Quant & Trading

Quant & Trading holds 30 saved posts from 5 creators, saved between 2026-01 and 2026-10 (2 S-tier, 11 A-tier, 14 B-tier, 3 C-tier). The most-tagged tools are Python, NumPy, Numba, VectorBT and joblib. Most-saved creators: @quant.dhawan (26). 3 curated guides draw 3+ entries from it, starting with Physics Models → Market Alpha: When Scientists Become Traders, 25 Agents Walk Into a Market: AI-Powered Trading Infrastructure, Forecast the Weather, Not the Price — gating models by tradeability.

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All 30 entries · best first

  1. SWasserstein Distance — measuring the backtest-to-live reality gapUses Wasserstein Distance and Sinkhorn Divergence to mathematically measure drift between backtest distributions (blue) and live market conditions (orange). Detects…@quant.dhawan · 2026-02-15 · technique
  2. SHurst Exponent — 3D surface of BTC memory and mean-reversion zonesPlots the Hurst Exponent of BTC-USD as a 3D surface. H>0.5 = trending (momentum), H<0.5 = mean-reverting, H=0.5 = random walk. Shows how market 'memory' varies across…@quant.dhawan · 2026-01-08 · technique
  3. AHidden Markov Models — detecting market regime shifts automaticallyUses HMMs to mathematically deduce hidden market states from observable returns and volatility. Identifies low-vol bull, high-vol bear, and recovery regimes. Better than…@quant.dhawan · 2026-04-07 · technique
  4. AOrnstein-Uhlenbeck Process — mean reversion for pairs tradingSimulates the OU process showing mean reversion dynamics with theta (reversion speed), mu (equilibrium), and sigma (noise). Core model for pairs trading, interest rate…@quant.dhawan · 2026-03-12 · technique
  5. AVolatility Surface — regime shifts from smile to smirk3D visualization of implied volatility surface (moneyness x maturity x IV). Shows how the surface warps from gentle 'smile' to steep 'smirk' before tail-risk events as…@quant.dhawan · 2026-02-22 · technique
  6. AOmori's Law — earthquake aftershock math applied to market crashesApplies geophysics' Omori's Law to financial markets. Post-crash volatility aftershocks decay at a predictable rate following power-law dynamics, not randomly. Shows…@quant.dhawan · 2026-02-19 · technique
  7. ALempel-Ziv Complexity — compression algorithms to detect market predictabilityApplies the LZ compression algorithm (behind .zip files) to financial time series. When LZ complexity is low, patterns repeat and the market is more predictable. When…@quant.dhawan · 2026-02-03 · technique
  8. AMonte Carlo — 25,000 shuffled BTC returns to separate edge from luckRuns 25,000 Monte Carlo simulations by shuffling daily BTC-USD returns to test whether a strategy's performance is genuine edge or statistical luck. One backtest isn't…@quant.dhawan · 2026-01-25 · technique
  9. AMinimum Spanning Tree — graph theory reveals S&P 500 hidden structureApplies graph theory (Minimum Spanning Tree) to the S&P 500 to map the hidden network structure between stocks. Reveals sector clusters and systemic risk connections…@quant.dhawan · 2026-01-23 · technique
  10. AKalman Filter — adaptive signal extraction for non-stationary marketsFinancial data is non-linear and non-stationary, breaking standard filters. Kalman Filter adapts in real-time, unlike lagging moving averages or FFT (which assumes…@quant.dhawan · 2026-01-14 · technique
  11. ARandom Matrix Theory — cleaning correlation matrices from noiseStandard correlation matrices treat random noise as valid connections. Random Matrix Theory (RMT) filters eigenvalues to 'clean' the matrix, keeping only statistically…@quant.dhawan · 2026-01-11 · technique
  12. APhase Space Reconstruction — unfolding hidden BTC volatility dynamicsUses Phase Space Reconstruction (PSR) with time delay tau=3 to unfold BTCUSD volatility into a multi-dimensional manifold. Reveals whether market is in stable regime or…@quant.dhawan · 2026-01-06 · technique
  13. AVectorBT Grid Search — mmap data, joblib batching and vectorized backtestsA speed recipe for strategy grid searches with VectorBT: load OHLCV via numpy memmap (mmap_mode='r', copy=False) to avoid RAM blowups, fan thousands of backtests across…@quant.dhawan · 2026-01-02 · technique
