New Residential Homes Sales and Inventory Months of Supply – Easy Trends (thru September 2014)

Sales of new residential homes contributes to the GDP, and the level of supply can indicate something about prices.  I’m continuing a feature called “Easy Trends” – a place where I’ll analyze the recent trend for an indicator (in this one, it is new residential homes sales and inventory) and discuss whether it is currently going up, down or neither.  You can read the basics of my methodology on the FAQ page.

NOTE: You may be reading an outdated analysis.  Please visit my latest new residential homes inventory months of supply trend analysis for more info.

Quick ‘n Easy

For new residential homes reports, there are two key things to look at: 1) number of homes sold and 2) inventory of homes for sale.  When there are too many new residential homes still left unsold (inventory) on the market, it usually means that prices will be dropping because supply is greater than demand.  A good way of measuring the inventory is to calculate how long it would take that inventory to sell at the current pace of sales.  The normal level of supply for new residential homes is a little less than 6 months.

For new residential homes reports, there are two key things to look at: 1) number of homes sold and 2) inventory of homes for sale.  We care about the number sold because each one contributes to the overall economy (builders get paid, brokers get paid, companies that made the raw materials get paid, etc).  We care about inventory because when there are too many new residential homes still left unsold (inventory) on the market, it usually means that prices will be dropping because supply is greater than demand.  The opposite is true if there is very low inventory.  A good way of measuring whether current levels of new residential homes are too high or too low is to calculate how long it would take the current inventory to sell at the current annual pace of sales.  For example, if there are 150,000 unsold new residential homes with the most recent report saying the annual pace of sales was 225,000, here’s what the calculation would look like:

Example:
225,000 new residential homes sold per year
divide by 12 to get 18,750 new residential homes sold per month
150,000 unsold homes divided by 18,750 sold per month = 8 months supply

Here’s a graph of the New Residential Homes Sales followed by Inventory Months of Supply from Calculated Risk:

New Residential Homes Sales September 2014 - Calculated Risk

Courtesy: CalculatedRiskBlog.com

 

New Residential Homes Inventory Months of Supply September 2014 - Calculated Risk

Courtesy: CalculatedRiskBlog.com

 

New Residential Homes Trends and Projections

Below, I will discuss whether the indicators are currently in a trend, when the last confirmed trend was and what that says about projecting the next data points to be released. I usually start my trend analysis from about three years ago.

continue reading…

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Initial Weekly Unemployment Claims (4-Week Moving Average) thru Week Ending October 18, 2014 – Easy Trends

In this article, I’ll do an “Easy Trends” analysis of the initial weekly unemployment claims data.  “Easy Trends” is a place where I’ll analyze the recent trend for an indicator and discuss whether it is currently going up, down or neither.  You can read the basics of my methodology on the FAQ page.

NOTE: You may be reading an outdated analysis.  Please visit my latest unemployment claims trend analysis for more info.

Quick ‘n Easy

By tracking the number of people who are filing for unemployment benefits for the first time each week, we get a quick insight into the latest status of the economy’s health.  Fewer claims equals more jobs, which equals more income, which usually equals more consumer spending (70% of the economy!) that supports company profits, which in turn can lead to more hiring.

Quick Version of Easy Trends Analysis

For the Initial Weekly Unemployment Claims series, I will be doing only a brief update as long as the level of claims is nice and low (below 350,000) and there isn’t a confirmed upward trend (which is undesirable of course). I will only call out a few specific statistics that I like to track. I’ll be tracking the trends, but it takes a lot of time to do the post, so I won’t do a post with the full analysis unless there is any cause for concern. Bottom Line: If you’re seeing my “quick version” of this analysis – don’t be worried about weekly jobless claims!

4-week moving average of weekly initial unemployment claims: 281,000   (good - we want this number to be below 350,000)

4-week moving average of weekly initial unemployment claims as a percent of the total size of the nation’s workforce: 0.18 percent   (good)

Current Trend: Confirmed downward trend of about 4,000 fewer claims per month   (good – right direction)

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Existing Homes Sales and Inventory Months of Supply (thru September 2014)

Most of homes sold are existing homes sales, so it is an important area of the housing sector to follow.  I’m continuing a feature called “Easy Trends” – a place where I’ll analyze the recent trend for an indicator and discuss whether it is currently going up, down or neither.  You can read the basics of my methodology on the FAQ page.

NOTE: You may be reading an outdated analysis.  Please visit my latest existing homes sales and inventory months of supply trend analysis for more info.

Quick ‘n Easy

Typically, if it would take longer than 6 months for the unsold inventory of existing homes (not newly built) to be sold at the latest pace of sales, we can expect prices for existing homes to go down.  If it’s less than 6 months, we can expect prices to go up.

You can get a sense for whether there are too many existing homes still on sale (inventory) by taking the total inventory and dividing it by the pace of sales.  The result is “months of supply,” which basically means that if existing homes were to continue selling at the same rate as the most recent month of data, the current inventory of homes would be sold by that many months.  A normal reading is around 6 months – higher number means too much inventory, and if supply is greater than demand, that usually means prices will drop.

Here’s a chart of the Existing Homes Inventory Months of Supply from Calculated Risk: (focus on the red line)

Existing Homes Months of Supply September 2014 - Calculated Risk

Courtesy: CalculatedRiskBlog.com

Existing Homes Sales Trends and Projections

Below, I will discuss whether the indicator is currently in a trend, when the last confirmed trend was and what that says about projecting the next data point to be released.  I typically start my analysis from three years ago. continue reading…

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Note to my readers…

Due to another hectic week, I won’t be posting updates until at least Friday, possibly not until the weekend. However, I wanted to note that if I did have time to do my weekly economic indicator roundup, it would show no changes to ratings, thus it would continue to suggest sluggish growth (positive growth but below historical averages).

