Category Archives: Stock

January Barometer

The January barometer is the hypothesis that stock market performance in January (particularly in the US) predicts its performance for the rest of the year. So if the stock market rises in January, it is likely to continue to rise by the end of December. Probably the best known is “as January goes, so goes the year”. Another says that the first 5 trading days determine the market’s returns for the whole year ahead. And another says that how January performs predicts the direction of the market for the remaining months of the year. The January barometer was first mentioned by Yale Hirsch in 1972. Historically if the S&P 500 goes up in January the trend will follow for the rest of the year. Conversely if the S&P falls in January then it will fall for the rest of the year.

If an investor believes in the ability of the January barometer to predict the equity market’s performance, he will only invest in the market in the years when the barometer predicts the market will rise, and stay out of the market when it forecasts a market pullback. It is difficult to produce excess returns based on this theory. Since the improved performance by staying out of the market during bad times can be more than offset by larger losses incurred when the barometer incorrectly predicts a bull market. January tends to be one of the market’s best months every year, rising an average of 1.3% since 1929, see our January Effect. And because the stock market rises in most years, there’s some inherent bias in the data itself. So, while the barometer works well in predicting up years (some studies even suggest that up Januaries mean up years 85% of the time), it doesn’t do so well in predicting down years. When January is down, the market continues to fall only 46% of the time.

From 1950 till 1984 both positive and negative prediction had a certainty of about 70% and 90% respectively with 75% in total. After 1985 however, the negative predictive power had been reduced to 50%, or in other words, no predictive powers at all. The following table shows the wrong prediction of January Barometer :

Year January S&P End of Year S&P Comments
1946 7% gain Loss 17.6% Start of bad misfire
1947 2.4% gain Loss 2.3% Not right, but no biggie
1948 4% loss Gain 3.5% What the f?
1956 3.6% loss Gain 6.5% Minor
1960 7.1% loss Gain 4.5%  
1966 0.5% gain Loss 13.5%  
1968 4.4% loss Gain 12.6%  
1970 7.6% loss Gain 8.4%  
1978 6.2% loss Gain 7.7%  
1982 1.8% loss Gain 16.8%  
1984 0.9% loss Gain 2.3%  
1987 13.2% loss Gain 9.9%  
1990 6.9% loss Gain 0.3%  
1992 2% loss Gain 6.6%  
1994 3.3% gain Loss 4.6%  
2001 3.5% gain Loss 13%  
2003 2.7% loss Gain 26.4% significant
2005 2.53% loss Gain 8.36% Minor disappointment
2009 8.5% loss Gain 35% Worst loss
2010 3.9% loss Gain 12.6%  
2011?      
       
       

5 wrongs for the most recent decade:

Year 2001: gain of 3.5% but loss of 13% year end.

Year 2003: The S&P has a loss of 2.7% but the S&P finished with significant  26.4% gain.

Year 2005: there was a minor misfire in 2005.

Year 2009: the January barometer is a big fake. January 2009 saw the S&P 500 fall 8.5%, only to finish with one of the best years on record as stocks soared 35% the rest of the way. Anybody who followed the barometer religiously in the year 2009 missed out on one of the most profitable market swings in a generation.

Year 2010: After a 3.9% January loss, the S&P finished with a 12.6% gain.

The year 2011 is not finished yet, what 2011 is going to be? What about 2012? Evidence also suggests that other months, such as April and November, are just as good at predicting the year as January. So why does January get all the attention? Read our other theories such as the January effect, Presidential Cycle and Halloween indicator.

Halloween indicator

The Halloween indicator is a variant of the stock market adage “Sell in May and go away,” the belief that the period from November to April has significantly stronger growth on average than the other months. In such strategies, stocks are sold at the start of May and the proceeds held in cash; stocks are bought again in the autumn, typically around Halloween. This Halloween indicator is partially related to another well known effect: The January Effect.

 

Though this seasonality is often mentioned informally, it has largely been ignored in academic circles (perhaps being assumed to be a mere superstition). Nonetheless analysis by Bouman and Jacobsen (2002) shows that the effect has indeed occurred in 36 out of 37 countries examined, and since the 17th century (1694) in the United Kingdom; it is strongest in Europe. According to the efficient-market hypothesis, this is impossible.

 

It is not clear what causes the effect. Many supporters of the Halloween indicator suggest that people taking vacations and holidays during the summer months can lead to market weakness. There are exceptions: between April 30 and October 30 2009, the FTSE 100 gained 20% (from 4,189.59 to 5,044.55).  We can not say the Halloween Indicator existed in each and every year. But that’s hardly surprising, since no indicator works all the time. The question is, over progressively longer horizons, does the success rate grew to very impressive and consistent levels (should be much higher than 50%).

 

Most interesting about the effect is that it shows that stock market returns in many countries during the period May-October are systematically negative or lower than the short-term interest rate, which also goes against the efficient-market hypothesis. Stock market returns should not be predictably lower than the short term interest rate (risk free rate).

 

Popular media often refer to this market wisdom in the month of May, claiming that in the six months to come things will be different and the pattern will not show. However, as the effect has been strongly present in most developed markets (including the United States, Canada, Japan, the United Kingdom and most European countries) in the last decade – especially May-October 2009 – these claims are often proved wrong.

 

One study which tests the Halloween indicator in US equity markets found similar results as Bouman and Jacobsen (2002) over the same time period but using futures data over the period April 1982- April 2003 and after excluding the years 1987 and 1998 no longer found a significant effect, leading these researchers to conclude that it was not an “exploitable anomaly’ during that time period in the United States.” Other regression models using the same data but controlling for extreme outliers have found the Halloween effect to still be significant. The original saying is “Sell in May and go away, stay away till St. Leger Day”, referring to the last race of the British horse racing season, however this day is unlikely to be known by non-Brits so it is replaced by Halloween (which in turn is Samhain, about one-eighth year after the equinox).

Even a stopped clock is right twice a day

Even a stopped clock is right twice a day

There are many different ways to predicate stock market.  Some are well known, some are not, but all theories have their true believers. First I will list a few very “reliable rules”. Then I will list a few common but not so reliable ones. For each of the topic below, we will have follow up posts with in depth study and discussions.

Reliable Rules:

Rule #1 Buy low and sell high: everyone knows that, this rule for sure is working, I definitely believe it!

The financial markets are usually efficient. When the markets are not fully efficient, you may benefit from it.

Insider trading:  This is the most effective winning strategy. Most people including theUS government would agree with me on this one. Recently the government sent billionaire Raj Rajaratnam to 11 years in prison. The government rigorously proved that insider trading is profitable, I have no doubt about that.

Market manipulation: bear raid, churning, rumors. Note that market manipulation is prohibited in theUnited States under Section 9(a)(2) of the Securities Exchange Act of 1934.

Not so reliable rules:

I have crafted this statement even before I have posted this article to cover my rear end: “I’ve been getting loads of emails from people who have lost most of their money and are looking for some direction as to what they might consider doing. Yes, I was right/(or wrong), no one could have anticipated the catastrophic event, but exceptional times need exceptional measures. Etc.”

January effect: increase in buying securities before the end of the year for a lower price, and selling them in January to generate profit from the price differences.  It is called January effect but now the date may be moved earlier because people are buying the stocks earlier to profit from it. One theory explaining this phenomenon is that income tax-sensitive investors sell stocks for tax reasons at year end (such as to claim a capital loss) and reinvest after the first of the year. The second reason is the payment of year end bonuses in January. Some of this bonus money is used to purchase stocks, driving up prices. The third reason is that may people max out the retirement contribution at the end of a year and contribute to their retirement saving at the start of the year. The January effect does not always materialize; for example, small stocks underperformed large stocks in January 1982, 1987, 1989 and 1990.

Presidential Cycle: The first year is the weakest of all four years. Higher returns during the last two years of a Presidential term than the first years.  The expectation is that as a President takes office he begins to implement his proposals and investors, hunker down waiting to see the results.  During the final two years the President becomes more concerned with his re-election and will ‘prime the pump’ in order to secure re-election.

Halloween indicator: it is a variant of  “Sell in May and go away”. It is the belief that the period from November to April has significantly stronger growth on average than the other months. In such strategies, stocks are sold at the start of May and the proceeds held in cash (e.g. a money market fund); stocks are bought again in the autumn, typically around Halloween.

January barometer:  it is the hypothesis that stock market performance in January (particularly in theUS) predicts its performance for the rest of the year. So if the stock market rises in January, it is likely to continue to rise by the end of December. Historically if the S&P 500 goes up in January the trend will follow for the rest of the year. Conversely if the S&P falls in January then it will fall for the rest of the year. From 1950 till 1984 both positive and negative prediction had a certainty of about 70% and 90% respectively with 75% in total. After 1985 however, the negative predictive power had been reduced to 50%, or in other words, no predictive powers at all.

Mark Twain: it is the phenomenon of stock returns in October being lower than in other months. The name comes from the following quotation in Mark Twain’s Pudd’nhead Wilson: “October. This is one of the peculiarly dangerous months to speculate in stocks. The others are July, January, September, April, November, May, March, June, December, August, and February.”  The 1929, 1987 and 2008 stock market crashes roughly occurred in October.

Turn of the Month Effect: higher returns around the turn of the month. Turn-of-the-month is defined as beginning with the last trading day of the month and ending with the third trading day of the following month. It is saying that positive returns only in the first half of the month, and the last day of one month and the first three of the next are particularly high. Investors making regular purchases may benefit by scheduling to make those purchases prior to the turn of the month. Nobody knows the reason behind such pattern.

Monday Effect: Monday tends to be the worst day to be invested in stocks. Suicides are more common on Monday than on any other day. Could the effect be caused by the moods of market participants? People are generally in better moods on Fridays and before holidays, but are generally grumpy on Mondays.

Super bowl indicator: This is an indicator based on the belief that a Super Bowl win for a team from the old AFL (now American Football Conference AFC) foretells a decline in the stock market for the coming year (bear), and that a win for a team from the old NFL (National Football Conference NFC division) means the stock market will be up for the year (bull). This indicator has been surprisingly accurate (around 85% correct) over the past years.

Years ending in 5: The DJIA had never had a down year in any year ending in 5. DJIA ended on 12/31/2004 at 10,783 and 12/30/2005 at 10,717, so this trend may have ended with 2005.

Stock Split Effect: before and after a company announces a stock split, the stock price rises. This is momentum effect because a stock split is as result of the stock risen too high. The stock splits are often viewed by investors as a signal that the company’s stock will continue to rise.

Merger Effect: the value of the company being acquired tends to rise while the value of the bidding firm tends to fall.

Bare knees, bull market: The market rises and falls with the length of skirts. In 1987, when designers switched from miniskirts to floor-length skirts just before the market crashed. A similar change also took place in 1929.

Drug Production Indicator: Stock prices and anti-depressant production are inversely related. This indicator suggests that when the market is rising, fewer people need anti-depressant to heal market-induced problems.

Holiday Effect: the general strategy is to purchase stocks one or two days prior to a holiday and sell stocks just after the holiday.

Astrology:  predicting major economic trends as they relate to certain cycles, specifically on the cycles of outer planets; finding the best industry to be in for a particular period of time based on major planetary configurations; identifying the best stocks to own during a particular time period; identifying the best date and time to buy or sell a stock; correlating the Astrological aspect to the movement of stock market in day trading.

Lunar cycle: stock returns are lower on the days around a full moon than on the days around a new moon.

Elliott Wave: it is a form of technical analysis that traders use to analyze financial market cycles and forecast market trends by identifying extremes in investor psychology, highs and lows in prices, and other collective factors. This principle has many believers, however critics says as follows:

Technical analyst David Aronson wrote: The account is especially persuasive because EWP has the seemingly remarkable ability to fit any segment of market history down to its most minute fluctuations. I contend this is made possible by the method’s loosely defined rules and the ability to postulate a large number of nested waves of varying magnitude. This gives the Elliott analyst the same freedom and flexibility that allowed pre-Copernican astronomers to explain all observed planet movements even though their underlying theory of an Earth-centered universe was wrong.