Reddit Posts
Remember my post about BTC news trading being dead? I dug into SOL/LINK and actually found a 15-minute latency window
Built a realtime BTC market regime classifier using HMM — happy to discuss the approach
I just integrated a Hidden Markov Model (HMM) for regime detection – here's why it changed everything about my trade filtering.
My quant system wants to short SOL here – but it's blocking itself. Here's why.
Mentions
Post is by: talissman_7 and the url/text [ ](https://goo.gl/GP6ppk)is: /r/CryptoMarkets/comments/1ttwh61/remember_my_post_about_btc_news_trading_being/ A week ago I posted that 2-year dataset showing how HFTs completely front-run BTC macro news in milliseconds. The general consensus in the comments was basically "yeah, manual traders are just exit liquidity" But it got me thinking about mid-caps (like SOL, LINK, AVAX) where the order books are way thinner. I went back to my pipeline and ran the tick data for those specific alts against the exact same news shocks Turns out, there actually is a structural 15 to 30-minute lag. Capital rotation doesn't happen instantly across the board, the lagging order books physically take time to absorb the shock But before you try to trade this, I realized it's a trap if you don't filter it This 15-minute decay window only exists in specific market conditions. If you try playing this lag during a flat or choppy market, the initial price spike just creates a liquidity vacuum and mean-reverts instantly. You just get chopped up To actually isolate the signal, I ended up running a Gaussian Hidden Markov Model (HMM) on the volume and spreads to classify the market into 3 regimes: trending up, trending down, and flat/range-bound. When you filter the news events only through the directional momentum regimes, that 15-minute delayed inertia on alts becomes super clear I threw together a quick Jupyter notebook showing how I calibrate the HMM regimes, along with a 500-row sample dataset so you can test the latency distribution yourself without needing the full database Repo is here if you want to mess around with it: [https://github.com/talisman-ep/cross-asset-latency-hmm.git](https://github.com/talisman-ep/cross-asset-latency-hmm.git) Are any of you guys trading cross-asset lag on lower timeframes, or do you mostly stick to raw price action? Curious how you handle regime filtering when trading news *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/CryptoMarkets) if you have any questions or concerns.*
By "digesting", I mean how the order book reacts to a news shock based on the current market regime. In a flat market, a news spike gets faded (mean-reverts). In a trending market, the momentum sustains The "action taken" is simple: macro news drops -> check BTC's instant reaction -> if the HMM regime confirms a trend, long lagging alts like SOL or LINK. They take 15-30 mins to absorb that same capital rotation
Yeah, fair points all around. Thanks for the detailed breakdown.The HMM approach for regime conditioning makes total sense, especially with the ETF messing up the baseline vol in 2024. I just stuck to calendar buckets for the sample so it’s easier to read, but a 3-state model is definitely the way to go for the actual backtest. Regarding the timestamp lag-that’s actually exactly why I lean so heavily on the T+15m window. I assume HFTs with direct feeds are already front-running the CoinDesk API by 30-60s anyway. Beating them at T0 is a lost cause, so the dataset is really built to model the absorption tail and liquidity digestion rather than the initial print. The clustering issue is a great catch though. Definitely needs a de-overlap step for the pooled stats. I’ll shoot you a DM, would love to hear how you guys handle the mid-cap asymmetry.
Nice expansion on the sample. A few methodology notes (I work on data at Coinpaprika, fwiw): The 2-year window catches one full cycle, but regime mix matters more than length. If you split 2024 vs 2025 vs 2026 you will probably see post-ETF news desensitization that washes out in pooled stats. A 3-state HMM on realized vol gives a cleaner conditioning variable than calendar buckets. Two other knobs that move results a lot: headline timestamp source (CoinDesk publish time can lag the wire by 30 to 90 seconds on big stories, worth cross-checking against Reuters/Bloomberg if you have it) and whether you de-overlap clustered events. 3,700 events over 2 years is roughly 5 per day, so 15-min windows are overlapping constantly and inflating the apparent reaction. Worth running the same study on a mid-cap altcoin basket too. Reaction half-life there often runs 2 to 3x BTC and the asymmetry between bullish and bearish prints flips. Happy to compare notes on methodology in DM if useful.
