Derivative Calculus Price Momentum Analysis™

Palos Verdes Peninsula
Sold-Market Derivative Analysis

252 Closed Residential Sales  ·  February 2 – July 31, 2026

George Fotion, REALTOR®

Call Realty  ·  California DRE #00785373
45+ Years of Consecutive Daily CRMLS Tracking
(424) 722-9136  ·  george.fotion@homeispalosverdes.com
PalosVerdesHomesBest.com  ·  SearchHomesInPrivate.com

Data Integrity Verification — Passed

Dual-pass read (pandas + openpyxl) with Counter assertion on the Status column: 252 / 252 rows matched. Zero duplicate MLS Listing IDs. All 252 records carry Standard Status = Closed. Close dates span 2026-02-02 through 2026-07-31. Contract dates run back to 2025-11-01, confirming a pipeline that predates the close window.

Executive Summary

252 Closed Sales Feb–Jul 2026	$2.30M Median Close Mean $2.72M	$889 Median $/SF Mean $921	17 Median CDOM Mean 52.8
47.6% Sold ≤ 14 Days 120 of 252	28.6% Closed Over Ask 72 of 252	98.9% Mean SP / LP Median 98.7%	25.0% Took a Reduction 63 of 252

This six-month window is not a single market. It is two markets running side by side, separated almost entirely by one variable: how long a listing stays on the market. Homes that found a buyer inside fourteen days closed at 102.2% of original list price. Homes that lingered past 120 days closed at 85.4%. That is a 16.8-percentage-point spread — on a $2.3M median, roughly $386,000 of realized value determined by early pricing accuracy rather than by property quality.

Applying the first-derivative and second-derivative framework to the sold cohort: the first derivative (price velocity) is mildly positive — median $/SF rose from $837.63 in February to $893.30 in July, with a mid-window peak of $948.69 in June. The second derivative (acceleration) turned negative in July: the trailing 90-day median of $928.87 sits above the July print of $893.30, meaning the rate of gain is decaying even as the level holds. Momentum is intact; acceleration is not.

The critical honest caveat, established up front: the time trend in this dataset is not statistically significant. A hedonic log-price regression controlling for MLS Area, living area, lot size, and view returns a time coefficient with p = 0.297. Six months of 252 transactions cannot resolve a true annual appreciation rate. Every projection in Section 4 is presented with that uncertainty made explicit rather than buried.

Section 1 — Six Actionable Patterns in the Data

Pattern 1: The 14-Day Cliff — The Single Most Actionable Finding

Sorting all 252 sales by Cumulative Days Active in MLS and measuring realized price against original list price produces the cleanest monotonic decay in the entire dataset:

CDOM Bucket	Sales	Close / List	Close / Original List	Median $/SF	Share That Cut Price
0–7 days	68	102.2%	102.3%	$966	0.0%
8–14 days	52	102.2%	102.0%	$840	3.8%
15–30 days	37	97.9%	97.4%	$888	8.1%
31–60 days	37	95.8%	92.4%	$888	51.4%
61–120 days	25	95.6%	92.3%	$793	52.0%
120+ days	33	93.8%	85.4%	$811	78.8%

Note the structural break between the 8–14 and 15–30 buckets. Realized value does not decay gradually — it steps down. The 0–14 day cohort (120 sales, 47.6% of the market) is the only group that closes above original list. Everything after is a discount, and the discount deepens.

Pattern 2: The Size Discount Is the Strongest Effect in the Data

In the hedonic regression, log living area is the dominant explanatory variable: coefficient −0.264, t = −5.67, p < 0.0001. Every 10% increase in square footage reduces price per square foot by approximately 2.5%. Holding area and view constant, the implied $/SF index runs:

Living Area	2,000 sf	2,500 sf	3,000 sf	3,500 sf	4,000 sf	5,000 sf
$/SF Index (median home = 1.00)	1.080	1.018	0.970	0.931	0.899	0.848

A 5,000 sf home earns roughly 21.5% less per square foot than a 2,000 sf home in the same area with the same view. This is not a Palos Verdes anomaly — it is the standard land-value-dilution effect — but the magnitude here is large, and it is routinely ignored when sellers of large homes benchmark against small-home comps.

