($SPY) The most clever rug pull I’ll ever witness

It’s not everyday (let alone even on a monthly basis) I feel necessary to post a blog & give an update on the market for any type of short-term event. That being said, I felt the need for a few reasons. First reason being redemption, & I say that because on 01/23/2020, I saw the < -3% selloff coming. Don’t get me wrong, by 01/22/2020 I knew we had DP prices for $SPY that needed to get filled > our ATH @ the time ($333.41 to get filled, while ATH @ time was $332.95). Even with a selloff coming, I gave it < 2 weeks for a new ATH to come, & from the looks of what historical data was saying, a -2% decline would’ve been around the worst of it. 01/22/2020 marked the first time I saw a $ price > ATH’s that took > 12 days to get filled. Not only that, but the selloff was also the most significant out of other occasions my program has seen a $ price > than a current ATH. Out of the few times, where either a high range or a $ price prints that happens to be > than $SPY’s ATH, and the the difference in $ terms is too extreme to expect it to get filled quickly, the next part of the process is a buyable dip of  -1.5% on average. Historically, it hasn’t taken long after that selloff that, a new ATH is made, and the $ price becomes “filled”. 06/20/2019 was a perfect example, high range of $297.11 shows up, (ATH @ time is $296.30, following 5 day % return is around -2%).    

Now, without going too far into detail about all that, lets get to the redemption part of this, because it’s not often you see a Friday $500 OTM yolo turn into ……. $28,000.. I mean, I did call it. It was textbook type tuff. Trade of a lifetime though.

…………..best…………….

…………………………..trade………………….

……………………………………………I’ve………………..

……………………………………………………..never.made

but f* it

It may seem off topic, but the introduction for the -1.5% day we had on 01/24/2020 is important. Throughout the day, I run a script analyzing so many (custom) variables to get an idea as to how current day’s data correlates to other historical day(s) data. Kudos to any quants that’ve created their own intra-day pattern recognition program, but this is nothing like it. Out of 15 different variables, including some of the basics (% chg from open, avg vol per min, etc.,) it’s generally easy to pull up a chart of any historical day from 2018/2019/early 2020 and compare it to whatever price action is for the current day. That typically only paints half a picture, but an ideal case would be to see multiple compariosns that all point to the same type of price action. Here’s an example of what those variables would look like by EOD for 02/14/2020:

Before I tie things together, it’s important to reference the intro of how scenarios work, what they mean for short/long-term trends, & the correlation between extreme events. If you’re like me, you can vividly remember the bull trap from 12/03-12/04/2018. Before you finish reading, now might be a good time to pull up a chart of $SPY and take a peep @ the following dates to see the significance.

• 10/18/2018
• 10/24/2018
• 11/14/2018
• 12/04/2018
• 01/24/2020
• 02/14/2020

In the chart below, in case you couldn’t tell, the dates above are highlighted by red arrows. For the longer-term perspective, I felt it necessary to throw out the plain & simple fact trend is still in a bull run (& in $SPY’s case, there’s still a $338.76 price that needs to get filled, I’m expecting it to get filled before the first week of March 2020).

By 01/22/2020, I knew $SPY had a new ATH to fill ($333.41). Did it have to get filled by week’s end? No. Is there a chance we selloff -2% like 06/20/2019? Maybe take 2 weeks for that situation to play out? Sure. By 01/23/2020 I had a feeling the new ATH wouldn’t be made, & I was prepared to see a -2% decline over the following few trading days, I was also ready to start buying the dip; who wouldn’t if you knew fresh ATH’s would be made before the month was over? Skip to 01/24/2020, we selloff -1.5%. After going over the EOD data, I was shook. Expectant of the selloff, I was obviously short, & I knew there wasn’t any reason to have weak hands throughout the day. What I wasn’t expecting was the significance of the panic selling we saw; I’m not talking about the panic selling you see in a chart, or a fat candle w/ plenty of volatility, I’m talking about panic selling leaking through the data I look through daily. The most surprising part of it all? 02/14/2020 topped 01/24/2020. Yet, $SPY closed +.04%. This past Friday, yet we saw the MOST panic I’ve ever recorded. Every one of those dates mentioned, notice anything about them..? Each one of those red dots on the chart above have massive intra-day declines, & we had more selling this past Friday than every one of them. At one point, I couldn’t even find accurate scenarios based on Fridays data, why? Because the first step to finding scenarios with the least amount of noise possible, is to first filter only comparisons using a % chg from the open, from there – variables are clustered & filtered for the best / most adequate results.The reason scenarios were nowhere near as accurate was due to the fact that we had printed a new ATL for a unique variable that gives significance to the selloffs in each of the dates mentioned above.

 So, in case you’re wondering how any of those massive selloffs correlate to this past Friday.

Let’s put this simply.  The amount of panic selling the market ($SPY) has seen on days where we’ve sold off < -1%, just from the open, we saw M.O.R.E on Friday Feb 14th, 2020. Again, we closed +.04%. How miraculous, no? It’s amazing to see something so extreme as an ATL QRS Index print, with no selloff. Let me reiterate, although there’s no flaw/inconsistency/hiccup in the data I look at. When you put 2 & 2 together, I built the narrative that, not only is a rug about to disappear like a table cloth below dinner plates, but the entire floor is about to deteriorate. I’m not talking “bear market” scenario (yet), because I know first-hand, $SPY is going to kiss $338.76 before anything drastically bearish happens. I’d rather explain with data than exaggerate, so, I’ll leave it to the scenarios listed.

If you have the time/effort/curiosity to analyze the picture yourself & compare column by column to get to your own conclusion on which is the best match, knock yourself out. I’ll wrap this up with a few of my own notes to break a few things down.

1. Bottom list, 02/14/2020 is ONLY comparison w/ negative QRS index to NOT close < -1% from the open (ChgO column)
2. ALQ, VSR,  (“Avg Liquidity Change”, “Volumn sneakR Ratio”). ALQ for 02/14/2020 #1 lowest in all comparisons for bottom list, obviously, volatility wasn’t present. Only date in list w/ a close comparison is 01/24/2020. VSR, same thing. High VSR = higher volume = higher volatility. 12/02/2019, 01/24/2020 are only ones in the same arena as the VSR for 02/14/2020.
3. SS (“sneakR Sum”) (Note: QRS Index is based on “SS”). Only 2 other comparisons in bottom list have sneakR sums >= 10k, 12/04/2018 and 12/02/2019. Out of those 2, 12/04/2018 is the only one with a QRS Index < 0, 12/04/2018 is also the 2nd lowest QRS index printed by 4PM, next to 02/14/2020.
4.   If only using volume & % chg from open, 09/26/2018 is a close one to take into consideration. But the avg QR (“qratio”, also tied to QRS Index) is the farthest off in distance wise, & typically, avgQR matches are only “close” matches if the distance between 2 comparisons are extremely small. Another anomoly would be the ALQ, where 09/26/2018 has much higher market expectations vs 02/14/2020 looking like someone about to get caught w/ their pants down (no expectation of volatility).

In conclusion, I’m looking forward to perma-bearing the fuck out of this next week before a new ATH is made. Thanks for coming to my TED talk.