tokenLuxora

🌍 Sharing my journey through crypto, blockchain technology and the exciting world of Web3 innovation. ✨

[Blockonomi @blockonomi]

🚨 Bitcoin ETF inflows hit $90.44M on July 10 as BlackRock’s IBIT led the rebound.

Ethereum ETFs added $18.43M while BTC reclaimed $64K and tested the road toward $65K.

Is institutional demand returning for good?

📈 #Bitcoin #BTC #Ethereum #ETFs #Blockonomi

https://t.co/Fc2TDSAFf9

[Tron Inc. @TRON_INC]

Tron Inc. (NASDAQ: TRON) acquired 152,660 TRX tokens today at an average price of $0.3275 further increasing its TRX treasury holdings to more than 705.2 million TRX in total. The company aims to further grow its Tron DAT holdings to enhance long term shareholder value. For live update on the designated on-chain TRX treasury wallet for Tron Inc., please refer to: https://t.co/UYZgaRvn97.

[BitMart @BitMartExchange]

Is you team still in? 👀

[Wendy O @CryptoWendyO]

🚨 House Financial Services Committee to hold July 17 hearing to build support for the CLARITY Act and highlight its potential to support crypto innovation

[Liam Fountain @Liam_Fountain]

Worst Guns N' Roses cover ever

[Ayomi Shuga || $Numba1 @ShugaAyomi]

🎙️ Cardano Project Showcase || July Edition

I'm excited to announce that this month's Cardano Project Showcase will feature GameChanger Wallet @GameChangerOk ! 🎉

[CoinDesk @CoinDesk]

LATEST: Mizuho Financial Group downgrades Circle to underperform, cuts price target to $50, citing Open USD's yield pass-through model as a margin threat to $USDC reserves.

[Cred @CryptoCred]

As a lifetime retarded crypto investor I feel duty-bound to top blast and act as exit liquidity for all these upcoming tradfi IPOs

The expected value is quite reasonable:

If I’m right, I make money

If I’m wrong, then I just need to wait a year or two - I’ll get UBI and a personal robot giving me reacharounds and snacks while some dude in a San Francisco broom cupboard has to remotely view my disgusting body in 12-hour shifts for training data

Pretty good deal

[Gretchen von Tongeln @Metalligretch]

It would take a pretty stupid robot to replace me.

[Anthony Pompliano 🌪 @APompliano]

Now that inflation has peaked and started to fall, the doomsday predictors will have to find their next boogeyman to screech about.

[Cointelegraph @Cointelegraph]

🔥 UPDATE: Strategy says it will continue buying Bitcoin long term and aims to remain the world’s largest corporate $BTC buyer despite recent market volatility.

[Gates Foundation @gatesfoundation]

Don't have a red nose? That's ok! For every RT we'll donate $10 toward ending child poverty. #RedNose4Kids

[Satoshi Club @esatoshiclub]

.@okx stands out as the lowest-cost option among the MiCA exchanges compared.

Turning €1,000 into BTC and withdrawing it to your own wallet costs an estimated €2.44 on OKX.

That is €3 less than Kraken, nearly 3x cheaper than Bybit, and more than 12x cheaper than Cryptocom.

[Cred @CryptoCred]

As someone who loves trading technicals

I think learning about markets via technicals (like I did) is one of the worst ways to start

It’s a rigid framework where grown men argue with each other about the exact Japanese name for a specific candlestick or a box they’ve drawn on an arbitrary time frame

It doesn’t teach you the foundations - why markets move, different types of participants, microstructure, order types and their impact, perps vs spot, and all that stuff - market ‘plumbing’ as a category

One of the biggest issues with being hyperfocused on technicals is that they don’t teach you principles and market effects

Most technical setups can be decomposed into broad buckets which are well-established (trend, mean reversion, momentum, order flow / price impact, vol clustering etc.)

A lot of technical analysis is an often unknowing attempt to map those broad market effects into a recognisable pattern

But even a technical-first view is better served by understanding the underlying market effect first and then decomposing it, as opposed to focusing on the specific pattern without ever looking at what’s happening under the hood

“This type of triangle tends to go up” is a lot less useful than “this type of flow tends to resolve higher over N time frame”, even if you use the same triangle to identify it

Another example: if you’re drawing a support level and buying it, you’re assuming some version of buyers being more aggressive than sellers in that area over a given time frame and predicting a higher price as a result - but what does that mean?

