overview of 1-2% drop at open from previous SPY close

December 6, 2018

Adam Grimes has an interesting post on using statistics to map the trading day (https://adamhgrimes.com/using-statistics-to-map-the-trading-day/) .  Before the open today, I gathered the following data on the high, low when the SPY opened between 1 and 2 percent below the prior close (there were about 200 instances):

 

prior cls vs opn hgh vs opn low vs opn cls vs opn cls vs prior cls
0% -1.00% 7.17% 0.00% 5.54% 3.86%
10% -1.05% 2.81% -0.15% 1.99% 0.66%
20% -1.10% 2.05% -0.32% 1.24% -0.07%
30% -1.14% 1.68% -0.47% 0.79% -0.60%
40% -1.20% 1.41% -0.72% 0.33% -0.93%
50% -1.28% 1.23% -0.90% 0.02% -1.30%
60% -1.38% 1.06% -1.12% -0.44% -1.64%
70% -1.48% 0.87% -1.38% -0.83% -2.20%
80% -1.59% 0.47% -1.80% -1.25% -2.62%
90% -1.73% 0.24% -2.57% -1.82% -3.25%
100% -1.96% 0.02% -6.89% -6.54% -7.83%

It appears that today it opened down about 1.6% (80 percentile), fell another 1.31% (70 percentile), reversed and rose 1.52% (lets say 35 percentile), with a close up 1.47% from the open (~15 percentile) with a slight negative close of -.15% ( ~ 25 percentile).

So, while there was fairly wide swings, today wasn’t totally out of line other days with 1-2 percent drops from opening.  the median down would have been only -.9% lower than the open and 1.23% up from the open for the high.   The more unusual behavior was that it ended near the highs of the day – more typically it closes near the open on days like today.

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S&P 500 Draw downs from All Time Highs

November 24, 2018

Rather than look at bull vs bear markets, I decided to look at draw downs from all time highs.  The top 25 draw downs (since 1950 using Yahoo! and other data, excluding the current draw down) are in the table below. A few observations:

  • The longest stretch was about 6.6 years between all time highs – 1973 through mid 1979, and that was preceded by one that was between 1969 and 1972. it was followed in 1980 (though 1982) with another 27% draw down.  1968 high (108.37) to the 1982 high that broke the draw down (142.46) was about a 2% compounded yearly gain – excluding dividends.
  • The two worst draw downs were in the 2000’s.
  • After you get past the top 4, the length of time between all time highs decreases noticeably – almost always than 2 years.
  • Draw downs over 20% only occurred 9 times in the past 68 years (although 44% of the time was in one of those draw downs).
  • typically,the low is before the middle of the time period.
drop between highs START low date END years
-56.78% 10/9/2007 3/9/2009 3/28/2013 5.5
-49.15% 3/24/2000 10/9/2002 5/30/2007 7.2
-48.21% 1/11/1973 10/3/1974 7/17/1980 7.5
-36.06% 11/29/1968 5/26/1970 3/6/1972 3.3
-33.51% 8/25/1987 12/4/1987 7/26/1989 1.9
-27.97% 12/12/1961 6/26/1962 9/3/1963 1.7
-27.12% 11/28/1980 8/12/1982 11/3/1982 1.9
-22.18% 2/9/1966 10/7/1966 5/4/1967 1.2
-21.47% 8/3/1956 10/22/1957 9/24/1958 2.1
-19.92% 7/16/1990 10/11/1990 2/13/1991 0.6
-19.34% 7/17/1998 8/31/1998 11/23/1998 0.4
-14.82% 1/5/1953 9/14/1953 3/11/1954 1.2
-14.38% 10/10/1983 7/24/1984 1/21/1985 1.3
-14.16% 5/21/2015 2/11/2016 7/11/2016 1.1
-14.02% 6/12/1950 7/17/1950 9/22/1950 0.3
-14.02% 8/3/1959 10/25/1960 1/27/1961 1.5
-12.08% 7/16/1999 10/15/1999 11/16/1999 0.3
-10.80% 10/7/1997 10/27/1997 12/5/1997 0.2
-10.59% 9/23/1955 10/11/1955 11/14/1955 0.1
-10.23% 10/9/1989 1/30/1990 5/29/1990 0.6
-10.16% 1/26/2018 2/8/2018 8/24/2018 0.6
-10.11% 9/25/1967 3/5/1968 4/29/1968 0.6
-9.76% 3/20/1956 5/28/1956 7/16/1956 0.3
-9.63% 2/18/1997 4/11/1997 5/5/1997 0.2
-9.60% 5/13/1965 6/28/1965 9/27/1965 0.4

Daily SPX moves when above vs below 200 day simple moving average

October 27, 2018

Eddy Elfenbein commented about the importance of the 200 day SMA when looking at volatility, so I decided to take a look.

