% of S&P 500 Stocks Above 50 DMA

One indicator I sometimes like to look at to see if the market is getting a bit frothy is the % of S&P stocks that are above their 50 day moving average.

As you can see from the chart below, its at a very big high, almost 90% though in the last few days, its starting to drop.

Looking at the same chart for 200 day moving average, you see another high of 87%...

Market Overbought?

My feeling (note: FEELING) is that the market's starting to get overbought...  There's been too much rallying of the general market while several individual companies are starting to drop.  I usually see this sign before markets reverse.  Then again, usually this happens a month or more before the drop actually happens.

Will the trend continue?  Who knows but some of my indicators support overbought positions if not yet reversals.

Just a thought.

Is Market Getting Overbought?

The S&P 500 is hitting more and more new highs, just barely in range of 1500 now.  After an extremely strong second half 2012 and a strong YTD in 2013...are we getting a bit too far?  A good indicator I've always used is the % of stocks that are above their moving day average.  As you can see below, we are getting close to the highs that usually indicate a medium term drop/consolidation.

Interesting thing to consider when you look to buy into the market some more...

Lite posting lately but big news next week

Unfortunately, been a bit busy lately so haven't had time to do much posting.  On the bright side, after some delay due to corporate compliance issues, expect some big news next week!

Declining Trend in GDP Growth Post WWII Recessions

Bespokeinvest.com came out with a post recently calling the current economy "Obamalocks" since its featuring subpar growth with accomodative fed policies.  I don't quite agree with their explanation but its interesting to look at the data they accumulated.  



As you can see from their chart, the current 2009 recession recovery has been relatively weak.  They have some inaccuracies/inconsistency in their number, one example is that they counted median without 2009 numbers but counted average with 2009 numbers.  I didn't check if their GDP numbers are accurate but one thing that struck to me is if you look at the increasing red trend.  If you average out the GDP numbers for each recession and plot it by date, you'll find something interesting.

Notice the very obvious trend where the GDP growth trend after every recession post WWII is progressively getting worse.  The only big outlier is the 1958 recession which was much lower but this may be more of a definition.  If you look at the tablet above from Bespoke, they included several negative GDP values about 3 years after the recession.  So in essence 1958 had a slight double dip recession effect in its average.  If you take that double dip value out, you'll find a much better fit.  While thats questionable from a methodology standpoint, its still interesting to see the long term trend.

Data excluding "double dip" effect from 1958 recession

So what's responsible for this slowdown in GDP recovery trend?  I have some theories but not sure.  Will have to look into it some more.

How accurate are stock pickers?

Ran into this article from the CXO Advisory group today and thought it was interesting.  I'm sure everyone who reads about the market comes across various newsletters are experts that proclaim they know what the market will do in the future (hey I do this too but I don't get paid for it) and wondered how accurate it is.  CXO looks at their predictions and determines how accurate their advice is.  Turns around, most predictions are about a coin flip at ~45-50% (note that this is different than predicting what one company out of hundreds will do well, it merely says if the stock they chose did well).  I'm interested to see if they have a figure for what % of companies do well.

This info is not intended for you to only follow the accurate callers as past performance is not indicative of future results.

See full link

Grading Methodology:

The essential grading methodology is to compare forecasts for the U.S. stock market (whether quantified or qualitative) to S&P 500 index returns over the future interval(s) most relevant to the forecast horizon. However, many forecasts contain ambiguities about degree and timing, equivocations and/or conditions. In general, we:

• Exclude forecasts that are too vague to grade and forecasts that include conditions requiring consideration of data other than stock market returns.
• Match the frequency of a guru’s commentaries (such as weekly or monthly) to the forecast horizon, unless the forecast specifies some other timing.
• Detrend forecasts by considering the long-run empirical behavior of the S&P 500 Index, which indicates that future returns over the next week, month, three months, six months and year are “normally” about 0.1%, 0.6%, 2%, 4% and 8%, respectively. For example, if a guru says investors should be bullish on U.S. stocks over the next six months, and the S&P 500 Index is up by only 1% over that interval, we would judge the call incorrect.
• Grade complex forecasts with elements proving both correct and incorrect as both right and wrong (not half right and half wrong).

Weaknesses in the methodology include:

• Some forecasts may be more important than others, but all are comparably weighted. In other words, measuring forecast accuracy is unlike measuring portfolio returns.
• Consecutive forecasts by a given guru often are not independent, in that the forecast publishing interval is shorter than the forecast horizon (suggesting that the guru repetitively uses similar information to generate forecasts). This serial correlation of forecasts effectively reduces sample size.
• In a few cases, for gurus with small samples, we include forecasts not explicitly tied to future stock market returns. There are not enough of these exceptions to affect aggregate findings.
• Grading vague forecasts requires judgment. Random judgment errors tend to cancel over time, but judgment biases could affect findings. Detailed grades are available via links below to individual guru records. Within those records are further links to source commentaries and articles (some links are defunct). Readers can therefore inspect forecast grades and (in many cases) forecast selection/context.
• S&P 500 Index return measurements for grading commence at the close on forecast publication dates, resulting in some looseness in grading because forecast publication may be before the open or after the close. Very few forecast grades are sensitive to a one-day return, and we try to take looseness into account in grading any forecasts that focus on the very short term.

