If you want a job as a journalist, you’re expected to show up with some of your best published or unpublished articles. An aspiring advertising creative will bring their portfolio of dazzling copy with them to a job interview. So, if you fancy yourself as an algorithimic trader, you might assume you'll need to bring your algos with you to your next job interview with a top quant fund.
Writing your own trading algos can indeed be helpful, as can referring to them in interviews, but not for the reasons you might expect. You also need to think carefully about the purpose of the algo before you fire up your coding tools and start writing.
An algo is proof you can generate alpha
This is the most obvious reason to write your own algo. If you have a succesful trading strategy then the fund will hire you immediately, confident that you can quickly start generating fat profits. At least that's the theory. - The realit is that reputable funds can be extremely picky.
For the best chance of a positive result, the strategy embedded in your algo should already be trading within an existing fund. Trading a strategy with your own capital is the next best thing, but this comes with further caveats. - For example, is your strategy scalable to insitutional levels of capital? Is your strategy too similar to existing strategies within the fund? Does it fit the funds mandate and client appetite? Does the fund have the neccessary infrastructure to trade your favourite instruments?
There is also the thorny issue of proving you have actually earned any claimed returns. Best of all is an audited track record, but few independent traders can afford to get this. Plenty of websites exist to showcase algo strategies, but most of these lack credibility in the industry as they are plagued by fraudulent con artists. Two honorable exceptions are Quantopian and Fundseeder.
Worst of all is a strategy with excellent theoretical simulated performance, but no live track record. You’re unlikely to get a job offer with this unless you already have an excellent industry pedigree.
An algo will help you demonstrate coding pedigree
Not all funds will be looking for ‘plug and play’ algos. But all will be looking for evidence that you can develop such an algo once they have hired you. A major part of the required skillset is the ability to code.
It’s difficult to glean evidence of coding ability from CVs, as most are over confident and vague when it comes to the specifics (I have interviewed self proclaimed experts in Python who didn’t know what a list comprehension was). Interviews and coding tests are time consuming, and often too superfical.
But if you have put your coding projects on an open source site like Github, then potential employers can easily check up on your abilities. They can do this manually, or by using automated code quality checks. A project with a lot of downloads is also a good sign.
Of course you don’t have to upload a complete trading strategy; any relevant code will do, and a smaller self contained project will be easier to evaluate. Useful examples might include a paper on machine learning analysis complete with code and data, or a particularly clever system for concurrently harvesting high volumes of tick data.
An algo will show you can handle implementation hurdles
Creating a trading algo isn’t just about finding some secret alpha. Algo traders also spend time doing more mundane tasks like cleaning data, worrying about day count fractions, and dealing with misaligned daylight savings time changes.
A trading system can show that you have worked through these relatively boring processes, and learned something. Such a system need not contain proprietary alpha; in fact it might be better to implement a simple and well known trading strategy which interviewers will be familiar with.
If you have also implemented such a system with real money, then you could have learned some valuable pyschological lessons, such as the pain you will feel when an automonous system that you don’t directly control loses money.
An algo will demonstrate your interest in the markets
For students looking to break into the industry it’s always useful to mark yourself out by demonstrating a deep interest in the financial markets. Again, it isn’t necessary to develop a complete trading system, or even to trade at all. As an example, when I was interviewing for my first job in trading I was able to talk the interviewer through a novel statistical arbitrage strategy. I had never actually traded the strategy, or even coded it up. But I still got the job.
Robert Carver is a former head of fixed income at quantitative hedge fund AHL, and the author of 'Systematic Trading' and 'Smart Portfolios'. He now designs trading strategies for trading his own money.