First, I looked at the VIX when SPX above vs below the 200 day SMA – these are the median values for the past 20 or so years.   More recent periods have less volatility

vix when SPX below 200 day SMA 25.08
vix when SPX above 200 day SMA 15.68

Now looking at daily moves over the same time period:

% daily change when SPX median down up
 below  200 SMA 0.97% 1.07% 0.82%
 above  200 SMA 0.44% 0.40% 0.47%
all days 0.55%

I’m surprised at the results – the daily moves are twice as much when the SPX is below the 200 day SMA then when it is above the 200 day SMA.  Similar results if you look at the 100 SMA day, although the percentage moves are a little less (.88% vs .97%, .43% (100) vs .44%(200)).  If you look at the last 10 years or so:

% daily change when SPX median down up
 below  200 SMA 0.88% 1.12% 0.78%
 above  200 SMA 0.33% 0.29% 0.39%
all days 0.36%

I also find it interesting that when below the 200 day, the down moves are larger than then up moves, but above the 200 day, the up moves are typically larger than the down moves.

SPX – new 52 week high – where is the SPX a year later

October 1, 2018

I did an investigation of what happens a year later after the SPX has hit a 52 week high (intraday).  looking back from 1950

all once ever 20 days
down 369 62
up 1399 199
down 21% 24%
up 79% 76%
if down, avg down -8.69% -8.34%
if up, avg up 14.90% 14.29%

 

There were over 1700 new 52 week highs since mid 1950, and 20% of the time it was lower a year later, which leaves near 80% it being higher.  When it was lower, it averaged about 8.7% loss, nearly 15% gain when it was higher.  In order to reduce the occurrences of multiple days occurring in a group, I put in a test to only look at occurrences that had 20 trading days between highs (the third column) (meaning if there was an intraday high on days 1, 2, 15 and 21, I would only look at days 1 and 21 ).  In that case, the number of occurrences lower raised to 25%, but the average gain or loss was relatively close to the previous results.

the last 20 years

all once ever 20 days
down 86 13
up 463 69
down 16% 16%
up 84% 84%
if down, avg down -8.26% -10.09%
if up, avg up 11.83% 11.15%

Here the gain was less, but the percent of losing occurrences was down.

Finally, looking at all cases – for any given day, where was SPX a year later?  74% of the time it was higher, for an average gain of 16% (slightly better than if invested at all time high).   overall, the typical one year gain was around 8%.

down 4485
up 12509
down 26%
up 74%
if down, avg down -11.53%
if up, avg up 16.16%

looking over the past 20 years, the percent up/down were similar, but the percentage gain/loss were significantly different – -16.85% loss and only 14.85% gain.

Median Vix by month

September 17, 2017

based on YAHOO! data, this is the median monthly VIX values.  sub 11 values are rare, but they have happened before (eg November 2006-February 2007).  we have already surpassed  2006 for the most months with an  under 12 value.  in the fourteen years prior to 2005, there wasn’t a month with a VIX reading below 11, and this year we have had the most – going on four. 1995 was a relatively quiet year – 11 of the 12 months had a median of less than 13.  over all years, the average is 19.46, but the median is only 17.59.

