Texas Valuation Professionals

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

That solar system on your roof? It’s not just saving you money, it’s actually creating value. That’s “intrinsic value” in action—turning sunlight into measurable dollars! ⁠ ⁠ Save this tip for later 👇⁠ ⁠ #SolarValue #IntrinsicValue #BehindTheMeter #SolarSavings #HomeValue #GreenEnergy

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."

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.

Holistic Adjustment Technique Module 3 - The Problem of Pleasure Continuing in the ongoing discussion of my new valuation method which I call HAT (Holistic Adjustment Technique), I talk about reframing the sales comparison...

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.

Supply/Demand Metrics 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...

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.

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.