Financial economics is a discipline in economics that is concerned with the analysis of the use and distribution of resources in the market. It studies how different factors such as opportunity cost, risk, time, etc. play a crucial role in creating incentives or disincentives for any specific decision. It involves employing complex financial models to test the variables influencing a particular decision. Rational consumer behaviour is an important and common assumption with these models. Microeconomics, econometrics and basic accounting concepts form the pillar of this discipline of economics. Financial economics requires a basic understanding of the concept of probability and statistics.
Comparing the three
Now that we have individually learned about all three disciplines the difference is very evident. Let’s compare how they differ from each other, starting with the comparison between financial mathematics and financial analysis. Financial mathematics is a field of applied mathematics that is concerned with the financial markets whereas financial analysis is the assessment of different elements that paints a picture of the functioning of the business which will help different stakeholders in informed decision making. Financial economics is heavily concentrated on two aspects of finance, asset pricing and corporate finance. The role of a financial economist requires collecting and analysing statistical data using different sampling and econometric techniques.