Financial Engineer

As a Financial Engineer/ Financial Mathematician, you will be part of a cross-functional team which is involved in conducting statistical & mathematical deductions using various formula and methods. You will also write or build and use various mathematical/ financial modeling techniques to accurately describe financial situations, economic relations, financial market dynamics, investment flows, financial risks, taxation efficacies, and other relevant issues of practical significance in the financial and economic realm.

You will be using various statistical, data analytical, and financial software to carry out your work. You will write or build different mathematical and financial models as well as algorithm (a set of rules used in calculations or computing or other problem-solving operations using a computer) to solve complex financial problems using computers. 

You will write or build different mathematical and financial models as well as algorithms to predict various future scenarios in the financial and economic realm or space. For example, predicting how the price of a stock (equity share of a company) may change over time; how currency exchange rate may change over time (exchange rate means at the rate in which currency is converted, for example from Indian Rupee to US Dollar); how economic growth rate may change over the next 3 years; out of the total number of people who have a particular health insurance policy, how many people may make a claim over the next 10 years; and so on.

Brief about possible duties

You will have to apply your expertise in forecasting, quantitative analysis, data science, scenario modeling and data visualization. You will also have to collate, assess, analyze, present, report and communicate data/ results, along with implications. These data/ results will be generated through stochastic analyses (analyzed statistically but not predicted precisely), mathematical modeling, and financial modeling. You will have to report these through many means such as online reporting, analytical reports, financial presentations, presentations at conferences, etc. for a variety of audiences using visual tools that can effectively communicate the story behind the numbers.

What is forecasting?

Now, “forecasting” (which will be a regular responsibility), in this case, means to predict future trends of events that may happen specifically due to certain finance-related decisions, allocation of resources or economic relationships, etc.

What is financial modeling?

Financial modeling means writing or developing a set of rules/formulas and algorithms for solving a financial problem or carry out some calculations using financial theories, concepts, and formulas. Such rules/formulas and algorithms are executed using computer software. 

What is mathematical modeling?

Mathematical modeling implies using linear algebra, natural logarithms, calculus, statistics, and the concepts of relations & functions to achieve a particular result or to determine the factors playing a part in an event (such as the rise/ fall of wages or stock price and valuation etc.) or to estimate the values of such factors/ parameters.

The numbers are always drawn from existing real-time values to create huge datasets and apply statistical hypothesis testing to forecast future possibilities.

What is statistical hypothesis testing?

Statistical hypothesis testing or confirmatory data analysis uses a set of random variables, the variations of which are used to test whether a particular “hypothesis” or the basis of observing a process is true or untrue.Commonly, two datasets are compared where usually one is formed through collecting data (called “sampling”) and the other is a synthetic data set from an idealized model.

Some popular techniques

Understand that, you will be involved in using financial and mathematical modeling for forecasting via assessing of large repetitive real-life datasets containing numbers gathered from real-time scenarios to prove a particular point using tools used widely in Mathematics and Statistics such as Random Walks, Monte-Carlo simulation, fuzzy logic, decision tree models, neural network models, linear regression models, Fourier transform, representation theory etc.

Intricate and extensive concepts

These intricate & extensive techniques require profound understanding and knowledge before being logically applied to real existing cases. This further means that professionals practicing in this field are highly qualified individuals with expansive experience in particular academic areas especially Economics, Mathematics or Statistics.

Today, most investment decisions are driven by a pre-programmed set of instructions (algorithms) fixed in a suite of financial software.

These algorithms, that fuel what is universally called algorithmic trading today, come from financial models with different dependent & independent variables such as time, price, and volume. These are commonly called parameters. What investment managers do is just set the values of the variables or parameters in the software.

The software then takes automated decisions to carry out transactions (buy and sell stocks, bonds, currencies, etc.). This automated trading is therefore called algorithmic trading.

This is currently the hottest area in which Financial Engineers/ Mathematicians are finding work with just engineering degrees / Mathematics / Statistics degrees. No prior background in Finance is required.

Algorithmic Trading –how financial modeling is used in making investment decisions in stock markets

Algorithmic trading, automated trade execution and high-frequency trading (HFT-execute a very large number of orders within seconds) at the millisecond timescale were developed to make use of the speed & data processing advantages that computers have over humans. In the 21st century, algorithmic trading has been gaining traction with both retail and institutional traders.

It is widely used by investment banks, pension funds, mutual funds, and hedge funds that may need to perform trades too fast for human traders to react to. In India, 33.33% of the exchange trades are done through algorithmic trading. In the US, it is 70% and in Europe 40%.

In simpler terms

Stock trading was mainly a paper-based activity before electronic trading took over. One needed to be physically present to buy or sell stocks and there were actual stock certificates.

Now, we can write an algorithm and instruct a computer to buy or sell stocks for you when the defined conditions are met. These programmed computers can trade at a speed and frequency that is impossible for a human trader. So now there are markets in which computers trade against other computers.

4 Components of Algorithmic Trading Systems

Data Component

Algorithmic Trading systems use structured data, unstructured data, or both. Structured data includes spreadsheets, CSV files, XML, Databases, etc. Inter-day prices, end of day prices, and trade volumes are usually available in a structured format. Unstructured data include news, social media, videos, and audio.

Model Component

Financial models represent how the algorithmic trading system believes the markets (or the outside world) work. These financial models do one common thing: reducing a complex system into a quantifiable set of rules which describe the behavior of that system under different scenarios.

Execution Component

The model component identifies certain trades and the execution component carries out or performs the transactions. The speed of the execution, the frequency at which trades are made, the period for which trades are held, etc. are factors that need to be satisfied.

Monitor Component

The monitor component is powered by AI basically to make the entire algo trading system adapt to the dynamism of the markets and changing environments.

