Quantitative Investing Takes Away Human Emotion

September 16, 2015

The word “algorithm” is an increasingly popular term used in finance. Along with robo-advice and smart beta, it has captured the interest of industry pundits and journalists. But what really is an algorithm? And how and why is it used across the financial services sector?

Definition At Hand

The Oxford dictionary defines the word algorithm as “a process or set of rules to be followed in calculations or other problem solving operations, especially by a computer”.

In simpler terms, an algorithm is just a series of steps to perform a certain task. There are three main ingredients to an algorithm: inputs, a set of rules for the process to follow to perform the task at hand, and an output.

Considering that in essence an algorithm is a well-defined process of steps for accomplishing a certain task, it is easy to see how computers and algorithms go together like bread and butter. With the advent of computers, more and more sophisticated algorithms have been devised and become available in our daily lives.

But algorithms are not limited to the financial sector – we see them being used everywhere, whether it be a Google search algorithm, auto-matching couples on online dating sites, driving instructions from a GPRS device, online loan approvals based on the information supplied about an individual’s financial background, or even cooking a dish by following a recipe.

Applying Algorithms To Finance

For a financial adviser, the risk-rating process of a client is also an algorithm. The task is to assess the risk level that would be most suitable for that particular client. The inputs are the answers given by the client about his or her financial background and goals, time horizon for investment, preferences, and risk appetite.

Algorithms can crunch heaps of data in a fraction of a second. It is unsurprising, then, that algorithms are used extensively in finance ranging from the simplest to the very sophisticated. Quants and financial engineers have developed algorithms to predict price movements, develop arbitrage strategies with a view to exploit price discrepancies, price certain financial instruments, identify and mitigate various sources of financial risk in a plethora of various scenarios, match orders and route trades, for market making.



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