Inquiry for Aspiring Quant

Hi everyone good day!

I just want to inquire the appropriate background of a Quant.

Apologies for the newbie question I lack background to fully ask the right question.

Anyway, I do know Quant is a broad term spanning different roles at the industry. However, let’s narrow it down to a Quantitative Researcher at a Quantitative Proprietary Trading firm like Jane Street, Susquehanna International Group, and Optiver.

I know Quantitative Finance cover areas in Computer Science, Mathematics, and Statistics. However, what confuses me as a Mathematics major is the lack of financial background needed to enter the industry. I know internships train us for that but I see lots of distrust on economic and financial theory.

I was thinking of adding an Econometrics and Mathematical Economics to add a thorough background of theory but according to papers like Dr. Marcos Lopez de Prado’s Journal of Portfolio Management Articles state that Economics & Finance are inefficient and impractical with the real world setting.

So I am quite confused where Quants find or extend the problems if these theories are faulty and impractical. As a mathematician, I don’t see how I can model something without thorough understanding of what I’m modelling.

Or rather, Quants also learn extensive economic and financial theory during their internship/university and apply accordingly or Quants reject all theory and take specific inputs from observation of data and try to model with limited understanding. The former makes the most sense to me than the latter.

If the former is true, then is it safe for me to double-major in Economics-Mathematics or If the later is true, then, specialising in my study with computational element is the focus.

Lastly, maybe the answer may not be available above from my attempts to understand with my limited background.

I may be spouting some nonsense but do enlighten me, any response would be appreciated.

Thank you in advance!
 
If I can get away with a sweeping statement, economics is mostly garbage. It's elite ideology often dressed in fancy mathematics. Economists are propagandists for the status quo. Sasan Fayazmanesh puts it more eloquently than I could:

Why were the experts so wrong? They were wrong mostly because economics is an underdeveloped discipline dominated by pure, unabashed ideology. The dominant school of economic thought during the Great Depression was, and remains to this day, the “neoclassical” or marginalist school. But in the “neoclassical” world there is no such thing as a crisis. This is not the real world in which we live. It is a classless world, consisting of “consumers” and “producers.” It is a harmonious world modeled mostly after mathematical physics. In such a world there is no history; there is no past, no present and no future. Nothing of consequence ever happens in this world, especially no catastrophic event. This unreal, insipid and a-historical marginalist world should have been abandoned a long time ago, particularly after the Great Depression. Yet, its seemingly mathematical elegance combined with its unadulterated and brazen defense of capitalism, or “free market” as its proponents prefer to call it, has kept it alive. Of course, since the Great Depression the “neoclassical” theory has been somewhat amended by a few ideas from the British aristocrat John Maynard Keynes, ideas that tried to add some elements of reality to the unreal theory. But the result, the so-called “neoclassical synthesis” or “neo-Keynesianism,” is no more than a hodgepodge of disjointed, unclear and incoherent ideas that are fed to the students of economic theory under the rubric of “micro” and “macroeconomics.”


Quant finance, on the other hand, is an attempt to use math and computation to make some money. It's an extension of a historical process that began in the Middle Ages, as Fayazmanesh explains in another essay:

... But as a historian of economic thought, and as one who has been interested in the market mechanism in the early stages of development of capitalism, I know that hedging and gambling in the market place are old practices, at least as old as the “commercial revolution” or the development of “merchant capitalism” in the 13th century. Indeed, as I have argued in my book, Money and Exchange: Folktales and Reality, and in some other essays, in medieval trade merchants regularly tried to cheat one another in the market place. [3] In so doing they used other merchants’ ignorance of arithmetic to swindle them. Arithmetic—which at the time consisted mostly of knowledge of the Arab numerals, four basic mathematical operations and the “golden rule,” or the “rule of three,” where a missing fourth number in two equal ratios is found—had just reached Europe by way of Arab merchants. Between the 13th and 16th centuries a group of merchants in Europe, particularly in Italy, wrote manuscripts to teach merchants’ children, who attended special training schools, the newly received arithmetic. But what is perhaps most interesting about these manuscripts is that almost all of them teach how to use arithmetic, particularly in the act of barter, to cheat their trading opponents and increase what they called the “overprice.” As such, these medieval manuscripts taught that the rule of exchange was to come out ahead in transaction and that barter was “nothing but giving a good for another in order to get more.”


To make a long story short, in the medieval markets arithmetic became a tool, a “financial innovation” to use the language of the modern market, to make more money. The rule of the game was to take advantage of arithmetical ignorance of others to gain as much profit as possible. This was how capitalism was born. It was born not of honesty, equality, justice or fairness in exchange, but of deceit, swindle, inequality, injustice and unfairness. It was also in this same period that one can find the emergence of many other financial innovations, such as forward contracts and bills of exchange, innovations that tried to increase profit by reducing uncertainty and risk.

 
Hi everyone good day!

I just want to inquire the appropriate background of a Quant.

Apologies for the newbie question I lack background to fully ask the right question.

Anyway, I do know Quant is a broad term spanning different roles at the industry. However, let’s narrow it down to a Quantitative Researcher at a Quantitative Proprietary Trading firm like Jane Street, Susquehanna International Group, and Optiver.

I know Quantitative Finance cover areas in Computer Science, Mathematics, and Statistics. However, what confuses me as a Mathematics major is the lack of financial background needed to enter the industry. I know internships train us for that but I see lots of distrust on economic and financial theory.

I was thinking of adding an Econometrics and Mathematical Economics to add a thorough background of theory but according to papers like Dr. Marcos Lopez de Prado’s Journal of Portfolio Management Articles state that Economics & Finance are inefficient and impractical with the real world setting.

So I am quite confused where Quants find or extend the problems if these theories are faulty and impractical. As a mathematician, I don’t see how I can model something without thorough understanding of what I’m modelling.

Or rather, Quants also learn extensive economic and financial theory during their internship/university and apply accordingly or Quants reject all theory and take specific inputs from observation of data and try to model with limited understanding. The former makes the most sense to me than the latter.

If the former is true, then is it safe for me to double-major in Economics-Mathematics or If the later is true, then, specialising in my study with computational element is the focus.

Lastly, maybe the answer may not be available above from my attempts to understand with my limited background.

I may be spouting some nonsense but do enlighten me, any response would be appreciated.

Thank you in advance!
Hello there. I am also a newbie, but I have done enough research about the subject in question. The prospective employers will expect lack of financial background in the case of PhD and train you. You must focus on technical aspects. You are expected to master statistics, probability and stochastic calculus. You are also expected to be a master software developer, seemingly. Economics won't help here, and you are advised to take computer science as minor. If you don't want to do PhD, you can always do M.S financial engineering from a well reputed university in newyork or london for finance knowledge. But if you want to do PhD, there is no need for financial background. But you shall do PhD from IVY league or oxbridge. Also, economics and finance are very much different. So I advise you to choose CS as minor.
 
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