Trader (equities, FX, crypto). Behavior specialist. To join Matrix trading community: https://teapaw.org/t.co/gggoC51BqD
Joined July 2019
- Tweets22.3K
- Following132
- Followers31.5K
- Likes5.5K
Pinned Tweet
tradethematrix.net
Blog content on topic of trading, financial markets and macro.
$CKX 20 mil market cap company with 800k yearly revenue but gets 1 bil equity investment. What am I missing, where is this going to be consumed on?
Gonna be so right on this, and the post gets 0 action. Shows you most have no read on the rig and US public is sleep walking into turbolence.
Took me few years of consistent posting to get many SC traders on board that smallcaps indeed are rigged.
I dont have enough time to get many on board with this, assuming we are very close to events coming online.
A good chance this sequence of events follows:
-investigations find tons of irregularities
-election results get invalidated
-mass riots across US
-insurection act gets evoked
If so (some) people will learn for first time that #elections are rigged.
There is no way to inspect source code of Gemini so you can never know what AI is told to tell by truth and what not. Yet billions will use it. A way cheaper tool of indoctrination than using human beings to spread lies when macro riggers need it so.
What i wrotte in my 4th turning articles over past two years is that once 4th turning goes global they will start to target our electrical/water/food supply infrastructure. What do you think those actions at BBC are for. Its for that-grid down.
A good chance this sequence of events follows:
-investigations find tons of irregularities
-election results get invalidated
-mass riots across US
-insurection act gets evoked
If so (some) people will learn for first time that #elections are rigged.
For the truth seekers out there: How do you catch #AI lying and what specifically to focus on?: ---Contradictions.---
When first answer is completely contradicted by answer number 2 thats your go to. And if you keep asking it and every next answer contradicts validity or construct of prior one (each time with added new key focus variable) you are digging into truth hole.
AI almost NEVER admits defeat if you ask it about subjects of government sponsored or rig inc agendas. Never. It is programmed to always find another route of explanation. I have performed by now thousands of promts or subquestions. It just very rarely gives up.
You need high certainty that what you are asking it you are probably right and you have researched it deeply. And then if it keeps contradicting itself in the answers (focus on the details) its likely trying to deceive.
Keep in mind. Most AI code is NOT open source. You have no idea what it is meant to answer truthfully and what subjects not.
Garner is great actress but its very sus they give her roles which promote (and glorify) mass scale thieves (inventing Ana and now this), both of those two real life characters were installed by global rig inc (long story to explain).
So...is there a hidden twist to her? Or maybe its nothing and its just personality fit for such roles. But usually when there is a smoke there is a fire more likely.
If there was internal rig on financing of illegal voters to vote for X side and you wanted to hide the tracks/footprints, an attack as such would be launched.
(Again i am not suggesting either side did it, its the middle man financing both sides more likely).
BREAKING EXCLUSIVE: FEC Gets Hacked, Goes Dark for 41 Hours During Early Voting with No Proof of Containment joehoft.com/breaking-exclusi…
Also if you see this guy outperforming all other funds while everyone is red (like we see many funds lately) thats not a good sign. Last time that happened was 2008 with shitstorm following.
$SPY shorts over past two days. One cut today but the rest of trades delivered decent. Its hindsight now but should have been mixing in some 0DTE puts too.
This would be another better example how to properly structure backtest with meaningful output:
teapaw.org/Valckrie/status/211849…
Notice that there is significant cluster of such samples around crisis environment even if there is slight recovery after many of those drops (using my data example on prior post), since equity indexes when they decline they dont go straight down usually its a zig zag motion with fake recovery pullbacks.
Those kind of posts show you many in financial markets dont know how to gather valuable stat data. Poorly structured test gives you noise.
I have rephrased the question that initial poster has made to AI by adding or changing two variables. -1.One is explain the macro context behind situations when there is no reclaim of initial selloff and when there is.
-2.And another variable- instead of looking for what happens the next day after initial selloff we look whether in next 10 trading days the selloff is completely reclaimed. Because if market is still healthy that should happen. And if there are broad macro issues under the hood it wont, it will go down. What initial poster did is useless as data will be close to noise because time interval is too short and has no correlation to macro outlook because of it.
