Why go for Algorithmic Trading?
In India, Algorithms that use Application Programming Interfaces (API) are the most commonly used ones. Here, the investor selects the strategy, which he then programmes and are executed by the Broker.[2]
Hover over to see average compensation details. This data was sourced from submissions at levels.fyi. L1 Full Stack 175k – Base N. A. – Stock 100k – Bonus N. A. Infrastructure 200k – Base N. A. – Stock 200k – Bonus L1 Core dev 175k – Base N. A. – Stock 120k – Bonus L1 Trading Infrastructure 200k – Base N. A. – Stock 300k – Bonus Mid Data 200k – Base N. A. – Stock 100k – Bonus
What’s going on with Algo Trading today?
Be careful with this question: it could be sensible due diligence, or a check to see if you can explain complex ideas. But it could be a trap: less ethical firms will interview traders without any intention of hiring to gather ideas. Keep your answers general and stick to non disclosure agreements.
10. Write a python program to calculate X! recursively. What will happen if X=2000? How would you solve this problem?
Coding is a big part of trading systematically, but the amount of coding experience you’d be expected to have will vary. Some firms will be looking to hire hotshot programmers who can write production ready code. At others the real programming is done by professional developers, but you’d still be expected to analyse data and build prototype strategies.
Another source of talent for the systematic trading business is buy side analysts, whether from equity, FX or fixed income. This type of question checks your market knowledge, and will also find out if you can think rigourously about predictability and risk.
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What affects Algorithmic Trading?
But it doesn’t stop here. This is just what you should be knowing about Algorithmic Trading. Following are some of the most commonly asked questions which we came across during our Ask Me Anything session on Algorithmic Trading. The questions range from basics to some really interesting and professional ones.
You might get a Deja vu, looking at some of these questions and think… “Haven’t I thought of this before?” If not, you’ll probably wonder “Why haven’t I thought of this before?”
So, here goes:
We’ve talked about the extent to which large financial firms are becoming tech firms. But I expect that it’ll start accelerating in the other direction: big tech firms will become financial firms.
What about the impact of a more algorithmic financial system on retail investors? We’ve mostly been talking about big institutional investors, which makes sense because that’s where the money is. But how do these types of tools filter down to the ordinary investor who’s maybe got a small retirement fund?
Some of the most prominent hedge fund managers of the last few decades—Steve Cohen, Paul Tudor Jones—are going against type and launching technology-driven quantitative investment funds. They employ physicists and computer scientists to write algorithms to invest money, because that’s what investors want. You’re seeing a massive arms race across hedge funds to rebrand themselves in that direction.
I was always interested in economics and had a quantitative background. Anyone who succeeds academically where I grew up ends up being very quantitatively oriented. After school, as I was trying to find a profession that would be financially rewarding but would also allow me to use what I studied, I started looking at the financial industry. I ended up taking a job on a trading floor in an investment bank.
So as those techniques get diffused across the industry as a whole, they start to be less of a differentiator. How does this impact employment? How do you see these technologies affecting either how many people the financial industry employs, or the level of skill required in different roles?