List:

Guru	Forecasts	Accuracy	Guru	Forecasts	Accuracy
David Nassar	44	68.2%	Doug Kass	178	47.6%
Jack Schannep	61	66.7%	Jeremy Grantham	37	47.5%
Ken Fisher	115	65.0%	Don Hays	85	47.1%
David Dreman	44	63.6%	James Stewart	115	47.0%
James Oberweis	35	62.9%	Marc Faber	154	47.0%
Louis Navellier	149	59.9%	Richard Band	31	46.9%
Jason Kelly	125	59.4%	Jim Cramer	62	46.8%
Dan Sullivan	115	59.1%	Gary D. Halbert	93	46.4%
John Buckingham	17	58.8%	Dennis Slothower	144	45.3%
Cabot Market Letter	48	58.8%	Jim Jubak	141	44.2%
Steve Sjuggerud	49	58.5%	Bill Cara	198	44.2%
Richard Moroney	55	56.4%	Tim Wood	182	43.8%
Carl Swenlin	125	55.4%	Martin Goldberg	109	43.1%
Jon Markman	36	55.3%	Price Headley	348	42.0%
Aden Sisters	39	54.8%	Gary Savage	119	41.9%
Bob Doll	161	54.7%	Linda Schurman	57	41.4%
Paul Tracy	52	53.8%	Donald Rowe	69	40.6%
Bob Brinker	44	53.3%	Igor Greenwald	37	40.5%
Mark Arbeter	230	53.2%	Bob Hoye	54	40.4%
Gary Kaltbaum	144	53.1%	John Mauldin	211	39.9%
Robert Drach	19	52.6%	Nadeem Walayat	66	39.7%
Don Luskin	201	52.0%	Jim Puplava	43	39.5%
Laszlo Birinyi	27	51.9%	Comstock Partners	203	39.3%
Tobin Smith	281	50.2%	Gary Shilling	40	37.5%
James Dines	39	50.0%	Bill Fleckenstein	148	37.3%
Ben Zacks	32	50.0%	Richard Russell	166	36.9%
Richard Rhodes	42	48.8%	Mike Paulenoff	12	35.7%
Bernie Schaeffer	81	48.8%	Abby Joseph Cohen	56	35.1%
Stephen Leeb	27	48.3%	Peter Eliades	29	34.5%
S&P Outlook	145	48.3%	Curt Hesler	92	33.0%
Carl Futia	96	48.1%	Steven Jon Kaplan	99	31.4%
Clif Droke	97	48.1%	Robert McHugh	128	28.9%
Charles Biderman	48	47.9%	Steve Saville	35	23.7%
Trading Wire	69	47.8%	Robert Prechter	23	21.7%

Graphic Chart - Five Years Later

Interesting chart from the NYTimes:

 

Five Years Later, Some Countries Still Lag

Five years ago, in the fourth quarter of 2007, the United States economy peaked before what became known as the Great Recession set in. Some countries, China and Australia among them, never saw their economies decline, but most did, and some of the largest economies remain smaller than they were in 2007. The world economy — measured by total gross domestic product in 56 countries for which data are available — is now about 6 percent larger. But share prices have yet to fully recover in most countries. Related Article »

S&P 500 Returns by Sector

The year is finally over.  Overall, 2012 was great for the stock market after a dismal 2011.  Below is the performance data from Standards & Poor for the S&P 2012 Year performance, broken out by sector:

Index Name	Adjusted Market Cap ($Million)	Index Level	Performance
			1 Day	MTD	QTD	YTD
TOTAL RETURNS
S&P 500 (TR)	N/A	2,504.44	1.69%	.91%	-.38%	16%
PRICE RETURNS
S&P 500	12,742,436.25	1,426.19	1.69%	.71%	-1.01%	13.41%
PRICE RETURNS BY SECTOR
Energy	1,400,015.46	532.96	2.09%	.52%	-3.31%	2.33%
Materials	461,613.38	237.62	2.02%	2.89%	2.04%	12.24%
Industrials	1,290,086.56	328.75	1.87%	2.26%	2.96%	12.46%
Cons Disc	1,464,901.61	376.06	2%	.24%	1.57%	21.87%
Cons Staples	1,352,391.20	360.78	1.11%	-2.54%	-2.48%	7.52%
Health Care	1,530,449.35	462.95	1.22%	-.38%	-.5%	15.19%
Financials	1,989,102.90	221.24	1.39%	4.56%	5.32%	26.26%
Info Tech	2,426,353.68	463.82	2.16%	-.12%	-6.21%	13.15%
Telecom Svc	389,865.37	146.04	1.14%	-1.09%	-7.06%	12.5%
Utilities	437,656.73	177.66	1.39%	-.24%	-3.91%	-2.91%

As you can see, total return including dividends was a sweet 16% while non-div return was still a nice 13.41%.  The two big winning sectors for the year: Financials at 26.26% and Consumer Discretionary (really? in such a depressed economy?) at 21.87%.


There was only one loser: Utilities at -2.91%.  This can be seen as more of a correction as 2011 was great for the Utilities and dividend sector.  Energy was also a big loser at 2.33%.  If the trend plays out that the poor performer becomes better next year, energy may be an interesting play for 2013.

Sector Breakdown

 (as of 31-Dec-2012)