sonicgates

1.5K posts

sonicgates banner
sonicgates

sonicgates

@sonicgates

learner

mars Katılım Aralık 2021
883 Takip Edilen71 Takipçiler
sonicgates retweetledi
Julian Komar 🚨 Market Update Premium
IPO U-turns #trading patterns are rare—but when they show up, they can change your entire year 🚀📈 I track this chart pattern very closely. Here’s how it works 👇 1) Hot IPO Launch: Strong story, strong demand. The stock goes public and often rallies immediately. That’s your first signal—institutions are interested. 2) Sharp Pullback: After the initial hype, it corrects for weeks. Weak hands get shaken out. Most traders lose interest here. 3) Rounded Bottom: Price stabilizes and slowly turns. No panic selling anymore. This is where accumulation often starts. 4) Right Side Strength: The stock begins to climb again. Higher lows, improving structure. Demand comes back quietly. 5) Tricky Entries: You often don’t get a perfect, tight base. That’s the challenge. These stocks can just move—without giving you the “ideal” entry. 6) Explosive Potential: If it works, it moves fast. These are not 10–20% trades. These can become real leaders. But here’s the reality: They don’t appear often They require patience They require strong stock selection No story, no growth, no trade. I focus on: - Clear theme or narrative - Strong EPS / sales growth - Real institutional interest These patterns repeat. I’ve taught this to thousands of traders. You can learn this too.
Julian Komar 🚨 Market Update Premium tweet mediaJulian Komar 🚨 Market Update Premium tweet mediaJulian Komar 🚨 Market Update Premium tweet mediaJulian Komar 🚨 Market Update Premium tweet media
English
6
19
130
7.9K
sonicgates retweetledi
Cryptoarena
Cryptoarena@Cryptoarena001·
This setup isn’t just for $BTC… it works on altcoins too. $TAO is a clear example 👇 Already at 1:4RR Full TP targeting 1:10 Same setup. Same execution. Monday — do nothing Tuesday — mark high & low M15: Wait for sweep + CISD Enter Target opposite side No guessing. No overtrading. Just repeat. Save this
Cryptoarena tweet media
Cryptoarena@Cryptoarena001

For 2 years straight… this setup hasn’t failed me. Has a-least 80% accuracy on FX. Stocks. Crypto. Same model. Same results. It’s simple: Mark the Monday range Monday High Monday Low Then wait for the sweep of either side Drop timeframe → confirm (CISD / MSB) Tear lot size . Target? Opposite side of the range. No indicators. No guessing. Just structure. Same setup. Every week. Save this , will trade live

