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A discrete Markov chain is basically a random walk on a graph, where each outgoing edge has a fixed probability. Cool fact: any initial distribution on a sufficiently nice* Markov chain converges to its stationary distribution after many steps—because it's a contraction mapping.

Keenan Crane

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181,771 views • 2 years ago •via X (Twitter)

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One of the simplest algorithms for sampling from a probability distribution is Random Walk Metropolis-Hastings. It proposes new samples by taking Gaussian-distributed steps, accepting or rejecting them to maintain the target distribution. I call this pdf the "fidget spinner".

One of the simplest algorithms for sampling from a probability distribution is Random Walk Metropolis-Hastings. It proposes new samples by taking Gaussian-distributed steps, accepting or rejecting them to maintain the target distribution. I call this pdf the "fidget spinner".

Alec Helbling

79,904 views • 1 year ago

$GRASS is live on Robinhood Chain. If you want a stock, walk to it. CA : 0x16391c40e85fb2246a2c8c17bfa2594c5d3ef84b

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💿 Sonova Presents: PlayCat’s Debut into Soneium Chain Great days ahead Sonieum 💿 Community! PlayCat has officially landed on the Soneium chain and is making its debut as an Official Builder in Soneium chain! 🐱 This is not a drill — it's a purr-fect storm of innovation, fun, and serious blockchain IP mastery. PlayCAT 🐱 is bringing the heat, helping build a future in Soneium one paw-some leap at a time! Get ready to watch this kitty take over the blockchain universe — because where PlayCat lands, the culture thrives! 💿

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Sonova💿

28,990 views • 1 year ago

⚡ @SupraOracles is excited to announce the integration of our decentralized Verifiable Random Function (dVRF) service on BNB Chain (BNB Chain) 🎉 This allows devs on BNB Chain to access a provably fair source of randomness for GameFi, #NFT minting, and on-chain lotteries 🎮

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267,100 views • 2 years ago

Why did most major banks build tokenization on a private chain? Because deal terms, trading volumes, and business relationships can't be public. OPN Chain has a native privacy layer. Sensitive data stays encrypted off-chain. Validators never process private payloads. Privacy isn't an add-on. It's the foundation. Accelerate ⋂

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A Carnegie Mellon student launched a Markov Chain model that reads the structure beneath the price and made $67,000 in three weeks on Polymarket. In his applied mathematics classes he studied Markov Chains - the same model physicists used to simulate neutrons in nuclear reactors. The same model describes how prices move on prediction markets. He wrote a Python script. > Takes 60 days of contract price history. > Builds a transition matrix - a map of how the price actually moves between states. > Runs 10,000 simulations in a tenth of a second. > Calibrates the result against data from 72.1 million real trades. The output is an exact probability and position size. No gut feeling. His first test day brought $3,400. A week later he improved the result and hit $17,000. His balance has now reached $67,000. full guide on how to build the same model - in the article below.

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Damir Akaza

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Institutions want to build on Ethereum and leverage its incorruptibility, hard finality, and global liquidity. But many financial use-cases can’t be run on a chain where everything is public by default. Here’s how Prividium extends Ethereum for enterprises:

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BSCN

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HOOD10 Index

11,229 views • 16 days ago

Math quant bot on Polymarket made over $457K PnL in 20 days - he turned $7,387 → $457k profit it uses Markov Chains to find "mispriced" windows on BTC and ETH up/down markets - made 14,200+ predictions, with ~$22,850 avg. daily profit by exploiting gaps humans miss at 3AM strategy: a 1h BTC/ETH up/down market is a binary contract it pays $1 if event happens → $0 if not Markov Chains give you the probability of the next market state based on: > current state of the market (up / down / flat) > transition matrix built from live price data > diagonal persistence value - how stable the current state is formula: p̂ − market_price ≥ 0.05 AND P(j, j) ≥ 0.87 bot profile: - read article below to understand how Markov Chains are used to extract edge from prediction markets

bodila

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renaissance technologies hasn't had a losing year since 1988 not because they're smarter or have better data they're asking a completely different question than everyone else while retail asks "will it go up" quant desks ask something else entirely which state is the market in right now, and with what probability does it transition to the next tool for that: markov chains markets cycle through states - trending, ranging, volatile, reversing each transition has a historical probability you can calculate trending -> stays trending: 48% trending -> ranging: 34% trending -> reversing: 18% you don't pick direction. you calculate expected value across every possible transition enter only when the math is positive that's it. that's the entire edge the framework is 119 years old - andrei markov published it in 1906 it's in every statistics textbook on earth nobody in your trading group ever mentioned it paper is free, data is free, implementation is 200 lines of python they kept you staring at candles while they ran probability tables Bookmark it or lose last chance to be quant

renaissance technologies hasn't had a losing year since 1988 not because they're smarter or have better data they're asking a completely different question than everyone else while retail asks "will it go up" quant desks ask something else entirely which state is the market in right now, and with what probability does it transition to the next tool for that: markov chains markets cycle through states - trending, ranging, volatile, reversing each transition has a historical probability you can calculate trending -> stays trending: 48% trending -> ranging: 34% trending -> reversing: 18% you don't pick direction. you calculate expected value across every possible transition enter only when the math is positive that's it. that's the entire edge the framework is 119 years old - andrei markov published it in 1906 it's in every statistics textbook on earth nobody in your trading group ever mentioned it paper is free, data is free, implementation is 200 lines of python they kept you staring at candles while they ran probability tables Bookmark it or lose last chance to be quant

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Euclid was built to unify movement across chains, turning fragmented liquidity into a connected network. Today we have a new objective 🚀 → Complete a total of 25 transactions → 5 transactions on each chain → Each transaction must be at least $5 → Required chains: Base, Polygon, Monad, BNB Chain, Arbitrum Your reward is a high-grade stamp: → "Constellation Runner" and 50,000 Astra

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212,467 views • 2 years ago

♾ Onefinity Chain ♾ The next steps have been solidified, and the path to the future is now set. OneFinity Chain is poised to be the first EVM-compatible Sovereign Shard on Multiversᕽ, charting a clear path for the future. #MultiversX #EGLD

♾ Onefinity Chain ♾ The next steps have been solidified, and the path to the future is now set. OneFinity Chain is poised to be the first EVM-compatible Sovereign Shard on Multiversᕽ, charting a clear path for the future. #MultiversX #EGLD

OneFinity Chain | Testnet September 23rd

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A new primitive is on its way. xRWA enables tokenized equities to be staked for network security — activating real-world assets directly within a multi-asset PoS architecture. Powered by $BB on BounceBit Chain.

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