17.59 1 2 3 4 5 6 7 8 9 10 11 12
1991 17.44 26.91 21.45 16.81 17.34 17.21 16.99 17.44 15.38 17.13 16.21 17.38 18.12
1992 15.36 17.63 17.37 16.85 16.48 15.05 14.72 13.47 14.48 13.63 17.06 14.37 12.26
1993 12.43 12.11 13.43 13.60 12.80 13.64 12.25 11.33 11.96 12.70 11.83 14.12 11.06
1994 13.86 11.27 13.91 14.87 16.61 14.08 13.13 11.82 11.97 13.25 15.13 16.29 13.03
1995 12.30 12.15 11.42 12.02 12.41 12.21 11.67 12.46 12.90 12.10 14.25 12.46 11.50
1996 16.25 13.45 14.74 17.79 16.41 16.01 16.73 17.87 15.67 16.16 16.26 15.85 18.85
1997 20.95 19.46 19.98 19.93 19.64 19.91 20.17 20.68 23.75 23.88 21.61 32.09 26.22
1998 23.14 23.44 19.87 19.31 21.96 20.66 21.70 18.44 30.33 37.90 34.08 27.19 25.17
1999 24.10 28.60 29.29 24.84 23.30 25.87 23.24 20.35 24.42 24.53 24.02 22.07 21.97
2000 23.24 22.93 23.41 22.37 27.02 25.87 21.73 19.79 17.87 19.68 24.98 26.62 26.71
2001 24.26 24.55 22.03 28.61 27.78 23.15 20.70 22.51 21.75 35.25 32.32 25.90 23.69
2002 26.39 22.25 22.37 19.07 19.69 20.06 24.83 33.97 32.98 37.47 34.09 28.17 28.29
2003 19.85 25.53 31.98 30.44 22.55 20.03 20.58 19.18 18.77 19.25 17.68 16.93 16.70
2004 15.33 16.12 15.90 17.87 15.62 18.13 15.19 15.68 16.22 14.06 15.05 13.30 12.55
2005 12.52 13.34 11.60 13.15 14.53 13.85 11.90 10.96 13.21 12.64 14.87 12.06 11.35
2006 12.00 11.94 12.36 11.58 11.75 13.88 16.53 14.90 12.41 11.97 11.15 10.83 10.85
2007 16.43 10.92 10.34 14.81 12.92 13.23 14.73 16.00 25.05 22.78 18.79 25.94 22.07
2008 25.10 25.43 25.33 26.32 21.43 18.18 22.42 24.14 20.65 31.70 62.90 61.43 53.32
2009 28.57 44.11 44.66 43.71 37.81 32.20 29.62 25.52 25.01 24.32 23.65 23.08 21.38
2010 21.71 19.16 21.71 17.69 16.62 31.66 29.23 24.88 25.44 22.51 20.21 19.55 17.58
2011 20.72 17.34 16.59 20.20 16.43 17.07 18.83 19.28 35.06 37.00 32.22 32.00 25.11
2012 17.52 20.54 18.19 15.54 17.77 21.65 21.11 17.50 15.32 14.84 16.13 16.65 16.81
2013 13.75 13.55 13.50 13.11 13.62 13.10 16.86 13.79 14.22 14.37 14.71 12.86 13.91
2014 13.67 13.28 14.51 14.52 13.82 12.42 11.59 12.02 12.42 12.88 16.53 13.33 15.30
2015 15.32 19.45 15.45 15.07 13.30 13.08 14.02 13.41 13.77 24.25 16.11 15.78 17.73
2016 14.31 23.95 21.75 15.87 13.96 14.69 17.81 12.85 12.38 13.48 14.24 13.72 12.22
2017 11.23 11.55 11.49 11.66 12.89 10.44 10.44 10.03 11.35 10.66 #NUM! #NUM! #NUM!

Some monthly behaviors for SPX

September 3, 2017

Looking at monthly performance of S&P 500 index (using Yahoo finance figures) since 1980, July and September have been the worst months of the year based on the percent that are down or the median gain(loss) of the month. On the other hand, September makes a low that is lower than the preceding August about one third of the time, unlike July which makes a lower low than the preceding June nearly half the time.

month months with gains since  1980 median gain low lower than prior month
1 61% 1.57% 39%
2 63% 0.91% 39%
3 63% 1.23% 38%
4 71% 1.05% 28%
5 68% 1.18% 38%
6 58% 0.08% 46%
7 47% -0.35% 47%
8 58% 0.54% 41%
9 46% -0.35% 34%
10 65% 1.81% 52%
11 70% 2.15% 30%
12 73% 1.26% 27%

SPX monthly ranges

September 5, 2016

The high low range of the SPX for the month of August 2016 was 2.1% (computed using Yahoo! data = (high – low)/open), the 9th smallest range since 1950 (800 months worth of data).  I was curious how it varied by month, and also what happens after a low range month. Over all months, the average range is 6.4%, with a median value of 5.6% and standard deviation of 3.5%.  If the month range was less than 3% (56 times out of the 800), then the next month’s average was 4.5%, median of 4.4% and standard deviation was 1.6%. So if this September 2016 is typical, there should be around a 100 point (+/-35 pts) range in the SPX.  While the bottom 10% of the month’s ranges seem to be around 3.2% (with standard deviation of .3%), the 90% value of the months is at 10.3% with a standard deviation of 2.3%.  October, with an average range of 8.2%, exceeds January (at 7%) by a hefty margin, although the median for October at 5.8% is slightly above all months (January at 6.3% comes in first).

