מדד S&P 500לונג
SPY/SPX: Top's probably not in.
מעודכן
Hey everyone,
Excited to do this post. This is a new approach to looking at things that I found super insightful and excited to share my findings with the community!
As the title suggests, the top is likely not in. How can we know this? Well, besides the very obvious bullish price action and the fact that buyers won’t let anything drop 1$ without aggressively buying, there are other, more objective ways to measure tops and such.
One approach that many would use would be using the ATR range. However, ATR ranges are a little flawed, especially when looking at larger picture stuff (like annual levels). This is because ATR has limitations, such as:
a) It is not inflation adjusted,
b) It requires a moving average of at least 14 periods, which, in some cases, are beyond the stock’s life time,
c) Is a trailing average that does not correct for bearish years and bullish years. Thus, the results are skewed if bearish years fell within the ATR trailing range.
You can correct for this by doing what I do, which is creating models that look at the entire life span of a stock and correct for bullish and bearish years. However, this also has some limitations, some of the same as ATR, such as:
a) Over-correcting for Bullish and Bearish years,
b) Insufficient history on most stocks to have a very rigorous model,
c) Difficulty accounting for fundamental and other economic catalysts. Models tend to be unbiased and so omit periods where economic circumstances propped stocks up or down.
So how can we account for this, simplify it and come up with useable data?
Well, the easiest way to do it, is to do a cross between an ATR and a model, using scaled data (to control for inflation) and looking at ATR of the scaled data and comparing current moves to averages as well as other times where there were similar economic and fundamental circumstances.
To do this, we can use stats software such as R, SPSS, SAS, Excel or MATLAB, pull the data, standardize it and get our results. Let us do this for SPX, as it has more history.
Here we have SPX’s annual returns. Converting the Close to Open difference to a percent return is a simple way of standardizing data. Now, on its own, this doesn’t tell us much, because returns are dynamic and ever changing, influenced by a combination of fundamental, economic and investor sentiment catalysts. However, we can begin to make sense of things if we start applying some concepts of ATR, most notably if we take the average gains the SPX does in a year. Doing this, we get 6% average annual return since the 1800s. However, if we isolate for ONLY bullish years, or years where SPX’s gains were >0, our average becomes 16%.
Currently, SPX is at a 14% gain on the year. We can hone in a bit more, by isolation SPX’s Max gain. Doing this, we see that SPX’s biggest gain in 1 year happened in 1933, when it gained 46%.
How about normal, bull market years?
To figure this out, the easiest way is to rank the data from highest to lowest or lowest to highest. Then, we can take the mean, median and mode of the ranked data. We already have the mean, which is 16%, but with ranked data we can get the median and mode.
First, the mode. Remember, mode is the value that occurs the most frequently. For SPX, the mode is interestingly enough 14%. Which means, of all of SPX’s bullish years, more times than not they ended at a 14% gain.
Now for the median. Remember, the median is the middle value of ranked data. And surprise! Its also 14%!
Its difficult to interpret what this could mean. It does tell us that we don’t have a perfect, normal distribution, because, despite the median and mode being the same, the mean is not the same (remember its 16%). But, it is close!
So what does this tell us?
Before we make inferences about this data, I think its important that we look at a few other things first. Most notably, the standardized version of the high to low value. The gains that we have looked at only represent the open to close. However, very rarely if ever has SPX ever closed on a high or low. So we would anticipate, looking at the actual range from high to low, we would get some different values. So let’s take a look at this on SPX’s bullish years:
Looking at this, the average high to low is 25%. Currently, SPX is sitting at 16%. Exciting right? This is very far from where we are now!
The MAX High to Low percent was 121% and the min was 4%. The max happened in 1933, the same year that the SPX gained a whopping 46%. For interest sake, let’s rank this data from low to high and calculate the median and mode. Doing this gives us the following:
The mode is 15% and the median is 24%.
So how can we use this data to make predictions about SPX? Well, we can actually calculate the targets based on the average of these values. So let’s get into it.
Assuming that SPX is going to close at the average, between 14% and 16%, that would convert to a price target of 5409.53 - 5504.43. So, provided this is a bullish year (which it looks like it will be), we can expect our close to fall somewhere between 5400 and 5500, which is the average closing range of bullish years.
However, SPX is still trailing below the expected high to low range, with an average range of 25% which is also the median (roughly). So with SPX’s YTD low of 4682.11, that would convert to a high of 5852.64.
I don’t want to make this post too long, but I have replicated this with SPY as well and here is the data in a nutshell:
SPY’s average gain on bullish years is 18%.
SPY’s average high to low range on bullish years is 29%.
SPY’s current gain on the year is 15%, and SPY’s current high to low range on the year is 16%. This gives the following price targets on SPY:
Expected close (assuming we close at the annual average): 557.15
Expected High (assuming we meet the average high to low range): 601.67.
One final note about SPY, interestingly, SPY’s largest gain was in 1995 at the start of the tech bubble where it gained a whopping 35%! Imagine SPY closing this year around 637.42?! Unthinkable! But .. possible?
This is not trading advice, just trying to put things into perspective for people. I see a lot of short biased ideas continually popping up. For us to meet the average high to open range by selling, would require a HUGE tank from this position. I find the most likely and realistic is a continuation up from here to meet the average move.