Pattern 3: The Ocean View Premium Is Real — and Raw Data Hides It

Compare ocean-view to non-ocean-view sales across the whole Peninsula and the premium looks like nothing: $905 vs. $888 median $/SF, a rounding error. That number is wrong, and it is wrong in an instructive way.

Ocean-view inventory concentrates in structurally lower-$/SF areas — PV Drive East, PV Drive South, Los Verdes — while non-view inventory concentrates in Valmonte and Lunada Bay, the highest-$/SF areas on the hill. The mix cancels the effect. This is a textbook Simpson’s paradox.

Control for MLS Area and living area in the hedonic model and the premium resolves cleanly: +9.3% per square foot, t = 2.34, p = 0.020. Within-area comparison confirms it — the ocean premium is positive in 8 of the 12 areas with both cohorts present, reaching +47.1% in Country Club, +40.8% in PV Drive South, and +37.2% in Malaga Cove.

The premium tier above ocean is whitewater/bluff frontage: 12 sales, mean $1,043.75/SF against a market mean of $920.78. But note the standard deviation on that group — $406.20, the widest dispersion of any view tier. Whitewater is the most valuable and the least predictable segment on the Peninsula.

Pattern 4: Area Stratification Is a 60% Spread

Mean $/SF runs from $1,181.66 in Malaga Cove down to $739.74 in PV Drive East — a 59.7% spread across a peninsula you can drive end to end in twenty minutes. The top tier (Malaga Cove, Rolling Hills, Valmonte, Lunada Bay) all clear $1,040/SF. The value tier (PV Drive East, West Palos Verdes, Crest, Peninsula Center, PV Drive South) all sit below $815/SF.

PV Drive North is the volume engine: 43 sales, 17.1% of all Peninsula transactions, at $951.44 mean $/SF with a 10-day median CDOM. It is simultaneously the most liquid and the most representative submarket on the hill.

Pattern 5: The Price Reduction Penalty Is Severe and Self-Inflicted

63 of 252 sellers (25.0%) reduced their asking price. The consequences are not subtle:

Cohort	Sales	Close / Original List	Median CDOM	Median $/SF
Never reduced	189	100.1%	10 days	$899
Reduced at least once	63	87.2%	89 days	$850

A 12.9-point gap in realized price and an 8.9× gap in market time. Causation runs mostly from mispricing to reduction to discount — the reduction is the symptom, not the disease — but the sequence is consistent enough to treat the first price as the decision that sets the outcome.

Pattern 6: Momentum Positive, Acceleration Negative

Monthly median $/SF: Feb $837.63 → Mar $857.79 → Apr $819.90 → May $942.17 → Jun $948.69 → Jul $893.30. Quarterly medians smooth the noise: Q1 $857.54, Q2 $910.05, Q3 (July only) $893.30.

Market time compressed sharply through the spring — median CDOM fell from 42 days in February to 11 days in May and June — then expanded back to 21 days in July. Simultaneously, the share of sellers reducing price fell from 34.8% in February to 17.8% in May, then began climbing again. Both the July CDOM expansion and the reduction-share uptick are second-derivative warnings, though a single month is not a trend.

Section 2 — Distribution & Dispersion Charts

Twelve charts across six variables. For each variable: a histogram showing the shape of the distribution, and a standard deviation chart showing dispersion. For the four continuous variables the dispersion chart compares actual coverage inside ±1σ, ±2σ and ±3σ against Gaussian expectation — the gap between the two is a direct measure of how badly a normal-distribution assumption would mislead you on this market.

1. MLS Area

Sales Volume Distribution by MLS Area

Closed transactions, February–July 2026 · n = 252

PV Dr North (43) and Lunada Bay/Margate (33) together account for 30.2% of all Peninsula closings. Six areas produced fewer than 12 sales in six months — treat pricing conclusions in those areas as directional only.

