Why should someone working in systematic trading be irrelevant in 5 years?
Do I need a PhD in a quantitative field to get a job in algorithmic trading?
- Thread starter nightmarish
- Start date
Why should someone working in systematic trading be irrelevant in 5 years?
Btw, how I do put my foot in the door? I am going to teach myself algorithmic trading by reading textbooks and doing some projects, and I'm planning to attend conferences and make connections on linkedin, but is that enough to get me a job?
Q
7th Behavioural Finance and Capital Markets Conference 2017
https://www.eventbrite.com.au/e/7th...s-conference-2017-tickets-35713687601?aff=es2
Bringing together finance scholars and practitioners and research students to participate in and partake in the presentation of state-of-the-art research in the fields of Behavioural Finance, Experimental Finance and Capital Markets/Market Microstructure.
UQ
7th Behavioural Finance and Capital Markets Conference 2017
https://www.eventbrite.com.au/e/7th...s-conference-2017-tickets-35713687601?aff=es2
Bringing together finance scholars and practitioners and research students to participate in and partake in the presentation of state-of-the-art research in the fields of Behavioural Finance, Experimental Finance and Capital Markets/Market Microstructure.
UQ
First of all, feel free to call it algorithmic trading, quant trading, quantitative trading etc.. they are all applicable
Speaking from experience:
No, you do not need a PhD to get into quant trading. There are plenty of people to begin a career in quant trading without a PhD but come from a quantitative field like yours. Like an earlier poster replied, the PhD is often added as a recruitment filter - This tends to be more so for quant trading divisions within bigger banks as opposed to smaller quant trading firms.
In addition, knowledge of the world of finance isn't necessarily important either. In fact many quant trading firms adopt recruitment policies like Renaissance where they stay well clear of "wall street types" and recruit based on a prospective hire's scientific and quantitative work and acumen.
That said, there are prerequisites. If you hope to get into the gritty part of quant trading, you'll spend every day knee deep in code - sifting through historic data, building models, backtesting them, analysing the results, improving the model etc.... As such, your programming skills are expected to be stellar, and you'd be expected to pick up and work with libraries the team uses fairly quickly.
Your approach to this seems good, but in addition to familiarising yourself, whats really important is that you show what you can do practically - if you want to work somewhere building machine learning regression or DNN models, then do a project where you've gone out, found a large dataset, built models and have results - this doesn't have to be using financial tick or minute bar data, it can be any dataset you find interesting. Whats important is showing you have the ability to go through those steps and have an end product.
Putting your foot in the door first thing coming after coming out of school is no doubt difficult, but keep at it.
Speaking from experience:
No, you do not need a PhD to get into quant trading. There are plenty of people to begin a career in quant trading without a PhD but come from a quantitative field like yours. Like an earlier poster replied, the PhD is often added as a recruitment filter - This tends to be more so for quant trading divisions within bigger banks as opposed to smaller quant trading firms.
In addition, knowledge of the world of finance isn't necessarily important either. In fact many quant trading firms adopt recruitment policies like Renaissance where they stay well clear of "wall street types" and recruit based on a prospective hire's scientific and quantitative work and acumen.
That said, there are prerequisites. If you hope to get into the gritty part of quant trading, you'll spend every day knee deep in code - sifting through historic data, building models, backtesting them, analysing the results, improving the model etc.... As such, your programming skills are expected to be stellar, and you'd be expected to pick up and work with libraries the team uses fairly quickly.
Your approach to this seems good, but in addition to familiarising yourself, whats really important is that you show what you can do practically - if you want to work somewhere building machine learning regression or DNN models, then do a project where you've gone out, found a large dataset, built models and have results - this doesn't have to be using financial tick or minute bar data, it can be any dataset you find interesting. Whats important is showing you have the ability to go through those steps and have an end product.
Putting your foot in the door first thing coming after coming out of school is no doubt difficult, but keep at it.
Yeah exactly. Take you for example, what's it like hitting rock bottom in life? Also, Ive never heard the term "humping drywall", is that some type of slang you use in the industry or just one of youre freaky sexual fantasies?
I was not trying to insult you, but it certainly sounds like you are envious of the people in the institutional quant finance. Certainly, now you are going to argue loudly that you are not
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That argument makes no sense.
The threat of irrelevancy and obsolescence applies to us all. In an age where AI and automation is growing by leaps and bounds, what jobs are going to provide life long security without threat of being replaced? The answer is very few if any. We have bots that can do jobs formerly done by doctors, lawyers, engineers, etc, besides the lower level tasks, and we're just in the relative infancy of advanced AI.
We will all have to learn to adapt to an ever changing jobs market. If you can land a good job one is interested in that pays well NOW, one should take it, always have an eye towards the future.
Enlighten us then. Tell us how you paved your way out of the rat race, to financial freedom, working a "real job".