Safe trades everyone!
Excited to do this post. This is a new approach to looking at things that I found super insightful and excited to share my findings with the community!
As the title suggests, the top is likely not in. How can we know this? Well, besides the very obvious bullish price action and the fact that buyers won’t let anything drop 1$ without aggressively buying, there are other, more objective ways to measure tops and such.
One approach that many would use would be using the ATR range. However, ATR ranges are a little flawed, especially when looking at larger picture stuff (like annual levels). This is because ATR has limitations, such as:
a) It is not inflation adjusted,
b) It requires a moving average of at least 14 periods, which, in some cases, are beyond the stock’s life time,
c) Is a trailing average that does not correct for bearish years and bullish years. Thus, the results are skewed if bearish years fell within the ATR trailing range.
You can correct for this by doing what I do, which is creating models that look at the entire life span of a stock and correct for bullish and bearish years. However, this also has some limitations, some of the same as ATR, such as:
a) Over-correcting for Bullish and Bearish years,
b) Insufficient history on most stocks to have a very rigorous model,
c) Difficulty accounting for fundamental and other economic catalysts. Models tend to be unbiased and so omit periods where economic circumstances propped stocks up or down.
So how can we account for this, simplify it and come up with useable data?
Well, the easiest way to do it, is to do a cross between an ATR and a model, using scaled data (to control for inflation) and looking at ATR of the scaled data and comparing current moves to averages as well as other times where there were similar economic and fundamental circumstances.
To do this, we can use stats software such as R, SPSS, SAS, Excel or MATLAB, pull the data, standardize it and get our results. Let us do this for SPX, as it has more history.
Here we have SPX’s annual returns. Converting the Close to Open difference to a percent return is a simple way of standardizing data. Now, on its own, this doesn’t tell us much, because returns are dynamic and ever changing, influenced by a combination of fundamental, economic and investor sentiment catalysts. However, we can begin to make sense of things if we start applying some concepts of ATR, most notably if we take the average gains the SPX does in a year. Doing this, we get 6% average annual return since the 1800s. However, if we isolate for ONLY bullish years, or years where SPX’s gains were >0, our average becomes 16%.
Currently, SPX is at a 14% gain on the year. We can hone in a bit more, by isolation SPX’s Max gain. Doing this, we see that SPX’s biggest gain in 1 year happened in 1933, when it gained 46%.
How about normal, bull market years?
To figure this out, the easiest way is to rank the data from highest to lowest or lowest to highest. Then, we can take the mean, median and mode of the ranked data. We already have the mean, which is 16%, but with ranked data we can get the median and mode.
First, the mode. Remember, mode is the value that occurs the most frequently. For SPX, the mode is interestingly enough 14%. Which means, of all of SPX’s bullish years, more times than not they ended at a 14% gain.
Now for the median. Remember, the median is the middle value of ranked data. And surprise! Its also 14%!
Its difficult to interpret what this could mean. It does tell us that we don’t have a perfect, normal distribution, because, despite the median and mode being the same, the mean is not the same (remember its 16%). But, it is close!
So what does this tell us?
Before we make inferences about this data, I think its important that we look at a few other things first. Most notably, the standardized version of the high to low value. The gains that we have looked at only represent the open to close. However, very rarely if ever has SPX ever closed on a high or low. So we would anticipate, looking at the actual range from high to low, we would get some different values. So let’s take a look at this on SPX’s bullish years:
Looking at this, the average high to low is 25%. Currently, SPX is sitting at 16%. Exciting right? This is very far from where we are now!
The MAX High to Low percent was 121% and the min was 4%. The max happened in 1933, the same year that the SPX gained a whopping 46%. For interest sake, let’s rank this data from low to high and calculate the median and mode. Doing this gives us the following:
The mode is 15% and the median is 24%.
So how can we use this data to make predictions about SPX? Well, we can actually calculate the targets based on the average of these values. So let’s get into it.
Assuming that SPX is going to close at the average, between 14% and 16%, that would convert to a price target of 5409.53 - 5504.43. So, provided this is a bullish year (which it looks like it will be), we can expect our close to fall somewhere between 5400 and 5500, which is the average closing range of bullish years.
However, SPX is still trailing below the expected high to low range, with an average range of 25% which is also the median (roughly). So with SPX’s YTD low of 4682.11, that would convert to a high of 5852.64.
I don’t want to make this post too long, but I have replicated this with SPY as well and here is the data in a nutshell:
SPY’s average gain on bullish years is 18%.
SPY’s average high to low range on bullish years is 29%.
SPY’s current gain on the year is 15%, and SPY’s current high to low range on the year is 16%. This gives the following price targets on SPY:
Expected close (assuming we close at the annual average): 557.15
Expected High (assuming we meet the average high to low range): 601.67.
One final note about SPY, interestingly, SPY’s largest gain was in 1995 at the start of the tech bubble where it gained a whopping 35%! Imagine SPY closing this year around 637.42?! Unthinkable! But .. possible?
This is not trading advice, just trying to put things into perspective for people. I see a lot of short biased ideas continually popping up. For us to meet the average high to open range by selling, would require a HUGE tank from this position. I find the most likely and realistic is a continuation up from here to meet the average move.
Safe trades everyone!
עסקה פעילה
I suspect we see how this is playing out, huh? 
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