Texas Valuation Professionals

📣 Patent Pending!

I've been waiting a long time to say that. Honestly, I thought that I would have had this filed almost a year ago. I actually had my first successful test of a computational architecture on 12/31/2024.

So why didn't I file it sooner? There was a bottleneck in the process...me. I lacked the knowledge to fully grasp the implications of what I built. I thought I was building a tool for a technique, but I began to realize that I'd stumbled upon a paradigm shift in valuation which I lacked even the vocabulary to describe.

The last year has been one of intense growth in knowledge, experimentation with variations in architecture, and also the slow realization that no man is an island.

I have a lot of gratitude for Paul Rayburn, CNAREA, DAR and Joshua Walitt. Both agreed to allow me to demonstrate the method, solicit feedback, and discuss the implications.

Paul Rayburn and I share a similar philosophy of the need to collaborate in the valuation community. He does that so well. He is impressive in the extreme with his own projects and I have learned a lot from our conversations over the past couple of years.

Josh Walitt is one of the clearest communicators I know. Although he is a master teacher, he is an even better student. The kind who is genuinely curious and asks the sort of questions which have helped me to realize that knowledge remains fruitless until it can be communicated well.

Thanks also go to Brennan Hudson. Brennan is the youngest Certified Appraiser in my office and is quickly becoming one of the best appraisers that I've ever worked with. He has been testing different iterations of my method since almost the beginning.

In the coming days and weeks, I'll begin talking more about the method. I'll be posting much of that content on my YouTube channel. (I'll post a link to the channel in the comments.) I'll also be working on some papers and related content as time goes on. I started calling this method the "Holistic Adjustment Technique" sometime last year, but it really is more of a method than a technique which will become clear.

I've posted the first video which begins to explain how we've been taught to view the sales comparison approach in a deterministic way, but it actually represents an interconnected system of uncertainty which can't be ignored.

First Teaching Module for New Real Estate Valuation Method! This is the first in the series of teaching modules which explain the theory behind Brent Bowen's new Valuation Method he's been calling "HAT" (Holistic Adju...

Part 6 of the Zone of Inference Series: Bayesian Reasoning

In the first five posts of this series, I’ve been laying out some of the real world complexities in handling small or highly variable data sets (aka, comparables). If you haven't read the first 5 posts, I recommend doing so as I've covered a lot of ground. A brief summary:

1) Adjustments live in the Zone of Inference — neither fact nor opinion
2) Mathematical indeterminacy means no single “correct” adjustment
3) Valuation is a probabilistic problem, not a deterministic one
4) Markets are 'interdeterminate': variables interact and constrain one another
5) Interdeterminacy defeats simple, linear reasoning

All of that raises an obvious question:
How should we reason when the data cannot fully resolve the problem?

A part of the answer comes from a framework widely used in other fields that deal with small, noisy, highly variable data sets: Bayesian reasoning.

At its core, Bayesian reasoning is not about complex math. It’s about how we think under uncertainty.

In simple terms:
-We don’t start from zero knowledge
-We update our understanding as new evidence appears
-Prior well-supported experience/observation matters
(even when those observations aren't directly useful for a given assignment)

In appraisal, Bayesian reasoning means recognizing that accumulated market evidence can inform:
-The direction of an influence
-The plausible range of market reaction
(even when the current comparables are too messy within an interdeterminate system)

Bayesian reasoning is really helpful in understanding the dangers of a "default to zero" mindset when influences aren't easy to extract from a data set. When we default to a $0 adjustment simply because paired sales or sensitivity analysis don’t resolve an effect cleanly, we aren’t being neutral—we’re making a strong assumption of market indifference. In interdeterminate systems, that assumption is often less defensible than a bounded adjustment grounded in prior evidence and logic.

Bayesian reasoning doesn’t replace paired sales, market studies, or modeling. It works with them, helping us navigate the Zone of Inference (without pretending markets are more precise than they are, and without pretending uncertainty equals zero).

Bayesian reasoning and mathematically derived Bayesian priors have a valuable place in the context of probabilistic reasoning and analysis. As I continue this series, I'll begin to show how these can fit into a completely new way of thinking about and applying the sales comparison approach in valuation.