Investing can be very emotional. The people, products, and history of legendary companies can lead investors to become attached to a particular security. The prospect of gaining or losing a significant amount of money can make investors behave irrationally. Potential highs, lows, and feelings attached to investing can disturb the ultimate goal of making money. Focusing on the latter and reducing the impact of the rest, a quantitative approach to investing tends to pay attention to numbers rather than illusory things.

Quantitative Investing

Quantitative investing is a management method based on econometric models for making investment decisions. In general, quantitative models are often used in the management of mutual funds. These are econometric models that integrate a set of financial and economic data. The model establishes an essential portfolio based on the managers' guidelines and the data that has been entered into the model. This portfolio is then submitted to a management committee that can modify it based on qualitative data or on a database that is too recent to have been integrated into the model. The econometric model, therefore, often provides a basis that will open up the investment decision process.

In certain types of management, the quantitative model is the only element of the decision. In index management, for example, only the replication of an index is taken into account without financial analysts. Managers are developing a quantitative method that allows an index like the S&P or the MSCI to be replicated, for example. Index management has cost advantages. Indeed, line by line replication of an index does not require research work by analysts.

Model or quantitative investing is often seen as a black box that is only accessible or understandable for insiders.

It is investing without emotion. Investing follows a predefined, complex strategy that is supported in a disciplined manner. Thanks to good investment results, these funds have slowly but surely become an indispensable place in the investment world.

The advantages of quantitative investing are scalability, objectivity, and tight control of risks. There are also disadvantages. Quantitative models are, by definition, a simplification of reality, which means that not all possible influences can be included.

Some stats

- On average 51% of assets managed by the 11 most significant investment funds in the world are using Quant;

- All principal investment banks in the world have Quant analysis and trading department using Quant;

- Quant investment model automatically decides more than half of securities trading orders in developed countries' stock markets;

- A study of the income of investment experts shows that the experts using Quant are having the highest average salary on Wall Street.

Why Models Beat Human

Trading involves concentration, and emotions ruin it. What if we use something that does not have any feelings at all? And that are the models; they are amazingly consistent, do not feel hunger, and do not make a bad investment. 

Furthermore, the Quant model is more comprehensive than traditional investment methods when it utilizes the advantages of fundamental analysis, technical analysis, and statistical analysis. Simultaneously, based on advanced algorithms, Quant searches accurately and quickly process market information. Thus detect 'buy and sell' signals and devise a reasonable investment allocation strategy for each investment. Individually, to optimize profits and minimize risks for the entire portfolio. This process uses many sophisticated and sophisticated algorithms that require the help of computer software.

First, computers are superior to humans when they can process vast amounts of information immediately to look for signs of buying and selling. More importantly, machines are not governed by common sense - people cannot overcome "greed and fear" in investing.

Secondly, the mathematical tool can quickly check the reliability of signs of buy and sell in the market that computers have detected, and at the same time, decide to allocate the amount of investment for each individual investment. Logically, optimize the investment efficiency and control the risk of the entire portfolio. Machinery has provided maximum support for humans.

Quantitative Investing Performance

Through research on the operation of investment funds applying Quant models in the past 20 years, the fund returns from 15% to 35% / year, the average rate of about 20%. Among them is the Renaissance Technologies Foundation (Ren Tech) (source: Bloomberg), with assets of 20 billion USD, which is run by James Simmons - Harvard math professor. For the past 25 years, this fund has always achieved an average profit (after fee) of 35% / year. Although funds usually do not publish detailed operational details, we can see an increase in the volume of investment assets using the Quant model. The external manifestation of this is the increasingly active recruitment of Quant specialists from banks and investment funds.

Quant Investing Disadvantages

However, every medal has a dark side. The Quant model also has potential risks that need to be taken into account when applying, such as the risk of choosing a model, the risk of input quality, and the liquidity risk of the market. The LTCM Foundation's failure in 1998, for example, was run by Professor Myron Scholes, who won the Nobel Prize in Economic Science in 1997.

Conclusion

In this article, you've learned that quantitative investing can lead to great returns. Two of the best quantitative investment strategy are the Acquirer's Multiple, developed by Tobias Carlisle, and the Trending Value Strategy, developed by James O' Shaughnessy. They both consistently beat the market to a large extent in the last 50 years. 

If you want to go deeper about it, I suggest this article where we teach you how to apply these strategies using our stock screener.