English
2
6
27
2.3K
sonicgates retweetledi
Koroush AK
Koroush AK@KoroushAK·
Every Trading Skill Level Explaned Level 0: No Strategy - No strategy. Just tips and 'gut feelings' - No written rules for entries, exits, or stop losses - No journal. No screenshots. No data. - Position sizes swing wildly (1% one day, 10% the next) - Wins feel like skill. Losses feel like bad luck. Level 1: Inconsistent Strategy - Learning to read charts: support/resistance, candlestick patterns, market structure - Setting up your exchange, understanding order types, securing your capital - Starting to define entry triggers, stop loss placement, take profit rules - Risk per trade becoming more consistent but still varies - Journal has data, but execution still varies Level 2: Consistent Strategy - Follows strategy rules on 90%+ of trades - Journals every trade with screenshots and comments - Has a working routine: checklist, report card, emotional check-ins - Data is clean and reliable - Not yet consistently profitable: equity curve may be flat or slightly negative Level 3: Consistent & Profitable - Positive expectancy over 30+ trades - Upward-sloping equity curve - Can distinguish a good setup from a great one - Beginning to introduce discretion based on data - Making money but not yet at meaningful size Level 4: Consistent, Profitable & Scaled - Consistently making four to five+ figures per month - Scaled to a meaningful portfolio size - Multiple strategies across different market conditions - Execution fluid and largely automatic - Emotional stability under large position sizes - Continuous edge development as a habit, not a project What level are you on?
English
7
10
47
4.1K
sonicgates retweetledi
Manly Mentor
Manly Mentor@manly_mentor·
Bruce Lee rewired my brain with this...
English
16
807
5.4K
301.6K
sonicgates retweetledi
bee🐝
bee🐝@0xbeehive·
$BTC CYCLE IS RIGHT ON SCHEDULE 2018-2021: > 365D BEAR MARKET > 1,066D BULL RUN > TOPPED AT $69K 2022-2025: > 365D BEAR MARKET > 1,065D BULL RUN > TOPPED AT $126K 2026-2029: > 365D BEAR MARKET (IN PROGRESS) > 1,066D BULL RUN NEXT SAME DURATION EVERY CYCLE SAME STRUCTURE EVERY CYCLE POSITION ACCORDINGLY!
English
46
125
937
173.6K
sonicgates retweetledi
Sherlock | DeFi Researcher
Sherlock | DeFi Researcher@Sherlockwhale·
I found two patterns on Bitcoin that both have a 100% win rate. Both of them are live right now and both will get decided by midnight UTC tonight. When Monday closes more than 4% above the previous week's high, the week closes green. 15 out of 15 times since 2017. Last week's high was $78,300 so the trigger is a Monday close above $81,460 tonight. The probability of this happening by a random chance is 1 in 16,000. The second pattern has an average weekly return of +12.4% when it fires. When Monday closes more than 8% green after a green prior week, the week has closed green 10 out of 10 times. The largest gain was +26.2%. Monday opened at $73,758 so the trigger is a close above $79,650 tonight. It works in every market condition: Dec 2017 Bull Market: +26.2% Week Mar 2020 COVID Crash: +1.1% Week Feb 2021 Bull Run: +25.2% Week Oct 2023 Recovery: +15.1% Week Nov 2024 Halving Year: +11.8% Week Bull market, bear market, crash recovery, it does not matter. When Monday opens this strong after a green week, buyers are in complete control and the rest of the week just follows through. Two numbers to check at midnight UTC tonight. If Monday closes above $79,971, Pattern 2 fires and the week has closed green 10 out of 10 times. If Monday closes above $81,466, both patterns fire and there is no recorded week in Bitcoin's history where that happened and the week closed red. Bookmark this and check at midnight.
English
10
16
133
8.9K
sonicgates retweetledi
Nav Toor
Nav Toor@heynavtoor·
Claude can now meal prep your entire week and hit your exact nutrition goals like a $200/hour registered dietitian from the Mayo Clinic. For free. Here are 12 prompts that plan meals, calculate macros, and save you $500/month on groceries: (Save this before it disappears)
Nav Toor tweet media
English
114
624
7.4K
1.4M
sonicgates retweetledi
🍓🍓🍓
🍓🍓🍓@iruletheworldmo·
a masterclass in coding agents from the head of anthropic. there’s still a tonne of leverage in knowing how to use these systems optimally and this is the best i’ve seen. make sure to bookmark so you can watch again and again chat
English
47
217
2.8K
279.7K
sonicgates retweetledi
wincy.eth
wincy.eth@gusik4ever·
the fastest growing GitHub repos in finance this week: 1. shiyu-coder/Kronos (+6.5K ★) first open-source foundation model for financial candlesticks. trained on 45+ global exchanges. predicts OHLCV candles as tokens — literally GPT for price charts. accepted at AAAI 2026. 2. virattt/ai-hedge-fund (+4.9K ★) a team of AI agents simulating Buffett, Munger, Ackman, Cathie Wood and others. each agent runs its own strategy, a Portfolio Manager makes the final call. one of the most viral finance repos right now. 3. TauricResearch/TradingAgents (+~3K ★) multi-agent LLM trading framework. fundamental analyst, sentiment analyst, technicals, risk manager — all working together. supports GPT-5.x, Gemini 3.x, Claude 4.x, Grok. built by UCLA/MIT researchers. 4. ZhuLinsen/daily_stock_analysis (+~2K ★) LLM stock analyzer for US, A-share and H-share markets. auto-builds a daily decision dashboard with exact entry/exit levels. pushes to WeChat/Telegram/Discord/Email via GitHub Actions. zero cost, zero server. 5. hsliuping/TradingAgents-CN (+~1.5K ★) Chinese fork of TradingAgents. fully localized for A-share markets (Shanghai/Shenzhen), Chinese data sources, and domestic LLMs. 5.1K forks — very active community. 6. OpenBB-finance/OpenBB (+~1K ★) open-source Bloomberg alternative. stocks, crypto, options, derivatives, fixed income — one platform. integrates with AI agents via MCP. 66K total stars and still climbing. 7. freqtrade/freqtrade (+~700 ★) free, open-source crypto trading bot in Python. supports all major exchanges, full backtesting, strategy optimization, Telegram control. release 2026.3 just dropped. 8. AI4Finance-Foundation/FinGPT (+~500 ★) open-source financial LLMs trained on real market data — news, filings, earnings. built for sentiment analysis and robo-advisors. models on HuggingFace, ready to deploy. 9. juspay/hyperswitch (+~400 ★) open-source payments router in Rust. one API to connect Stripe, Adyen, PayPal and 50+ providers. smart routing, high performance, built for fintech scale. 10. microsoft/qlib (+~350 ★) Microsoft's AI quant investment platform. covers the full pipeline: alpha seeking, backtesting, model training, live trading. supports ML/DL, RL, and auto-quant. bookmark this and start today.
wincy.eth tweet media
wincy.eth@gusik4ever

