It is not a secret that the stock market tends to perform better during the end of month/beginning of month and middle of month periods than during the rest of the month. What is less known is that certain sectors tend to perform even better than the overall market during these time periods.
(See also Where NOT to Invest, Er, Soon (Part 1))
Jay’s Seasonal Health Care Strategy
As always, what follows is not a “recommended trading strategy”. It is presented solely as “food for thought” (or perhaps I should say “meds for thought”). Anyway, for illustrative purposes we will adopt an aggressive trading strategy as follows:
*We will use Health Care UltraSector ProFund (ticker HCPIX, which tracks the Dow Jones U.S. Health Care index using leverage of 1.5-to-1; so I the index rises 1% today the fund should rise 1.5%);
We will hold HCPIX ONLY on:
*The last 4 trading days of the month
*The first 2 trading days of the month
*Trading days numbers 9, 10, 11 and 12 each month
The rest of the time we will hold cash; For the purposes of this test, no interest is assumed to be earned while out of HCPIX
Figure 1 displays the hypothetical growth of equity using the approach.
For the record, $1,000 starting on 6/19/2000 grew to $20,995, or +1,999%.
Figure 2 displays the year-by-year results.
Figure 2 – Jay’s Seasonal Health Care Strategy Year-by-Year (6/19/00-5/13/16)
One question that invariably arises when talking about a specific seasonal approach such as this is, “What do I miss by being out of HCPIX the rest of the time?” Based on my own thorough analysis I believe the answer to that question is “Pain and suffering”.
Figure 3 answers the question of what would have happened to an initial $1,000 invested in HCPIX only during “all other days” besides the ones listed earlier.Figure 3 – Growth of $1,000 in HCPIX during all other trading days (6/10/2000-5/13/2016)
For the record, starting on 6/19/2000 (when HCPIX started trading):
*$1,000 invested only during the seasonally favorable periods grew +1,999% (to +$20,995)
*$1,000 invested only during all other days shrank -89% (to $111)
These are the kinds of disparities that we “quantitative types” refer to as “statistically significant”.