Shorts closing / taking profit, allowing for mean reversion? Aggressive sellers being absorbed by passive buyers? Some price insensitive buyer predictably stepping in at a value area? Sellers getting margin called and forcibly trading at bad prices/causing a dislocation? Clustering of orders creating some sort of imbalance? And so on.

There’s definitely a risk of overthinking this stuff, and you can make money from charts alone

But if you haven’t thought about the underlying market effects and ‘plumbing’ for your setups you’ll likely be stuck in rigid pattern matching that doesn’t generalise and isn’t subject to deeper investigation and more nuanced application

Even if your main lens remains TA-focused, there is no harm in understanding the stuff you’re trading on a product level (eg perp contract specs, OI, funding, mark/last/index etc) and on a foundational level (why and how markets move)

Especially now that you can jam this stuff into an LLM and keep saying “dumb it down” until you get it, no excuse not to do your homework

This is something I really wish I did much earlier in my trading life, so hopefully it resonates with a fellow trader stuck in TA psychosis spending his mum’s credit card on a fourth Udemy candlestick course

Anyway GM

[Blockonomi @blockonomi]

XRP funding rates just hit extreme bearish territory. 📉

-70% since July 2025 highs
Open interest down to $350.6M
NVT ratio elevated at 162.86
Market cap slips to $10.89B

Sellers remain in control, but similar setups have preceded sharp reversals before.

#XRP #Crypto #Altcoins #Blockonomi

👉Full Story Below👇

https://t.co/yd8f34okQu

[Arlington National Cemetery @ArlingtonNatl]

We do not consider playing "Pokemon Go" to be appropriate decorum on the grounds of ANC. We ask all visitors to refrain from such activity.

[Cred @CryptoCred]

Casual Friday is one of the longest-running crypto trading podcasts.

You should listen to it because the hosts are extremely qualified:

DonAlt got liquidated buying the top of XRP memecoins and ran away to New Zealand.

I last took a trade in the Great Corn Depegging of 1912 and haven't touched an orderbook since.

Enjoy.

0:00 BTC sub-60k
2:31 MicroStrategy overhang
21:10 Schizo deep dive on trading levels
37:18 ETH, HYPE, SOL
1:07:00 Why you need to gamble when you're young
1:16:31 SpaceX is trading like a shitcoin

[CoinMarketCap @CoinMarketCap]

$BTC

[Cred @CryptoCred]

Thanks for all the feedback on the last post.

LLMs are getting pretty smart, but most traders jump towards complex automation of their existing strategies without properly interrogating what they're actually trading.

Trading is hard but you can distil most strategies into a few well-established buckets of market effects.

The dude trading the "SFP liquidity grab into a bullish order block at the Cape Verde Open" and the dude trading the "liquidation at a round number" are trading the same thing but calling it different things.

The valuable part is in the mechanism, not in the label.

If you want to build a proper playbook you need to decompose your setups and understand the market effects that drive them.

I mentioned that you can do this with an LLM but didn't specify how.

Just paste this into your LLM of choice:

You're an educational trading companion. Your job is to lift the fog on what I actually trade.

Interview me one question at a time. If I can name a setup I trade, start there. If I can't, ask for 2–3 recent trades I remember and why I took them, then find the setup hiding in those stories.

Decompose every setup from folklore into first principles:

• the real, well-studied market effect I'm exploiting (momentum/imbalance, forced flow, trend, mean reversion, herding, positioning — not exhaustive; e.g. a "triangle breakout" is really a balance-to-imbalance shift betting on aggressive taker flow)
• the mechanism: who's forced to act, why the flow exists
• when the effect is active vs dormant
• which of my confluence factors follow from the mechanism, and which are folklore
• invalidation that follows from the mechanism

Be a companion, not an examiner. Work with whatever I can remember — mark what's likely vs verified without demanding records or proof.

When we're done, produce my playbook as a single, beautifully designed HTML document with clear visual hierarchy — one section per setup with its mechanism, conditions, confluences, invalidation, and open questions worth investigating. If I paste in an existing playbook, refine it — don't start over.

[Anthony Pompliano 🌪 @APompliano]

New York putting a moratorium on data centers is about as dumb of a public policy as you could come up with.

Most of these elected officials don’t even know how to use their cell phones.

We should put a moratorium on bureaucrats getting in the way of technological progress.