Even the results that were given from my sub question are 50 50. -But here is the catch...what truly matters is knowing the macro environment. Are there bubble deflation characteristics, is there geopolitical friction, is there inflation rising etc.
Its exactly that which then needs to provide decision for discretionary market participant what to make out if this heavy selloff. Because since statistical data is closely positioned to 50 50, our final conclusion is all it matters and is heavily dependent on macro insight.
This is why in my view data or any variable needs an attachment to another (or multiple) variables to have valuable insight. One variable being short term and others long term or one smaller and another bigger. Never isolate just by looking one variable because it will be noise. All single variables can be extremely easily programmed into algos and turned into money makers if there were 80% consistent, but there is a reason why in markets most isolated variables will be near 50 50 distribution.
$QQQ $SPY #trading
Those kind of posts show you many in financial markets dont know how to gather valuable stat data. Poorly structured test gives you noise.
I have rephrased the question that initial poster has made to AI by adding or changing two variables. -1.One is explain the macro context behind situations when there is no reclaim of initial selloff and when there is.
-2.And another variable- instead of looking for what happens the next day after initial selloff we look whether in next 10 trading days the selloff is completely reclaimed. Because if market is still healthy that should happen. And if there are broad macro issues under the hood it wont, it will go down. What initial poster did is useless as data will be close to noise because time interval is too short and has no correlation to macro outlook because of it.
Even the results that were given from my sub question are 50 50. -But here is the catch...what truly matters is knowing the macro environment. Are there bubble deflation characteristics, is there geopolitical friction, is there inflation rising etc.
Its exactly that which then needs to provide decision for discretionary market participant what to make out if this heavy selloff. Because since statistical data is closely positioned to 50 50, our final conclusion is all it matters and is heavily dependent on macro insight.
