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"In TradFi, options volume often exceeds spot. In crypto, it's 5% of it." Jaewon Yu, CCO at @SignalPlus_Web3 — the platform handling 20–25% of global crypto options volume — on the gap he thinks is about to close fast. Just over six months since launch in October 8, 2025, Bullish options has become #2# globally for BTC options by open interest (The Block) and still growing, with institutional-grade infrastructure and deep liquidity through our global order book. Are your firm positioned for this “tremendous growth”? (Views expressed are those of the speakers and do not represent the views of their organizations. Options trading involves significant risk and is not suitable for all investors. Please review Bullish's risk disclosures prior to trading. This is not investment advice.)

👀 Top Crypto Fundraising Last Week 1️⃣ Kalshi (@Kalshi) - $1.2B; Prediction Markets 2️⃣ Exa (@ExaAILabs) - $250M; API, x402 3️⃣ Variational (@variational_io) - $50M; DEX, Perpetuals, Options 4️⃣ SignalPlus (@SignalPlus_Web3) - $40M; CEX, Perpetuals 5️⃣ Dust (@DustHQ) - $40M; Developer Tools 6️⃣ PopDEX (@popdex_) - $30M; DEX, Perpetuals 7️⃣ Catena Labs (@catena_labs) - $30M; Payments, AI, AI Agents 8️⃣ TownSquare (@TownSquarexyz) - $16M; Yield Aggregator, Lending, RWA 9️⃣ Eisen - $10.0M; RegTech 🔟 Checker (@checkercorp) - $8M; API

We are proud to have hosted the "Closed-door Roundtable on the 15th Five-Year Plan and the Blueprint of Hong Kong's Digital Finance Ecosystem over the Next Five Years". With discussion led by Legislative Council Member Hon. Duncan Chiu, 22 industry leaders representing core aspects of Web3 ecosystem in Hong Kong shared feedback on their past development and presented suggestions which may contribute to Hong Kong's next 5-year strategic Web3 blueprint. An incredible lineup of blockchain infrastructure leaders, institutional digital asset participants and platforms, regulatory experts and Web3 trailblazers engaged in high-frequency, unfiltered strategic discussions across five core tracks, including: - Digital Finance Policy - Institutional Crypto Adoption & Tokenized RWA - Compliance & Security Infrastructure - Stablecoins & Digital Payments - Hong Kong Hub for Innovative Technology Companies @henrychen_cy from @snzholding representing co-operator of Hong Kong Ethereum Community Hub (ETH HK Hub) attended the roundtable discussion and provided suggestions including Incentivizing Talents and Web3 Innovation in Hong Kong, enabling easier localization infrastructure for start-up Web3 companies, clarity on VA advisory and management licensing regime, recognition of ecosystem built upon open protocol and permissionless blockchain etc. Our mission is to act as the ultimate community platform providing critical infrastructure, resource support, and business acceleration for Web3 entrepreneurs especially technical founders. Thanks for participation from industry leaders including: @snzholding @HashKeyGroup #AnchorpointFinancialLimited# @animocabrands @BaillieGifford @chainlinklabs #EFUNDHK# @galaxyhq @OrderlyNetwork @RD_Technologies @SignalPlus_Web3 @SlowMist_Team @StarchildOnX

THE MATH NEEDED FOR TRADING (COMPLETE ROADMAP): today I'll will break down the essential math you need for trading & this is the exact roadmap that helped me personally when i started, i thought math was for interviews, two months into live trading i realized every position i took was pure math running in production here's the complete map of what math actually fires on real trades: --------------- 1. statistics and probability every price move is signal plus randomness. statistics separates the two what you need: > mean, median, expected value = EV formula (win% × avg win) - (loss% × avg loss) is what you're actually maximizing > variance and standard deviation = foundation of every position sizing formula, becomes volatility when applied to returns > correlation from -1 to +1 = tells you if strategies are actually independent > correlation 0.9 across 3 strategies = you have one strategy dressed as three > conditional probability = the biggest edge upgrade retail misses. P(win) = 55% unconditionally, but 70% when VIX < 15 > Bayes' theorem = how you update beliefs when new information arrives. never work with static beliefs > central limit theorem = why portfolio-level statistics behave cleaner than individual trades > linear and logistic regression = building blocks for mean reversion and binary prediction --------------- 2. linear algebra the moment you hold multiple positions, you're doing linear algebra whether you know it or not what you need: > scalars, vectors, matrices = your portfolio is a weighted sum of vectors > portfolio variance = w^T Σ w. not the sum of individual variances. one matrix operation > eigenvalues and eigenvectors = reveal where risk actually lives. in a 500-stock universe, top 5 eigenvectors explain 70% of variance. the other 495 are noise > PCA and SVD = reduce 50 correlated indicators into 5 independent factors explaining 90% of variation --------------- 3. time series analysis markets have memory. today's price depends on yesterday's. volatility clusters. trends persist what you need: > stationarity = assumption most statistical tests make, but markets aren't stationary, this is why strategies decay when regime shifts > autocorrelation = positive means momentum, negative means mean reversion, zero means random walk > ARIMA = framework for forecasting returns and volatility > GARCH = formalizes what every trader knows, volatility clusters. after a big move expect more volatility > cointegration = the foundation of pairs trading. two assets can both trend but their spread stays stationary --------------- 4. risk management math edge doesn't matter if you size wrong what you need: > Value at Risk = 95% VaR of $5,000 means 95% of the time you won't lose more, but 5% of the time you might lose much more > Sharpe ratio = (return - risk-free rate) / volatility. institutional threshold is Sharpe > 1.5 before deployment > maximum drawdown = biggest peak-to-trough loss. more intuitive than volatility for most traders > Monte Carlo simulation = randomizes trade sequencing to show the range of possible outcomes > Kelly criterion = f* = (bp - q) / b. professionals use 0.25x to 0.5x fractional Kelly because your true edge is never certain --------------- 5. stochastic calculus (for options) if you trade options, every price on your screen came from a stochastic differential equation what you need: > Black-Scholes = dS = μS dt + σS dW. the underlying follows geometric Brownian motion > Ito's Lemma = why the σ² term exists. this is why gamma exists > Heston stochastic volatility = dv = κ(θ - v)dt + ξ√v dW. captures the volatility smile that Black-Scholes misses > delta hedging = stochastic calculus running in production. every rehedge is dictated by the SDE governing the underlying --------------- MINIMUM TO START you don't need everything above to start for your first backtest: > mean, median, standard deviation > correlation > basic probability > Sharpe ratio and max drawdown start with statistics, that alone separates you from 95% of retail traders --------------- every real trade is math executing in production: > entry = conditional probability > validation = statistics > portfolio = linear algebra > sizing = Kelly optimization > risk = VaR, Sharpe, max drawdown > options = stochastic calculus the traders who make consistent money see markets as continuous equations, everyone else guesses if you're a complete beginner shoot me a DM and I'll share the resources with you MATH IS EVERYTHING <3