Idea two: Quant consigliere to lead quant bootstrapping

Pros/Cons: Solves the big early team, small later on, Solves the ex-post-facto problem. Strategy leaking depends whether the post-launch team is external or internal.

Quant bootstrapping:

Quant bootstrapping is the idea that you fund quant development cheaply and ALSO somehow delay paying for the most expensive labor costs until the strategy launches, so you can fund those costs from PnL.

The idea is then:

  • Get the most expensive people/person to accept delayed payment out of PnL.

  • Use internal people you already have to make up the rest of the team.

  • Develop the strategy with only the most critical safeguards. Keep track of the safeguards you are skipping. Launch the strategy. Then using the PnL hire a team to go put those safeguards in later.

For that to work you need to 1. Use someone who will accept delayed funding. 2. Do it cheaply, but keep the few time-bombs to a minimum. 3. Defuse the bombs before they go off.

#1 Probably easier to do by hiring an external consultant with multiple streams of income. Also hire someone senior who has an income cushion.

#2 Get someone on the team with an extensive history of on-the-ground battlefield experience, who knows potential problems, the underlying causes and how to prevent them — especially hidden problems that manifest later.

#3 Explain the concept of time-bombs to leadership before agreeing to start. Don’t go ahead unless you feel completely sure that leadership is completely comfortable with the fact that all the early PnL will go to fund the consigliere and fund bomb disposal.

Quant consigliere — Alpha, data, team, culture. Quant prediction, platform, teams and keys to making quant successful— and applications to algorithmic trading.

Quant consigliere — AI tools. AI tools and original AI research. Supported by quant alpha research partner — who can augment with context for the application of AI to investment and trading.

Based on feedback, we are working on a creative solutions to several problems setting up quant at a small to medium sized firm.

Big early team, small later on

Quant strategy setup and implementation requires a big team early on to set up all the platform things, and automate inference, data pipelines and data cleaning. Then the team gets smaller. This is somewhat annoying for a small firm since you would spend a lot of money to find and hire and then integrate a large number of people who you don’t need long term.

Ex-Post-Facto Problem

Smaller firms with a performance fee structure find that it’s much better to fund any strategy development from performance fees. This is tricky with quant, due to the relatively large amount of up-front work, followed by lower amount of work ongoing.

Idea one: Outsourced quant team.

Build a full outsourced quant team.

Pro: Solves the “big early team, small later on” problem

Cons: Possible strategy “leaking”. Still has some of the “Ex-post-facto” problem, although upfront cost is smaller due to “sharing” the cost with other firms.

Subject to demand, we may consider setting up a full quant team that any firm can hire. This would let a senior sponsor build and launch alpha strategies with a single permanent hire. For legal and compliance reasons we recommend that an internal hire - or existing person — own the alphas and oversee their execution. The external team could include any or all of the following — quant researcher, AI scientist, quant-dev, quant platform, data, data licensing, data ops, data validation, quant risk, and alt-data legal. FYI, this is a potential solution to the “big early team, small late team” puzzle.