The recent housing market slowdown has been disproportionately due to a pullback in demand and not an increase in supply. In fact, supply – as measured by new for-sale listings – decreased compared to a year ago, which is atypical in slowing markets.
Over the last twelve months, active demand — as measured by the number of people actively shopping for a home – has fallen by an estimated 30%
While overall for-sale inventory has risen, a low flow of new listings entering the market and the enduring strength of outstanding mortgages offer some support to otherwise falling prices.
The housing market is undergoing a swift rebalancing. After two years of double-digit percent increases and 13 consecutive months in which a new all-time record pace was set, national annual home value growth peaked in April and has now slowed for five consecutive months. It may be tempting to conclude this slowdown has been caused by the housing shortage turning into a glut, similar to what happened during the Great Recession 15 years ago. However, an analysis of recent housing market data indicates that it's been a sharp pullback in demand for housing that is disproportionately responsible for the current slowdown in price growth. Active for-sale inventory rose steadily through the spring and summer but still sits nearly 40% below pre-pandemic levels. Meanwhile, new for-sale listings were down 16% in September compared to a year prior – a similar annual shortfall that was seen in August and in July.
This dynamic is unlike previous housing market slowdowns that led to price declines, and persistent tight supply could insulate the market from a significant price correction, even as demand has fallen off. For instance, in the Great Recession home value declines were accompanied/prompted by an increase in new listings, including many distressed sales.
Demand Retreat Largely Responsible For Slowing Price Growth
The increase in inventory despite a sharp slowdown in new listing activity suggests that active demand for housing has fallen sharply. Put simply, sales – flows out of the pool of available inventory – have decreased by more than the decline in the number of new homes coming on the market, allowing the overall stock of available for-sale inventory to increase.
There are many variables that affect housing supply and demand – income, interest rates, etc. – and ultimately home prices depend on the number of active home shoppers and the number of available homes for those shoppers to select from. But quantifying demand is challenging due to the fact that we cannot observe it directly.
A standard matching model [1] – as in the one shown in a recent paper by Anenberg and Ringo – is one method in which to estimate recent changes in demand for housing amid changing market conditions. The model – which leverages not just inventory levels, but the flows of inventory into and out of the market – disentangles whether the pandemic frenzy and the current housing market slowdown were caused by a demand freeze or supply surge.
A pullback in demand has pushed prices downward, but while the housing market isn't nearly as tight as it was earlier, a lack of for-sale listings is providing some support for prices against further declines. Months' supply — a gauge of market tightness which measures how long it would take for all active for-sale listings to sell, given the current volume of sales – has increased by 29 days when compared to a year ago but remains well below pre-pandemic levels, still down 40 days when compared to September 2019. A recent paper from the Federal Reserve board suggests that months' supply explains 80% of the variation in house price growth – an increase in the metric tends to slow price growth, and vice versa. This has certainly held true recently, but while price growth has stalled or reversed in most U.S. markets, relatively low months' supply should continue to offer some support for prices, at least in the near-term.
How We Got Here
Until recently, a surge in home buying demand had pushed sales and prices higher and higher. Competition among buyers resulted in bidding wars that pushed price increases into unprecedented annual growth territory.
During the pandemic, housing inventory fell in most US metropolitan areas in part because home buying demand surged with changing demographics and record low interest rates. The result was a large increase in sales that consistently outpaced the flow of listings coming on the market. Supply, as captured by the flow of new listings coming on the market, failed to keep up with persistent increases in home buying demand.
The increase in the number of potential new buyers relative to the stock of housing for sale raised the likelihood that a seller would find a buyer. As a result, the time it took for the typical home to sell decreased and the stock of available housing was not replenished quickly enough. Months' supply fell rapidly. And with all that pressure, prices increased.
Since then, sharp mortgage rate increases – brought upon by tighter monetary policy and other factors – coupled with record home price growth and lagging income growth have pushed housing affordability to an all time low, forcing the housing market to downshift.
Recently-hot Markets Seeing the Most Pronounced Demand Pullback
Across the country, affordability challenges have pushed potential buyers to the sidelines. Of course, this demand destruction has been more pronounced in some markets than in others. Markets with the highest prices a year ago saw disproportionately larger declines in active demand in the 12 months that followed.
Markets like Boise City, ID (-54.7%), Austin, TX (-52.7%), Phoenix, AZ (-60.5%), Las Vegas, NV (-55.4%), which all saw substantial home price increases during the pandemic's first couple years, as well as some Florida markets like Fort Myers (-44.3%) and Jacksonville (-45.6%), have seen a disproportionate pullback in demand amid worsening affordability. In markets like these, houses are staying on the market longer, allowing inventory to grow more rapidly than in other markets and placing more downward pressure on prices.
Other major markets have seen a much smaller pullback – or in a couple cases, even an increase – in buyer demand compared to a year ago. In New Orleans, LA, demand for homes was 16% stronger in September compared to the previous year, and demand for homes in Richmond, VA rose 9% over that same period. Syracuse, NY (-8.9%), Toledo, OH (-10.2%), Pittsburgh, PA (-12.7%) and Buffalo, NY (-13.9%) all saw modest declines in demand from a year ago., Rochester, NY (-15.3%), Madison, WI (-18.4%), Mc Allen, TX ( -18.8%), Allentown, PA (-19.2%). Perhaps it is also worth pointing out that New Orleans, LA is the only metropolitan area in the country to see both an increase in demand and supply – new listings – when compared to a year ago.
In the past 12 months, house price growth declined least in areas that saw the smallest increase in months' supply. These are markets with a lesser pullback in demand relative to the retreat in new listings. On one hand, falling demand acts to bring down prices. On the other hand, falling supply puts upward pressure on prices. Although housing demand fell sharply over the past year, demand remains elevated relative to available inventory for-sale in comparison to the pre-pandemic period.
Appendix: The Housing Search Model
While we can directly track the changes in the number of houses that are for sale, we do not directly observe the number of individuals who are currently searching for a home. However, data on new listings, for-sale inventory and sales can help us infer changes in homebuyer demand (see Anenberg and Ringo, 2022)
As in Anenberg and Ringo (2022), we define supply as the monthly flow of homes coming onto the for-sale market: new listings. The total inventory of homes for sale is a function of:
New listings/sellers,
The rate at which homes are sold,
The rate at which unsold homes are withdrawn from the market,
Available inventory evolves according to the following equation:
The stock of houses available for sale at the start of the next period is the stock this period net of the outflow of units arising from sales and withdrawals plus the inflow of new units.
Demand is defined as the flow of prospective buyers that enter the market each month as well as those who exit the market or find a home. Similarly to the supply of homes for sale, there exists a stock of currently-searching buyers that evolves according to:
Where is the net inflow of new buyers and outflow of discouraged buyers. The stock of buyers who are searching for a unit is being replenished by an inflow of new buyers and depleted as buyers either find a home or become discouraged and exit the market.
Supply and demand interact via the search and matching process, which is modeled as Cobb Douglas with constant returns to scale. Under Cobb-Douglas, the probability that a unit sells is:
The rate of home sales q is determined by the market tightness and a technology parameter that determines the efficiency of the matching function. The parameter is the elasticity of the probability of a sale with respect to market tightness – in other words how sensitive the probability of a sale is to the market tightness. The more interested buyers for each house there are in the market, the faster the house is likely to sell and is an increasing function of market tightness.
Plugging equation (3) into equation (2) and rearranging, we can express the net flow of new buyers as:
The net flow of new buyers depends only on variables that can be directly observed.
Using Zillow data for new listings, for-sale inventory, sales, and calibrated with Anenberg and Ringo (2022) estimates for matching efficiency and the elasticity of sales with respect to market tightness (=1.4, =0.84), we can back out an estimate for the number of buyers that are currently on the market.
For the full discussion on the choice of the model's parameters, see Anenberg and Ringo (2022)[i].
[i] Elliot Anenberg and Daniel Ringo (2022) "Volatility in Home Sales and Prices: Supply or Demand?, " Finance and Economics Discussion Series 2022-041. Washington: Board of Governors of the Federal Reserve System, https:
Over the last few years, digital currencies and gold have become decent barometers of speculative investor appetite. Such isn’t surprising given the evolution…
Over the last few years, digital currencies and gold have become decent barometers of speculative investor appetite. Such isn’t surprising given the evolution of the market into a “casino” following the pandemic, where retail traders have increased their speculative appetites.
“Such is unsurprising, given that retail investors often fall victim to the psychological behavior of the “fear of missing out.” The chart below shows the “dumb money index” versus the S&P 500. Once again, retail investors are very long equities relative to the institutional players ascribed to being the “smart money.””
“The difference between “smart” and “dumb money” investors shows that, more often than not, the “dumb money” invests near market tops and sells near market bottoms.”
That enthusiasm has increased sharply since last November as stocks surged in hopes that the Federal Reserve would cut interest rates. As noted by Sentiment Trader:
“Over the past 18 weeks, the straight-up rally has moved us to an interesting juncture in the Sentiment Cycle. For the past few weeks, the S&P 500 has demonstrated a high positive correlation to the ‘Enthusiasm’ part of the cycle and a highly negative correlation to the ‘Panic’ phase.”
That frenzy to chase the markets, driven by the psychological bias of the “fear of missing out,” has permeated the entirety of the market. As noted in “This Is Nuts:”
“Since then, the entire market has surged higher following last week’s earnings report from Nvidia (NVDA). The reason I say “this is nuts” is the assumption that all companies were going to grow earnings and revenue at Nvidia’s rate. There is little doubt about Nvidia’s earnings and revenue growth rates. However, to maintain that growth pace indefinitely, particularly at 32x price-to-sales, means others like AMD and Intel must lose market share.”
Of course, it is not just a speculative frenzy in the markets for stocks, specifically anything related to “artificial intelligence,” but that exuberance has spilled over into gold and cryptocurrencies.
Birds Of A Feather
There are a couple of ways to measure exuberance in the assets. While sentiment measures examine the broad market, technical indicators can reflect exuberance on individual asset levels. However, before we get to our charts, we need a brief explanation of statistics, specifically, standard deviation.
“Like a rubber band that has been stretched too far – it must be relaxed in order to be stretched again. This is exactly the same for stock prices that are anchored to their moving averages. Trends that get overextended in one direction, or another, always return to their long-term average. Even during a strong uptrend or strong downtrend, prices often move back (revert) to a long-term moving average.”
The idea of “stretching the rubber band” can be measured in several ways, but I will limit our discussion this week to Standard Deviation and measuring deviation with “Bollinger Bands.”
“Standard Deviation” is defined as:
“A measure of the dispersion of a set of data from its mean. The more spread apart the data, the higher the deviation. Standard deviation is calculated as the square root of the variance.”
In plain English,this meansthat the further away from the average that an event occurs, the more unlikely it becomes. As shown below, out of 1000 occurrences, only three will fall outside the area of 3 standard deviations. 95.4% of the time, events will occur within two standard deviations.
A second measure of “exuberance” is “relative strength.”
“In technical analysis, the relative strength index (RSI) is a momentum indicator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset. The RSI is displayed as an oscillator (a line graph that moves between two extremes) and can read from 0 to 100.
Traditional interpretation and usage of the RSI are that values of 70 or above indicate that a security is becoming overbought or overvalued and may be primed for a trend reversal or corrective pullback in price. An RSI reading of 30 or below indicates an oversold or undervalued condition.” – Investopedia
With those two measures, let’s look at Nvidia (NVDA), the poster child of speculative momentum trading in the markets. Nvidia trades more than 3 standard deviations above its moving average, and its RSI is 81. The last time this occurred was in July of 2023 when Nvidia consolidated and corrected prices through November.
Interestingly, gold also trades well into 3 standard deviation territory with an RSI reading of 75. Given that gold is supposed to be a “safe haven” or “risk off” asset, it is instead getting swept up in the current market exuberance.
The same is seen with digital currencies. Given the recent approval of spot, Bitcoin exchange-traded funds (ETFs), the panic bid to buy Bitcoin has pushed the price well into 3 standard deviation territory with an RSI of 73.
In other words, the stock market frenzy to “buy anything that is going up” has spread from just a handful of stocks related to artificial intelligence to gold and digital currencies.
It’s All Relative
We can see the correlation between stock market exuberance and gold and digital currency, which has risen since 2015 but accelerated following the post-pandemic, stimulus-fueled market frenzy. Since the market, gold and cryptocurrencies, or Bitcoin for our purposes, have disparate prices, we have rebased the performance to 100 in 2015.
Gold was supposed to be an inflation hedge. Yet, in 2022, gold prices fell as the market declined and inflation surged to 9%. However, as inflation has fallen and the stock market surged, so has gold. Notably, since 2015, gold and the market have moved in a more correlated pattern, which has reduced the hedging effect of gold in portfolios. In other words, during the subsequent market decline, gold will likely track stocks lower, failing to provide its “wealth preservation” status for investors.
The same goes for cryptocurrencies. Bitcoin is substantially more volatile than gold and tends to ebb and flow with the overall market. As sentiment surges in the S&P 500, Bitcoin and other cryptocurrencies follow suit as speculative appetites increase. Unfortunately, for individuals once again piling into Bitcoin to chase rising prices, if, or when, the market corrects, the decline in cryptocurrencies will likely substantially outpace the decline in market-based equities. This is particularly the case as Wall Street can now short the spot-Bitcoin ETFs, creating additional selling pressure on Bitcoin.
Just for added measure, here is Bitcoin versus gold.
Not A Recommendation
There are many narratives surrounding the markets, digital currency, and gold. However, in today’s market, more than in previous years, all assets are getting swept up into the investor-feeding frenzy.
Sure, this time could be different. I am only making an observation and not an investment recommendation.
However, from a portfolio management perspective, it will likely pay to remain attentive to the correlated risk between asset classes. If some event causes a reversal in bullish exuberance, cash and bonds may be the only place to hide.
BUFFALO, NY- March 11, 2024 – Impact Journals publishes scholarly journals in the biomedical sciences with a focus on all areas of cancer and aging research. Aging is one of the most prominent journals published by Impact Journals.
