Texas Valuation Professionals

03/07/2026

How does the concept of intrinsic value impact solar? Listen to this brief explanation…

03/06/2026

Holistic Adjustment Technique Module 4 - Interdeterminacy

I've introduced this term before, but this video goes more in depth about this concept and why it is critical in both the theory and practice of modeling real estate markets in a sales comparison approach.

Respecting the organic and structural interplay between variables (i.e., adjustment factors) was essential in the development of the method I'm endeavoring to bring to the appraisal community.
https://youtu.be/aKwG618g01k

This module defines the term interdeterminacy and why it is helpful in better understanding how to model a real estate market effectively.

03/02/2026

DFW Market Update - First Quarter 2026

After looking at local February data, I just updated the "Market Trends at a Glance" section of my website. I thought that I'd share my summary for those interested in the Dallas/Fort Worth residential real estate market.

"While the first quarter of 2026 is in many ways following seasonal norms, the overall market so far has been weaker than previous years. Relative to the same time last year, sales activity is muted with fewer closed sales, homes taking longer to sell, and supply still elevated throughout much of the Dallas/Fort Worth metroplex. Elevated supply is most pronounced in areas where new construction has continued to add to the housing stock.

Interest rates declined substantially in 2025 and pricing also declined in most market segments. The question remains whether those conditions will be sufficient to recover demand. Early indications are that buyer activity may be increasing. The number of showings per listing in February 2026 was higher than the same month in 2025. This may indicate that price and interest rate reductions may result in a stronger spring market. They may be more cautious than in previous years, but there ARE buyers out there. How many of these 'potential' buyers become 'actual' buyers is something which remains to be seen."

02/27/2026

Holistic Adjustment Technique Module 3 - The Problem of Pleasure

This is Module 3 in my discussion which is laying the foundation for my new appraisal method which I'm calling the Holistic Adjustment Technique (Patent Pending). Essentially, before I can describe the method we have to accurately frame the valuation problem. In Module 1, I asserted that it is not possible to support an adjustment in isolation. In Module 2, I discussed determinism in 2 ways and showed how a deterministic framework may not be helpful in describing a market.

In this module we talk about how the Sales Comparison Approach is a hedonic valuation model. 'Hedonic' derives from the Greek word for 'pleasure'. If we are trying to measure and isolate pleasure, we will encounter some problems. Those problems have to be addressed for the model (Sales Comparison Approach) to be employed effectively.

Continuing in the ongoing discussion of my new valuation method which I call HAT (Holistic Adjustment Technique), I talk about reframing the sales comparison...

02/16/2026

Holistic Adjustment Technique Module 2 - Determined vs. Determined

I have to give credit to Louis J. Pitoni, SRA for this video. He asked a great question about the first video in my Holistic Adjustment Technique series, which prompted what I hope will be a helpful addition to the discussion.

In a nutshell - Determined vs. Determined - what do I mean?

This video gives a demonstration that shows that this question isn't just merely semantics. Understanding the two definitions and their implications is critically important in the building blocks of a truly reliable sales comparison approach.

https://youtu.be/DBtB4KsX9Sw

Determine vs Determined - This is the second video in the series to explain the theory and practice of the Holistic Adjustment Technique. This one answers a...

02/13/2026

I've recently begun posting content which provides the conceptual framework for my new appraisal method called the Holistic Adjustment Technique (patent pending).

This is the first module which begins the discussion with the assertion that adjustments can't be supported in isolation.

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...

01/24/2026

📣 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.

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...

01/07/2026

I made a video to demonstrate the analysis of some supply and demand metrics along with charts which demonstrate price change (in my case, the output of my technique for creating a subject-specific market index).

While I've regularly discussed supply and demand shifts in a narrative format, I've started to include these supply/demand metric visuals as well. I've really found them helpful for me to both internally validate and externally demonstrate my conclusions. In other words, it helps me to answer the questions:

1) Does my pricing data really say what it appears to say?
-and-
2) Can my client draw the same conclusions about market changes from what I've presented?

Microeconomics is a core knowledge base which appraisers must draw from every day. Unfortunately, current educational requirements don't demand the mastery which is required for appraisers to become market experts.

