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Brent Beshore @BrentBeshore
, 16 tweets, 4 min read Read on Twitter
Read @ryan_caldbeck’s thread, then come back.

We’ve been exploring this topic @adventur_es for 3-4 years now. In addition to an information advantage and a large sample size, transaction costs and governance are crucial components in private transactions.
These two additional components, transaction costs and governance, comprise friction that is 1000X higher than public markets. Quant hedge funds can identify and purchase a stock in a blink at almost no cost and with no governance function, then sell it just as easily.
PE must hire talented (expensive) people to find, negotiate, diligence, document, govern, and eventually created a negotiated sale. This hardship is costly, but also provides opportunities for alpha.

In PE, here’s how a quant system might work at scale:
1) Would be factor-driven that selects for probabilistically advantageous situations, with some factors being universal and others being industry-specific, or perhaps macro-specific (interest rates/inventory analysis). But remember, small/private company data is notoriously bad.
2) The PE brand goes from being largely irrelevant to a must-have. Going “out-bound” with traditional biz dev doesn’t work. You must get willing sellers to raise their hands, self-educate, and self-extract information. This is a complete inverse of how the current system works.
3) Standardize an offer that is easily understood and highly attractive. Some combination of above-market multiples, seller-friendly terms, and speed to close. Most sellers have FOMO higher than a pack of hormonal teenagers. The offer must be take-it-or-leave-it.
4) Make due diligence discovery a one-sided fill-in-the-blank affair but intentionally intensive and on a shot clock, with light touch judgement from highly experienced deal pros. This selects for teams that are organized and thoughtful, creating a proprietary factor.
5) Standardize documentation with default settings across ~400 decisions and require a specific situational hardship to alter. Initially lawyers will be a major impediment, as phantom nuance is a major source of their financial gain.
6) The seller creates a post-close leadership plan, with employment agreements and incentives that align to that plan. A portion of the purchase price is tied to the successful execution.
7) Standardize reporting and portfolio management. Very little “tuning” and almost all governance-related oversight, similar to a public company board, but streamlined. This also eliminates a theoretically large source of alpha, although my friend @verdadcap would disagree.
8) Create a SWAT team of fix-it pros for when things go south and is called in by the board.

9) Create an open auction system for selling the companies that allows potential bidders to monitor progress, effectively doing on-going diligence. Offers are submitted until acceptable.
That sound complicated and hard? It is, but heck, so is traditional private equity.

While we’re no where close to creating this type of system, @adventur_es has taken baby steps towards it and we want to go much further, at least in areas that don't create unnecessary sterility.
We track factors that we believe are advantageous, constantly thinking of new ones and fine-tuning the weighting.

The vast majority of our deal flow is in-bound.
For over a year we’ve been working on standardized deal docs that clearly explain the “middle ground” for each decision. Eventually we'll open source them.

We often co-create leadership plans and almost always tie a financial outcome to them.
Ultimately, I agree with @ryan_caldbeck that a systematic quant approach to PE would beget a massive outcome. The devil is in the details. Unfortunately those details are many and don’t lend themselves to an algorithmic solution.
If others have thought about this problem, specifically related to PE, I’d love to chat. Please reach out.

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