Credit: Impact Journals
BUFFALO, NY- March 11, 2024 – Impact Journals publishes scholarly journals in the biomedical sciences with a focus on all areas of cancer and aging research. Aging is one of the most prominent journals published by Impact Journals.
Impact Journals will be participating as an exhibitor at the American Association for Cancer Research (AACR) Annual Meeting 2024 from April 5-10 at the San Diego Convention Center in San Diego, California. This year, the AACR meeting theme is “Inspiring Science • Fueling Progress • Revolutionizing Care.”
Visit booth #4159 at the AACR Annual Meeting 2024 to connect with members of the Agingteam.
About Aging-US:
Agingpublishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.
Agingis indexed and archived byPubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed Central, Web of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).
Please visit our website at www.Aging-US.com and connect with us:
NY Fed Finds Medium, Long-Term Inflation Expectations Jump Amid Surge In Stock Market Optimism
One month after the inflation outlook tracked by the NY Fed Consumer Survey extended their late 2023 slide, with 3Y inflation expectations in January sliding to a record low 2.4% (from 2.6% in December), even as 1 and 5Y inflation forecasts remained flat, moments ago the NY Fed reported that in February there was a sharp rebound in longer-term inflation expectations, rising to 2.7% from 2.4% at the three-year ahead horizon, and jumping to 2.9% from 2.5% at the five-year ahead horizon, while the 1Y inflation outlook was flat for the 3rd month in a row, stuck at 3.0%.
The increases in both the three-year ahead and five-year ahead measures were most pronounced for respondents with at most high school degrees (in other words, the "really smart folks" are expecting deflation soon). The survey’s measure of disagreement across respondents (the difference between the 75th and 25th percentile of inflation expectations) decreased at all horizons, while the median inflation uncertainty—or the uncertainty expressed regarding future inflation outcomes—declined at the one- and three-year ahead horizons and remained unchanged at the five-year ahead horizon.
Going down the survey, we find that the median year-ahead expected price changes increased by 0.1 percentage point to 4.3% for gas; decreased by 1.8 percentage points to 6.8% for the cost of medical care (its lowest reading since September 2020); decreased by 0.1 percentage point to 5.8% for the cost of a college education; and surprisingly decreased by 0.3 percentage point for rent to 6.1% (its lowest reading since December 2020), and remained flat for food at 4.9%.
We find the rent expectations surprising because it is happening just asking rents are rising across the country.
At the same time as consumers erroneously saw sharply lower rents, median home price growth expectations remained unchanged for the fifth consecutive month at 3.0%.
Turning to the labor market, the survey found that the average perceived likelihood of voluntary and involuntary job separations increased, while the perceived likelihood of finding a job (in the event of a job loss) declined. "The mean probability of leaving one’s job voluntarily in the next 12 months also increased, by 1.8 percentage points to 19.5%."
Mean unemployment expectations - or the mean probability that the U.S. unemployment rate will be higher one year from now - decreased by 1.1 percentage points to 36.1%, the lowest reading since February 2022. Additionally, the median one-year-ahead expected earnings growth was unchanged at 2.8%, remaining slightly below its 12-month trailing average of 2.9%.
Turning to household finance, we find the following:
The median expected growth in household income remained unchanged at 3.1%. The series has been moving within a narrow range of 2.9% to 3.3% since January 2023, and remains above the February 2020 pre-pandemic level of 2.7%.
Median household spending growth expectations increased by 0.2 percentage point to 5.2%. The increase was driven by respondents with a high school degree or less.
Median year-ahead expected growth in government debt increased to 9.3% from 8.9%.
The mean perceived probability that the average interest rate on saving accounts will be higher in 12 months increased by 0.6 percentage point to 26.1%, remaining below its 12-month trailing average of 30%.
Perceptions about households’ current financial situations deteriorated somewhat with fewer respondents reporting being better off than a year ago. Year-ahead expectations also deteriorated marginally with a smaller share of respondents expecting to be better off and a slightly larger share of respondents expecting to be worse off a year from now.
The mean perceived probability that U.S. stock prices will be higher 12 months from now increased by 1.4 percentage point to 38.9%.
At the same time, perceptions and expectations about credit access turned less optimistic: "Perceptions of credit access compared to a year ago deteriorated with a larger share of respondents reporting tighter conditions and a smaller share reporting looser conditions compared to a year ago."
Also, a smaller percentage of consumers, 11.45% vs 12.14% in prior month, expect to not be able to make minimum debt payment over the next three months
Last, and perhaps most humorous, is the now traditional cognitive dissonance one observes with these polls, because at a time when long-term inflation expectations jumped, which clearly suggests that financial conditions will need to be tightened, the number of respondents expecting higher stock prices one year from today jumped to the highest since November 2021... which incidentally is just when the market topped out during the last cycle before suffering a painful bear market.
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