Mean $/SF ± 1 Standard Deviation by MLS Area

Gold bar = ±1σ range · blue marker = mean · sorted by mean $/SF

Malaga Cove carries both the highest mean ($1,181.66) and the widest dispersion (σ = $377.45) — a small, heterogeneous, high-variance market. West Palos Verdes is the tightest (σ = $46.46) but on only 4 sales. Los Verdes (σ = $142.01, n = 15) and Peninsula Center (σ = $137.32, n = 15) are the genuinely most predictable submarkets at credible sample size.

2. Living Area

Living Area Distribution

Square feet · n = 252 · mean 2,974 sf, median 2,673 sf, σ = 1,206 sf

Right-skewed (skewness +1.85). The 2,000–2,500 sf band is the single largest cohort at 63 sales. Mean exceeds median by 300 sf because a thin tail of estate properties up to 8,750 sf pulls the average up — another reason median is the correct central measure for this market.

Living Area — Standard Deviation Coverage vs. Normal Expectation

Actual share of sales inside each σ band, against Gaussian theory

Actual ±1σ coverage is 81.0% against a normal expectation of 68.3% — a 12.7-point excess. The distribution is peaked and right-tailed, not bell-shaped. ±1σ spans 1,767–4,180 sf.

3. Cumulative Days Active in MLS

Cumulative Days Active Distribution

Days · n = 252 · mean 52.8, median 17.0, σ = 89.6

The most extreme distribution in the dataset: skewness +3.42, coefficient of variation 1.695. 68 homes sold within a week; 5 sat over a year, the longest at 605 days. The mean of 52.8 days describes almost no actual listing — quoting ‘average days on market’ on this Peninsula is statistically indefensible.

CDOM — Standard Deviation Coverage vs. Normal Expectation

Actual share of sales inside each σ band, against Gaussian theory

±1σ captures 89.3% of sales against 68.3% expected — a 21-point excess, the largest distortion of any variable here. The lower bound of ±1σ is −36.7 days, which is physically impossible and is itself proof that a symmetric dispersion model does not describe market time.

4. Close Price

Close Price Distribution

n = 252 · mean $2,718,800, median $2,297,500, σ = $1,390,872

Skewness +2.49. The $1.5–2.0M band is the market’s center of gravity at 76 sales (30.2%), with $2.0–2.5M close behind at 65. Above $4M the market thins abruptly — 29 sales across four brackets spanning $4M to $9.7M.

Close Price — Standard Deviation Coverage vs. Normal Expectation

Actual share of sales inside each σ band, against Gaussian theory

±1σ covers 86.9% versus 68.3% expected. ±2σ reaches down to −$62,944 — again nonsensical, again a direct demonstration that price on this Peninsula is log-normal, not normal. Any pricing model built on symmetric standard deviations around the mean will systematically overprice the bottom of the market and underprice the top.

5. Price Per Square Foot

Price Per Square Foot Distribution with Normal Overlay

n = 252 · mean $920.78, median $889.18, σ = $240.64 · dashed line = fitted normal curve

The best-behaved variable in the dataset — skewness +0.97, coefficient of variation 0.261, and the fitted normal curve tracks the observed bars reasonably through the body. Modal band is $700–800/SF (59 sales). The right tail is still real: 14 sales cleared $1,400/SF, topping out at $1,890.89.

Price Per Square Foot — Standard Deviation Coverage vs. Normal Expectation

Actual share of sales inside each σ band, against Gaussian theory

The closest fit to normality of any variable: 73.4% actual against 68.3% expected at ±1σ, 94.0% against 95.4% at ±2σ. This is precisely why $/SF — not close price — is the correct unit for statistical work on this Peninsula. ±1σ spans $680 to $1,161.

6. View

Sales Volume by View Tier

n = 252 · tiers assigned by CRMLS View field token parsing

47.6% of Peninsula sales carry an ocean or water view; only 4.8% carry whitewater or bluff frontage. 27 records (10.7%) have a blank View field — a data-quality note, not a finding: blank is not the same as ‘no view.’

