Valuation Frequency in Direct Real Estate: When More Frequent Isn’t More Informative

In direct real estate, a more frequently updated valuation can look more precise without actually being more informative. That is the central point of B. P. Nesbitt’s June 2026 paper, “Valuation Frequency in Direct Real Estate,” which asks whether daily, monthly, or quarterly marks truly improve price discovery in an asset class that trades infrequently and is often appraised with a lag.

The distinction matters because investors often treat a more frequent NAV as if it were a better NAV. But in illiquid property markets, a daily or monthly value is often built from older appraisal anchors, roll-forwards, and managerial judgment rather than from fresh market transactions. In that setting, more frequent publication may improve convenience, but not necessarily truth.

What the paper examined

Nesbitt’s paper compares valuation frequency across five cycles: daily, monthly, quarterly, semi-annual, and annual. The core question is not whether higher-frequency values can be produced, but whether they incorporate new information as often as they are published. The paper also develops a framework to separate three things that are often blurred together: latent economic value, formal appraisal value, and interim dealing value.

To test the idea, the author uses a stylized Monte Carlo simulation that holds the informational environment constant while varying the valuation frequency. That is a useful design because it isolates the mechanism: does more frequent reporting improve valuation, or does it just subdivide the same smoothed signal into smaller pieces?

What the paper found

The results are not “daily is bad” or “quarterly is enough.” They are more nuanced than that.

On average pricing error, daily valuation performs best, monthly is in the middle, and quarterly is worst in the baseline simulation. So yes, more frequent marks can reduce measured error. But the deeper result is that daily valuation often behaves like interpolation rather than genuine daily price discovery. Its measured volatility is extremely low, and it does not improve recognition lag much except in the most severe shock scenario.

Monthly valuation comes out looking like the most balanced compromise. It meaningfully improves error versus quarterly valuation, recognizes ordinary shocks faster, and does not flatten the volatility profile to the same degree as the daily series. In plain English: monthly updates seem to add useful timeliness without pretending the market is continuously repricing every day.

The paper also finds that higher-frequency dealing values can remain materially dependent on slower appraisal anchors. That means a fund can publish values more often while still carrying much of the same lag and smoothing problem underneath. In open-ended and semi-liquid structures, that can create dilution risk, liquidity illusion, and investor-transfer effects when subscriptions and redemptions are struck against values that are not fully current.

Regarding the findings, Nesbitt offered the following caution: “The simulation evidence reported here should be read as exploratory, but it is still revealing.”

What investors should take away