If you’ve been following around with our Algo 101 series, you’ve already gotten a taste of parts 1 and 2 with our TWAP and VWAP posts; and if you haven’t read those, we recommend taking 5 mins after this to get a quick refresher.
So, this is the third post in this series helping those interested in algorithmic execution understand how different types of algorithms work and the execution objectives they’re intended to solve.
Continue Reading →This is the second post in our Algo Execution Educational 101 Series to help those interested in algorithmic execution understand how different types of algorithms work and the execution issues they’re intended to solve. This week we’re focusing on the VWAP algo.
Continue Reading →With automated trading and algorithmic execution strategies accounting for 85% of equities trading, its no secret algos have become a useful implementation tools in Futures markets. Algos have a lot going on from TWAP vs brISK, to implementation and slippage cost; and that’s just the tip of the ICEBERG. So what better way to educate than to create an Algo Execution Educational 101 Series….Algos 101 for short. In this series, we’ll be explaining how the different types of algorithms work and execution issues that they aim to solve.
First up: the TWAP Algo.
Continue Reading →Today’s top firms know there’s more to alpha than just higher trading profits. There’s also minimizing trading costs when implementing your investment strategies. Aside from fixed costs like brokerage and exchange fees, the somewhat hidden costs of execution slippage can erode your alpha and impact overall performance. Not being able to get filled at the price or time you desire creates meaningful consequences, especially when those numbers are compiled over the course of many trades and a significant period of time. Traders must balance price and market impact costs when implementing their investment strategies.
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Liquidity dislocations during the pandemicOver the course of the last few weeks we’ve experienced unprecedented moves in our markets, with major indices like the Nasdaq falling -28% from its highs, only to recover by advancing +31%. Meanwhile, the sudden and sharp decline in demand for oil resulted in never before seen price movements including a $50+ daily move into negative pricing.
While the rollercoaster ride has been either terrifying or exciting for traders depending on their positions and risk sizing – the end of day price movements are just the surface level story. The other, and for many…the more important part of the story, has been what has transpired in the market microstructure and liquidity as a result of the historical volatility. The story of how the microstructure and liquidity of futures markets has changed, and in some ways perhaps remained consistent, during these huge daily moves appear to be catching the attention of sophisticated traders.
Continue Reading →California, Washington, New York, and now Illinois have been issued stay-at-home orders. With restaurants closed and the work from home rules in effect, gone is the easy access to the well-stocked office kitchens and pantries. We wondered how the RCM-X team of quants and engineers would survive.
Note: Our team of mathematicians, physicists, and engineers know algo execution strategies, but we also know quant + kitchen [can] = fire-y disaster… (especially when you reach out to your team and ask how they’re going to survive the COVID-pocalypse and the answers mostly consisted of Mac & Cheese, Frozen Pizza, and Ramen).
So, in order to lend a helping hand to our in-house quants as well as clients far and near, we’ve compiled a list of our favorite meal recipes to get you through these uncertain times.
The VIX has spiked to its highest level since 2008. The stock market has had the fastest bear market correction ever. Oil fell 33% in overnight markets, in one night. We’re seeing 6% moves in the S&P in the matter of 14 minutes. Suffice it to say, things have been volatile and spreads are widening.
We’re quants and algos people, not politicians or economists looking to answer what all this means. But in light of the current situation, our clients are asking us one simple question:
“Is it ever too volatile for Algo Execution?”
It’s clear that computerized algorithms are finding their way into nearly every sector of our modern lives, from what shows we watch to what route we take to work, to what goods are suggested for us to get delivered right to our doors. The investment and trading world is no exception. Over the past decade, algos have become increasingly essential for traders of all shapes and sizes. And now the key is not just the use of algos in trading, but to choosing the best ones to use.
Trade idea testing + trade order execution + trade size generation = algo??? That’s one way to look at it, and indeed we have a whole in-house team dedicated to building algos to do some of these pieces every day with our RCM-X team.
While the difference between an alpha generating algo and an execution algo which through costs savings adds alpha may be a bit nuanced to some, its not to everyone. So, what does each part of the “algo equation” mean, and how does it all work together to produce the algos that we all know (and some love)?
A recent graphic by Tractica shows that over $7.5 Billion dollars is forecasted to be spent on Algorithmic trading strategy improvement via AI in the next 10 years. Wow! That’s a lot of quants in the world’s payroll. What exactly is a quant? How do algorithms (algos) fit in? And what does Artificial Intelligence have to do with all of it?
