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:   4-week   /   Headline-Adjusted

Incorrect:   13-week   /   Weight-Adjusted Combo

 

Accuracy of the Weight-Adjusted Combination Models

Regular Weight-Adjusted Combination: 0.17 percent too pessimistic

Headline-Adjusted Combination: 0.64 percent too optimistic

 

Accuracy of Individual Models

4-week Model:  0.12 percent too optimistic

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

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

13-week Model:  0.25 percent too pessimistic

Correct Prediction of S&P 500 Direction thru Last Week’s Close:  12 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 1.1 percent   (down 0.4 percent from last week)

13-week Model: Negative effect of 0.2 percent   (down 1.4 percent from last week)

Notes: The headline effect went down an average of 0.9 percent from last week, so headlines are artificially holding down the markets by about 0.65 percent right now.

 

Stock Market Forecast Summary for Upcoming Week

Here’s the breakdown:

continue reading…

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Initial Weekly Unemployment Claims (4-Week Moving Average) thru Week Ending July 19, 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: 302,000   (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: 0.19 percent   (good)

Current Trend: Confirmed downward trend of about 1,500 fewer claims per month   (good)

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New Residential Homes Sales and Inventory Months of Supply – Easy Trends (thru June 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 June 2014 - Calculated Risk

Courtesy: CalculatedRiskBlog.com

 

New Residential Homes Inventory Months of Supply June 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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Job Growth – Jobs, Employment, Labor and Livelihood Overview (JELLO) – Easy Pod (July 23, 2013)

Job growth is key to a thriving, healthy economy.  I’m continuing a feature called “Easy Pod” – a collection of indicators that help portray the current status of something.  In this post, that something is the employment situation of the country, which of course will examine job growth as a major factor.

NOTE: There may be a more recent publication on this topic.  You may be interested in my latest Job Growth (JELLO) Easy Pod analysis.

Quick ‘n Easy

Why do we care about job growth?  Without jobs, consumers can’t be consumers because they wouldn’t have any money to spend.  In a healthy economy, we see strong job growth and a low unemployment rate.

Why do we care so much about jobs, employment, labor and livelihood so much? (OK – so that last term is something I threw in there to make “JELLO” work – investors don’t use that one!)  Simply put, jobs are the lifeline of the economy.  When the economy is working at its best, we have great ideas that turn into great products.  And those great products have to be manufactured, marketed and sold to the consumer.  In order to make all of that happen, there have to people working to make it happen.  That means job growth.  And the income they take home will enable them to buy a house, a car, groceries, clothes, toys, appliances, vacations and tickets to the movies.  All of the money they spent is now income for another set of people, who then go and do the same thing.  Without a job, consumers don’t have (or don’t act like they have) the money to buy anything, so the whole thing slows down.  That’s good enough for an “Easy” look at why we want to see job growth and why jobs matter.

There are a number of indicators that shed light on what’s happening in employment, and there are even some people who combine these indicators into one number (an index) to give a summary.  In this “Easy Pod” I will take a look at a few indicators and indices that I like to follow to decipher what’s happening in job growth.  Check back regularly for updates.


Quick Summary

(Last JELLO Easy Pod was December 20,  2013)

Indicator (Click for details – only works if full article is open) Current Rating (Change Since Last Easy Pod)
Monthly Change in Nonfarm Payrolls Positive
Employment Trends Index Positive
ISM Report on Business Positive
Gallup Daily Poll: U.S. Employment Negative
Easynomics Temporary Staffing Index Positive
Intuit Small Business Employment Index Neutral   (Upgrade)




Indicator: Nonfarm Payrolls – Monthly Change   |   POSITIVE
Easy Intro: None yet   |   Link to Nonfarm Payrolls data   |   Latest Date This Info Represents: June 2014

Quick ‘n Easy

The monthly change in jobs (excluding farming jobs, because they have lots of ups and downs that mask the underlying trend) is one of the most widely accepted barometers of the labor market.  The average monthly change over the past three months has been better than enough to keep pace with the growing force, but we need strong growth for some time to compensate for all the job losses of the Great Recession.

Nonfarm Payroll Employment SA - June 2014 - FRED

Source: StLouisFed.org

Easy Description: Every month, the Bureau of Labor Statistics (BLS) issues the “Employment Situation Summary” and discusses the changes in the labor market.  The headline number everyone looks for is the change in nonfarm payrolls.  The reason we are looking for the change in number of “nonfarm” jobs is that farming is a very seasonal business, so its patterns mask the general underlying trends in the regular labor market.

Generally speaking, we need about 100,000 new jobs per month to keep up with the number of people who are entering the labor force nationwide.  Because we’ve lost millions of jobs since the financial crisis of 2008, we’ll need numbers significantly above that for several years before we get back to “normal” levels.

