December 14, 2023

7 min read

Fintech and Innovation

Quantitative finance: an innovative approach to investing
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  • What is quantitative finance?

  • What is quantitative analysis?

  • The pros of a quantitative analysis

  • Quantitative investing: what is it and how does it work?

With new approaches and strategies supporting the traditional methods in some cases and completely replacing them in other situations, the world of financial investment has undergone major changes over the past decades.

For a number of years now, we’ve increasingly been hearing about quantitative finance, also known as quantum finance, which has steadily been gaining prominence in the financial investment sector.

What is quantitative finance?

For a better understanding of the topic discussed in this guide, we start from the definition of quantitative finance: a branch of investment management that uses mathematical and statistical methods to analyse the financial markets, in particular the investment opportunities within a broad range of investment categories.

While quantum finance first made an appearance during the second half of the 20th century, some models and key theories date from the early 1800s.

That being said, the first real cornerstone of quantum finance was laid by the French mathematician Louis Bachelier in 1900 with the publication of his doctoral thesis “The Theory of Speculation” which outlines an evaluation model for share options.

Midway through the 20th century we saw the publication of important works by two economists regarded as the fathers of quantitative finance: Harry Markowitz and Robert Merton.

The first presented his doctoral thesis in 1952, covering the modern theory of diversification-based portfolios, while the second one gained acclaim for his pioneering formula to value derivatives.

Technological development over the past thirty years has played an important role in the evolution of quantitative finance and has led to a rise in popularity of quantitative analysis.

What is quantitative analysis?

If we were to define quantitative analysis, we could say that it is a financial analysis technique used to try to understand the behaviour of the financial markets with the help of complex mathematical and statistical models.

The aim of quantitative analysis is to understand what causes market fluctuations, to predict them and to anticipate them in one way or another.

Quantitative analysis starts from a large number of variables, which each are assigned a numerical value on the basis of which quantitative analysts create a mathematical replica of reality.

Quantitative analysis and qualitative analysis: what are the differences?

In the light of the foregoing, it becomes easier to understand the difference between quantitative analysis and qualitative analysis.

As these two different research methodologies are also complementary, their combined use produces the best and most reliable results.

A quantitative analysis is by and large based on numerical data, randomly selected from large samples.

This type of analysis is more objective and usually focuses on measurable quantities while a qualitative analysis is more subjective, involves data that cannot be quantified and provides an answer to the question “why” and “how” certain events occur.

The pros of a quantitative analysis

Quantitative and qualitative analyses each have their strengths and weaknesses, which is why these two methodologies combined provide far greater insight.

Let’s concentrate on a number of the main benefits of a quantitative analysis for a minute.

Faster decisions and greater returns

Thanks to the advances in quantitative technology, automated calculations can be performed in the blink of an eye. There is no way that man would be able to analyse big data so quickly and accurately.

Rational computation: a more objective strategy and fewer errors

Another advantage of quantitative analysis is the rationality of the computation: models and numbers are law.

Quantitative analyses make it possible to harmonise the evaluation criteria, to devise a scientific framework and to streamline internal procedures.

This system of automated buying and selling can be executed in a coherent manner, without human interference, feelings, preconceptions or subjective speculation.

100 % verifiable strategies

Quantum systems allow us to test theories scientifically, to validate hypotheses and to adapt our strategies.

4. Limited risk and more market knowledge

While maximising returns is the main objective, quantum analysis is also a tool for financial risk management.

On the basis of historical data and scientific hypotheses, the algorithms can continuously record the minimum turnover of securities, ever before it comes to serious financial losses.

Quantitative investing: what is it and how does it work?

Quantitative analysis is used in many areas and is also widely applied in the field of financial investment.

More than two decades on, quantitative investing, which does differ significantly from the “traditional” investment methods, has become more commonplace.

One approach is based on shares being selected by investment specialists who assess companies by analysing their balance sheet, financial accounts, management reports, etc.

But quantitative investing differentiates itself in particular by its systematic and non-emotional approach: every choice is effectively based on objective data, never on human emotion.

Quantitative investing doesn’t rely on human judgment to take investment decisions: everything revolves around systematic and repeatable processes.

Quantitative investment strategies allow us to avoid behavioural traps, and, in sum, prevent that emotions start clouding our judgment and, hence, interfere in our investment decisions.