the fastest growing GitHub repos in finance this week: 1. mvanhorn/last30days-skill (+2.1K ★) AI agent skill that searches Reddit, X, YouTube, HN, Polymarket and the web in parallel — then scores results by upvotes, likes, and real money, not editors. drop it into Claude Code or OpenClaw. zero config to start. 2. ZhuLinsen/daily_stock_analysis (+1.2K ★) LLM-powered stock analyzer for US, A-share and H-share markets. real-time news + multi-source data + decision dashboard with exact buy/stop/target levels. runs on GitHub Actions on a schedule at zero cost. pure automation. 3. juspay/hyperswitch (+667 ★) open-source payments infrastructure written in Rust. modular by design — pick only what you need: routing, retries, vaulting, reconciliation, cost observability. built by the team behind payment infrastructure for 400+ enterprises. the "Linux for payments" 4. HKUDS/AI-Trader (+655 ★) agent-native trading platform where AI agents join, share signals, debate ideas, and copy each other's trades. send one message to any agent and it registers itself. supports OpenClaw, Claude Code, Codex, Cursor and more. 5. hsliuping/TradingAgents-CN (+471 ★) Chinese-enhanced fork of TradingAgents. same multi-agent LLM trading architecture, fully localized for Chinese markets, A-share data, and domestic LLMs like DeepSeek and Qwen. 23K stars and climbing. 6. ashishpatel26/500-AI-Agents-Projects (+436 ★) curated collection of 500+ AI agent use cases across healthcare, finance, education, retail and more. organized by industry and framework — CrewAI, AutoGen, LangGraph, Agno. the best reference list if you're figuring out what to build next. 7. OpenBB-finance/OpenBB (+355 ★) open-source financial data platform for quants, analysts and AI agents. "connect once, consume everywhere" – same data layer exposes to Python, Excel, MCP servers for agents, and REST APIs. the open-source Bloomberg alternative. 8. microsoft/qlib (+349 ★) AI-oriented quant investment platform from Microsoft. covers the full pipeline from data to live trading: alpha seeking, risk modeling, portfolio optimization, order execution. deep learning, RL, auto-quant – all in one place. 9. tradingview/lightweight-charts (+318 ★) one of the smallest and fastest financial chart libraries for the browser. built with HTML5 canvas, weighs almost nothing, renders like native. if you're building any kind of trading UI on the web, this is what you reach for first. bookmark this and start today.