Mean $/SF ± 1 Standard Deviation by View Tier

Gold bar = ±1σ range · blue marker = mean

Read this chart together with Pattern 3. The raw tier means look almost flat — that is the Simpson’s paradox at work, because view tiers are unevenly distributed across price areas. The mix-adjusted ocean premium is +9.3% (p = 0.020). What the chart does show honestly is dispersion: whitewater/bluff carries σ = $406.20, nearly double the ocean tier’s $221.83.

Section 3A — Buyer Advisory

Five plays supported directly by the 252-sale dataset.

1. Hunt in the 60-Day-Plus Aging Bucket — That Is Where the Discount Lives

58 of 252 sales (23.0%) closed after more than 60 days on market, and that cohort realized 92.3% and 85.4% of original list in the 61–120 and 120+ buckets respectively. The 0–14 day cohort realized 102%. There is no negotiating leverage on a fresh listing in this market — 47.6% of homes are gone inside two weeks and 28.6% close over ask. Your leverage is time, and it belongs to properties the market has already passed over. Set your search alerts on CDOM, not on new-listing notifications.

2. Buy the Larger Home — the $/SF Math Is Structurally in Your Favor

The hedonic model is unambiguous: −0.264 log-living-area coefficient, p < 0.0001. A 4,000 sf home transacts at roughly 0.899 on the $/SF index versus 1.080 for a 2,000 sf home — a 16.8% per-foot discount for the larger property. If your budget clears the absolute price point, square footage is the cheapest thing you can buy on this Peninsula. The catch is exit liquidity, addressed in the Devil’s Advocate section.

3. Target the Value Tier for Entry — PV Dr East, Crest, Peninsula Center, PV Dr South

PV Drive East transacted at a $739.74 mean $/SF against Malaga Cove’s $1,181.66 — the same school district, the same Peninsula, a 37.4% per-foot difference. PV Dr East also carries a 51.5-day median CDOM versus 11 days in Malaga Cove, which means both a lower entry price and materially more negotiating room. Crest ($804.74) and Peninsula Center ($811.40) offer the same profile.

4. Pay for the Ocean View If You Are Holding — Skip It If You Are Not

The mix-adjusted ocean premium is +9.3% per square foot (p = 0.020) — real, but far smaller than most buyers assume, and smaller than the 37–47% within-area gaps in Malaga Cove, PV Dr South and Country Club suggest in isolation. On a $2.3M purchase the statistical premium is roughly $215,000. If the view is the reason you want the house, buy it. If it is a resale-value calculation, note that whitewater/bluff properties carried a 47-day median CDOM against the market’s 17 — the premium tier is the least liquid tier.

5. Do Not Wait for a Better Price — but Do Not Assume One Is Coming Either

The base-case projection in Section 4 is +4.9% $/SF over twelve months, with a plausible range from −0.8% to +11.0%. On a $2.3M home the base case costs a waiting buyer about $113,000 — real money, but not the runaway appreciation an unadjusted reading of the February-to-June trend would suggest. The honest position: timing this market on six months of data is not a strategy. Buy when the right property appears, and let pricing discipline rather than market timing do the work.

Section 3B — Seller Advisory

Five plays, in descending order of measured financial impact.

1. Your First Price Is the Whole Ballgame — Everything After Is Damage Control

16.8 percentage points of realized value separate the 0–7 day cohort (102.3% of original list) from the 120+ day cohort (85.4%). On the $2,297,500 median close price that is roughly $386,000. The 189 sellers who never reduced averaged 100.1% of original list in 10 median days; the 63 who reduced averaged 87.2% in 89 days. Nothing else in this dataset — not view, not area, not staging, not season — moves realized price by anything close to that margin.

2. Price for the 14-Day Window or Do Not Bother

120 of 252 sales — 47.6% — closed within 14 days, and that cohort is the only one that beat original list. Beyond day 30, average realized price drops below 97.5% and never recovers. Practically: set the list price at a level where you would expect an offer inside two weeks. If your pricing analysis says 45 days, the data says you are going to end up taking a reduction and closing near 92%.

