Brief of The four phases of investment management During the past century

there have been four distinct periods in investment management. 

The move is clear towards an approach based on scientific evidence. 

Let's see what these four moments have been and what we are experiencing right now. 

The four periods in investment management: 

1) From 1900 – 1950 Technical analysis Investment in this period of history was aimed at speculation. 

I remember reading and laughing a lot at Groucho Marx's stories about his investments in the 1920s boom. 

In those early moments there were no financial theories, no computers, mathematical models were very simple and access to information very limited.  Investment decisions are made based on stories, and investment professionals receive no formal education. 

Technical analysis comes to light with Dow studies. 

2) From 1950 – 2000 Econometrics and fundamental analysis At this time, thanks to the academy, the concepts of diversification, risk premium and valuation appeared. 

 Great advances for new awards that illustrate us with Modern Portfolio Theory MPT, Financial Asset Valuation Model or CAPM, Arbitrage Pricing Theory or APT, Different Risk Factors, or Black's Model -Scholes among others. 

 Here investments are made based on a financial analysis of specific opportunities. The investment professionals who are awarded are already accredited with the CFA or Chartered Financial Analyst. 

3) From 2000 – 2015 Microstructure and high-frequency trading in investment management Technology is making a big breakthrough in terms of computing, storage and networking, which makes possible a new way of approaching markets. 

Mathematical models become more complex and little by little investment decisions are based more on research and development of models supported more and more in technology. 

The firms with the best results become the ones that use these quantitative techniques and now only seek as employees graduates in mathematics, engineering, science and technology. 

4) Since 2015 Machine learning (Automatic learning)

In recent years the explosion of alternative data has changed the research objectives. It is now moving from valuation and forecasting to direct estimation. This is made possible by machine learning, hence the super demand by investment houses for data scientists and automation experts.