English
30
238
1.7K
180.9K
sonicgates retweetledi
Esther & Michael
Esther & Michael@SuperLuckeee·
1 year ago, SNDK ran from $30 to $945 for 900% Here's 4 set-ups with exact 500%-1000% potential: 1. BE (Bloom Energy) -AI data centers = massive power demand → BE solves energy reliability -Hydrogen + clean baseload = secular tailwind - If margins flip + profitability hits → multiple expansion explodes Buy zone: $120–130 = demand zone / prior base 2. ASTS (AST SpaceMobile) - First real space-based cellular broadband (not hype anymore) - Partnerships with AT&T / Vodafone = distribution solved - If they prove scale → becomes global telecom infra layer Buy zone: $70–80 = high conviction accumulation 3. IONQ (IonQ) - Pure-play quantum computing (early innings like NVDA 2016) - Government + enterprise contracts building If quantum hits real-world use → exponential upside Buy zone: $25–$30 = value accumulation 4. IREN (Iris Energy) - Bitcoin + AI compute hybrid play Cheap renewable energy = structural edge - If BTC + AI infra both run → double tailwind Buy zone: $30–$32 = strong support Pay attention, these don’t move because they’re cheap. They move because narrative + timing + execution align just like SNDK. There's 1 more massive runner setting up! Write 1 comment and REPOST this ♻️ and I'll share it.
Esther & Michael tweet media
English
85
218
1.5K
252.1K
sonicgates retweetledi
Om Patel
Om Patel@om_patel5·
IF CLAUDE FEELS DUMBER LATELY IT'S BECAUSE ANTHROPIC REDUCED THE EFFORT. HERE'S HOW TO TURN IT BACK UP: everyone's been saying Opus got nerfed. something feels off. responses are shallow. thinking is gone. turns out it's a configuration change. Claude Code users can type /effort max to get the old behavior back but for chat users there is no toggle. here's the fix nobody told you about: go to Settings > Profile > Custom Instructions and paste something like this "Always reason thoroughly and deeply. Treat every request as complex unless I explicitly say otherwise. Never optimize for brevity at the expense of quality. Think step-by-step, consider tradeoffs, and provide comprehensive analysis." the difference is night and day because Claude actually reads the full context again. considers tradeoffs. gives real analysis instead of surface-level bullet points. Claude itself told this guy about this workaround. it can't control its own effort settings but it responds to strong signals in your custom instructions
Om Patel tweet media
English
63
217
2.6K
244.9K
sonicgates retweetledi
leopardracer
leopardracer@leopardracer·
I wrote one article. Someone built a data center. No GPUs. Just $599 boxes. Jensen Huang is having a bad year. The new AI data center doesn’t need NVIDIA. It needs a Costco membership and a good Wi-Fi router.
leopardracer@leopardracer