Yes, and there's a structural reason for it: entries and exits require fundamentally different signals. Entries are pattern recognition — 'conditions X, Y, Z are present, take the trade.' Exits require knowing when those conditions are no longer valid. That's a regime detection problem, not a pattern problem. The clearest way to think about it: your entry signal tells you the regime is favorable. Your exit signal should fire when the regime is ending — not when price hits an arbitrary target. A trailing stop or fixed TP is essentially guessing when the regime ends. Sometimes it works; often it leaves money on the table or gets stopped out before the move completes. What actually helps: 1. **Regime-conditional exit**: if you entered on a TRENDING signal, exit when the trend regime score drops (HMM confidence crosses below threshold, Hurst drops below 0.5, ADX collapses). You're not guessing price — you're detecting when the reason you entered is no longer true. 2. **Asymmetric stops**: in trending regime, give the trade more room (trend has persistence). In ranging regime, tighten stops immediately (mean-reversion makes extended losses likely). Entries feel easier because you control when you enter. Exits force you to react. The fix is turning exits from reactive decisions into rule-based regime detection.
Regulatory clarity removes a systematic risk premium. Whether it pumps is a different question from whether the regime changes. HMM regime reads TRENDING DOWN @ 73% confidence right now, Hurst 0.669. That trend has memory — it doesn't flip on a single catalyst unless the catalyst changes capital flow structure, not just sentiment. The exit liq scenario is more likely if: (1) price runs 5-8% on the news, (2) regime stays TRENDING DOWN underneath, (3) volume shows distribution not accumulation. News-driven spikes inside a downtrend tend to get sold into. The scenario where CLARITY actually sustains a move: institutional players who've been risk-off on regulatory uncertainty start accumulating systematically. That shows up as a regime flip — HMM switching to TRENDING UP with growing confidence over days, not a single candle.
Yeah, screenshot AI is useless I don't blame you. This is different. It's a live quant engine that runs actual statistical models (HMM, GARCH, Hurst, Kalman) on real-time data. It doesn't guess or 'predict.' It just reads the market's current state trending, choppy, volatile and adapts. It scales risk when the regime is stable, filters out noise, and even blocks trades when the market is behaving randomly. The quality isn't about being right. It's about knowing when not to trade. That's the part I find interesting
Post is by: denze-702 and the url/text [ ](https://goo.gl/GP6ppk)is: /r/CryptoMarkets/comments/1slpnqo/i_just_integrated_a_hidden_markov_model_hmm_for/ For a long time, my "machine" relied on static logical confluences—Trend, Structure, and Volume. While effective, these systems are inherently fragile because they assume the market exists in a single, constant state. I've just completed the integration of a Hidden Markov Model (HMM) to serve as the suite's primary \*\*Regime Detection\*\* layer. Here is the quantitative logic behind the shift. \--- \### The Problem with Standard Algos Most systems are "curve-fitted" to a specific past. They work until the market shifts from a low‑volatility mean‑reversion state to a high‑volatility directional expansion. By the time a standard indicator reacts, the drawdown has already begun. \--- \### The Markov Solution Instead of following price, the engine now treats the market as a mathematical \*\*Hidden State\*\*. By calculating state transition probabilities, the suite identifies which regime we are currently in: \- \*\*Steady Accumulation\*\* (low noise / low vol) \- \*\*Volatile Expansion\*\* (high momentum / high noise) \- \*\*Distribution / Pivot\*\* (exhaustion) \--- \### How this changes execution \*\*1. Dynamic Logic Gating\*\* If the HMM detects a regime transition with low confidence, the engine automatically suppresses signals. It doesn't matter how "good" a setup looks – if the regime isn't supportive, the trade is discarded. \*\*2. Asymmetric Risk Scaling\*\* The Kelly Criterion position sizing now scales based on the probability of the current regime persisting. \*\*3. Noise Filtering\*\* We use a Kalman filter combined with the Markov states to strip away "false breakouts" that occur during regime shifts. \--- \### The Benefit This isn't about finding a "holy grail" indicator. It's about building a system that understands \*\*context\*\*. We aren't optimizing for a date in history; we are optimizing for mathematical states. It's the difference between guessing where the ball will land and calculating the physics of the throw. \--- I'm curious—for those of you building in the quant space: are you still relying on multi‑timeframe confluence for regime filters, or have you moved toward more autonomous state‑space models like HMM or GMM? \*\*TL;DR:\*\* \*Added Hidden Markov Model for regime detection. System now suppresses trades during low‑confidence regime transitions, even if the setup looks good. Kelly sizing scales with regime persistence probability.\* \*Not financial advice. Just the math behind my personal system.\* *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/CryptoMarkets) if you have any questions or concerns.*
Post is by: denze-702 and the url/text [ ](https://goo.gl/GP6ppk)is: /r/CryptoMarkets/comments/1slmnev/my_quant_system_wants_to_short_sol_here_but_its/ I run a quantitative trading system that combines 16 models (Hurst, HMM, VRT, LPPL, Kalman, etc.) into a single confluence score. Right now it's showing a SHORT setup on SOL, but \*\*the system is actually filtering the trade out\*\*. Here's what's happening – and why I'm NOT taking this trade. \*\*The Setup (what the math says):\*\* | Metric | Value | |--------|-------| | Direction | SHORT | | Entry | $83.59 | | Stop | $84.25 (GARCH + S/R enhanced) | | Target 1 | $82.27 (2R) | | Target 2 | $81.61 (3R) | | R:R | 2.0:1 / 3.0:1 | \*\*The Problem – Why the system is BLOCKING this trade:\*\* | Issue | What the data shows | |-------|---------------------| | \*\*VRT Gate\*\* | RANDOM WALK (VR = 1.002) – Cannot reject random walk hypothesis. Trend signals suppressed. | | \*\*Confluence Score\*\* | Only 41/100 – Conflicted across timeframes (15M:43, 1H:66, 4H:35, 1D:58) | | \*\*Size Multiplier\*\* | ×0.10 – Extreme volatility/regime + counter-HTF | | \*\*HTF Cascade\*\* | BEAR but system says "counter-HTF" – conflicting signals | | \*\*kRSI\*\* | NOISY (Δ29.1) – Kalman filter lagging, suggesting chop | | \*\*Volume\*\* | Low (5/25 score) – No conviction | | \*\*EMA Stack\*\* | Bearish, but price is BELOW EMA200 – that's actually bearish alignment, yet the system still blocks due to other factors | \*\*The Verdict from my system:\*\* ❌ SIGNAL FILTERED \*\*What this means:\*\* The math says "yes, the setup looks short, but the broader market regime is RANDOM WALK right now. Don't trust the trend signals. Don't take this trade." \*\*Why I'm posting this:\*\* Anyone can post their winning trades. I'm posting a trade my system WANTS to take but is smart enough to reject. That's the value of quantitative filters. \*Not financial advice. This is my personal system output – currently in RANDOM WALK regime, so I'm sitting on my hands.\* *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/CryptoMarkets) if you have any questions or concerns.*
