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Sector Rotation Makes Technology Line Up With Strong Seasonality Pattern

We are already in October …. How did that happen?Also, I am writing this article while sitting in a Starbucks in Jakarta, Indonesia. The combination…

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We are already in October .... How did that happen?

Also, I am writing this article while sitting in a Starbucks in Jakarta, Indonesia. The combination of the hotel, the Starbucks, the internet, and me have not been very successful so far ;) Recording a Sector Spotlight show will therefore be pretty much impossible.

However, we are once again at the start of a new month, and thus ending the previous month, which means looking at seasonality and monthly charts.

Given the situation, I will attack both items in articles rather than on video. Starting with seasonality.

The table above shows the seasonality data as I always use it in Sector Spotlight.

After September living up to the expectation of being a weak month for the market, the S&P was down almost 5% vs. the seasonal average of minus 0.4%, we are now entering the strongest period of the year.

In the top half of the table, you see the percentage of time (last 20 years) that a sector has outperformed SPY. For SPY itself it is the percentage of time where SPY closed the month higher than it opened. So 65% of the time, SPY closed the month of October higher than it started.

In the bottom half of the table is the average performance relative to SPY. For SPY it is the outright average performance. 1.4% for October.

Sneak peeking ahead shows that November and December are, historically, expected to be even stronger.

Going over the relative performances for the sectors shows strong expectations for Technology 70% and Financials 60% and a weaker outlook for Health Care 35% and Energy 40%.

Following the expected relative performances in the bottom half, Technology is expected to outperform SPY by 0.7%, and Financials 0.4%.

Health Care is expected to underperform 0.8%. Energy is the odd one out, the average (expected) performance for this sector over the last 20 years is 0.2% over SPY. In combination with outperformance in October in only 40% of the time, this means that WHEN Energy outperforms the market it is outperforming very strongly.

Current Rotation

The RRG above shows the current rotation for US sectors.

Technology is inside the weakening quadrant but has already started to pick up relative momentum, a continuation of this rotation could bring XLK back towards the leading quadrant and thus maintain a leading role within SPY.

Financials has entered the leading quadrant from improving but is losing relative momentum. Relative strength needs to improve rapidly for this sector in order to keep the relative uptrend and live up to the seasonal expectation.

Health Care is inside the improving quadrant but seems ready to roll over and start heading back down toward lagging, which would be fully in line with the seasonal expectation.

Energy, finally, is the strongest sector in terms of RS-Ratio at the moment. This definitely does not align with the seasonal expectation for an underperformance but it DOES align with the observation that WHEN Energy outperforms in October it outperforms strongly.

Information Technology (70%/+0.7%)

The price chart for XLK certainly got damaged last month but on a relative basis it is still holding up well. The raw RS-Line is moving sideways while the JdK RS-Momentum line is digesting the recent decline and starting to move upward.

The recent bounce off of support in the price chart will help relative strength to maintain current levels and potentially improve further. An upward break of relative strength out of its small consolidation will very likely be the trigger for a renewed period of outperformance and bring XLK back into the leading quadrant.

Financials (60%/+0.4%)

Following the recent break below its previous low on the price chart, XLF has now started a new series of lower highs and lower lows. This will make it difficult for relative strength to hold up at current levels. The lack of relative momentum (JdK RS-Momentum) is already showing up.

This makes it doubtful whether XLF will be able to live up to its positive seasonal expectation for October.

Health Care (35%/-0.8%)

The healthcare sector is struggling. On the price chart, the last two rallies did not manage to reach the resistance area around 140 and at the moment the price is testing the upward-sloping support line for the fourth time. A break below this line will confirm underlying weakness and very likely trigger more downside movement. When that happens all previous lows will potentially act as support on the way down.

With JdK RS-Ratio still well below 100 and JdK RS-Momentum rolling over it looks as if the tail is ready to roll over and head back toward the lagging quadrant on the RRG.