Key Roles and Responsibilities

As a financial Engineer/ Financial Mathematician, you will be engaged with one or more of the following roles & responsibilities as well as other associated duties:

1. You will apply mathematical or statistical techniques to address issues of practical significance in finance, such as assets valuation, securities trading, investment management, or market regulation.
2. You will investigate methods for financial analysis to create mathematical models used to develop improved analytical tools or advanced financial investment instruments.
3. You will research or develop analytical tools to address issues such as equity portfolio optimization, performance measurement, profit & loss measurement, or pricing models.
4. You will apply your expertise in forecasting, quantitative analysis, data science, scenario modeling and data visualization to help optimize workforce strategy (acquire, retain, develop, motivate & deploy human capital) or assist in increasing/ sustaining shareholders’ interests.
5. You will develop core financial models, using advanced statistical, quantitative, or econometric techniques.
6. You will devise or apply independent tools and techniques for verifying results of analytical procedures.
7. You will collaborate with data engineering & visualization engineers to access and manipulate data, explain data gathering requirements, and display results
8. You will collaborate with product development teams to research, model, validate, or implement quantitative structured solutions for various types of markets economies.
9. You will confer with market experts or analysts on trading strategies, market dynamics or performance for the development of quantitative techniques.
10. You will collate, assess, analyze, present, report and communicate data/ results, along with implications, generated through stochastic analyses (analyzed statistically but not predicted precisely), financial modeling and mathematical modeling through online systems, creating reports, corporate financial presentations, presentations at conferences, etc. for a variety of audiences using visual, recommendation-oriented tools that communicate the story behind the numbers.

• You should have interests for Investigative Occupations. Investigative occupations involve working with ideas and quite a lot of thinking, often abstract or conceptual thinking. These involve learning about facts and figures; involve the use of data analysis, assessment of situations, decision making and problem-solving.
• You should have interests for Conventional Occupations. Conventional occupations involve repetitive and routine tasks as well as fixed processes or procedures for getting things done. These occupations involve working more with data, systems, and procedures and less with ideas or creativity.

Knowledge

• You should have knowledge of Mathematics – Knowledge of arithmetic, geometry, trigonometry, and other mathematical disciplines and their applications.
• You should have basic programming skills in Python and knowledge of basic algebra (algebraic concepts such as functions & variables), basic statistics, linear algebra, and calculus which are all frequently used in programming.
• You should have knowledge of Computers - Knowledge of computer hardware and software, computer programming, computer networks, computer, and mobile applications.
• You should have knowledge of Economics - Knowledge of economic principles and practices; understanding how various resources such as land, labor, and capital are used; how market demands rise and fall; how a country collects and spends money; and similar other economic issues and situations.
• You should have knowledge of Accounting - Knowledge of various principles and methods for maintaining records of commercial and financial transactions and records, preparing various reports and statements, ensuring compliance with commercial and business laws and rules of a country, etc.
• You should have knowledge of analytical and scientific software such as IBM SPSS Statistics, Insightful S-PLUS, SAS, StataCorp Stata, The MathWorks MATLAB, etc; business intelligence and data analysis software such as MicroStrategy, etc.
• You should have knowledge of tools such as R, Python, SQL, Tableau, Visier, Salesforce and Excel to drive analytics and knowledge of Earned Value Management Systems (EVMS) processes and practices.

Skills

• You should have Systems Analysis Skills - determining how a system should work and how changes in conditions, operations, or the environment will affect outcomes.
• You should have Systems Evaluation Skills - identifying measures or indicators of system performance and the actions needed to improve or correct performance, relative to the goals of the system.
• You should be skilled in Computer (Data Analysis and Visualisation) - using SPSS, SAS, SAP Hana, IBM Cognos, MATLAB, Minitab, Google Analytics, RapidMiner, R, Apache Hadoop, Apache Spark, Tableau, Visual Basic, etc.
• You should have Quality Control Analysis Skills - conducting tests and inspections of products, services, or processes to evaluate quality or performance.
• You should have Critical Thinking skills- Skills in the analysis of complex situations, using logic and reasoning to understand the situations and take appropriate actions or make interpretations and inferences.
• You should have Judgment and Decision Making Skills - considering pros and cons of various decision alternatives; considering costs and benefits; taking appropriate and suitable decisions.
• You should have Problem Solving Skills - Skills in analysis and understanding of problems, evaluating various options to solve the problems and using the best option to solve the problems.
• You may need Programming Skills - writing computer programs for various applications, installation of computer programs and troubleshooting of problems in computer programs or software.

Ability

• You should have Deductive Reasoning Ability - apply general rules and common logic to specific problems to produce answers that are logical and make sense. For example, understanding the reasons behind an event or a situation using general rules and common logic.
• You should have Problem Sensitivity - The ability to tell when something is wrong or is likely to go wrong. It does not involve solving the problem, only recognizing there is a problem.
• You should have Inductive Reasoning Ability - to combine pieces of information from various sources, concepts, and theories to form general rules or conclusions. For example, analyzing various events or situations to come out with a set of rules or conclusions.
• You should have Information Ordering Ability - to arrange things or actions in a certain order or pattern according to a specific rule or set of rules (e.g., patterns of numbers, letters, words, pictures, mathematical operations).
• You should have Fluency of Ideas - The ability to come up with several ideas about a topic (the number of ideas is important, not their quality, correctness, or creativity).

Personality Traits

• You are always or mostly careful about your actions and behavior.
• You are always or mostly disciplined in your action and behavior.
• You are always calm or generally remain calm in most situations.
• You are imaginative sometimes.
• You are always or mostly organised in your day-to-day life and activities.