monthly ranges for spx

 

average median std dev count 10.00% 90.00%
all 6.4% 5.6% 3.5% 800 3.2% 10.3%
after <3% 4.5% 4.4% 1.6% 56 2.8% 6.3%
January 7.0% 6.3% 3.3% 67 3.3% 11.5%
February 5.5% 5.0% 2.5% 67 2.9% 8.2%
March 6.1% 5.4% 3.6% 67 2.8% 8.7%
April 6.0% 5.3% 2.7% 67 3.6% 9.6%
May 6.1% 5.5% 3.2% 67 3.1% 9.2%
June 5.9% 5.2% 2.3% 67 3.1% 9.4%
July 6.3% 5.5% 3.1% 67 3.5% 10.2%
August 6.7% 5.9% 3.7% 67 3.2% 12.9%
September 6.6% 5.9% 3.2% 66 3.2% 10.3%
October 8.2% 5.8% 6.0% 66 3.3% 16.8%
November 6.8% 6.0% 3.7% 66 3.4% 10.3%
December 5.5% 5.2% 2.5% 66 2.6% 9.1%

5 day historical volatility by weeks of the year

August 14, 2016

5 day historical volatility
I did a quick study to see the how seasonal volatility was during the year. For this study, I looked at the standard deviation of the logarithm of the price changes for the prior 5 days, using only on the last trading day of the week for the chart. I used the SPX since 1994 from Yahoo! Finance. Here is a graph of the average, median, and top and bottom 25 percentile.  In the above change, 101 is week 1, which I am using as the week with the first Friday of the new year.  Overall, looking at the average (grey line) there is a slight downward slope from the end of January through July, then slight pick up through mid October, and then finally a slight fall until year end – except a bit of a bump around the first week in December.  The line for the bottom 25 percentile is fairly flat all year long, while the top 25% percentile has much more variability.

SPY vs USO – daily direction

April 9, 2016

I was curious about how often the direction (ignoring magnitude) was the same for USO vs SPY, using data from Yahoo!.  The chart below indicates, over a 10 day period, how often the two moved together.  The first set of data is the last 2500 days, second set tries to eliminate  overlaps and takes the every 10th data point, and the last column looks a back over the last 25o trading days (about 1 year).  For example, the direction (either up or down) being the same six times in the past 10 days happens about 21% of the time.  Overall there is a slight bias to going in the same direction.

DAYS 2500 2500 (EVERY 10) LAST 250
1 0.35% 0.00% 0.00%
2 1.60% 1.50% 2.40%
3 3.45% 3.50% 2.80%
4 7.90% 8.00% 8.40%
5 12.40% 11.00% 8.40%
6 21.05% 24.50% 18.80%
7 25.20% 23.00% 27.60%
8 20.00% 21.00% 24.80%
9 6.85% 7.00% 4.00%
10 1.15% 0.50% 1.60%

spy vs uso

SPY open – predictions on close

April 3, 2016

I was curious how the SPY performed based on comparing the open vs prior close. In particular, I was curious if the open was lower, what is the likelihood that the close would also be lower than the prior day’s close.  I grouped the differences into 3 groups, down > .1%, up > .1% and where the change was less than .1%.  Using Yahoo Finance, adjusted data, I found

 

 cls < prior cls  cls similar p cls  cls > prior cls
open < prior close 64% 6% 30%
 open unchanged  43%  10%  47%
 open > prior close  28%  4%  68%

each row is sums to 100%, so for the first row, if the open was more than .1% below the prior day’s close, then 64% of the time the close was also below the prior day’s close, 6% the change was less than +/- .1% and 30% the close was more than .1% greater than the prior day’s close.

I looked to see if being above or below some simple moving average made a difference, and there wasn’t too much, of the numbers I looked at the 100 day had the most impact.

below 100 SMA
62% 4% 34%
42% 6% 52%
30% 2% 68%
above 100 SMA
64% 7% 29%
43% 11% 46%
28% 5% 68%

The value of the Vix was slightly more significant, but the movement was generally from closing down for the day to closing unchanged (about 3% chance of unchanged with vix>24.9 vs 9% chance when the vix is < 13.25)

vix > 24.9 (about 20% of the time)
67% 3% 30%
46% 2% 52%
28% 2% 70%
vix < 13.25 (about 20% of the time)
59% 9% 32%
37% 11% 51%
29% 7% 65%

So, it appears that the market will close lower about 2/3 of the time if it opens lower, and similarly if it opens higher, about 2/3 of the time it will close higher.  Not surprisingly, a low VIX environment will have more little changed occurrences.