This rotation would be in line, and confirm, the expected seasonal weakness for this sector.

Energy (40%/+0.2%)

The Energy sector seems to be at a crossroads, pretty much as suggested by the seasonality pattern.

The sector historically only outperforms 40% of the time, meaning that it underperforms 60% of the time. But the average relative return for October is at +0.2%. As said above this means that if and when the sector outperforms in October it will outperform strongly. Otherwise, there would not be a +0.2% average relative performance against SPY.

Looking at the price chart we see XLE pushing against overhead resistance but so far not being able to break it. Raw RS managed to get out of a small falling channel but is now running into trouble to push higher.

Hence with the price just below resistance and RS on the verge of rolling over, I can now see two scenarios for XLE.

The first is in line with the seasonal pattern. Ie an underperformance vs SPY. when the price will not be able to break resistance and the rally in RS stalls. The expected (out)performance in that case will be around 0-0.2%, in line with the market.

In the second scenario, XLE will break above resistance and accelerate higher in price which will then drag relative strength higher and push XLE deeper into the leading quadrant.

A make-or-break situation therefore which relies on the breaking of resistance.

All in all, the tails for Technology, positive, and Healthcare, negative, seem to be best positioned to follow their seasonal expectation. Financials not so much and Energy will very likely either go nowhere or, in case of a break, rally significantly relative to SPY.

#StayAlert, --Julius



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Homes listed for sale in early June sell for $7,700 more

New Zillow research suggests the spring home shopping season may see a second wave this summer if mortgage rates fall
The post Homes listed for sale in…

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  • A Zillow analysis of 2023 home sales finds homes listed in the first two weeks of June sold for 2.3% more. 
  • The best time to list a home for sale is a month later than it was in 2019, likely driven by mortgage rates.
  • The best time to list can be as early as the second half of February in San Francisco, and as late as the first half of July in New York and Philadelphia. 

Spring home sellers looking to maximize their sale price may want to wait it out and list their home for sale in the first half of June. A new Zillow® analysis of 2023 sales found that homes listed in the first two weeks of June sold for 2.3% more, a $7,700 boost on a typical U.S. home.  

The best time to list consistently had been early May in the years leading up to the pandemic. The shift to June suggests mortgage rates are strongly influencing demand on top of the usual seasonality that brings buyers to the market in the spring. This home-shopping season is poised to follow a similar pattern as that in 2023, with the potential for a second wave if the Federal Reserve lowers interest rates midyear or later. 

The 2.3% sale price premium registered last June followed the first spring in more than 15 years with mortgage rates over 6% on a 30-year fixed-rate loan. The high rates put home buyers on the back foot, and as rates continued upward through May, they were still reassessing and less likely to bid boldly. In June, however, rates pulled back a little from 6.79% to 6.67%, which likely presented an opportunity for determined buyers heading into summer. More buyers understood their market position and could afford to transact, boosting competition and sale prices.

The old logic was that sellers could earn a premium by listing in late spring, when search activity hit its peak. Now, with persistently low inventory, mortgage rate fluctuations make their own seasonality. First-time home buyers who are on the edge of qualifying for a home loan may dip in and out of the market, depending on what’s happening with rates. It is almost certain the Federal Reserve will push back any interest-rate cuts to mid-2024 at the earliest. If mortgage rates follow, that could bring another surge of buyers later this year.

Mortgage rates have been impacting affordability and sale prices since they began rising rapidly two years ago. In 2022, sellers nationwide saw the highest sale premium when they listed their home in late March, right before rates barreled past 5% and continued climbing. 

Zillow’s research finds the best time to list can vary widely by metropolitan area. In 2023, it was as early as the second half of February in San Francisco, and as late as the first half of July in New York. Thirty of the top 35 largest metro areas saw for-sale listings command the highest sale prices between May and early July last year. 

