Home » attain alternatives blog » Talking Asset Allocation, AI, and the Alpha Process with ReSolve Asset Management on The Derivative

Talking Asset Allocation, AI, and the Alpha Process with ReSolve Asset Management on The Derivative

Is now the time to ditch stocks and buy bonds? Gold? Should you just go to cash? These types of asset allocation decisions are hard enough in the calmest of times – and downright impossible when overwhelmed with fear and panic in times like the past few weeks as stocks have given back a good chunk of their 2019 gains.

If only there were a way to automate those asset allocation decisions, with reams and reams of academic rigor and research behind the algorithmic allocation models. That sure seems like it would be a better way to approach it, and we were lucky to sit down with the smart folks at ReSolve Asset Management, who pretty much do just that, for a great podcast episode.

ReSolve is a systematic asset manager out of Toronto focusing on unique and advanced ways of implementing global asset allocation to generate alpha. In fact, they think of themselves as having a sort of Alpha factory with specific inputs and processes to output the desired product (risk adjusted returns):

 

ReSolve operates managed accounts, private funds, and a mutual fund (RDMIX); using varying automated investment and allocation strategies; including flavors and ensembles of trend following, carry, seasonality, skewness, behavioral arbitrage, and AI/machine learning informed “alpha buckets”.

In this episode, we sit down with Rodrigo Gordillo, Adam Butler, & Mike Philbrick talking about filling in the gaps with mid-frequency trading, learning the ins-and-outs of staying low-carb (while maintaining thick skin), how to build the right team using zebras in a herd of deer, winning the content game, and much more.

For more on ReSolve Asset management, visit their website, check out their Twitter, and take a listen to their very own podcast – Gestault University.

Find the full episode links of The Derivative below: