Category Archives: Uncategorized

Tis’ the Season to ‘Get Small(Cap)’

A lot has been written lately about the tendency for small-cap stocks to outperform large-cap stocks during the upcoming time of the year (for example).  And rightly so.  For whatever reason, the relationship between large-caps and small-caps has shown itself to be highly seasonal over the years. Let’s take a closer look.

Jay’s Large-Cap/Small-Cap Calendar

The table below displays my calendar for when to hold large-cap stocks versus when to hold small-cap stocks.

*Note that TDM stands for “Trading Day of the Month” and NOT date of the month – i.e., Mar 10 means at the close on the 10th trading day of March small-caps are sold and large-caps are bought.

*Also, for June and September if there are less than 22 trading days in the month then the trade is made at the close on the last trading day of the month.

From Close on Trading Day of Month To Close on Trading Day of Month Hold
Mar 10 May 12 Large-Cap
May 12 Jun 22 Small-Cap
Jun 22 Aug 6 Large-Cap
Aug 6 Sep 22 Small-Cap
Sep 22 Nov 15 Large-Cap
Nov 15 Mar 10 Small-Cap

Figure 1 – Jay’s Large-Cap/Small-Cap Calendar

The Test

*For testing purposes we will use ticker RUI (Russell 1000 Large-Cap Index) and ticker RUT (Russell 2000 Small-Cap Index).

*First we will look at a buy-and-hold approach using both indexes, then will compare it to our switching method.

The Results

Figure 2 shows the growth of $1,000 invested in each index separately as well as combined since January 4, 1989.2Figure 2 – Growth of $1,000 invested in RUT and RUI (separately and “Split” between the two); 1/4/1989-11/21/2017

Figure 3 applies the calendar displayed in Figure 1 –  i.e., Ticker RUI is held from March TDM 10 through May TDM 12, the last trading day of June through August TDM 6 and the last trading day of September through November TDM 15 (with all switches being made at the close of the day). Ticker RUT is held during all other periods as indicated in Figure 1.

Note: The “red” line in Figure 3 is the “green” line from Figure 2 and represents splitting an initial $1,000 investment between RUI and RUT on a buy-and-hold basis.

Figure 3 then displays the “Switching” results versus the “Splitting” results (i.e., simply buying and hold both indexes).

3Figure 3 – $1,000 invested using “Switching” strategy versus “Splitting” money evenly between two indexes; 1/4/1989-11/20/2017

For the record, the “Switching” strategy gained +3,727% since 1989 versus +892% for the “Splitting” strategy.  While the Switching strategy return is 4.17 times greater than simply splitting money between both indexes, it does not come without risk and volatility. To wit:

*The average 12-month standard deviation of returns is actually higher (18.1%) using the Switching strategy versus splitting (16.8%)

*The Worst 12-month % decline for the Switching Strategy is still a whopping -45.8% – almost as much as the -49.0% for splitting.

Measure Switch Split
Average 12-mos. % +14.5% +9.2%
Median 12-mos % +14.8% +10.9%
Std. Deviation% 18.1% 16.8%
Average/Standard Deviation 0.80 0.55
Worst 12.mos. % (-45.8%) (-49.0%)
% 12-mos. UP 82.1% 76.3%
% of 12-month periods outperforms 84.1% 15.9%

Figure 4 – Comparative Results: “Switching” versus “Splitting”; 1/4/1989-11/20/2017

Figure 5 displays the year-by-year results.

Year Switch Split Diff $1,000 $1,000
1989 22.9 19.4 3.5 1,229 1,194
1990 (9.5) (14.1) 4.6 1,112 1,025
1991 40.7 35.3 5.4 1,565 1,387
1992 17.6 10.7 6.9 1,841 1,536
1993 13.1 12.0 1.0 2,082 1,721
1994 4.6 (2.8) 7.4 2,177 1,672
1995 31.0 30.3 0.7 2,852 2,179
1996 21.0 17.3 3.7 3,450 2,555
1997 32.6 25.7 6.9 4,577 3,213
1998 11.8 12.0 (0.2) 5,116 3,599
1999 14.8 18.5 (3.7) 5,873 4,266
2000 28.1 (6.2) 34.3 7,522 4,000
2001 3.8 (7.6) 11.4 7,807 3,695
2002 (17.0) (22.3) 5.4 6,483 2,870
2003 35.2 35.6 (0.3) 8,768 3,890
2004 27.2 13.1 14.1 11,157 4,401
2005 6.6 3.8 2.8 11,898 4,570
2006 18.1 15.2 3.0 14,053 5,263
2007 5.4 0.5 4.8 14,807 5,290
2008 (30.8) (37.0) 6.2 10,247 3,335
2009 24.6 25.3 (0.8) 12,765 4,180
2010 20.5 19.6 0.8 15,378 5,001
2011 (2.1) (3.1) 1.0 15,058 4,845
2012 21.0 14.2 6.8 18,220 5,535
2013 40.7 33.9 6.8 25,642 7,411
2014 14.8 7.1 7.7 29,437 7,936
2015 1.5 (3.5) 4.9 29,875 7,661
2016 12.0 14.6 (2.5) 33,475 8,779
2017 14.3 13.0 1.4 38,273 9,917

Figure 5 – Year-by-Year Results; 1/4/1989-11/20/2017

The next switch occurs at the close on 11/21 (15th trading day of November 2017 out large-caps and into small-caps).

Summary

The “system” (such as it is) described herein is by no means of the “you can’t lose” variety (note the “Worst 12-month % loss” of -45.8%).  Still, the fact that this entirely mechanical – and calendar-based – approach outgained a simple buy-and-hold approach by over 4-to-1 overall, and during 84% of all rolling 12-month periods – is nothing to sneeze at.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

 

 

 

Emerging Markets and the U.S. Election Cycle

It is widely known that the four-year U.S. Election Cycle has an influence on the U.S. stock market.  What is not so widely known is that other markets also seem to “walk to the beat”.  Take for example “emerging markets.”

The Test

For testing purposes we will use the MSCI Emerging Markets Index (Gross Dividend) Monthly Total Return from the PEP Database from Callan Associates starting in January 1988.

The ETF ticker EEM (iShares MSCI Emerging Markets ETF) started trading in May 2003 and can be used for trading purposes.

The EEM Election Cycle Calendar

Figure 1 displays my Emerging Markets Election Cycle Calendar. During months marked EEM, the Emerging Markets Index is held.  The same months are used over the course of each 4-year cycle.

1

Figure 1 – Jay’s Emerging Markets Election Cycle Calendar

To be clear, during each post-election year in the U.S. (i.e., 1989, 1993, 1997, etc.) we would hold the Emerging Markets Index during the months of January, April, May, July, September, November and December.  During all other months during that year we would NOT hold the Emerging Markets Index.

Figure 2 displays the growth of $1,000 invested in the MSCI Emerging Markets Index (actual results using EEM will likely be slightly lower due to ETF fees) ONLY during the months marked EEM during every 4-year U.S. presidential election cycle starting in 1988.2Figure 2 – Growth of $1,000 invested in MSCI Emerging Markets Index ONLY during Favorable Election Cycle Months; 1988-2107

Figure 3 displays the growth of $1,000 invested the MSCI Emerging Markets Index ONLY during the months NOT marked EEM during every 4-year U.S. presidential election cycle starting in 1988.3Figure 3 – Growth of $1,000 invested in MSCI Emerging Markets Index ONLY during non-Favorable Election Cycle Months; 1988-2107

For the record:

*$1,000 invested in the “favorable” months grew to $145,908 (+14,491%)

*$1,000 invested in the “other” months declined to $166 (-83%)

Figure 4 displays a few comparative values between holding the emerging markets index during the “Favorable” versus “Unfavorable” months.4

Figure 4 – 12-months returns for Favorable versus non-Favorable Months; 1988-2017

Summary

So is the calendar displayed in Figure 1 guaranteed to generate profits ad infinitum into the future?  Not at all. But the results displayed herein do suggest that there just might be something to this whole 4-year cycle “thing”.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

 

 

 

Dollar Downer?

The U.S. Dollar attempted to rally recently following a pretty relentless January into September decline.  Is that rally over?  And if so is there a play to be made?

Before proceeding further, there are two important things to note:

*I am very bad at making predictions (OK, technically I am very good “making” predictions, I’m just not that good at “being right” when I do).

*This blog DOES NOT offer investment advice. I just tell you what I know (or more accurately – what I think I know) or what I see and sometimes offer examples of ways to trade said items.

Are we clear?  OK, then let’s proceed.  Figure 1 displays ticker UUP – an ETF that tracks the U.S. Dollar Index.1Figure 1 – Ticker UUP (Courtesy ProfitSource by HUBB)

You can see the long decline in 2017, the recent rally, and now an Elliott Wave “Wave 4 Sell” as generated by ProfitSource by HUBB.  Does this guarantee that the next down leg in the dollar has begun?  Not at all.  First off, Elliott Wave counts can be a bit nebulous at times. Also, not every “Elliottician” will agree with the count as it appears in Figure 1 (in fact, trying to get to Elliott counters to agree on a given count is sort of like trying to get Republicans and Democrats to agree on – well, anything).  The reason I like using ProfitSource for this purpose is that – for better or worse – it has an objective built in algorithm for generating Elliott Wave counts.  Bottom line – it is far less subjective than anything I would come up with on my own.

Figure 2 displays the current Elliott Wave counts for four currency ETFs – FXA (Australia), FXB (British Pound), FXC (Canadian Dollar) and FXE (Euro).  As currencies (mostly) trade inversely to the U.S. Dollar it is interesting to note that all four of these recently generated “Wave 4 Buy” signals.2Figure 2 – Tickers FXA, FXB, FXC, FXE (Courtesy ProfitSource by HUBB)

As FXE is the most heavily traded – both in terms of shares and options – let’s take  a closer look as shown in Figure 3.3Figure 3 – Ticker FXE (Courtesy ProfitSource by HUBB)

As you can see – again, for better or worse – the ProfitSource wave count is projecting a move to the 118.78 to 124.40 range for ticker FXE between now and March 2018. IMPORTANT NOTE: I find these kinds of projections to be very enticing.  But remember, they are in fact nothing more than projections and NOT guarantees.  Bottom line: acting on an Elliott Wave projection requires something of a leap of faith and involves the assumption of speculative risk.

Example Trade

Once again, what follows is NOT a recommendation, only an example. Let’s assume one wants to speculate on a rise in ticker FXE.  In Figure 4 we see that the implied volatility for options on FXE is towards the low end of the historical range.4aFigure 4 – Ticker FXE with 90-day implied option volatility (Courtesy www.OptionsAnalysis.com)

This tells us two things:

*The amount of time premium currently built into FXE option prices is low

*One might be able to profit from an increase in IV

The example trade is called a “Call Backspread” and involves:

*Buying 2 Mar2018 FXE 115 calls @ 1.47

*Selling 1 Mar2018 FXE 113 calls @ 2.46

5Figure 5 – FXE backspread (Courtesy www.OptionsAnalysis.com)6Figure 6 –FXE backspread risk curves (Courtesy www.OptionsAnalysis.com)

As you can see in Figures 5 and 6:

*The cost to enter this trade – and the maximum risk – is $248.  However, a loss of -$248 would only occur if the trade is held until March expiration and FXE close that day at exactly $115 a share (i.e., we can eliminate the risk of a maximum loss simply by planning to exit the position prior to expiration).

*If FXE falls apart and collapses in price then the risk is only about -$55.

*If FXE rallies into the Elliott Wave projection range of 118.78 to 124.40 then the anticipated profit would be somewhere between +$150 and +$750, depending on how soon the move occurs and how high the price goes (sooner and higher are better).

One last item: if by chance implied volatility increases, this could inflate the profit potential for this trade.

Summary

Is the U.S. Dollar going to decline – and/or FXE going to rise?  I can’t predict that. But for what it is worth the current Elliott Wave projections are pointing in that direction.  The example trade discussed here is just one of many potential ways to  play such a move.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

 

 

When The Market is Up All Year

The S&P 500 Index has been up for the year the entire year of 2017.  Has this happened before?  And how did the market react the following year?

Rather than recreate someone else’s work I will simply include a link below to an article published at www.RealClearMarkets.com on 11/14.  The article – titled “The S&P 500 has been in the black all year — here’s what typically happens next” – was written by MarketWatch Writer Victor Reklaitis based on research done by Jani Ziedins of https://cracked.market.

For the record, I have to admit I was somewhat surprised by the results.  Rather than “give away” the somewhat surprising results, I will simply urge you to click the link below and read for yourself.

The S&P 500 has been in the black all year — here’s what typically happens next

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

 

The Most Wonderful Time of the Year (80% of the Time)

It is not a little known fact that the stock market has showed a tendency to perform well during the end-of-year “Holiday Season”.  How well?  Let’s take a look.

The Test

Let’s first define “Holiday Season” as it relates to the stock market.  We will focus our attention on the following period:

*From the close on the Friday before Thanksgiving through the close on the last trading day of the year.

Figure 1 displays the growth of $1,000 invested in the Dow Jones Industrials Average only during this holiday season time period starting in 1942.1Figure 1 – Growth of $1,000 invested in Dow Industrials ONLY from close on Friday before Thanksgiving through close on last trading day of the year; 1942-2016

For the record:

*# of times UP = 60 (80% of the time)

*# of times DOWN =15 (20% of the time)

*Average UP% Gain= +3.3%

*Average DOWN% Loss = (-1.8%)

*#of Rolling 5-year periods showing a gain = 69 (97% of the time)

*# of Rolling 5-year periods showing a loss = 2 (3% of the time)

*#of Rolling 10-year periods showing a gain = 66 (100% of the time)

*# of Rolling 10-year periods showing a loss = 0 (0% of the time)

The good news is the long-term consistency of returns (80% of all 1-yr, 97% of all 5-yr. and 100% of all 10-yr. periods show a gain)

The bad news is that this is still no “sure thing” as 15 times in 75 years – or 20% of the time – this supposedly “bullish” seasonal period showed a loss.  The 5 worst losing periods were:

2002 (-5.3%)

1966 (-2.9%)

1969 (-2.8%)

1980 (-2.6%)

1968 (-2.4%)

While these losses seem small, it should be noted that a “mere” -2.4% decline from current levels would knock roughly 560 points off of the Dow. A -5.3% declines would total roughly 1,250 Dow points.  That would not exactly qualify as “wonderful”.

Figure 2 displays the year by year results.

Year Seasonal %+(-)
1942 3.5
1943 2.2
1944 4.3
1945 0.3
1946 7.3
1947 (0.6)
1948 (0.1)
1949 3.4
1950 1.6
1951 3.2
1952 4.5
1953 1.8
1954 7.0
1955 1.1
1956 4.7
1957 (1.6)
1958 4.3
1959 5.3
1960 2.0
1961 0.3
1962 2.6
1963 4.1
1964 (1.9)
1965 1.7
1966 (2.9)
1967 5.2
1968 (2.4)
1969 (2.8)
1970 10.2
1971 9.8
1972 1.5
1973 (1.4)
1974 0.2
1975 1.4
1976 5.9
1977 (0.5)
1978 0.9
1979 2.3
1980 (2.6)
1981 2.6
1982 2.5
1983 0.6
1984 3.2
1985 5.6
1986 0.1
1987 1.3
1988 5.1
1989 3.8
1990 3.6
1991 9.2
1992 2.3
1993 1.6
1994 0.5
1995 2.5
1996 (0.4)
1997 1.8
1998 0.2
1999 4.5
2000 1.5
2001 3.2
2002 (5.3)
2003 8.6
2004 3.1
2005 (0.5)
2006 1.0
2007 (1.8)
2008 9.1
2009 1.1
2010 3.3
2011 3.6
2012 3.2
2013 3.2
2014 0.1
2015 (2.2)
2016 5.9

Figure 2 – % gain(loss) for Dow Jones Industrials Average during 3 Trading Days prior to Thanksgiving through December 31st (Dow Jones Industrials Average)

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

Bad Days for Electronics

In a recent series of articles (here, here and here) I wrote about certain days of the month that appear to be worse than others for the overall stock market.  The same is true for many stock market sectors.  Take the electronics-related sector, for example.

Bad Days for Semi’s/Electronics

For testing purposes we will use ticker FSELX (Fidelity Select Electronics).  However, because FSELX has switching restrictions another vehicle would need to be used for actual trading (see list of candidates further below).

Here are the “Bad Days” of the month for Electronics:

*Trading Days #5, 6 and 7

*Trading Days #13 and 14

*Trading Days -7, -6, -5

(The last trading day of the month is considered -1, the day before that -2 and so on)

How bad are they?

Figure 1 displays the growth of $1,000 invested in FSELX only on TDM 5, 6 and 71Figure 1 – FSELX on TDM 5, 6 and 7; 9/30/1988-11/7/2017

Figure 2 displays the growth of $1,000 invested in FSELX only on TDM 13 and 142Figure 2 – FSELX TDM 13 and 14; 9/30/1988-11/7/2017

Figure 3 displays the growth of $1,000 invested in FSELX only on TDM -7, -6 and -53Figure 3 – FSELX TDM -7, -6, -5; 9/30/1988-11/7/2017

Figure 4 combines all 3 “Bad Day” periods.4Figure 4 – FSELX TDM 5, 6, 7, 13, 14, -7, -6, and 5; 9/30/1988-11/7/2017

*From October 1988 into March 2000 FSELX gained +128% during the “Bad Days”, albeit in extremely volatile fashion.

*From March 2000 into May 2016, FSELX lost -94% during the “Bad Days”

*Since May 2016 FSELX has gained +36% during the “Day Days”

So no one should assume that FSELX is “doomed” to decline during these days.

Still, a net result of -81% is a net result of -81%.

The “All Other” Days

Figure 5 displays the growth of $1,000 invested in FSELX on ALL OTHER trading days each month since October 1988 versus buying and holding FSELX.5Figure 5 – Growth of $1,000 invested in FSELX during “All Other Days” versus Buy-and-Hold; 9/30/1988-11/7/2017

The comparative results appear in Figure 66Figure 6 – Avoiding the “Bad Days” versus Buy-and-Hold; Sep88-Nov2017

Alternative funds

Figure 7 – generated using the MatchMaker function in AIQ TradingExpert – displays a variety of funds and/or ETFs with a high correlation to ticker FSELX.  Most of these can be traded with no restrictions.7

Figure 7 – Alternative Funds/ETFs (Courtesy AIQ TradingExpert)

Summary

At first blush, the big returns generated by missing the “Bad Days” are pretty compelling.  Still, if we dig deeper there are questions to be answered.

The “Other” days underperformed buy-and-hold significantly into the Year 2000, and also since May 2016.  Also, one may question whether trading only the “Other” days is really a viable approach.  Consider:

*We are talking about at least 2 and sometimes 3 trades every single month no matter what

*The maximum drawdown (-47%) – while less than that of a buy-and-hold approach (-82.5%) – is well beyond the comfort zone for most traders

*This “System” – such as it is – can (and will) significantly underperform buy-and-hold over extended periods of time.

As always, I do not offer trading advice here, only information.  While there are questions to answers and doubt to overcome in this case, still a return of +33,700% using a completely objective approach versus +5,756% using buy-and-hold may be worthy of further research.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

A Bottom-Picking Portfolio

In a recent article I highlighted some stocks that appeared to have a chance of “putting in a low”.  In another article, I highlighted the potential usefulness of “horizontal lines” on a chart.  The phrase “putting in a low” is essentially a kindler, gentler version of the phrase “Hey, let’s pick a bottom”.

The reality is that the ability to “pick tops and/or bottoms” on any kind of a consistent basis is a skill that roughly 99.2% of all investors and traders do not possess.  That being said, there is such a thing as a legitimate “bottom formation” (at least in my market addled opinion).  A security that bounces several or more times off a particular price is sending information that the sellers may be running out of ammunition.  These levels can be observed by drawing horizontal trend lines across a price chart – connecting recent highs and/or lows at roughly similar prices.

“Loading up” in this situation is not recommended. But committing an acceptable percentage of one’s portfolio (a level which each investor must decide on their own) to such opportunities is a perfectly acceptable form of speculation.

So for arguments sake, below is a “Bottom Pickers Portfolio”.  As always, I am not recommending this as an investment, simply highlighting an alternative idea for your further consideration.

The Tickers

The tickers included in this portfolio are mostly all commodity related.  That is not a purposeful choice; they simply “fit the model”.

First is ticker BAL – an ETF that tracks the price of cotton futures.  The critical level for BAL is roughly the $43.50 area.1Figure 1 – Ticker BAL (Courtesy AIQ TradingExpert)

Ticker GDX tracks a gold stock index and has been consolidating in a relatively tight range after last year’s sharp rally and subsequent pullback.2Figure 2 – Ticker GDX (Courtesy AIQ TradingExpert)

Ticker JO tracks the price of coffee futures.  This is one of the weakest charts on the list and is dangerously close to failing to the downside.  However, if the low holds this will strengthen the outlook a great deal.3Figure 3 – Ticker JO (Courtesy AIQ TradingExpert)

Ticker SGG tracks the price of sugar futures. SGG has been consolidating in a narrow range for about four months.  Key price levels on the downside are $26.50 and the August 2015 low of $24.79.4Figure 4 – Ticker SGG (Courtesy AIQ TradingExpert)

Ticker SWN is Southwestern Energy Co.  After a long, devastating decline the stock is attempting to form a low in the $5 a share range.5Figure 5 – Ticker SWN (Courtesy AIQ TradingExpert)

Ticker UNG tracks natural gas futures.  Thanks to the advent of fracking – which is made natural gas abundantly available – the price of natural gas has collapsed in recent years.  In the past week it retested its 2016 low and then ticked higher.  Like JO, this one is precariously close to “failing”.  But for now…

6Figure 6 – Ticker UNG (Courtesy AIQ TradingExpert)

The Bottom Pickers Portfolio                      

I use AIQ TradingExpert software to create my own “Groups”.  So I created one called “Lows” to include the six tickers above.  The group consists of an equal dollar investment in each ticker.  The chart for this combination of tickers appears in Figure 7.

7Figure 7 – The “Lows” Group (Courtesy AIQ TradingExpert)

Summary

Let me be blunt.  There is every chance that the majority of the tickers highlighted above will continue their long-term bearish trends and break down to the downside causing further losses for those holding these shares.

The primary thing to highlight in this piece is a personal preference.  I prefer “horizontal” lines on a chart – i.e., straight across, left to right – to the more typical slanted trend lines that most traders use.  The reason is simply – upward or downward slanting trend lines require a trader to decide which two (or more) highs (or lows) to connect in order to draw the trend line.  At the end of the day this is often a subjective decision.

Horizontal trend lines – which connect to (at least roughly equal) highs or lows – are generated by the market itself and as such, are more objective in nature.  In other words, investor buying and selling determines these levels.

Will my “Bottom Pickers Portfolio” move to the upside or fail to the downside?  We’ll just have to wait to find out.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

Some Days Really are Worse than Others; Part III

In two articles (here and here) I tried to point out that there might be a way to know in advance if you are about to have a “bad day” – at least in the stock market.  Here I want to summarize everything in chart and one table.

First a recap.

The Bad Days

For our purposes we will count the first trading day of the month as TDM 1, the second as TDM 2 and so on.

We will also count backwards from the last trading day of the month as follows: The last trading day of the month is TDM -1, the next to last day is TDM -2 and so on.

Here are the “Bad Days” of the month:

*TDM 13 through TDM 16

*TDM -10 through TDM -5

For this piece I used daily price data for the Dow Jones Industrials Average starting on 12/31/1933 and for each calendar month I calculated the cumulative price gain or loss for the Dow:

a) On the “Bad Days” listed above

b) All other trading days of the month

The Results

In a nutshell, for every single month except August and December:

*The “Bad Days” lost money

*”All other days” made money

*For the month of August both periods lost money.

*For the month of December both periods made money.

Figure 1 summarizes everything starting on January 1st 1934

*The Column labeled “Bad Days” displays the cumulative price gain or loss or the Dow Jones Industrials Average by month ONLY during the “Bad Days” listed above.

*The Column labeled “All Other Days” displays the cumulative price gain or loss or the Dow Jones Industrials Average by month ONLY during all trading days of the month that DO NOT fit into the “Bad Days” listed above.

Month All Other Days

Cumulative % +(-)

Bad Days

Cumulative % +(-)

Jan +136.0% (-23.8%)
Feb +25.1% (-12.8%)
Mar +60.7% (-3.7%)
Apr +235.1% (-1.1%)
May +50.7% (-38.8%)
Jun +68.3% (-27.5%)
Jul +250.0% (-14.3%)
Aug (-6.1%) (-17.0%)
Sep +5.5% (-41.7%)
Oct +170.3% (-36.8%)
Nov +147.7% (-12.8%)
Dec +158.3% +50.7%

Figure 1 – Cumulative Monthly % +(-) for Dow on “Bad Days” versus all other days; 12/31/1933-10/31/2017

Figure 2 displays graphically the gain/loss per month during the “Bad Days”.  Note that December is the ONLY month to show a cumulative gain during these days.BaddaysFigure 2 – Dow %+/- by month ONLY during “Bad Days”

Figure 3 displays graphically the gain/loss per month during “All Other Days”.  Note that August is the ONLY month to show a cumulative loss during these days.nonbaddaysFigure 3 – Dow %+/- by month ONLY during “Bad Days”

Summary

So is it worthwhile to trade out of the market on the “Bad Days” and to be back in the market on “All Other Days”?  That’s not for me to say.  But 83+ years of market history makes a compelling case.

Have a Good Day (or not, you know, depending…)

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

Some Days Really are Worse than Others; Part II

In response to some questions on the “Avoid Bad Days System” –we’ll call it the ABD System for short (Note to myself: come up with a better name) I wrote about here, this article includes some more details, fact, figures, etc.

*In a nutshell, the ABD System outperforms by being out of the market during a lot of bad days.  It also does it by outperforming the overall market when the overall market has a bad year.  To wit:

*During the 21 calendar years since 1946 when the Dow has showed a loss for the year, the ABD System outperformed the Dow 20 times and underperformed only once.

Concistency is another key:

*ABD System showed a gain during all 68 rolling 5-year periods and outperformed the Dow during 48 of 68 rolling 5-year periods.

*ABD System showed a gain during all 63 rolling 10-year periods and outperformed the Dow during 54 of 63 rolling 5-year periods.

1-Year Returns

  System Buy/Hold BadDays System-Buy/Hold
Average 10.4% 7.9% (2.1%) +2.5%
Median 10.2% 9.7% (1.6%) +2.1%
Std Dev 11.9% 15.5% 8.5% 9.0%
Ave/Std Dev 0.87 0.51 (0.24) 0.27
Max% 36.4% 44.0% 15.3% 20.1%
Min% (16.4%) (33.8%) (23.0%) (16.2%)
# Up 59 51 33 40
# Down 13 21 39 32

Figure 1

5-Year Rolling Returns

System Buy/Hold BadDays System-Buy/Hold
Average 64.7% 46.7% (10.2%) +18.0%
Median 60.0% 47.8% (13.3%) +21.3%
Std Dev 36.2% 45.9% 16.4% 26.6%
Ave/Std Dev 1.79 1.02 (0.62) 0.68
Max % 149.7% 199.8% 37.4% 72.0%
Min % 2.6% (23.0%) (31.6%) (56.6%)
# Up 68 55 22 48
# Down 0 13 46 20

Figure 2 – Using 5-Year Look back at the end of each year

10-Year Rolling Returns

System Buy/Hold BadDays System-Buy/Hold
Average 176.4% 114.5% (21.1%) +61.9%
Median 156.3% 96.6% (21.6%) +67.3%
Std Dev 98.9% 95.6% 18.9% 46.5%
Ave/StdDev 1.78 1.20 (1.12) 1.33
Max % 408.2% 323.4% 19.2% 141.9%
Min % 26.1% (29.5%) (51.2%) (44.6%)
# Up 63 56 9 54
# Down 0 7 54 9

Figure 3 – Using 10-Year Look back at the end of each year

Year-by-Year Results 

Year System Buy/Hold BadDays System-

Buy/Hold

1946 10.1 (8.1) (16.2) 18.2
1947 (3.7) 2.2 6.6 (6.0)
1948 (3.0) (2.1) 1.3 (0.9)
1949 11.2 12.9 1.9 (1.7)
1950 7.9 17.6 9.4 (9.7)
1951 30.4 14.4 (12.0) 16.1
1952 4.5 8.4 4.1 (3.9)
1953 (1.2) (3.8) (2.3) 2.5
1954 33.4 44.0 8.2 (10.5)
1955 11.8 20.8 8.3 (8.9)
1956 13.9 2.3 (9.9) 11.6
1957 (5.1) (12.8) (7.8) 7.7
1958 32.9 34.0 1.1 (1.1)
1959 8.6 16.4 7.5 (7.8)
1960 7.0 (9.3) (15.0) 16.3
1961 23.2 18.7 (3.3) 4.4
1962 6.9 (10.8) (16.3) 17.7
1963 17.8 17.0 (0.4) 0.8
1964 12.7 14.6 1.9 (1.8)
1965 16.7 10.9 (4.7) 5.8
1966 (9.1) (18.9) (10.5) 9.8
1967 15.2 15.2 0.3 0.0
1968 15.1 4.3 (9.1) 10.8
1969 (7.3) (15.2) (8.2) 7.9
1970 13.4 4.8 (7.3) 8.6
1971 18.2 6.1 (10.0) 12.1
1972 11.8 14.6 2.8 (2.8)
1973 (8.9) (16.6) (8.1) 7.7
1974 (16.4) (27.6) (13.1) 11.2
1975 36.4 38.3 1.7 (1.9)
1976 5.1 17.9 12.5 (12.8)
1977 (6.1) (17.3) (11.7) 11.2
1978 7.0 (3.1) (9.2) 10.2
1979 0.5 4.2 4.0 (3.7)
1980 9.6 14.9 5.2 (5.4)
1981 (1.9) (9.2) (7.2) 7.3
1982 6.3 19.6 12.9 (13.3)
1983 10.3 20.3 9.3 (9.9)
1984 3.1 (3.7) (6.3) 6.8
1985 19.4 27.7 7.2 (8.2)
1986 10.9 22.6 10.9 (11.7)
1987 22.3 2.3 (16.2) 20.1
1988 13.1 11.8 (0.8) 1.2
1989 19.2 27.0 6.9 (7.8)
1990 13.1 (4.3) (15.2) 17.4
1991 28.2 20.3 (5.9) 7.9
1992 7.7 4.2 (3.0) 3.6
1993 13.5 13.7 0.5 (0.2)
1994 11.4 2.1 (8.0) 9.2
1995 29.7 33.5 3.2 (3.7)
1996 9.8 26.0 15.1 (16.2)
1997 34.0 22.6 (8.2) 11.4
1998 5.8 16.1 10.1 (10.3)
1999 23.6 25.2 1.6 (1.6)
2000 0.9 (6.2) (6.7) 7.1
2001 3.1 (7.1) (9.6) 10.2
2002 (7.7) (16.8) (9.5) 9.0
2003 36.1 25.3 (7.7) 10.8
2004 6.5 3.1 (2.8) 3.3
2005 2.8 (0.6) (3.0) 3.4
2006 13.3 16.3 3.0 (3.0)
2007 3.2 6.4 3.4 (3.2)
2008 (13.8) (33.8) (23.0) 20.1
2009 18.1 18.8 0.9 (0.8)
2010 17.3 11.0 (5.0) 6.2
2011 7.3 5.5 (1.3) 1.8
2012 9.7 7.3 (1.9) 2.4
2013 23.9 26.5 2.4 (2.6)
2014 (6.4) 7.5 15.3 (14.0)
2015 9.6 (2.2) (10.6) 11.9
2016 11.2 13.4 2.3 (2.2)
2017* 13.1 18.3 4.8 (5.1)

