The private equity asset class has grown rapidly since 2008, attracting institutional investors in need of higher returns than those expected from public market
papers.ssrn.com
• shared by 
Marcelino Pantoja
in #Measurement
•
over 2 years ago
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Founder-in-Residence @ Platform Venture Studio
I always found it odd that PE/VC fund managers expect their portfolio companies to quantify product-market fit and unit economics but they themselves are unwilling to quantify their fund performance to their own investors.
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"In PE, we identify several structural impediments to transparency. For example, returns and fees are not measured at the base asset or the industry level, thwarting meaningful comparison by investors. Since base asset data is not routinely collected, exercised, or modeled by limited partner investors (LPs), the true investment risk within their PE portfolios is largely unknown. Instead, LP datasets usually contain only the quantities needed to calculate an internal rate of return (IRR), namely cash flows of funds and their vintage year. In our experience, this is inadequate to achieve true ‘see-through’ to the base assets and overall portfolio transparency (i.e., organic finance). Indeed, it is within this opacity that a misalignment of interests between LPs and GPs has flourished. It may be tempting for the industry to accept opacity as a natural, permanent, and even desirable characteristic of private market investing. But, as we show below, opacity is an unchecked tax on participants, limiting the industry’s ability to evolve and curtailing its value-add to the broader economy."
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"Deeper datasets – widened in scope and made interrogable by modernized measurement – open up private equity to factor analysis for the first time. Modernized measurement is the missing link that allows external factors to be mapped reliably onto private assets, and from which investing intelligence can theoretically be extracted. It is entirely feasible, then, that beyond manager evaluation, a dataset of transitive and consistently derived quantities in time-series can support proprietary econometric modeling informative to returns, volatility, capital adequacy, investment pacing, and liquidity algorithms. In other words, insight garnered from factor analysis of assets outside the portfolio can feasibly be used to improve the management of assets inside the portfolio."
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