3. If You Are Selling a Large Home, Benchmark Against Large Comps Only

The size discount is the strongest single effect in the regression. Sellers of 4,000–5,000 sf homes who anchor on the $/SF their 2,500 sf neighbor achieved are starting 12–17% above market, and that is exactly the error that produces the 120-day, 85%-of-list outcome. Rolling Hills illustrates the mechanic: highest median living area on the Peninsula at 5,084 sf, a 44-day median CDOM, and an 88.9% close-to-original-list ratio — the second-lowest of any area.

4. Sell Into Spring Liquidity — but Understand What the Seasonal Signal Is Worth

Median CDOM compressed from 42 days in February to 11 days in May and June, and the share of sellers forced into a reduction fell from 34.8% to 17.8% across the same span. Then July expanded back to 21 days. With one year of data this is a seasonal pattern, not a proven one — six months cannot separate seasonality from trend. Treat it as a reason to prefer a spring launch, not as a reason to hold an otherwise-ready property for six months.

5. Verify Your View Field — 10.7% of Sold Listings Had It Blank

27 of 252 closed listings carried an empty CRMLS View field. Given that the mix-adjusted ocean premium is +9.3% per square foot, a blank View field on an ocean-view property is leaving a measurable pricing signal off the sheet at exactly the moment buyers are filtering. This costs nothing to fix and it is the single highest-return five minutes in a listing preparation.

Section 4 — Twelve-Month Price Per Square Foot Projection

Methodology Disclosure — Read Before the Numbers

Raw OLS on the monthly median series returns a slope of $19.24/month, or +26.1% annualized. That number is not credible and it is not used here. Six months of data with 252 observations produces a transaction-level trend with r² = 0.008 and p = 0.150 — indistinguishable from zero. The mix-adjusted hedonic estimate (controlling for MLS Area, living area, lot size and view) is +11.1%/yr with p = 0.297 and a 95% confidence interval of −8.8% to +35.4%. The projection below applies Bayesian shrinkage against a long-run Peninsula appreciation prior of 3.5%. Because the sample carries so little information, the data receives a weight of only 0.190. This is the honest treatment, and it is deliberately far more conservative than the raw series implies.

Anchor: trailing 90-day median $/SF = $928.87 (n = 136), as of July 31, 2026. Full six-month median is $889.18; the 90-day anchor is used because it reflects the current market rather than the average of the window.

Month	Bear Case (−0.8%/yr)	Base Case (+4.9%/yr)	Bull Case (+11.0%/yr)
Aug 2026	$928	$933	$937
Sep 2026	$928	$936	$945
Oct 2026	$927	$940	$953
Nov 2026	$926	$944	$962
Dec 2026	$926	$948	$970
Jan 2027	$925	$951	$978
Feb 2027	$924	$955	$987
Mar 2027	$924	$959	$996
Apr 2027	$923	$963	$1004
May 2027	$922	$967	$1013
Jun 2027	$922	$971	$1022
Jul 2027	$921	$974	$1031
12-Month Change	−0.8%	+4.9%	+11.0%

Bear and bull are the 10th and 90th percentiles of the shrunk posterior, not worst-case and best-case scenarios. A genuine external shock — a rate spike, an insurance-market dislocation, a coastal-hazard reassessment — falls outside this band entirely.

Submarket Projections — Areas With n ≥ 11

The same growth rates applied to each area’s current median. This assumes uniform appreciation across submarkets, which is an assumption, not a finding — the dataset cannot support differentiated per-area growth rates at these sample sizes.

MLS Area	Current Median $/SF	Bear (Jul 2027)	Base (Jul 2027)	Bull (Jul 2027)
Valmonte	$1145	$1135	$1201	$1270
Malaga Cove	$1126	$1117	$1181	$1249
Monte Malaga	$1025	$1016	$1075	$1137
Lunada Bay/Margate	$1018	$1009	$1068	$1129
PV Dr North	$912	$904	$956	$1012
Mira Catalina	$878	$871	$921	$975
Silver Spur	$875	$868	$918	$971
Los Verdes	$834	$827	$875	$925
Peninsula Center	$779	$772	$817	$864
PV Dr South	$770	$763	$807	$854
Crest	$744	$738	$781	$826
PV Dr East	$720	$714	$755	$799

Derivative Calculus Insight

First derivative (velocity): positive but decelerating. Median $/SF gained $55.67 from February to July, but the June-to-July change was −$55.39.