This is why in my view data or any variable needs an attachment to another (or multiple) variables to have valuable insight. One variable being short term and others long term or one smaller and another bigger. Never isolate just by looking one variable because it will be noise. All single variables can be extremely easily programmed into algos and turned into money makers if there were 80% consistent, but there is a reason why in markets most isolated variables will be near 50 50 distribution.
$QQQ $SPY #trading
Every single day $QQQ dropped 6% or more since its March 1999 inception, 30 total including today, and what happened at the next session's close:
𝟸𝟶𝟶𝟶-𝟶𝟷-𝟶𝟺: −𝟼.𝟾𝟼%, Next day: −𝟸.𝟻𝟻%
𝟸𝟶𝟶𝟶-𝟶𝟷-𝟶𝟼: −𝟼.𝟾𝟽%, Next day: +𝟷𝟸.𝟹𝟽%
𝟸𝟶𝟶𝟶-𝟶𝟺-𝟷𝟶: −𝟼.𝟷𝟶%, Next day: −𝟸.𝟹𝟽%
𝟸𝟶𝟶𝟶-𝟶𝟺-𝟷𝟺: −𝟾.𝟼𝟼%, Next day: +𝟷𝟷.𝟻𝟷%
𝟸𝟶𝟶𝟶-𝟶𝟻-𝟷𝟶: −𝟽.𝟸𝟽%, Next day: +𝟼.𝟷𝟷%
𝟸𝟶𝟶𝟶-𝟶𝟻-𝟸𝟹: −𝟾.𝟹𝟻%, Next day: +𝟼.𝟸𝟽%
𝟸𝟶𝟶𝟶-𝟶𝟿-𝟸𝟷: −𝟽.𝟸𝟽%, Next day: +𝟻.𝟿𝟷%
𝟸𝟶𝟶𝟶-𝟷𝟷-𝟶𝟾: −𝟽.𝟾𝟸%, Next day: −𝟶.𝟶𝟸%
𝟸𝟶𝟶𝟶-𝟷𝟸-𝟷𝟿: −𝟽.𝟼𝟸%, Next day: −𝟻.𝟽𝟹%
𝟸𝟶𝟶𝟷-𝟶𝟷-𝟶𝟸: −𝟾.𝟺𝟼%, Next day: +𝟷𝟼.𝟾𝟺%
𝟸𝟶𝟶𝟷-𝟶𝟷-𝟶𝟻: −𝟽.𝟼𝟻%, Next day: +𝟷.𝟷𝟶%
𝟸𝟶𝟶𝟷-𝟶𝟸-𝟸𝟽: −𝟼.𝟶𝟺%, Next day: −𝟹.𝟷𝟼%
𝟸𝟶𝟶𝟷-𝟶𝟹-𝟶𝟿: −𝟽.𝟶𝟷%, Next day: −𝟼.𝟸𝟷%
𝟸𝟶𝟶𝟷-𝟶𝟹-𝟷𝟸: −𝟼.𝟸𝟷%, Next day: +𝟻.𝟶𝟾%
𝟸𝟶𝟶𝟷-𝟶𝟹-𝟸𝟶: −𝟼.𝟽𝟹%, Next day: 𝟶.𝟶𝟶%
𝟸𝟶𝟶𝟷-𝟶𝟹-𝟸𝟾: −𝟾.𝟸𝟷%, Next day: −𝟷.𝟾𝟿%
𝟸𝟶𝟶𝟷-𝟶𝟺-𝟶𝟹: −𝟽.𝟹𝟹%, Next day: −𝟷.𝟽𝟼%
𝟸𝟶𝟶𝟷-𝟶𝟺-𝟸𝟹: −𝟼.𝟽𝟷%, Next day: −𝟷.𝟾𝟾%
𝟸𝟶𝟶𝟷-𝟶𝟿-𝟷𝟽: −𝟾.𝟻𝟶%, Next day: −𝟸.𝟸𝟺%
𝟸𝟶𝟶𝟷-𝟷𝟶-𝟷𝟽: −𝟽.𝟷𝟾%, Next day: +𝟸.𝟽𝟷%
𝟸𝟶𝟶𝟾-𝟶𝟿-𝟸𝟿: −𝟽.𝟿𝟺%, Next day: +𝟸.𝟾𝟾%
𝟸𝟶𝟶𝟾-𝟷𝟶-𝟶𝟽: −𝟼.𝟹𝟺%, Next day: −𝟶.𝟾𝟶%
𝟸𝟶𝟶𝟾-𝟷𝟶-𝟷𝟻: −𝟾.𝟿𝟼%, Next day: +𝟻.𝟺𝟸%
𝟸𝟶𝟶𝟾-𝟷𝟸-𝟶𝟷: −𝟽.𝟻𝟸%, Next day: +𝟹.𝟹𝟺%
𝟸𝟶𝟷𝟷-𝟶𝟾-𝟶𝟾: −𝟼.𝟶𝟸%, Next day: +𝟺.𝟾𝟸%
𝟸𝟶𝟸𝟶-𝟶𝟹-𝟶𝟿: −𝟼.𝟿𝟻%, Next day: +𝟻.𝟺𝟻%
𝟸𝟶𝟸𝟶-𝟶𝟹-𝟷𝟸: −𝟿.𝟷𝟽%, Next day: +𝟾.𝟺𝟽%
𝟸𝟶𝟸𝟶-𝟶𝟹-𝟷𝟼: −𝟷𝟷.𝟿𝟾%, Next day: +𝟽.𝟻𝟾%
𝟸𝟶𝟸𝟻-𝟶𝟺-𝟶𝟺: −𝟼.𝟸𝟷%, Next day: +𝟶.𝟸𝟺%
𝟸𝟶𝟸𝟼-𝟷𝟷-𝟶𝟻: −𝟼.𝟺𝟿%, Next day: ???
Summary across all 29 prior instances:
- Full history, 1999 to 2025: 17 green, 1 flat, 11 red. Avg +2.67%, median +2.71%.
- Post-2008, 9 instances: 8/9 green, 89%. Avg +4.16%, median +4.82%.
- Since 2010, 5 instances: 5/5 green, 100%.
The safest mentality to #investing or #trading is always to assume anything can get rugged but especially...if prior to where price is now there was parabolic run.
Parabolic moves just love to rug regardless if its golds market cap size or some smallcap company.