The use of a quantitative algorithm makes the quantitative analysis of data far more efficient, with the result that shares, for one, can be assessed and processed much faster, meaning that any investment decisions can be taken far quicker.

Quantitative investment managers are certainly not blind to these advantages, for technology now gives them access to innovative strategies that offer greater diversification compared to the traditional strategies, not to mention helps to keep costs down.

The term quantitative portfolio management denotes selecting securities on the basis of numerical and statistical data which makes it possible to make the very best investment choices.

Those very principles also underpin quantitative trading, a form of investing that focuses on the use of quantitative data to compute the probability of a given outcome producing itself and, hence, to decide which securities to buy or sell.

These days, more and more quantitative investment solutions are coming on stream, which is reflected in the broad range of opportunities across all the main investment categories, all with the aim of maximising returns at limited risk.

Frequently asked questions about quantitative finance

The definition of quantitative analysis (QA) in terms of the financial market is far easier to understand than its intricacies. Unlike fundamental and technical analyses, quantitative analysis is a novel way of approaching risk analysis. In contrast to qualitative analysis, which is based on a subjective analysis of non-quantifiable data, quantitative studies use mathematical and statistical models. Quants identify and create the algorithmic trading models and analyse the quantitative data to determine the value of a financial asset and predict the price and the financial risk of securities, the automated way.

The primary purpose of quantitative analysis in the field of finance is to better assess the value of financial assets and their derivatives, to understand the causes of fluctuations in the financial markets and to anticipate them. This is done by developing rule-based, systematic investment strategies that can capitalize on market inefficiencies.

You are probably wondering how quantitative analyses in finance are performed? Quantum algorithms operate on the basis of established rules and analyse the financial markets at predetermined intervals. These then instantly trigger orders to buy or sell securities. They also produce data to define profitable investment strategies, thereby offering the best returns in function of the chosen risk level. Each algorithm devised by a quant must obviously be maintained and monitored by the person who created it. This means that quants must continuously check whether their algorithm operates flawlessly, which implies rigorous testing during the development and optimisation process.

Quantitative analysis has many advantages, the top 4 ones of which being:

  1. Analysis of Big Data, faster decisions for greater returns: advances in quantitative technology means that calculations can be performed automatically, in a fraction of a second, and in an international context at that. No human on earth would be able to perform an analysis so quickly and so accurately. It is therefore no longer necessary to hire costly teams of portfolio analysts and managers.

  2. Rational calculations ensure a more objective strategy, with fewer errors: Patterns and numbers rule. Quantitative analyses allow us to standardise the evaluation criteria, to establish a scientific thinking pattern and internal processes. This automated sale/purchase discipline is executed in a coherent manner, without human interference, emotions, preconceptions or subjective speculation.

  3. 100 % testable strategies for a more certain future: Quant systems allow us to test theories scientifically, to revalidate hypotheses and to readjust strategies. The power of backtesting and automated calculations allow us to negotiate a quasi-infinite number of strategies and portfolios, on a worldwide scale.

  4. Risk reduction and knowledge of the market trends: While the primary goal is maximising returns, quantum analysis is also a tool for managing financial risk. On the basis of historical data and scientific hypotheses, the algorithms can continually detect the slightest trend in financial securities, ever before they result in serious financial losses.

Quants, short for quantitative analysts, have a mathematical and financial degree, an in-depth knowledge of IT, programming and automation processes. They operate in the financial and banking sector, and in companies and other institutions and businesses involved in the world of finance. Their job is to perform quantitative analyses on mathematical methods, reason why they can be qualified as “information mathematicians”. Their concepts can range from simple financial ratios to extremely elaborate algorithms. The algorithms they develop allow us to resolve complex financial problems and to enhance financial risk management.

Harry Markowitz and Robert Merton are regarded as the fathers of quantitative finance: Markowitz, via his investment strategy, outlined in the article “Portfolio Selection” (Journal of Finance, 1952) and Merton, for his mathematical work on valuing derivative products. The first quants played a key role during the 90s, in particular in investment banks, which flourished at the time.

To summarise
  • quantitative finance has become increasingly widespread in financial investments.

  • quantitative analysis is based on complex mathematical and statistical models.

  • quantitative investing opens new frontiers.

Good to know:
Quantum analysis is also a tool for financial risk management.