Collected Investopedia Guides to Quants - The Rocket Scientists of Wall Street Dec 09 2019 09:05 languageMoneyScience
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As financial securities become increasingly complex, demand has grown steadily for people who not only understand the complex mathematical models that price these securities, but who are able to enhance them to generate profits and reduce risk. These individuals are known as quantitative analysts, or simply "quants."
Due to the challenging nature of the work – a blend of mathematics, finance and computer skills – quants are in great demand and able to command very high salaries. In this article, we'll learn what they do, where they work, how much they earn, what knowledge is required and whether this may be the career for you.
- Quant traders use strategies based on quantitative analysis—mathematical computations and number crunching—to find trading possibilities that can involve hundreds of thousands of securities.
- An aspiring quant trader needs to be exceptionally skilled and interested in all things mathematical—if you don't live, breathe and sleep numbers, then this is not the field for you.
- A bachelor's degree in math, a masters degree in financial engineering or quantitative financial modeling or an MBA are all helpful for scoring a job; some analysts will also have a Ph.D. in these or similar fields.
- Lacking an advanced degree, a candidate should at least have on the job training and experience as a data analyst; experience with data mining, research, analysis, and automated trading systems are a must.
- Traders also need soft skills, such as the ability to thrive under pressure, maintain focus despite long hours, withstand an intense, aggressive environment and stomach setbacks and failures in pursuit of success.
- Quantitative trading is a strategy that uses mathematical functions to automate trading models. In this type of trading, backtested data are applied to various trading scenarios to spot opportunities for profit.
- The advantage of quantitative trading is that it allows for optimal use of backtested data and eliminates emotional decision-making during trading. The disadvantage of quantitative trading is that it has limited use. A quantitative trading strategy loses its effectiveness once market conditions change.