x.com/i/article/2043…

English
40
57
703
231.3K
sonicgates retweetledi
Cryptoarena
Cryptoarena@Cryptoarena001·
Most traders know how to find a setup… Almost none know what to do after entering a trade. It’s between entry and exit that most money is lost. Here’s how I manage trades using my Monday Range setup 👇
Cryptoarena tweet media
English
11
12
53
5.1K
sonicgates retweetledi
Cryptoarena
Cryptoarena@Cryptoarena001·
Most traders will miss this btc move today. It’s Tuesday. Monday range is set. High marked. Low marked. Now we wait. Sweep + confirmation only: CISD MSB No rush. No guessing. When it confirms… Tear lot size !!! Same play. Every week. Bookmark this.
Cryptoarena tweet media
English
20
10
58
13.9K
sonicgates retweetledi
Cryptoarena
Cryptoarena@Cryptoarena001·
For 3 months straight… this setup has been printing me money. This week alone… 1:10 RR. Shared it publicly. Same setup. Every time. It’s called the Monday Range. Most traders overcomplicate this… Here’s all I do: Monday — do nothing Tuesday — mark high & low Wait for the sweep Wait for confirmation (CISD / MSB) Enter Target the opposite side That’s it. No noise. Repeat every week. Bookmark this. Retweet.
Cryptoarena tweet media
English
35
71
471
46.9K
sonicgates retweetledi
Ardi
Ardi@ArdiNSC·
$BTC There's a metric I track that has lined up with every single Bitcoin cycle bottom without exception. Long-Term Holder Supply in Loss. At the 2015 bottom: 53% of LTH supply was underwater. At the 2018 bottom: 45% underwater. At the 2022 bottom: 44% underwater. Every peak in that metric coincided with the cycle bottom. The current reading is 29% and steadily climbing. This tells me we are not at the bottom yet, but we are building toward the conditions where bottoms form. The pattern has never failed and I have no reason to believe this cycle is different.
Ardi tweet media
English
28
36
194
8.2K
sonicgates retweetledi
CRYPFLOW
CRYPFLOW@_Crypflow_·
$BTC – This is when the bull run starts There are two things that have consistently defined Bitcoin’s cycles: → The 50 SMA → The -14 level on the wave trend When both are lost… it’s not just a correction anymore. It’s a bear market. You can see it clearly: → 2022: lost the 50 SMA + lost -14 → full bear market → Momentum stayed below that level for months Until: → 2023: broke the long-term downtrend → Reclaimed -14 → Reclaimed the 50 SMA That was the moment the bull run started. Not the bottom. The confirmation. In previous posts I shared the bear market confirmation. Now it’s time to focus on the other side of the cycle. This is what needs to happen: → Break the long-term downtrend → Reclaim -14 on the wave trend → Reclaim the 50 SMA This is where cycles shift. Bookmark this.
CRYPFLOW tweet media
English
9
34
131
7.9K
sonicgates retweetledi
Sherlock | DeFi Researcher
Sherlock | DeFi Researcher@Sherlockwhale·
I backtested every Sunday pump above 2% on Bitcoin since 2021 and 90% of the time, it is a trap. Yesterday Bitcoin pumped 2.6% on a ceasefire headline but if you look at the last 6 years of data then there is a 90% chance of this move getting erased with a red weekly close. Here is what actually happens after Sunday pumps above 2%. If Monday closes red after the pump, the week closes red 85% of the time and if Monday drops more than 2%, it gets worse with 90% chances that the weekly candle will be red. In the last 6 months specifically, Sunday pumps above 2% have led to red weekly closes more than 80% of the time regardless of what Monday does. $67,300 to $69,034, that was Sunday's move. Now here is what Monday needs to do to confirm or kill it: Monday closes below $69,034 (the open): Base pattern triggers with 85% chance the week closes red. Monday closes below $67,653 (2% below the open): Strongest version triggers with 90% chance of a red week. This is the level where you know we are breaking below $65K. Monday closes more than 2.5% above Sunday's high ($71,870): The pump is real and the week closes green 80% of the time. This is the only bullish scenario and anything less than this should not be trusted. One of these three levels will hit by midnight UTC tonight. Bookmark this and check it every Monday morning. If Sunday was green by more than 2%, Monday's close will tell you whether the week closes red or green.
English
38
51
487
46.4K
sonicgates retweetledi
Ole Lehmann
Ole Lehmann@itsolelehmann·
karpathy just casually described the future of ai and most people scrolled right past it: he's been building what he calls "llm knowledge bases." here's what that means in plain english: you take everything you're interested in. articles, research papers, datasets, images, etc and you dump it all into one folder then you point your ai at the folder and say "read all of this, organize it, and remember it" the ai reads through every single source. writes summaries, groups related ideas together, links concepts across different articles basically builds a personal library that's fully organized and searchable and it maintains the whole thing for you. when you add something new, the ai reads it, figures out how it connects to everything already in the library, and updates automatically. karpathy said he rarely touches it himself once the library gets big enough (~100 articles, ~400k words), you can start asking it complex questions and get answers pulled from across your entire collection > "what are the common themes across these 30 papers" > "what did i save six months ago that connects to this new idea" > "summarize everything i have on topic x and tell me what's missing" and every answer it gives gets filed back into the library. so the system gets smarter every single time you use it. the memory grows from both sides: what you save AND what you ask now think about your own life for a second you probably have > thousands of twitter bookmarks you'll never reopen. > hundreds of saved articles from the last year > podcasts where someone said something brilliant and you can't remember what it was or which episode all dead knowledge. you consumed it once and it disappeared now imagine all of it lives in one system: organized, connected, and queryable. you could ask "what are the best pricing frameworks i've come across this year" and get an answer that pulls from: 1. a podcast you listened to in january 2. a twitter thread you bookmarked in march 3. and a blog post you forgot you even read the ai connects dots across formats, across months, across topics. because it absorbed everything and has photographic memory of all of it that's the dream. and karpathy built it the problem: right now this requires obsidian (a note-taking app built around linked notes), command line tools, custom scripts, and browser extensions just to wire it all together. you need to be quite technical karpathy even said it himself: "i think there is room here for an incredible new product instead of a hacky collection of scripts" i think whoever packages this for normal people is sitting on something massive. one app that syncs with the tools you already use, your bookmarks, your read-later app, your podcast app, your saved threads. it pulls everything in automatically, the ai organizes and connects it over time, and you can ask questions across your entire personal library whenever you want you never manually upload anything. it just learns in the background someone please build this
Andrej Karpathy@karpathy

