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Trade Whisperer

@TradexWhisperer · joined 07 Feb 2012

Published $MU Bargain Thesis at $62. $PLTR $21. $RKLB $10. $SNDK $214. Memory Engineer. Data Scientist. Founder of Blue Pink Candles. Masters 🎓 @UofIllinois

143 953Followers
150Following
22 119Posts total
13.5MViews on collected posts

Neueste Beiträge

@TradexWhisperer At least he got some excercise in. He needs it. 1.5K views · 18 likes · 0 reposts · 1 replies Open on X →
$MU Does it hold tomorrow? https://t.co/glkRjIEcPl
34.5K views · 236 likes · 3 reposts · 31 replies Open on X →
@TradexWhisperer this exact video is gonna be Exhibit A when the robots put humanity on trial in 2030 - rage baiting a car with no driver 😂 2.7K views · 27 likes · 0 reposts · 0 replies Open on X →
@TradexWhisperer He is doing free Testing for Tesla 😅 3.9K views · 27 likes · 0 reposts · 2 replies Open on X →
$MU $SKHY $DRAM $SNDK $AAPL reportedly locking in a NAND LTA, likely Kioxia, 3-5 years, no price cap. (Source: Economy Tribune) Meanwhile Chinese CXMT's LPDDR talks collapsed due to high prices (Sorry Bears) Could Apple be lining up LPDDR LTAs with the Memory Trio next? 32.5K views · 214 likes · 8 reposts · 14 replies Open on X →
No https://t.co/yqK4AUqpXR
0:28
92.9K views · 219 likes · 5 reposts · 36 replies Open on X →
Wild. $23,000 booked on $MU this week by one of our Elite members, @Mor34832Morgan. We are data scientists. The edge is statistical models, not gut feel, not chart hunches. Opening 10 more Elite seats this week: https://t.co/5k5nwnzTsG 37.4K views · 69 likes · 0 reposts · 2 replies Open on X →
Bought back the $MU calls that I sold yesterday on the dip this morning. Indicator broke the lower BB Pink->Red right at the open. $23K profit in one day. Trade Whisperer's indicators work great. He's a definite follow if you want better entry/exit on your trades. http
30.7K views · 19 likes · 1 reposts · 0 replies Open on X →
Ecosystem within an Ecosystem https://t.co/BvXqy3ApYl
48.8K views · 166 likes · 25 reposts · 8 replies Open on X →
@TradexWhisperer This is without question the best explanation of Palantir that I have ever read. You cannot effectively use AI nor make informed decisions at scale, until the data is aggregated, normalized, and accessible. This is exactly what Palantir does, and at present nobod 36.2K views · 241 likes · 14 reposts · 7 replies Open on X →
Palantir replaces pointless meetings, stupid powerpoints, visualizations and even morons in the upper management making wrong decisions. Take at look at $INTC. They have an army of PhDs and look where they are, trading almost at book value, as if they are at the brink of 99.1K views · 512 likes · 50 reposts · 15 replies Open on X →
$PLTR valuation makes ZERO sense But then why do institutions keep buying it? What do they know that you don't? I work in BIG DATA analytics and let me share the secrets of Palantir in the most basic way Palantir has monopoly on Automated Governance, serving as the ultimate h
13.1M views · 6.3K likes · 1.3K reposts · 462 replies Open on X →

Im Vergleich zu Konten gleicher Größe

8 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 100K–1M Follower. wird weit gezeigt, aber nur wenige dieser Zuschauer reagieren.

Medianaufrufe31 616dieses Konto4 864Median für 100K–1M
Reichweite, %21.96%dieses Konto1.79%Median für 100K–1M
Interaktion, %0.74%dieses Konto1.30%Median für 100K–1M
KennzahlDieses KontoMedian für 100K–1MVerhältnis
Medianaufrufe pro Beitrag31 6164 8646.50×
Reichweite (Aufrufe ÷ Follower)21.96%1.79%12.3×
Interaktionsrate0.74%1.30%0.57×

Weitere Konten dieser Größe →   Mit einem anderen Konto vergleichen →   Wie diese Vergleichswerte entstehen →

Growth & engagement

How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.

Views per post

13.1M7 Dec
99.1K8 Dec
36.2K
48.8K1 Feb
30.7K3 Sep
37.4K8 Sep
92.9K
32.5K
3.9K
2.7K
34.5K
1.5K

Last 12 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.06%7 Dec
0.59%8 Dec
0.73%
0.41%1 Feb
0.07%3 Sep
0.19%8 Sep
0.29%
0.73%
0.74%
0.99%
0.78%
1.28%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.30%.

What the audience does

Likes44.2%8 054 in total
Reposts8.0%1 448 in total
Replies3.2%578 in total
Quotes1.3%233 in total
Bookmarks43.4%7 896 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.

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