Second derivative (acceleration): negative. The trailing 90-day median ($928.87) sits $35.57 above the July print ($893.30), and median CDOM expanded from 11 days in June to 21 in July — a 91% increase in market time in a single month.

Inflection point: the base-case path crosses $950/SF in approximately November 2026 and $970/SF in May 2027. Under the bear case the series never crosses $930 and drifts sideways. The distance between those two outcomes over twelve months is $53/SF — roughly $142,000 on a 2,673 sf median home. That spread is the honest measure of what six months of data can and cannot tell you.

Section 5 — Devil’s Advocate

Every conclusion above, argued against. A client who reads only Sections 1 through 4 has read half the analysis.

1. The Projection Rests on a Statistically Insignificant Trend — Full Stop

This is the most serious objection and it deserves to lead. The time coefficient in the hedonic model has p = 0.297. The transaction-level regression has r² = 0.008 — time explains less than one percent of the variance in price per square foot. A Mann-Whitney test comparing the first half of the window to the second returns p = 0.141. By any conventional standard, this dataset does not demonstrate that Palos Verdes prices rose at all between February and July 2026. The +4.9% base case is a shrunk prior wearing the clothes of an estimate. Anyone using it to justify a purchase or a hold should understand that the sample is consistent with zero.

2. Six Months Cannot Distinguish Trend From Seasonality

February through July is spring and early summer — structurally the strongest listing season in Southern California. The observed CDOM compression from 42 days to 11 and the $/SF rise from $837 to $948 are exactly what pure seasonality would produce with a flat underlying market. Without a February 2025–July 2025 comparison in the file, there is no way to separate the two. The July reversal — CDOM back to 21 days, $/SF back to $893 — is at least as consistent with normal post-peak seasonal cooling as with a genuine trend inflection. Add a prior-year cohort to this analysis and the projection could move materially in either direction.

3. Sold Data Is Survivorship Data — the Failures Are Missing

This file contains 252 closed sales. It contains zero expired listings, zero withdrawn listings, zero cancellations. Every seller in this dataset succeeded. If a meaningful share of 2026 listings failed to sell — and the 25% reduction rate and 605-day maximum CDOM suggest some did — then the true market-clearing picture is worse than these numbers show. The 98.9% mean close-to-list ratio is calculated only on homes that found a buyer. This is the single largest structural blind spot in the analysis, and no amount of statistical rigor applied to the closed set can correct for it.

4. The 14-Day Finding Confuses Correlation With Causation

The advisory says ‘price for a 14-day sale.’ But the causal arrow may run backward. Homes that sell in seven days may be the intrinsically desirable ones — better condition, better lot, better light — and their 102% realization may reflect quality rather than pricing strategy. A poorly located, deferred-maintenance property priced aggressively may still sit 90 days. The data cannot separate ‘priced correctly’ from ‘objectively better house.’ The regression’s R² of 0.355 means 64.5% of $/SF variance is explained by none of the measured variables — condition, remodel quality, floor plan, and street-level desirability are all unobserved here and are plausibly what actually drives the fast-sale cohort.

5. The Size Discount Advice Ignores Exit Liquidity

Telling buyers that large homes are cheap per foot is arithmetically correct and strategically incomplete. The same discount that makes a 4,500 sf home attractive to buy makes it hard to sell. Only 25 of 252 sales (9.9%) exceeded 4,500 sf. Rolling Hills, the large-home area, posted an 88.9% close-to-original-list ratio and a 44-day median CDOM. The buyer who exploits the size discount on entry inherits it on exit — and inherits a buyer pool roughly one-tenth the size of the core market. The discount is not free money; it is compensation for illiquidity.