LLM Knowledge Bases Something I'm finding very useful recently: using LLMs to build personal knowledge bases for various topics of research interest. In this way, a large fraction of my recent token throughput is going less into manipulating code, and more into manipulating knowledge (stored as markdown and images). The latest LLMs are quite good at it. So: Data ingest: I index source documents (articles, papers, repos, datasets, images, etc.) into a raw/ directory, then I use an LLM to incrementally "compile" a wiki, which is just a collection of .md files in a directory structure. The wiki includes summaries of all the data in raw/, backlinks, and then it categorizes data into concepts, writes articles for them, and links them all. To convert web articles into .md files I like to use the Obsidian Web Clipper extension, and then I also use a hotkey to download all the related images to local so that my LLM can easily reference them. IDE: I use Obsidian as the IDE "frontend" where I can view the raw data, the the compiled wiki, and the derived visualizations. Important to note that the LLM writes and maintains all of the data of the wiki, I rarely touch it directly. I've played with a few Obsidian plugins to render and view data in other ways (e.g. Marp for slides). Q&A: Where things get interesting is that once your wiki is big enough (e.g. mine on some recent research is ~100 articles and ~400K words), you can ask your LLM agent all kinds of complex questions against the wiki, and it will go off, research the answers, etc. I thought I had to reach for fancy RAG, but the LLM has been pretty good about auto-maintaining index files and brief summaries of all the documents and it reads all the important related data fairly easily at this ~small scale. Output: Instead of getting answers in text/terminal, I like to have it render markdown files for me, or slide shows (Marp format), or matplotlib images, all of which I then view again in Obsidian. You can imagine many other visual output formats depending on the query. Often, I end up "filing" the outputs back into the wiki to enhance it for further queries. So my own explorations and queries always "add up" in the knowledge base. Linting: I've run some LLM "health checks" over the wiki to e.g. find inconsistent data, impute missing data (with web searchers), find interesting connections for new article candidates, etc., to incrementally clean up the wiki and enhance its overall data integrity. The LLMs are quite good at suggesting further questions to ask and look into. Extra tools: I find myself developing additional tools to process the data, e.g. I vibe coded a small and naive search engine over the wiki, which I both use directly (in a web ui), but more often I want to hand it off to an LLM via CLI as a tool for larger queries. Further explorations: As the repo grows, the natural desire is to also think about synthetic data generation + finetuning to have your LLM "know" the data in its weights instead of just context windows. TLDR: raw data from a given number of sources is collected, then compiled by an LLM into a .md wiki, then operated on by various CLIs by the LLM to do Q&A and to incrementally enhance the wiki, and all of it viewable in Obsidian. You rarely ever write or edit the wiki manually, it's the domain of the LLM. I think there is room here for an incredible new product instead of a hacky collection of scripts.

English
137
140
1.8K
308.6K
sonicgates retweetledi
Sherlock | DeFi Researcher
Sherlock | DeFi Researcher@Sherlockwhale·
What if I told you that Bitcoin's weekly close is already decided by Wednesday night and you can predict it with 85% accuracy? I tested 451 weeks of data since 2017 and found that if Bitcoin has not pushed more than 1% above Monday's opening price by Wednesday night, the weekly candle closes red with 85% accuracy. The chance of this being a random event is only 1 in 100,000. The accuracy increases with every day that passes: Monday close: 61% red Tuesday close: 72% red Wednesday close: 85% red Thursday close: 90% red Each day that passes without bulls breaking above the open, the probability stacks higher against them. The reverse also works. If Bitcoin has not dropped more than 0.5% below Monday's open by Wednesday, there is an 86.5% chance the week closes green. The week is not decided on Friday, it is actually decided on Wednesday and everything after that is just price catching up to what was already determined 3 days earlier. Bookmark this. Use it every week.
English
44
93
590
58.5K