Commonalities in Quantitative Investment

Quantitative Investment

Quantitative investing is indeed interesting

My sharing

After recently re-reading some quantitative investment books, I found that these quantitative investment teams have many common characteristics. In particular, the following two books are highly recommended by me. I suggest that readers who are interested in quantitative investment must find time to read them in detail several times:

Several representives

  • Simmons’ renaissance
  • D.E. Shaw &Co
  • Long term capital management
  • APT
  • Bamberger
  • Kepler

Characteristics of team members

Members’ professional diversity

Take the Renaissance Company founded by Simons as an example. Most of the company’s members are Simons’ colleagues or friends in the mathematics world, including experts in Markov chains, Bayesian mathematics, data analysis experts, cryptography experts, statistics experts, and computer science experts. Programming experts, speech recognition experts, data cleaning and integration experts, machine learning experts, economists, chemists, biologists, physicist consultants, etc.

Each one requires a highly professional theoretical background and is a truly rare professional with specialized skills.

All are smart people

There are no exceptions for the members of the quantitative investment team. From the perspective of ordinary people, they are all extremely smart weirdos who are dedicated and motivated to work. They regard solving impossible problems as their goal.

Financial background does not matter

It doesn’t matter whether you have a financial background or not, but whether you have a smart mind determines whether you are suitable for quantitative investment. Because I don’t have financial knowledge, as long as I study hard and find someone to help me, I will definitely be able to change my life. However, whether one is smart or not is not impossible to make up for through acquired learning.

Extremely dependent on mathematics

All are mathematicians

The founders of famous quantitative investment teams, almost without exception, are all mathematicians. This is of course no coincidence.

Examples of false types include Nash, who invented game theory, Shannon, the master of information theory, Thorpe, the first quantitative trading mathematician, Kelly, who invented the Kelly formula, and Simons, the most successful quantitative investor.

Model is the foundation

All quantitative investment teams have only one goal–to build a model that can sustainably make profits and be automatically operated by computers. What it relies on are mathematical models, algorithms, and market tests.

Three major theorems

I found that most quantitative investment teams rely heavily on mathematical models. Among them, the three sets of Bayes theorem, statistical arbitrage, and regression testing are the most important. They almost constitute the core and necessary basic theorems of the quantitative investment team.

Data is important

All models, statistics, three theorems, trading trends, and historical lessons require reliable data as a basis, otherwise everything will be in vain.

Trading Characteristics

High frequency and large trading

Almost all quantitative investment teams use high-frequency and large-amount transactions; that is, trading a very large amount of financial products in a short period of time.

Trend trading

Most quantitative investment teams use trend trading. They all believe that the trend is the trader’s friend. As long as the trading method they bet on can make a lot of money, they will increase the amount of bets on hand until the bet amount is large. Until the trend you bet on expires or you can no longer make money.

Financial products involved

The financial products involved include stocks, foreign exchange, commodities, precious metals, crude oil, futures, indices, stock options, bonds, etc.

However, most quantitative trading is actually engaged in foreign exchange, commodities, precious metals, crude oil, futures, indices, and stock options that ordinary retail investors will not touch; that is, derivative financial products.

Quantitative Investment
credit: Ideogram

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