Long gone are the days of floor trading over loud shouting and writing trades down on paper. Since global markets have transitioned to digital, trading has significantly shifted further toward data and algorithms. This has also contributed to a huge change in the makeup of front office roles. For example, many financial institutions are focused on hiring quantitative developers, quantitative researchers, and quantitative traders to automate their investment strategies. Since there are programming and statistical components of these roles, those with more of a STEM background also have a shot at quant trading and development roles.
Quant trading is a skill in which mathematical modeling techniques are applied to computer algorithms and programs, with the aim of identifying and maximizing trading opportunities. It also involves researching historical data to better recognize and predict potential profit opportunities.
As financial institutions expand their quant trading operations, you might be wondering how you can take advantage of these opportunities as a finance or tech professional. Without the right skillset, however, the road to becoming a quant will not be an easy one. Here’s what it takes to make the cut:
The rise of quantitative trading has led to an entirely new type of candidate: one that not only has a background in finance, economics, or mathematics, but also has a strong understanding of at least one programming language. Computer systems with programming language compatibility include but are not limited to, Perl, C++, Java and Python.
“While these programming languages used to help traders stand out, today they are being considered a standard requirement,” says Michael Kang, Senior Director within Tandym Pro who specializes in quantitative/systematic markets. “Not many finance professionals possess this skillset, so employers are increasingly turning to tech companies to find the talent they need for these roles.”
Since you will be competing with professionals from different industries for these positions, you should ensure you are proficient in one of these in-demand programming languages: Python, Java, C++, and R.
As a quant you will be expected to develop, design, and execute unique trading strategies. As a result, you should have a strong understanding of standard trading concepts and popular algorithmic trading strategies.
“Making the effort to educate yourself on today’s most common trading strategies is especially important if you want to make the leap from the tech to the finance industry,” says Michael. “While your programming skills will certainly set you apart, they can only take you so far in the hiring process. To be able to land (and do) the job, you need to have a strong foundation of financial trading strategies in addition to software and automated decision support systems.”
If you are going to work in this field, you need to be exceptionally good with numbers. “Math is the foundation of quantitative analysis and trading,” says Michael. “In order to research the data, run tests, and implement the trade, you should understand a few different mathematical concepts.” This includes calculus, linear algebra, and differential equations, and probability and statistics.
In addition to the technical skills you should look to develop, Michael notes that soft skills like adaptability, problem solving, and the ability to take risks are key attributes in a good hire. “In this type of role, you’ll be dealing with evolving market conditions and be required to come up with innovative trading solutions,” he says. “Although the goal of quant trading is to minimize uncertainty, you’ll still be expected to understand risk management and risk mitigation techniques. To make a successful transition to this field, you need to be able to logically identify issues and think on your feet in order to execute a trade without alarming the market.”
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