Most of people wants easy money, that is the truth, very influenced by fantastic marketing on youtube finance videos, images people make money front their computers, posts about how to make money easily follwing a few trading rules, and so on. The internet is plagued of it. Good or bad, that is your business. But always remember, the money is limited, and to take huge amounts of money, can imply other person is losing it, so please dont be the money loser in this game.
This post does not pretend to show you how to make money as quant, but it attempt to give you an idea about why could be important to take into account the maths into your investing strategies, or why not.
First, is important to know what this word is. Quant is refered as a field in finance which use some technical knowledge such as computer science, financial engineering and statistics, summarizing, to improve the investing, risk management or/and financial analysis performance. This field is very commonly known because is changing the way institutions are investing part of their wealth, even if they are doing it with measure. This exposure to new ways to do investing, is involved in the need of beat the market in the competition for collect public money to invest with more yield. This way of doing, has some challenges, specially in regulation. The need of gather money, or rise funds, is in constant changes and with this its patterns. Here is when quant methodologies came to update investing views quickly. But not all is happiness.
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If you take a view on financial world, almost intuitively you can see some patterns which, or at least you must have heard about, mold the financial trading based on economic ideas in market agents insights. Many of this insights can be translated to mathematical formulas, trying to abstract the financial behavior, and this is the financial enginerring job. Many of this formulas let to build some complex asset products, which let to other products, likely unliquid, transform to mutant liquid assets, like CDO or bank notes, and so on. To build this products efficiently, institutions that build it must have the most information possible about the underliying assets, to price the new mutant product in the best way, and believe me, some times that people needs take some assumptions about reality without underlying assets information.
To achieve gather the most information possible, other people is analyzing a lot amounts of data, which extract patterns to build economic and financial models. In this moment computer science with data scientists is comming to this battle field. This people is day by day, second by second, looking into data, structured and unstructured data, financial or alternative data, to give to financial professionals a most wide view about the world behavior. Some times, in small firms, the same person must do both of them, build structured financial assets and alternative data analysis while computer scientists are coding in the most efficient way the code to do this automatically.
Beside, to build this models is important to know about statistics, and of course maths. Statistics is importante because in the common eyes, some patters can be wrongly seen as correlated or even as causal events, when really can not be that. A misconception as it, can address you to take erroneous investing positions, underperforming your strategy.
But like all in the life, not all is good. This approach have shown some pitfalls, specially when it is combined in algorithms. An example of this is the common known flash crash in 2010, when DJW and NASDAQ indexes, collapsed by few seconds, with quickly falling and recovering, in seconds. This pitfall is associated with high trading systems which incorporate in its models a pattern non-previewed. That is why its important taking in account how algorithmic trading is implemented. Maybe you thing you are a very small piece of all market, but one issue must be proposed is, what if many of the small pieces in the market do similiar positions, based on particular agents which spread some strategies to get money easily? .... well, could sound as conspiracy theory, but when people with money know that, can raise algorithms to bet against it .... that is mass behavior.
To know how it is influencing the banking and finance world, please take a view on jobs wepage tipying FRM, CFA, CQF, risk management, algorithmic trading, HTF, xVA, including python, java, julia or C++ in finance.
Thanks for reading my opinion. Please feel free to comment it.
Regards.