This week, there are several key reports that I normally cover. First are several reports that affect my housing-related indicators:

  • Existing Home Sales
  • New Home Sales
  • Consumer Price Index (the housing-related portion of this indicator is something I use as part of my calculations for the Easynomics Real Estate Price Stability Index)

There is also the release of September’s Chicago Fed National Activity Index (which I include in my weekly dashboard) as well as the Leading Economic Index by The Conference Board. Don’t forget weekly jobless claims, which have been the most optimist indicator we’ve been seeing lately. Busy week with lots of info! Let’s see what happens with the global growth story (i.e., slowdown) as well as any news regarding efforts to stop the Ebola virus.

Thanks for your continued support…

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Stock Market Forecast Update

I have updated my Stock Market Forecast page with the latest systems I’m testing.  You can read the explanation there in detail.  The quick summary is that I’m doing two primary models (4-week and 13-week), both using a linear regression model (a statistical way of finding a straight-line relationship between a set of variables and a calculated outcome) that involves four different technical analysis data points.

I graph the stock market forecast for each model over the coming 4-week or 13-week period.

Lastly, I will issue two weighted combination forecasts each week in my update post, each of which makes only one “official” forecast for the record book.  One represents a weighted average between where the two models think the S&P 500 will close this upcoming week.  The weights are based on how well each model explains the ups and downs of the S&P 500 – that is, using the “r-squared” for the regression analysis.  The other is a “Headline Adjusted” model, which tries to account for the fact that extreme and unforeseen events can throw off the models.  So, I remove data that seems affected by such effects and keep the more pure data.  This model will also make only one forecast, one week in advance.

Performance of Last Week’s Forecast

Weekly Direction of the S&P 500

Correct:   None

Incorrect:   4-week   /   13-week   /   Weight-Adjusted Combo   /   Headline-Adjusted

 

Accuracy of the Weight-Adjusted Combination Models

Regular Weight-Adjusted Combination: 7.47 percent too optimistic

Headline-Adjusted Combination: 1.78 percent too optimistic

 

Accuracy of Individual Models

4-week Model:  8.87 percent too optimistic

Correct Prediction of S&P 500 Direction thru Last Week’s Close:  0 out of 4 predictions

******************

13-week Model:  7.12 percent too optimistic

Correct Prediction of S&P 500 Direction thru Last Week’s Close:  0 out of 13 predictions

 

Estimated Effect of Headlines on Current Market Value

NOTE: This is based on a calculation I do after running the current week’s headline-adjusted forecasts.

4-week Model: Negative effect of 8.4 percent   (down 3.7 percent from last week)

13-week Model: Negative effect of 7.3 percent   (down 1.4 percent from last week)

Notes: The headline effect went down an average of 2.6 percent from last week, so headlines are artificially holding down the markets by about 7.9 percent right now.

 

Stock Market Forecast Summary for Upcoming Week

Here’s the breakdown:

continue reading…

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Stock Market Technical Analysis – Tech It Easy (thru October 17, 2014)

Stock market technical analysis is all you need to know, complete hogwash or somewhere in between.  It depends on who you ask.  If you find it interesting, you’ll probably like reading this weekly feature.

NOTE: You may be reading an outdated article.  Please visit my latest stock market technical analysis summary of the S&P 500 for more.

I used to have screenshots of the various stock market technical analysis assessments I present below, as well as a bit more analysis for each one. In order to save time, I will not be doing the screenshots and will abbreviate some of the text for each analysis as well. The last time I did a comprehensive analysis can be foundhere, in case you want to see what it looked like.

The next few paragraphs are my standard intro to stock market technical analysis – you can skip down to the table (or click “continue reading”) if you read this feature regularly: 

Many people who trade in the markets believe that there are patterns that can generally lead to profitable trades.  By analyzing stock charts that show the change in price along with the volume (how many shares were traded), “technical analysts” believe they have an edge and can time their trades profitably.  There is significant controversy over this subject, however.  Others say that, unless you have some information that no one else does, basically you can never beat “the market” because everything is already baked into the current price of a stock.

Nevertheless, supporters of stock market technical analysis are everywhere, and the tools for their trade can be found throughout bookstores and the Internet.  I like to follow some websites that do some of the work automatically and provide a snapshot opinion of whether a particular stock is considered “bullish” (going to go up in price), “bearish” (going to go down in price) or “neutral” (stay about the same price).

For simplicity, I’d like to start by showing you a snapshot of what several stock market technical analysis websites suggest about the exchange traded fund (ETF) with the ticker symbol of SPY.  This fund is supposed to go up and down the same as the S&P 500 index does.  And many people consider the S&P 500 index (a measure of the price of the 500 largest companies that trade in the U.S.) to be an accurate gauge of where “the market” stands.

For each of the sources below, where I have a choice, I will use a measure that attempts to predict the future direction of SPY or S&P 500 in the next 3 months.

S&P 500 Technical Analysis Summary

Source: Barchart.com   |  NEUTRAL

Quick ‘n Easy

Barchart.com uses three analyses to predict the direction of SPY over the next three months or so.  Looking at the average value and strength of these three signals, we can conclude that BarChart.com thinks that the price of SPY will stay about the same over the next three months.

Easy Notes: BarChart.com says that the price of SPY will probably stay about the same over the next three months.  This is the 4th consecutive “non-bullish” assessment after 18 consecutive weeks at a “bullish” rating.  Two of three signals are at “sell,” and one is strong and the other a weak signal.  Fortunately, two of three signals are headed in the right direction (the right direction would mean “buy” signals are strengthening and “sell” signals are weakening).  Overall, this is a neutral assessment, but it’s right on the border of being “bearish.”

continue reading…

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