Latest Reading: +288,000 nonfarm payrolls increase in June 2014.  The average of the three most recent months is about +272,000.  The graph on the right shows the total number of nonfarm jobs over the past five years.

NOTE: For simplicity, I am only reporting the results of the survey that is sent out to businesses.  In my “Easy Trends” analysis each month, I look at an average of that survey and another survey of households.  Here’s a link to my most recent analysis of nonfarm payrolls trends.

Implications: The country was absolutely bleeding jobs in the few months after the financial crisis hit in the fall of 2008.  Things steadily improved until a drop back in early summer 2010.  Ever since then, we still have not seen a negative number of nonfarm payrolls (excluding temporary Census workers hiring/laying off).  We probably need about 200,000 jobs a month right now to cover people entering the workforce and to get jobs for those who lost them.  The average of the latest three reports is well above that number and obviously still well above the 100,000 or so we’d typically need just to keep pace with the growing workforce.

Easynomics Rating Methodology: For this index, I will base my rating on whether the average of the three most recent readings is enough to keep pace with the growing workforce.  “Positive” for 3-month average of 100,000 or above, “Negative” for 3-month average below zero, and “Neutral” for anything in between.

continue reading…

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Existing Homes Sales and Inventory Months of Supply (thru June 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 up.  If it’s less than 6 months, we can expect prices to go down.

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 June 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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Economic Indicators Roundup (July 21, 2014)

Economic indicators are everywhere, so this is kind of like a dashboard that I like to follow.  For each indicator, I will try to give you a brief description, the latest reading and what I understand to be its implications.  For simplicity, I will assign each a rating of positive, neutral or negative.  For the economic indicators, I will denote in each one’s section how I decide which rating to give it.  At the end, I assign an overall rating, but this is just to guide me in my takeaway of where things stand.  It’s not scientifically rigorous or anything.

  • Positive - indicative of a healthy, growing economy.
  • Neutral - indicative of a slow or no growth economy but not a contracting (recession) economy.
  • Negative - indicative of a shrinking economy or recession.

(NOTE: For a “Quick ‘n Easy” read, just review the labeled white boxes, then skip to my “Easy Take” summary at the end.  You can review any charts/graphs afterward.  I want to make sure no one is intimidated by the length of my posts, even though I’m trying to making them easy …)


Quick Summary

Indicator (Click for details – only works if full article is open) Current Rating (change from previous roundup)
ADS Business Conditions Index Positive
Bloomberg Financial Conditions Index Positive
Daily Consumer Leading Indicators Negative
Citigroup Economic Surprise Index Neutral
Employment Trends Index Positive
Chicago Fed National Activity Index Neutral
Easynomics Real Estate Price Stability Index Positive
Easy Trends Dashboard   (min/max -3 to +3) +2.67 = Definitely moving in a positive direction, with hardly any unconfirmed trends or off-trend readings

NOTE: You may be reading an outdated analysis.  Please visit my latest economic indicators roundup.



Economic Indicator: ADS Business Conditions Index   |   POSITIVE
Easy Intro to ADS Business Conditions Index   |   Link to Source   |   Latest Date This Info Represents: July 12, 2014

Quick ‘n Easy

A combination of several key indicators of business conditions suggests, with high confidence, that at the end of March 2014 (most recent date for which there is data for all components of the index), conditions were above average (+0.311).  As of about a week and a half ago, it suggested, with low confidence, that current conditions were slightly above average (+0.173), historically speaking.  The index suggests that economic activity took a temporary dive in late 2013 before bouncing back quickly to levels slightly above historical averages.

Economic Indicators - ADS Business Conditions Index Jul 12 2014

Source: PhiladelphiaFed.org

Easy Description: Combines several indicators together to describe current business conditions.  A value above zero means that conditions are better than average, but below zero means worse than average.

Latest Readings:

July 12, 2014: Positive (+) 0.173 (includes weekly unemployment figures and maybe one other indicator)

One month prior: Positive (+) 0.165
One quarter prior: Positive (+) 0.197

The most recent date for which there is data for all components of the index is end of March 2014, when conditions were above average (+0.311).

Implications: After conditions took a hit starting mid-November 2013, we never went into a recession-type shrinking phase, and conditions quickly bounced back up to above average levels. Preliminary data suggests that conditions have been hovering around slightly-above-average levels.

Additional Info: This index provides confident readings about the past when all of the indicators have been collected (everything to the left of the left-most vertical line).  The readings in between the two vertical lines are somewhat less confident because they include some, but not all, of the indicators.  And the latest reading always falls to the right of the right-most vertical line and includes only a couple of indicators.

Easynomics Rating Methodology: For this index, I will use the very latest reading and rate anything between zero and minus (-) 1.00 as “neutral” – anything above or below that will be rated “positive” or “negative” respectively.

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