Explaining Financial Theory

Most of us relate finance to anything that has to do with money. We might finance a car, for instance, by taking out a loan and paying for our new ride over time. That definition of finance is thus correct but it presents only a tiny fraction of the whole picture.

The word 'finance' represents a discipline to be studied, a career field and anything that involves money and assets. So complex is the concept of finance - so multi-layered, that entire systems have been devised to manage and facilitate the transfer of money, currency and assets.

Naturally, there must be a way to execute these functions; that's FinTech's role but that's a wholly separate topic to explore. In this article, we take a look at some of the theories that underpin finance:

• Financial Mathematics and Quantitative Analysis
• Quantum Finance
• Behavioural Finance
• Experimental Finance
• Managerial Finance
• Financial Economics

You might raise an eyebrow at that last bullet point: isn't economics all about money? If so, what's the point of financial economics?

As we explained in our overview article, finance and economics are not synonymous but they are related concepts. Read on to find out more.

Understanding Financial Economics

Briefly, to make the distinction between finance and economics clear: real value in economics revolves around goods and services, whilst finance focuses on shares, prices and interest rates.

Thus, financial economics looks at how those two discrete aspects are related; its models centre on risk management, decision making and pricing in financial markets.

Financial economics comes under a great deal of fire  because of the long-held idea that price changes should follow distribution on one hand, and rational expectations versus market efficiency on the other. The two resultant challenges, departures from normality and rationality, thus take substantial work to overcome.

The common assumption is that financial decision-makers act rationally and that asset returns are 'normally' distributed, that is that they will follow a random walk.

In mathematics, that means random 'steps' in a mathematical space. If you've ever used a number line, you're familiar with the concept of random steps: X = 0 and a step in either direction is equally probable, for example.

But how does that apply to financial economics?

The 'random walk' assumption is undermined by empirical evidence that suggests risk managers, traders and analysts modify models as the current market states require. Likewise, the concept of rational action is thwarted by empirical evidence suggesting that financial decision makers act in many ways that are not in the least rational.

Behavioural finance is doing a fine job of disputing the long-held assertion that decision-makers act rationally, too. You'll read more about this sub-discipline later in this article.

In a nutshell, financial economics studies how rational investors make their decisions about investments and how they manage those decisions.

Managing finance is by no means a simple feat; like so much involving finance, currency and markets, it is a multi-layered proposition that you need to understand to be knowledgeable about finance.

What Is Experimental Finance?

This branch of financial theory is not difficult to understand; its name gives a clue to its purpose. At its most basic, the goal is to establish various market settings and conditions for agents to analyse participants' behaviour and the resulting trade flows. Naturally, price setting mechanisms, information distribution and market returns all factor into the studies' final output.

The purpose is twofold: first, to prove valid existing theories and, second, to extend those theories to other financial decisions and activities.

Some experiments are completely hypothetical. They take place in a laboratory setting and involve willing participants who answer a series of questions. Their answers are then compared to a control group whose financial experiences represent a baseline for that comparison.

Other experiments may consist of randomized trials or controlled field studies in which participants are treated in real-world conditions rather than in a laboratory-created environment. In that same vein we find natural experiments, essentially an empirical study of participants' actions and decisions under various sets of conditions - for instance, how they decide when exposed to a controlled set of variables and how their decisions change with a change of one variable.

Natural experiments are popular in financial and economic studies because they present easy interpretations of underlying assumptions that identify each participant and/or condition.

However, lab experiments are the most common, in part because the controlled setting presents little opportunity for contamination of experiment inputs or the resulting data. Also, they allow for a more accurate determination of causality - the influence of one state/object/event on a process or condition.

Still, experimental finance presents many advantages, particularly if the experiments are carefully designed. One such advantage is that, by altering only one variable at a time and keeping all other variables under control, the need for alternate results interpretation is eliminated.

Other challenges such as self-selection bias and unobservable variables (like those found in traditional analyses of experiment data) are largely avoided, too.

Defining Managerial Finance

From hiring additional personnel to discontinuing a product line, every managerial decision comes with a financial question baked in. Thus, any such question falls under the purview of managerial finance.

Managers plan, direct and control operations in their concerns so the techniques they develop and use to address those financial questions related to the managerial decisions they have to make. This sub-discipline addresses two aspects of finance: managerial accounting and corporate finance.

Corporate finance is, of course, the overall health of a corporation; its financial structure and managerial decisions impact the company's capital - in other words, its bottom line and how much money and assets it has to work with. By contrast, managerial accounting tells the company's management about the firm's performance and profitability,

Keep in mind that the practice of accounting is separate from studying and applying managerial finance; a position that does not have an active hand in the day-to-day running of a company. It concerns examining and assessing financial techniques for suitability and viability to an application rather than actually putting financial techniques to work.

Also, remember that managerial finance keeps an eye on the overall financial health of a company, so anything involving business optimization and generating revenue over the long haul will look to managerial finance models to develop advantageous strategies. Often, tried and true methods of corporate finance - capital budgeting and optimizing cash flow enjoy renewed scrutiny to ensure they are still sound strategies for a given situation.

Otherwise, standard cost and profitability analyses such as activity-based costing and cost-volume-profit analysis suffice, but only so long as the company's overall financial health is not projected to suffer.

How does managerial finance fit into the overall framework of financial systems? Find out in our companion article.

Unpacking Financial Mathematics

Before getting into financial mathematics, let's touch on the two remaining categories of financial theory: quantum finance and behavioural finance.

Lately, we've all heard the phrases 'the markets are spooked', 'markets are plummeting' and 'markets are skittish'.

Obviously, markets are not entities capable of emotion or action. When such phrases are used, they're meant to represent investor sentiment or action over some current happening. Elon Musk buying Twitter is a recent example of such. In a nutshell, these phenomena describe behavioural finance.

How investors - not markets - behave or, more specifically, the psychological makeup that drives investor behaviour is the foundation of behavioural finance. Behavioural finance analysts model the psychological factors that drive investors to react to market fluctuations as they do and then forecast financial activity based on those models.

They also look at empirical studies that show deviations from classic behavioural economics.

By contrast, quantum finance leaves investors and the factors that drive them out of the picture to focus on the problems inherent in finance, such as efficiently pricing financial instruments in a rapidly fluctuating market.

If by this sub-discipline's name, you guessed that finance has borrowed from physics, you are correct. Quantum physicists and economists have engineered the systems of computing in finance. These econophysicists, the people who work in this branch of financial theory, have devised several models to guide their work, the quantum binomial model and the quantum continuous model, to name just two.

Clearly, this field is maths-heavy; more so even than the financial mathematics sub-discipline, which we look at, now.

Simply put, it's applied mathematics for the financial markets with a targeted focus on modelling derivatives such as interest rates and credit risks. Good on you if you caught that one represents gains and the other, potential losses. This dual-track discipline breaks down into separate analytical branches.

One revolves around risk-neutral probability while the other dwells on actual probability.

Other areas of finance that draw on financial mathematics include insurance and portfolio management on the client side, and a variety of securities - government, asset-backed and corporate among them.

Now, explore the three main divisions of finance: personal, public and corporate.

*Disclaimer: The content of this article is intended for information purposes only, and should not be considered or used as financial advice.