How have you overcome this educational hurdle? Leave a comment with your experience or recommendations. Those comments might be helpful for those who feel like they need some additional resources.

If this is a hurdle which you are still tripping over, check out the comments from people who have found helpful resources. Also, feel free to drop me a note and let me know if there is something I can do to help fill in the gaps. I'm always happy to make another video if it's helpful.

PS - If you found this video helpful, please pass it along.

This video shows how visualizing supply and demand metrics alongside a custom market index can not only support conclusions about changing prices, but can he...

12/30/2025

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.

11/18/2025

Sharing some gratitude and an update on my class, Creating Formulas That Work.

11/10/2025

This is part 5 in a series of posts which I hope are helpful in reframing valuation theory and practice. In my last post, I introduced a new word which I'm finding helpful:

INTERDETERMINACY

In an 'interdeterminate' system, the variables we measure don’t just move together; they help define each other’s behavior.
That idea actually has two distinct forms, and understanding the difference between them helps explain why markets — and our data — so often resist simple, linear reasoning.

1️⃣ Organic Interdeterminacy
This is the kind that exists in the market itself — the natural interplay between features that shapes behavior.

There are causal elements to organic interdeterminacy. Remember my example from last time? The cost of remodeling rises with size, thus condition and GLA are causally linked. That is an organic interplay between condition and GLA that exists because of an actual interplay between those two variables.

These are market relationships, not statistical artifacts.

2️⃣ Structural Interdeterminacy

This happens when variables appear related because of how the data is structured, segmented, or sampled — even if the market itself isn’t creating that link.
Larger homes in the dataset are all newer, thus GLA and age appear linked.
Higher-quality homes are concentrated in one subdivision, thus quality and location appear linked.

Structural interdeterminacy is what we usually see expressed as correlation or collinearity — the statistical signatures of interdependent data.
But those measures only describe the pattern; they don’t isolate the cause.
Correlation and collinearity are measures of structural interdeterminacy, but they don’t help in isolating it.

So, why does this distinction matter?
-Organic interdeterminacy shows how the market truly behaves.
-Structural interdeterminacy shows how our dataset shapes what we can see.
Both make deterministic reasoning impossible, because both remind us that independence among variables is mostly an illusion. ♾️

That illusion is what leads to overconfidence in “precise” adjustments — when in reality, the value structure is a web of shifting, context-dependent relationships.

Recognizing interdeterminacy doesn’t mean abandoning structure; it means respecting it. So how can we respect interdeterminancy (of both kinds) in the way analyze markets?

I'll begin to talk more about that in future posts.

11/07/2025

This is part 4 in a series where I'm hoping to reframe the appraisal problem in a way that will change our perspective on how we approach the field of valuation, and the associated techniques and processes to arrive at an opinion of value.

In the last post, I agreed wholeheartedly with a comment that, "Appraisal is not rocket science." That's true, but not in the way that the phrase is typically used.

Rocket science is deterministic
Appraisal isn't.

The process of valuation takes place within 'interdeterminate' systems. 'Interdeterminacy' is literally 'the state of being mutually determined'. I coined this term (at least for use in this context) to refer to systems in which at least some of the constituent variables are interactive, or mutually constraining, such that each variable may help to determine the others.

In the last post, I demonstrated mathematical indeterminacy, where the system lacks sufficient data to be solved. While limited information is also a feature of real world systems (aka, markets), these systems are best described as interdeterminate, where interactions between variables themselves create at least a partially undetermined system.

At first, it might sound like correlation, but correlation only measures co-movement. Interdeterminacy goes deeper. It describes mutual influence.

Here are a couple of simple examples:
1) The cost of remodeling a larger home is higher than the cost of remodeling a smaller home, so differences in condition aren't just correlated with size, they are partly caused by it.
2) The traffic influence from an adjacent busy street can depend on the interplay of variables such as lot size, lot shape, and frontage (among others). It's not mere correlation. The extent to which that adverse influence is experienced is dependent upon other variables.

In interdeterminate systems each variable's effect exists in relation to other variables. These systems defy determinism and rely on probabilistic reasoning, methods, and descriptions.

In the next post, I'll break down interdeterminacies into two types.