Impact of automation, surging layoffs in the financial sector, the rise of robots and threat to our future, the list of such articles on the net seems endless.
But have you ever been in a similar situation?
Have you ever been at the risk of a layoff for want of better skilled, technologically enhanced workforce?
What did you do then?
Those from an MBA-Finance background evidently aspired to master their chosen field of work. Choosing to go for an MBA in finance would mean you are good at numbers, strategies, and money-making in general.
But what if, after certain years of work and excellence at it, you feel saturated again?
Either situation, an expected threat of layoff or a saturation from existing profile, both need a career upgrade.
Considering to upgrade your knowledge and career options?
Become a Quant.
As financial securities become increasingly complex, it is still interesting to note that it is the people who understand the trading strategies and are responsible for incorporating the same in algorithms.
Complex mathematical and financial models are drafted, interpreted and put to use by computerized mechanisms. There has been a steady growth in demand for people who not only understand the complex mathematical models that price these securities, but who can enhance them to generate profits and reduce risk. These individuals are known as quantitative analysts. To be specific, the people behind quantitative trading strategies are referred to as quants and quant traders.
Quantitative analysts design and implement complex models that allow financial firms to price and trade securities. They are employed primarily by investment banks and hedge funds, but sometimes also by commercial banks, insurance companies and management consultancies, in addition to financial software and information providers.
How to become a Quant?
Quants employ programmatic languages to deploy discretionary methods of trading. Primary methods of trading include traditional trading strategies. The same strategies which you may have acquired after a keen observation of the market data.