The Best Quant Tools and Resources of 2024
New year, new markets, new tech.
Sometimes markets go up, sometimes they go down; but one thing they always do — is change (“that’s why we keep coming back!”). If you’re a trader in the wild-west of the options market, aspiring to remain competitive and more importantly profitable, you’re going to need to tool-up.
So, today, we’ll be looking at a few key resources that we use in quant trading that you may not have heard of, but can be used to seriously up your game.
#1: Spyder IDE
Whether you’re a quantitative trader, researcher, or even just a regular trader who wants to up their edge — you need code — at least a little bit. While this may be common knowledge, you may not know that gone are the days of dead-eyed monotoned code terminals that knock you out if you stare for too long.
The Spyder IDE is essentially what would happen if Excel and Python had a baby. Have a look:
Pictured above is a real-time volatility surface of over 400 stocks in a clickable and scrollable format. All of the calculations were run in Python, but we can open and edit all of the data points by simply opening up the variable and clicking/typing around.
We’re just focused on the tools today, but if you’re interested in replicating this surface on your own, we’ve got you covered.
Inspecting the finer-points of your data is a necessary job, but sometimes you just need a simple, big-picture view that gives you the insights you need. Thankfully, Spyder comes with its own plotting functionality that allows you to make beautiful plots:
#2 PythonAnywhere Servers
We mean absolutely no shade when we say this — but when it comes to quant trading — your computer sucks.
Okay, maybe it doesn’t, but a standard home computer is not suitable for real-world quant deployment for a few reasons:
- Take a strategy that uses live data, for instance, our 0-DTE Machine Learning Strategy; Let’s say that we get the trade signal from home and we establish a new position. Things are going well, but oops — you spilled coffee on your outlet and now your internet is out.
— At best, you whip up a hotspot last minute and get things back up and running.
— At worst, your system fails to receive instructions on when to exit the position and holds a potentially multi-thousand dollar 0-DTE position into expiration — out-of-the-money and worthless. - In the quant space, trade secrets are important. When you’re working on an internal model, sometimes you have to do everything yourself — even calculating implied volatility from scratch. This is fine for a few tickers every once in a while, but if you need your own internal estimate of IV for 500 tickers to spot changes minute-by-minute — you’re going to need some serious compute power.
Thankfully, PythonAnywhere offers us a cheap and effective way of solving all of these problems. Here’s how:
“With every PythonAnywhere account, you get a number of CPU-seconds included each day. ….
A CPU-second is one second of full-power usage on a High Frequency Intel Xeon E5–2670 v2 (Ivy Bridge) Processor [….] Your code only uses up CPU seconds while it’s actually busy.”
So essentially, we get to have our tasks executed on an extremely powerful CPU, but we only get charged for the amount of time we actually use.
But it’s not all about money, the next major advantage is that using it is as simple as plopping in a Python script and allowing it to cook:
#3: Trading Bibles
If you know what quant trading is, you likely know what options trading is, and if you know what options trading is, you likely know about the OG “Options Trading Bible”:
Sheldon Natenberg’s “Option Volatility and Pricing” is given to every finance student and featured in every Top 10 Fintwit Book List for a good reason. This was essentially how wide swaths of the public found out about things like implied volatility, the greeks, and even more arcane concepts like dynamic hedging.
While this is still an extremely useful resource, there is just one caveat. It is decades old.
The budding quantitative trader will be entering a new world of meme-stocks, 0-DTE options, and all things which the book might be a bit too slow on.
However, this isn’t the only trading bible:
Made by the Quant Galore team (that’s us!), The Vol Trading Bible aims to be the successor to the OG. It contains everything needed to get a quantitative trader of the times up to speed:
- Zero-to-Hero Quant Tech Setup:
— Python, Databases, Servers — the whole shebang - Real-World Profitable Strats (With Backtests):
— Machine Learning Based 0-DTE S&P 500 Strategies
— Real-Time Volatility Surface Trading
and way more:
A wise man once said: “Keep it simple, stupid.”, and we couldn’t agree more. Regardless of where you are in your quant trading journey, there is a tangible benefit to be gained from further exploring even just one of these resources.
So, if you’re planning to put on your swimsuit and dive in with the sharks, just make sure you’re using the best tools for the job.
Happy trading! 😄
If this post piqued your interest, you’ll likely enjoy a few others that are even better:
