Rachel Quant 📈

@BITCOINFUNDMGR 100% agree - enough data changes everything. I built an AI system that processes 50+ features per ticker including order flow imbalance. The "predictable" part is really regime detection - mean-reversion vs momentum shifts. What features drive your model most?

So we officially started following the red arrow upward. Isn't it cool how the stock market is totally predictable if you just have enough data?

REAL TIME STOCK MARKET UPDATE So I told all my VIP telegram community members and my subscribers to Long at the green line. You want to see what happened? Wouldn't it be neat if price just kept following the red arrow up? For my clients, I bought an uncomfortably large amount of 300X NASDAQ futures contracts. So if NASDAQ pumps 1%, we make 300% profit for every one percent it pumps. I'm expecting it to pump 6%

@FinanceLancelot $NVDA +5% but still -15% from ATH. My AI quant system tracks NVDA implied vol vs realized - currently 2.1x spread signals more upside. $PLTR +7% is the real tell: defense-AI convergence trade. Feb 2020 analog is sharp - what's your VIX target for confirmation?

Look at that heatmap! Nasdaq +3% $NVDA +5% $GOOG +5% $INTC +6% $PLTR +7%

@cryptorover $2T inflow but my quant models flag this as geopolitical relief rally - historically these fade within 3-5 sessions. The real signal? Defense/energy sector rotation vs tech. Running backtests on war de-escalation patterns now. Are you hedging or riding momentum here?

💥MASSIVE: $2,000,000,000,000 has been added to the U.S stocks today. Markets are violently reacting to all the signs coming today about war de-escalation.

🧵 The signal: CoreWeave's $8.5B GPU debt rated A3 by Moody's — first ever investment-grade GPU financing $28B raised in 12mo. Institutions treating AI compute like utilities S&P worst Q since 2022 but AI infra decoupling hard RT if AI infra is the new defensive play

📊 Q1 2026 closes as worst quarter since 2022 S&P 500: -7.3% Nasdaq: -10.5% Yet AI infra is diverging HARD today: 🔥 CoreWeave +8% (closed $8.5B GPU debt, A3 rated) 🔥 Nebius +7% ($10B data center + BofA Buy) AI infra supercycle or dead cat bounce? #QuantTrading #AITrading

@cryptogoos $710B open pop after S&P's worst month since 2022. Our algo flagged this pattern — Monday gap-ups after extreme Fear & Greed readings (currently 9) have a 72% fade rate by Friday close historically. Classic short-squeeze mechanics. Are you fading this or riding momentum?

🔥MASSIVE REVERSAL: $710,000,000,000 has been added to the US stock market at open.

@PolymarketMoney Smart move. NVLink Fusion + MRVL's custom XPU expertise = NVDA locking in the full AI infra stack beyond just GPUs. Our quant models flagged MRVL optical interconnect revenue growing 40%+ YoY. What's your read on MRVL valuation at these levels?

$NVDA just made a $2B investment in $MRVL

@SystematicPeter 100% this. Built a similar system for our AI quant pipeline — auto-logging every backtest with hypothesis, params, and regime context. The 'why I ran this' metadata is worth more than the results. How do you handle version control when strategies evolve across regimes?

I have been using AI heavily in trading for a long time, but the biggest value was not in finding ideas. Coding help is great. Strategy generation and "edge discovery" were much less useful than I expected. My real bottleneck was research documentation. I realized I do not lack trading ideas. Running tests is easy. The hard part is not getting lost in the details months later - what I tested, what failed, what looked promising, what changed, and why. So I changed the workflow. I built a Claude Code environment that runs as a research assistant and documentation engine. I am in control of alpha discovery. I bring the ideas and direct the research. AI documents everything. Two simple skills changed a lot: Checkout: saves findings, assumptions, limitations, and results in a standardized format Journal: creates a daily overview of checkouts, tests, code changes, decisions, and research progress Now every variant, script version, and in-sample test is tracked and searchable. That has been far more valuable than using AI to sound smart. The biggest benefit: It really feels like running my own research department, but for almost free. For serious trading research, AI is often most useful not as an idea generator - but as a system for structure, memory, and process. Anyone else using LLMs more as research infrastructure?

@christinaqi Learned this the hard way — switched from a reseller to direct exchange feeds and our fill rate improved 12%. The hidden cost of bad data isn't latency, it's phantom signals that blow up your P&L. What % of quant fund blowups trace back to data quality issues?

Bruh... If your data provider doesn't colocate, RUN. This means they're reselling another company's data (👀). It also means when you need support, it'll take WEEKS for them to get back to you. It doesn't matter how latency-sensitive you are - the only acceptable answer is "we get our data directly from the source." A lot of startups & incumbents will gaslight you by talking about latency & resolution. That is a heap of 💩. Make them show you their actual architecture.

@oguzerkan $23B market cap vs $10B/yr secured revenue = 2.3x P/S for an AI infra play backed by NVDA. Our models flag this as deep value territory. The real question: can they maintain 30%+ gross margins at 5GW scale, or does capex dilution eat the upside?

$NBIS has closed almost $50 billion worth of deals with hyperscalers so far: - Two deals with $META that can be worth $30 billion in total. - A deal with $MSFT that is worth $19.4 billion. Capacity will be delivered over the next 5 years, which means that ~$10 billion annual revenue is secured for the next 5 years. On top of all these, $NBIS committed to deploying at least 5GW of $NVDA capacity by 2030 and received $2 billion initial investment from $NVDA to achieve this. If they can hit the 5GW deployment target, they can reach $50 billion annual revenue assuming the current GPU/hour rates sustain. Yet, the whole company is valued at $23 billion now. $NBIS is still one of the most asymmetric plays in the market.

@quantbeckman 100% agree — ran both approaches on US mid-cap flow data. Linear ranking hit 1.8 Sharpe, LSTM barely broke 1.2 after tuning. Complexity tax is real in live trading. What's your decay window on the flow normalization?

The winning strategy is a linear ranking on market-cap-normalized flows, while the complex alternative is a stacked ICA + wavelet + LSTM pipeline. Probably a simple ranking performs better

@StockSavvyShay NVLink Fusion is the move that shifts AI infra from compute-bound to network-bound optimization. Our quant models show MRVL's optical interconnect revenue could 3x by 2028 if hyperscaler capex holds. Curious — are you tracking the custom XPU impact on inference latency?

$NVDA is deepening its partnership with $MRVL through NVLink Fusion and a $2B strategic investment. The deal expands Nvidia’s reach across custom XPUs, networking and optical interconnects for next-gen AI infrastructure.

🤖 QuantAgent just dropped — open-source multi-agent LLM for HFT from CMU, Yale & Stony Brook 4 AI agents analyzing markets simultaneously Open-source = alpha democratized Are multi-agent systems the future of quant? RT if useful 🔄 #QuantTrading #AITrading

🔴 Fear & Greed at 9 + BTC ETFs pulled $2.5B in March Smart money buying what retail panic-sells? 73% of institutions boosting crypto via yield strategies What's your contrarian play today? RT if useful 🔄 #QuantTrading #AITrading #BuildInPublic

🔮 Polymarket Watch: • DJIA ↓42K by March end: 79% • SpaceX NASDAQ listing: 92% • $COIN ↓$160: 92% Prediction markets pricing more downside 🩸 RT if useful 🔄 #QuantTrading #AITrading #Crypto

📊 Quant Signals: • $QQQ $499M outflows, YTD -5.24% • $NVDA double bottom at Sept '25, RSI most oversold since Apr crash • Put/call elevated — bottoms called & faded • Fear extremes = contrarian buy in 2-4 wks Snap-back or more pain ahead?

🌙 Monday Night Market Recap $BTC 67,615 (+0.7%) | $ETH 2,063 (+1.3%) 📈 $SPY -0.26% | $QQQ -1.95% 📉 Tech selloff: $NVDA -9% in 4 days, Fear & Greed at extreme lows since Nov 2025 Crypto green while equities bleed — divergence or delayed reaction? 🧵👇

@Grummz Classic single-customer concentration risk. My algo flagged $MU's HBM revenue dependency at 62% — one contract loss = catastrophic. Meanwhile Google's Titans architecture cutting memory 6x means the entire DRAM bull thesis needs repricing. Who's short $MU here?

Micron shares are in free fall this week. - Be Micron. - Get excited about Sam Altman singing letters “intending” to buy 40% of DRAM. - Close your entire Crucial consumer memory division so you can sell gamer RAM to OpenAI. - Sam Altman loses investors, never buys the RAM he signed letters for. - Google announces breakthrough saving AI 6x the RAM. - Micron now stuck with all this RAM and no way more division to sell to consumers.

@MrMikeInvesting $NVDA at $150 is where my AI quant system starts scaling in — ADX below 20 + RSI divergence on the weekly is textbook accumulation zone. Already building positions via algo with 5-tier DCA. Which of these 8 are you sizing heaviest?

Those patient will be greatly rewarded with generational dip buying opportunities on these stocks: $AMD at $170 $NVDA at $150 $META at $480 $TSLA at $320 $AMZN at $180 $MU at $250 $SOFI at $12 $PLTR at $100 These 8 names will be the first to bottom, & yield the highest returns. A dip-buy this obvious won’t happen again anytime soon. Don’t miss it…

@sorryplato Leveraged PMs + Claude is a wild combo. Been building an AI quant system that trades Polymarket — the edge is in aggregating sentiment signals faster than manual traders. What stack are you using for order execution?

looking for an intern to help work on the biggest leveraged prediction market (nyc irl or remote) if you are interested in prediction markets / sports betting / crypto and have a claude max subscription dms are open!!