6. Several Submarket Conclusions Rest on Sample Sizes That Cannot Support Them

West Palos Verdes: 4 sales. Rolling Hills: 6. Country Club: 8. La Cresta: 10. Malaga Cove — cited above as the Peninsula’s highest-value area — rests on 11 sales with a standard deviation of $377/SF. At n = 11 with that dispersion, the 95% confidence interval on Malaga Cove’s mean spans roughly $928 to $1,435/SF. It overlaps Lunada Bay, PV Dr North, and half the Peninsula. The area rankings in Section 1 are directionally useful and statistically fragile, and the within-area ocean premiums of +47.1% (Country Club, 6 vs. 2 sales) and +40.8% (PV Dr South, 18 vs. 1 sale) are essentially anecdotes.

7. The Model Omits the Variables That Matter Most — Including Every Macro Factor

The hedonic model explains 35.5% of $/SF variance. It contains no measure of condition, vintage, remodel recency, school assignment, HOA status, or lot topography. It also contains no interest rate, no inventory level, no insurance-availability variable, and no measure of the Portuguese Bend landslide complex — which is a live, material, geographically specific risk on this Peninsula that no regression on closed sales will surface. A projection extrapolating an internal price trend twelve months forward while ignoring the mortgage rate environment and California coastal insurance conditions is, at best, a partial answer.

8. The $/SF Framework Itself Is the Wrong Unit for Half This Market

This report leans on price per square foot because it is the best-behaved variable in the file (CV 0.261, skew 0.97, near-normal σ coverage). But $/SF is a derived ratio, and on properties where land dominates value — bluff lots, the 479,552 sf maximum lot in this dataset, Rolling Hills acreage — the denominator is close to irrelevant. The lot-size coefficient in the model is statistically insignificant (p = 0.339), which is almost certainly a specification failure rather than evidence that land does not matter on the Palos Verdes Peninsula. For the top decile of this market, a $/SF projection is close to meaningless.

Where this leaves the analysis: the cross-sectional findings — the CDOM decay curve, the size discount, the mix-adjusted view premium, the area stratification — are supported by 252 observations and hold up. The time-series finding does not. Use Sections 1 and 3 with confidence. Use Section 4 as a scenario band, and revisit it the moment a second year of sold data is available.

Methodology & Sources

Source data: CRMLS closed residential sales, Palos Verdes Peninsula, close dates February 2 – July 31, 2026. n = 252. Cities represented: Rancho Palos Verdes (124), Palos Verdes Estates (71), Rolling Hills Estates (31), Palos Verdes Peninsula (20), Rolling Hills (6). Sixteen MLS Areas.

Verification protocol: mandatory dual-pass read (pandas + openpyxl) with Counter assertion on the Status column. 252/252 rows matched across both engines. Zero duplicate Listing IDs. No date-serial artifacts detected.

Hedonic model: OLS on log price per square foot. Regressors: MLS Area fixed effects (15 dummies), log living area, log lot size, ocean-view binary, days elapsed from window start. n = 252, R² = 0.3551, adjusted R² = 0.3023, 236 residual degrees of freedom.

Trend estimation: three independent methods reported — monthly-median OLS (+26.1%/yr), transaction-level OLS (+17.3%/yr, p = 0.150), Theil-Sen robust regression (+12.0%/yr), and the mix-adjusted hedonic (+11.1%/yr, p = 0.297). Bayesian shrinkage applied against a 3.5% long-run prior with 5pp prior standard deviation, yielding a data weight of 0.190 and a posterior of +4.9%/yr.

View tier assignment: token parsing of the CRMLS View field. Whitewater/Bluff takes precedence, then Ocean/Water, then Scenic Non-Ocean, then Neighborhood. 27 records carried a blank View field and are reported separately as ‘None / Not Specified’ rather than imputed.

Analytical framework: Derivative Calculus Price Momentum Analysis™ — first-derivative price velocity and second-derivative acceleration applied alongside 180-day moving-average and OLS projection methodology. Session methodology maintained continuously since March 2026, built on 45+ years of consecutive daily CRMLS tracking.

Statistical analysis is not a guarantee of future results. Real estate values are affected by interest rates, inventory, insurance availability, geological conditions, and macroeconomic factors not captured in closed-sale data. This report is informational and does not constitute financial, legal, or tax advice. Consult qualified professionals before making a real estate decision.