Figure 4 – Annual % +/(-) for ABD System versus Buy-and-Hold

*thru 10/31/2017

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.

 

 

 

Some Days Really are Worse than Others

Some days are great. Some days are awful. Some days fall somewhere in between the two extremes.  Wouldn’t it be nice if we could eliminate some of the awful days? Unfortunately, in life too often the awful days end up taking us by surprise.

The same holds true to an extent in the stock market – great days, awful days and everything in between.  The one difference – as it turns out – is that we may be able to identify some of the bad days in advance.

Trading Days Best Missed

For our purposes we will count the first trading day of the month as TDM 1, the second as TDM 2 and so on.

We will also count backwards from the last trading day of the month as follows: The last trading day of the month is TDM -1, the next to last day is TDM -2 and so on.

Here are the Trading Days Best Missed:

*TDM 13 through TDM 16

*TDM -10 through TDM -5

Note that there is invariably some overlap between these two periods. For example, during September 2017 TDM -10 through -5 extended from 9/18 through 9/25 while TDM 13 through 16 extended from 9/20 through 9/25.

Still, there is no “guesswork”. One simply counts the trading days for a given month – backwards and forwards – and notes the “seasonally unfavorable” days as days to avoid the stock market.

The Test

For our test we will hold the Dow Jones Industrial Average on all days that DO NOT fall between TDM 13 through 16 nor through TDM -10 through -5.

During those days we will hold cash, earning 1% interest per year.

Obviously, this “system” involves trading in and out every month. Is it worth it to trade so often?  Let’s look at the results and you can decide for yourself.

The Results

Figure 1 displays the growth of $1,000 invested in the Dow Jones Industrials Average ONLY on the “bad days” spelled out above since 1945.1Figure 1 – Growth of $1,000 invested in DJIA ONLY during TDM 13 through 16 and TDM -10 through -5; 12/31/1945-10/30/2017

Figure 2 displays the growth of $1,000 invested in the Dow Jones Industrials Average all days NOT included in the bad days spelled out above (blue line) versus $1,000 invested in the Dow on a buy-and-hold basis (red line). 2Figure 2 – Growth of $1,000 invested in DJIA during all “not bad” days plus 1% annualized interest when out of the market (blue line) versus buying-and-holding (red line); 12/31/1945-10/30/2017

For the record:

*Buying and holding the Dow during ALL trading days since 1945 produced a gain of +12,003%

*Buying and holding the Dow ONLY during TDM 13 through 16 AND TDM -10 through -5 produced a loss of -82%

*Buying and holding the Dow ONLY during all other days produced a gain of +81,661% (or 6.8 times that of buy-and-hold)

Summary

Most investors are not enamored with the idea of trading in and out of the stock market each and every month.  Which I get.  Still, the relevant question is “If you knew in advance when a bad day was coming (psst, in terms of the stock market, the results presented here suggest that maybe we do), would you do something about it?”

It’s a fair question.

Jay Kaeppel

Disclaimer:  The data presented herein were obtained from various third-party sources.  While I believe the data to be reliable, no representation is made as to, and no responsibility, warranty or liability is accepted for the accuracy or completeness of such information.  The information, opinions and ideas expressed herein are for informational and educational purposes only and do not constitute and should not be construed as investment advice, an advertisement or offering of investment advisory services, or an offer to sell or a solicitation to buy any security.