Zillow also found a wide range in the sale price premiums associated with homes listed during those peak periods. At the hottest time of the year in San Jose, homes sold for 5.5% more, a $88,000 boost on a typical home. Meanwhile, homes in San Antonio sold for 1.9% more during that same time period.  

 

Metropolitan Area Best Time to List Price Premium Dollar Boost
United States First half of June 2.3% $7,700
New York, NY First half of July 2.4% $15,500
Los Angeles, CA First half of May 4.1% $39,300
Chicago, IL First half of June 2.8% $8,800
Dallas, TX First half of June 2.5% $9,200
Houston, TX Second half of April 2.0% $6,200
Washington, DC Second half of June 2.2% $12,700
Philadelphia, PA First half of July 2.4% $8,200
Miami, FL First half of June 2.3% $12,900
Atlanta, GA Second half of June 2.3% $8,700
Boston, MA Second half of May 3.5% $23,600
Phoenix, AZ First half of June 3.2% $14,700
San Francisco, CA Second half of February 4.2% $50,300
Riverside, CA First half of May 2.7% $15,600
Detroit, MI First half of July 3.3% $7,900
Seattle, WA First half of June 4.3% $31,500
Minneapolis, MN Second half of May 3.7% $13,400
San Diego, CA Second half of April 3.1% $29,600
Tampa, FL Second half of June 2.1% $8,000
Denver, CO Second half of May 2.9% $16,900
Baltimore, MD First half of July 2.2% $8,200
St. Louis, MO First half of June 2.9% $7,000
Orlando, FL First half of June 2.2% $8,700
Charlotte, NC Second half of May 3.0% $11,000
San Antonio, TX First half of June 1.9% $5,400
Portland, OR Second half of April 2.6% $14,300
Sacramento, CA First half of June 3.2% $17,900
Pittsburgh, PA Second half of June 2.3% $4,700
Cincinnati, OH Second half of April 2.7% $7,500
Austin, TX Second half of May 2.8% $12,600
Las Vegas, NV First half of June 3.4% $14,600
Kansas City, MO Second half of May 2.5% $7,300
Columbus, OH Second half of June 3.3% $10,400
Indianapolis, IN First half of July 3.0% $8,100
Cleveland, OH First half of July  3.4% $7,400
San Jose, CA First half of June 5.5% $88,400

 

The post Homes listed for sale in early June sell for $7,700 more appeared first on Zillow Research.

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February Employment Situation

By Paul Gomme and Peter Rupert The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000…

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By Paul Gomme and Peter Rupert

The establishment data from the BLS showed a 275,000 increase in payroll employment for February, outpacing the 230,000 average over the previous 12 months. The payroll data for January and December were revised down by a total of 167,000. The private sector added 223,000 new jobs, the largest gain since May of last year.

Temporary help services employment continues a steep decline after a sharp post-pandemic rise.

Average hours of work increased from 34.2 to 34.3. The increase, along with the 223,000 private employment increase led to a hefty increase in total hours of 5.6% at an annualized rate, also the largest increase since May of last year.

The establishment report, once again, beat “expectations;” the WSJ survey of economists was 198,000. Other than the downward revisions, mentioned above, another bit of negative news was a smallish increase in wage growth, from $34.52 to $34.57.

The household survey shows that the labor force increased 150,000, a drop in employment of 184,000 and an increase in the number of unemployed persons of 334,000. The labor force participation rate held steady at 62.5, the employment to population ratio decreased from 60.2 to 60.1 and the unemployment rate increased from 3.66 to 3.86. Remember that the unemployment rate is the number of unemployed relative to the labor force (the number employed plus the number unemployed). Consequently, the unemployment rate can go up if the number of unemployed rises holding fixed the labor force, or if the labor force shrinks holding the number unemployed unchanged. An increase in the unemployment rate is not necessarily a bad thing: it may reflect a strong labor market drawing “marginally attached” individuals from outside the labor force. Indeed, there was a 96,000 decline in those workers.