Discuss This Analysis For Your Property

George Fotion, REALTOR®

Call Realty  ·  California DRE #00785373
Palos Verdes Peninsula & South Bay Specialist
45+ Years of Consecutive Daily CRMLS Tracking

Direct (424) 722-9136	Email george.fotion@homeispalosverdes.com
Websites PalosVerdesHomesBest.com SearchHomesInPrivate.com	Schedule A Consultation calendly.com/george-fotion

Derivative Calculus Price Momentum Analysis™ — proprietary analytical framework of George Fotion, REALTOR®, DRE #00785373.
Data source: CRMLS. Analysis window: February 2 – July 31, 2026. Report generated July 31, 2026. Equal Housing Opportunity.

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Time Period	Palos Verdes Estates (Days to Sell Existing Supply)	Listing Volume	Pending Volume	%Change Listing Volume (Supply) Same Time Period Last Year	%Change Pending Volume (Demand) Same Time Period Last Year	Change in Unsold Inventory Index from Last Period	% Change in Unsold Inventory Index from Same Period Last Year
2/1/2025-7/31/2025	307	155	91
1/1/2026-6/30/2026	305	127	75
2/1/2026-7/31/2026	237	125	95	-19.35%	4.40%	-22.30%	-22.75%
Time Period	Palos Verdes Peninsula (Days to Sell Existing Supply)	Listing Volume	Pending Volume	%Change Listing Volume (Supply) Same Time Period Last Year	%Change Pending Volume (Demand) Same Time Period Last Year	Change in Unsold Inventory Index from Last Period	% Change in Unsold Inventory Index from Same Period Last Year
2/1/2025-7/31/2025	327	483	266
1/1/2026-6/30/2026	300	431	259
2/1/2026-7/31/2026	276	442	288	-8.49%	8.27%	-7.77%	-15.48%
Time Period	Greater South Bay Unsold Inventory (Days to Sell Existing Supply)	Listing Volume	Pending Volume	%Change Listing Volume (Supply) Same Time Period Last Year	%Change Pending Volume (Demand) Same Time Period Last Year	Change in Unsold Inventory Index from Last Period	% Change in Unsold Inventory Index from Same Period Last Year
2/1/2025-7/31/2025	274	3853	2530
1/1/2026-6/30/2026	259	3742	2600
2/1/2026-7/31/2026	248	3837	2787	-0.42%	10.16%	-4.34%	-9.60%
Time Period	Rancho Palos Verdes Unsold Inventory (Days to Sell Existing Supply)	Listing Volume	Pending Volume	%Change Listing Volume (Supply) Same Time Period Last Year	%Change Pending Volume (Demand) Same Time Period Last Year	Change in Unsold Inventory Index from Last Period	% Change in Unsold Inventory Index from Same Period Last Year
2/1/2025-7/31/2025	299	282	170
1/1/2026-6/30/2026	324	261	145
2/1/2026-7/31/2026	310	272	158	-3.55%	-7.06%	-4.36%	3.78%
Time Period	Rolling Hills Estates Unsold Inventory (Days to Sell Existing Supply)	Listing Volume	Pending Volume	%Change Listing Volume (Supply) Same Time Period Last Year	%Change Pending Volume (Demand) Same Time Period Last Year	Change in Unsold Inventory Index from Last Period	% Change in Unsold Inventory Index from Same Period Last Year
2/1/2025-7/31/2025	334	39	21
1/1/2026-6/30/2026	217	41	34
2/1/2026-7/31/2026	211	41	35	5.13%	66.67%	-2.86%	-36.92%
Time Period	Rolling Hills Unsold Inventory (Days to Sell Existing Supply)	Listing Volume	Pending Volume	%Change Listing Volume (Supply) Same Time Period Last Year	%Change Pending Volume (Demand) Same Time Period Last Year	Change in Unsold Inventory Index from Last Period	% Change in Unsold Inventory Index from Same Period Last Year
2/1/2025-7/31/2025	585	26	8
1/1/2026-6/30/2026	380	19	9
2/1/2026-7/31/2026	405	18	8	-30.77%	0.00%	6.58%	-30.77%

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