Post is by: SquallLionheart and the url/text [ ](https://goo.gl/GP6ppk)is: /r/u_SquallLionheart/comments/1r1wx21/my_journey_into_automated_crypto_trading/ I have been trading crypto for 4-5 years now, I have passed multiple prop firms, multiple times, all eventually leading to ruin! I realized the weakest link in the chain most often human psychology! I decided, "It has to be better to automate this"... I already had a background in Javascript, I enjoyed tinkering and building stuff. I learned python as I started exploring yfinance and more importantly ta-lib (to calculate all the indicators I typically used in TradingView). This was a fun experience and slowly exposed me to AI prediction models, Random Forest Classification, LSTM etc. I trained models on years of daily candles (plus indicators), and began predicting tomorrow candle direction. This gave me a MASSIVE false-sense of genius (LOL). I wrote a nodejs application to call the python app, get prediction and execute trade on Bybit if confidence was high. Problem was, models were trained on ALL the datapoints (indicators, OHLCV), many of which were pointless unless normalized. After few weeks my balance was dust. New idea.... Just take all that data (pricing+indicators) for the past x days for BTC, and throw it into chatGPT and ask it to find high-confidence trades. This actually worked well for a time, but really suffered during choppy days/weeks... As, for the most part, it was giving me trade setups every day.   The more prescriptive I got in my prompt(s) to chatGPT, the more I realized I could probably just program exactly what I wanted. I tried removing AI completely and defined an SMC strategy with limited success. I reintroduced AI, with more of an "agentic" flow (not truely agentic though). I used a riskManager, portfolioManager, Trader (creates signal), Executor (makes trades)... This had amazing short-term results (due entirely to large position size), but ultimately rinsed my account after a string of losses. Which the continuing burden of *not-yet-being-a-millionaire* I turned my focus away from executing and back to data - I started building out the python data feed into a stand alone data API, storing historic data in supabase and serving up pricing and indicators. The most recent addition is a Hidden Markov Model (per ticker) to detect the current market regime and give it a score 0-100 (0-30 Bearish, 70-100 Bullish, 30-70 Chop).  Made a good portion available for free, eating the \~$20/month infra costs myself. Plan: when I turn back on autotrading with strict behavior depending on market regime, autotrading will help pay infra. **I'd love to hear:** * Has anyone else tried HMM for crypto? * What useful data features are missing? * Your own trading bot war stories! If you want to check out sample use case apps, they are in my Github Anyway thanks for coming to my TedTalk, any questions let me know... :) *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/CryptoMarkets) if you have any questions or concerns.*
Think a very interesting one is cxo (CargoX).topics; digitalisation of world trade / blockchain document transfer.. One of a few tokens which has a fiat inflow into the token which was earned outside crypto space. So it is not so much linked to general crypto markets, but to business success. U can check here; Cargox.io And for statistics here; https://cargox-tracker.eu/ Pros; low market cap, deflationary supply through buyback and burn / optional U can be a CargoX Relayer and get passive income (a bit of initial investment needed in cxo token 😅) unknown and unhyped / potential growth / stable and reputable customers (Egypt use it on a mandatory base/ VAE / Abu Dhabi Customs /HMM / etc.) Cons; communication of the team / dex only (liq. Is okay though)
HMM That was then, we have survived
lmao, the fucking irony of your statement Nah dude you’re just dumb I’m literally saying how people should grow their money by investing in businesses, **such as people who want to retire,** *which in turn allows money to keep circulating in the economy,* and mr.bigbrain over here mockingly exclaims “BuT wHat aBouT peOple whO wAnt tO RetiRe? sHoulD tHey nOt bE AlloWEd to sAvE or shOuLd tHeY jUst kEEp wAstiNg tHeiR paYcHeck aWay UNtil tHey die?? HMM??” lmao, yeah you belong in this sub
uhm market chaos, tarriffs on our neighbors, tarriffs on GPUs, cold war with China officially on, HMM WHO KNOWS WHY??
CargoX ist eine Firma, die eBOLs (electronic Bill of lading) anbietet. Das sind Zoll- und Besitzdokumente, die für jede internationalen Container-Verschiffung verwendet werden. Bisher papierhaft, jetzt dank CargoX auch auf der neutralen und fälschungssicheren Blockchain. Zeit- und Geldersparnis für die Reeder und die Exporteure von Gütern liegen zwischen 80-90%. Die Firma und die Technologie sind von den gängigen Handelsorganisationen und Versicherungen offiziell anerkannt. Mit jedem Dokument, dass den Exporteur ca 10 USD kostet, werden für 30cent CXO-Token geburnt und für 30 Cent tokenholder bezahlt, die als Relayer ihre Token „gestaked“ haben und damit die neutrale Blockchain darstellen. Der Rollout dieses Real World Produktes hat bereits begonnen: in Ägypten ist es seit 2 Jahren im Einsatz, verpflichtend für alle Exporte. Vereinigte Arabische Emirate folgen in 2025, der 8.größte Container-Reeder der Welt (HMM aus Südkorea) führt es auch ein. Mit vielen Ländern ist man in Verhandlungen über ein Rollout auch dort. Es dauert nur leider lange (meist Jahre), da es eben staatliche Stellen sind… Aber alle großen Länder haben sich verpflichtet, in den nächsten 10 Jahren ihren Handel zu digitalisieren. Vom Prinzip her ein NoBrainer: es macht finanziell Sinn, viele werden diese Neuheit nutzen in den nächsten 2-10 Jahren, CXO ist durch die burns deflationär. Konkurrenz ist zwar auch da, aber CargoX kann auf den Live-trackrecord in Ägypten verweisen. Herausforderungen: schwache Liquidität (Uniswap), Token ist unbekannt und wird von Firma nicht beworben (da Crypto bei staatlichen Stellen Vorurteile auslösen kann, wegen Teufelszeug und so…) Pro: Sehr eingefleischte TG Community
CargoX ist eine Firma, die eBOLs (electronic Bill of lading) anbietet. Das sind Zoll- und Besitzdokumente, die für jede internationalen Container-Verschiffung verwendet werden. Bisher papierhaft, jetzt dank CargoX auch auf der neutralen und fälschungssicheren Blockchain. Zeit- und Geldersparnis für die Reeder und die Exporteure von Gütern liegen zwischen 80-90%. Die Firma und die Technologie sind von den gängigen Handelsorganisationen und Versicherungen offiziell anerkannt. Mit jedem Dokument, dass den Exporteur ca 10 USD kostet, werden für 30cent CXO-Token geburnt und für 30 Cent tokenholder bezahlt, die als Relayer ihre Token „gestaked“ haben und damit die neutrale Blockchain darstellen. Der Rollout dieses Real World Produktes hat bereits begonnen: in Ägypten ist es seit 2 Jahren im Einsatz, verpflichtend für alle Exporte. Vereinigte Arabische Emirate folgen in 2025, der 8.größte Container-Reeder der Welt (HMM aus Südkorea) führt es auch ein. Mit vielen Ländern ist man in Verhandlungen über ein Rollout auch dort. Es dauert nur leider lange (meist Jahre), da es eben staatliche Stellen sind… Aber alle großen Länder haben sich verpflichtet, in den nächsten 10 Jahren ihren Handel zu digitalisieren. Vom Prinzip her ein NoBrainer: es macht finanziell Sinn, viele werden diese Neuheit nutzen in den nächsten 2-10 Jahren, CXO ist durch die burns deflationär. Konkurrenz ist zwar auch da, aber CargoX kann auf den Live-trackrecord in Ägypten verweisen. Herausforderungen: schwache Liquidität (Uniswap), Token ist unbekannt und wird von Firma nicht beworben (da Crypto bei staatlichen Stellen Vorurteile auslösen kann, wegen Teufelszeug und so…) Pro: Sehr eingefleischte TG Community
hahahahaha calm down bear. the top???? TOP????? HAHAHAHAHA please PLEASE be quiet. Quiet now. Bear. LOOK AT BITCOIN. WHAT IS IT? HMM?????? WHAT IS IT????? yup. Its at 61k........ why??????? CUZ WE ARE WINNING SO STOP!!!!! You sad bear.... sad sad..... sad ..... bear..... sad.....
If U take THE TIME to look into IT, then dat would be GREAT!!! They claim to only git THE MINER FEE, HMM!!! : (!!!
And with names like HMM, PLOP and JEB