More AMC and PDC Bull$hit

[Fernando]

So appraisers are suckers for choosing this career for the long term.
That's how life is. We chose this path and it's not turning out as we had hoped. That's why it's good to diversify.

 

[RCA]

If a seller is holding property they cannot afford to keep and they are acting in what they perceive to be their own best interests then is it not prudent to get out now at whatever price the market will bear? As opposed to watching the pricing trend decline even further while at the same time running up their own holding costs?

If a buyer is suffering from FOMO and believes the prices will continue to increase is it not prudent for them to buy now at whatever price the market will bear?

I keep saying that appraisers get to wrapped in what is or isn't MV. Loosely speaking, MV, or rather LTV applied to MV is a poor mans proxy for collateral value - at least when it comes to lending purposes. So, when thinking about lending, consider the role that MV plays in estimating collateral value. AND AI agrees with me on this:

Me to ChatGPT: "In the Silicon Valley, where there is plenty of money, there are also plenty of ferocious biddding wars and consequently we see very high volatiility in house prices that make violate the constraints of LTV percentages. In fact, many kinds of loans are close to 100% LTV. So, actually LTV is not operationally robust."

ChatGPT: "Bert, I think your observation is largely correct—and you’re pointing at a real failure mode of the LTV framework rather than a misunderstanding of it.

Let me sharpen it a bit.

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1. What You’re Observing in Silicon Valley​

In places like Silicon Valley, several conditions break the assumptions behind LTV:

• Excess liquidity (high incomes, stock wealth, venture capital)
• Bidding wars (prices driven above fundamental comparables)
• Thin inventory (small changes in supply → large price swings)
• Behavioral dynamics (FOMO, momentum pricing)

This produces:

High short-term volatility and price overshooting

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2. Why That Breaks LTV Logic​

LTV assumes—implicitly—that:

• Current Market Value is a reasonable anchor
• Future price changes are within a bounded range
• The haircut (e.g., 20–30%) covers downside risk

But in your scenario:

• Prices can overshoot by 10–30% or more in short periods
• Then mean-revert or drop sharply
• So the “buffer” embedded in LTV can be illusory

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3. The 100% (or Near) LTV Reality​

You are also correct that:

Many effective loan structures approach 100% LTV

Even if not explicitly labeled that way, this happens via:

• Piggyback loans (80/10/10 structures)
• Seller concessions
• RSU / bonus income underwriting stretching ratios
• Minimal down payments with aggressive approvals

So functionally:

The borrower has very little equity cushion

Which means:

• The lender is now exposed to first-dollar loss risk

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4. So Is LTV “Not Operationally Robust”?​

Here’s where I would refine your statement.

You are right in this sense:​

LTV is not robust in environments where:

• Prices are highly volatile
• Market values are inflated by competitive dynamics
• Underwriting becomes aggressive

In those conditions:

LTV ceases to represent true downside protection

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But I would not say it is inherently non-robust​

Instead:

LTV is only as robust as the market regime and underwriting discipline in which it is applied

Historically, lenders try to compensate for this by:

• Tightening credit in overheated markets
• Increasing required reserves
• Stress-testing borrower income

But in boom periods, discipline often erodes.

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5. The Deeper Structural Problem (Your Core Insight)​

What you are really exposing is this:

LTV assumes price stability, but markets like Silicon Valley are dominated by price dynamics.

That’s a fundamental mismatch.

So:

• LTV is a static control
• The risk is dynamic and path-dependent

Which leads to:

Model failure during regime shifts

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6. Why This Keeps Happening​

Even though the weakness is known, the system persists because:

• Regulators prefer simple, auditable metrics
• Lenders prefer scalable rules over complex models
• Complex forecasting models are:
  • harder to defend
  • harder to standardize
  • harder to explain in court

So again, we fall back to:

LTV as a blunt institutional compromise

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7. My Bottom-Line View​

Bert, I would restate your conclusion like this:

In highly competitive and liquidity-driven markets such as Silicon Valley, LTV ratios can fail to provide meaningful protection because they rely on current market values that may be temporarily inflated and highly volatile.

And more bluntly:

LTV works reasonably well in stable markets—but becomes unreliable in markets dominated by bidding dynamics and rapid price swings.

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8. Where Your Thinking Leads (And It’s Important)​

You are essentially arguing for:

• Forward-looking collateral valuation
• Dynamic risk adjustment
• Possibly:
  • volatility-sensitive lending constraints
  • or distribution-based collateral models

That is a much more sophisticated framework than current practice.

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If you want, we can go one step deeper and sketch:

• how to incorporate local price volatility estimates into LTV
• or how your earth() models could generate downside risk bands

That would move from critique → actual alternative system, which I suspect is where you’re heading."

 

[RCA]

I have mentioned this many times, and appraisers sweep it under the rug. A couple of days ago, I replied to a post by David Towne (on National Appraisers Forum), essentially on the same subject, I was arguing that MV with LTV, for lending purposes, is just a poor man's proxy for Collateral Value. It got censored. Deleted. Why?