short term working capital

The Development of Data-Driven Investing

Data-Driven Investing

From Financial Engineering Applied to Private Markets to Real Estate Asset Management and Retail Financial Advisory

People typically don’t enjoy arithmetic.

In order to escape obvious hazards like ferocious predators, the human brain developed to make quick, basic, intuitive decisions. The need for mathematics to survive was minimal, and for many people it still is. In fact, the mental energy needed to do math would have been better spent elsewhere.

Regrettably, dangers in finance are often less evident and necessitate a deliberate strategy to adequately manage. In actuality, they are incredibly complex, requiring not only a great qualitative understanding of the business aspects connected with an investment but also comparably intricate arithmetic in order to quantify them meaningfully.

Alone, computations are insufficient.

It is not math that was one of the main reasons of the 2008 financial crisis, but rather a lackluster attempt to determine which relevant elements to include in the computations.

(One could argue that these elements were purposefully left out in order to prolong the immensely lucrative game of musical chairs, but that’s an other story.)

Therefore, most people consider risk based on an intuitive sensation that often has nothing to do with reality, rather than using math.

Someone who fears flying on a commercial aircraft but has no trouble rushing through traffic on a clogged highway where the likelihood of death is clearly higher is a pretty regular example of this phenomenon. People frequently assume that they have control over a situation, which lowers risk, but this is not always the case, especially when it comes to financial problems. This misconception is a major contributing cause to this misestimation.

Even though they have little to no experience in the field, people’s desire to lower perceived risk through direct control is most frequently expressed through real estate investing.

The ultra-high-net-worth individuals who depend on a family office for full financial and investing services—a starkly ironic example of this paradox—always DIY when it comes to real estate.

When real estate investors do, in fact, start thinking about risk management, they typically speak in terms of operational heuristics: lower risk by purchasing the worst home in the best neighborhood, hiring experts, taking out a loan on favorable terms, etc. Despite the fact that these quasi-solutions start to address the problems that all increase the likelihood of a bad outcome, they are insufficient, as the enormous losses suffered by investors in 2008 made painfully clear.

And similarly to pre-2008, when the previous ten years’ bull market had lulled investors into a false sense of confidence, this wave of do-it-yourself investors is ill-prepared for the next catastrophe, which is probably going to happen soon.

Here is a concrete illustration of how an average real estate investor or asset manager considers and conveys their predicted performance in comparison to the most correct way to do so (assuming the approach has no actual track record over the course of a full market cycle):

Representative of Real Estate Asset Manager

An overview of a typical real estate asset manager’s strategy analysis may be found in the left column (Pro Forma Returns). For the accurate analysis, see the Theoretical Track Record column on the right.

The pro forma is based on the assumption that market circumstances from prior years will persist forever.

The best predictor of future performance is the theoretical track record, which transforms the strategy into an extensive set of objective rules. Real historical data is then plugged into those rules to determine how the strategy would have performed versus each stage of the market cycle.

This disparity between the theoretical track record and pro forma performance is a very regular occurrence. It clarifies why real estate sponsors who reduce payouts are a frequent source of conflict for independent broker-dealers, or “IBDs.”

While gathering all the information needed to fully comprehend how an investment plan would have done over the course of a market cycle is undoubtedly time-consuming, what other option is there? Stealing the life savings of others and yourself?

Conversely, a complex sector indirectly supports the average financial advisor, despite the advisor’s lack of sophistication. The issue facing ordinary investors is that expertise serves the interests of the financial industry’s elite rather than its clients.

Since they are usually standard allocations with real track records spanning decades, there’s usually no need to even build a theoretical track record or backtest a traditional portfolio.

These common allocation models work as follows, which explains why so many people choose to do their own investing because they are justifiably disenchanted with conventional financial advisors