Earlier in the week, the BLS announced JOLTS (Job Openings and Labor Turnover Survey) data for January. There isn’t much to report here as the job openings changed little at 8.9 million, the number of hires and total separations were little changed at 5.7 million and 5.3 million, respectively.

As has been the case for the last couple of years, the number of job openings remains higher than the number of unemployed persons.

Also earlier in the week the BLS announced that productivity increased 3.2% in the 4th quarter with output rising 3.5% and hours of work rising 0.3%.

The bottom line is that the labor market continues its surprisingly (to some) strong performance, once again proving stronger than many had expected. This strength makes it difficult to justify any interest rate cuts soon, particularly given the recent inflation spike.

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Mortgage rates fall as labor market normalizes

Jobless claims show an expanding economy. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.

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Everyone was waiting to see if this week’s jobs report would send mortgage rates higher, which is what happened last month. Instead, the 10-year yield had a muted response after the headline number beat estimates, but we have negative job revisions from previous months. The Federal Reserve’s fear of wage growth spiraling out of control hasn’t materialized for over two years now and the unemployment rate ticked up to 3.9%. For now, we can say the labor market isn’t tight anymore, but it’s also not breaking.

The key labor data line in this expansion is the weekly jobless claims report. Jobless claims show an expanding economy that has not lost jobs yet. We will only be in a recession once jobless claims exceed 323,000 on a four-week moving average.

From the Fed: In the week ended March 2, initial claims for unemployment insurance benefits were flat, at 217,000. The four-week moving average declined slightly by 750, to 212,250


Below is an explanation of how we got here with the labor market, which all started during COVID-19.

1. I wrote the COVID-19 recovery model on April 7, 2020, and retired it on Dec. 9, 2020. By that time, the upfront recovery phase was done, and I needed to model out when we would get the jobs lost back.

2. Early in the labor market recovery, when we saw weaker job reports, I doubled and tripled down on my assertion that job openings would get to 10 million in this recovery. Job openings rose as high as to 12 million and are currently over 9 million. Even with the massive miss on a job report in May 2021, I didn’t waver.

Currently, the jobs openings, quit percentage and hires data are below pre-COVID-19 levels, which means the labor market isn’t as tight as it once was, and this is why the employment cost index has been slowing data to move along the quits percentage.  

2-US_Job_Quits_Rate-1-2

3. I wrote that we should get back all the jobs lost to COVID-19 by September of 2022. At the time this would be a speedy labor market recovery, and it happened on schedule, too

Total employment data

4. This is the key one for right now: If COVID-19 hadn’t happened, we would have between 157 million and 159 million jobs today, which would have been in line with the job growth rate in February 2020. Today, we are at 157,808,000. This is important because job growth should be cooling down now. We are more in line with where the labor market should be when averaging 140K-165K monthly. So for now, the fact that we aren’t trending between 140K-165K means we still have a bit more recovery kick left before we get down to those levels. 




From BLS: Total nonfarm payroll employment rose by 275,000 in February, and the unemployment rate increased to 3.9 percent, the U.S. Bureau of Labor Statistics reported today. Job gains occurred in health care, in government, in food services and drinking places, in social assistance, and in transportation and warehousing.

Here are the jobs that were created and lost in the previous month:

IMG_5092

In this jobs report, the unemployment rate for education levels looks like this:

  • Less than a high school diploma: 6.1%
  • High school graduate and no college: 4.2%
  • Some college or associate degree: 3.1%
  • Bachelor’s degree or higher: 2.2%
IMG_5093_320f22

Today’s report has continued the trend of the labor data beating my expectations, only because I am looking for the jobs data to slow down to a level of 140K-165K, which hasn’t happened yet. I wouldn’t categorize the labor market as being tight anymore because of the quits ratio and the hires data in the job openings report. This also shows itself in the employment cost index as well. These are key data lines for the Fed and the reason we are going to see three rate cuts this year.

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