  14. BFive fringe GitHub repos — WiFi sensing, offline 400B LLM, satellite captureA hype-framed listicle of open-source projects: RuView turns WiFi into a through-wall person sensor, Flash MoE runs a 400B model on an iPhone offline, a walk-through…@cracked.artificial · 2026-09-30 · repo
  15. BHeston Model — stochastic volatility for realistic options pricingExplains why Black-Scholes fails (constant vol assumption) and how the Heston Model introduces stochastic volatility. Captures the volatility smile and skew that basic…@quant.dhawan · 2026-04-09 · technique
  16. BCox Process — doubly stochastic Poisson for bursty market eventsStandard Poisson processes assume constant event rates, but markets are bursty. The Cox Process (Doubly Stochastic Poisson) uses a CIR-driven random intensity to model…@quant.dhawan · 2026-04-08 · technique
  17. BAvellaneda-Stoikov — optimal spread calculation for market makersThe Avellaneda-Stoikov model solves the stochastic control problem for market making. Calculates optimal bid-ask spread based on volatility, time horizon, and inventory…@quant.dhawan · 2026-04-06 · technique
  18. BHFT short-term reversal — buy weekly losers, sell winners across 4,500 stocksA 60 Minutes clip with Manoj Narang describing a cross-sectional mean-reversion test: buy $5 of stocks down 5% last week, sell $10 of stocks up 10%, across the whole…@7am.research · 2026-04-05 · technique
  19. B3D Yield Curve Surface — visualizing cross-asset macro regimes3D visualization of yield curve dynamics across macro regimes: COVID-19 vol shock (VIX spike, yield compression), Fed tightening cycle (curve inversion). Shows how…@quant.dhawan · 2026-02-25 · technique
  20. BSingular Spectrum Analysis — non-parametric trend extraction from noisy dataSSA decomposes time-series into trend, cycles, and noise without assuming a fixed functional form. Breaks data into reconstructed components (RC 1+7 trend, RC 2+3…@quant.dhawan · 2026-02-10 · technique
  21. BFast Fourier Transform — decomposing NVDA price into frequency signalsApplies FFT to NVDA price action to decompose it into frequency components, separating noise from dominant cycles. Shows how to identify the strongest periodic signals…@quant.dhawan · 2026-01-27 · technique
  22. BAvalanche Model — self-organized criticality explains market crashesMarkets reach self-organized criticality where small perturbations trigger cascading failures. The 'news' doesn't cause the crash — the system was already at a critical…@quant.dhawan · 2026-01-21 · technique
  23. BIsing Model — modeling herd behavior and market phase transitions3D lattice visualization of the Ising model applied to financial markets. Blue=sellers, orange=buyers. At high volatility the market is random; as social pressure…@quant.dhawan · 2026-01-19 · technique
  24. BTick Data vs OHLC — you're trading on 0.002% of available dataDaily OHLC candles compress ~86,400 seconds of market data into 4 numbers — throwing away 99.998% of information. Makes the case for tick-level and limit order book…@quant.dhawan · 2026-01-17 · inspiration
  25. BLyapunov Exponent — measuring chaos in BTC tick-level microstructureVisualizes the Lyapunov Exponent of BTC-USD microstructure data. Positive exponent = chaotic/unpredictable, negative = deterministic. Reveals that what looks random on…@quant.dhawan · 2026-01-15 · technique
  26. BContinuous Wavelet Transform — time-frequency analysis of QQQApplies CWT to QQQ to analyze frequency-domain dynamics over time. Unlike FFT (fixed window), wavelets capture how dominant frequencies shift across regimes. Reveals the…@quant.dhawan · 2026-01-13 · technique
  27. BStable Distribution — modeling fat-tailed crashes beyond GaussianMarkets go up slowly but crash fast. Standard Gaussian models underestimate crash probability. Uses Stable (Levy) distributions to properly model fat tail events and…@quant.dhawan · 2026-01-09 · technique
  28. CEMA9 + VWAP crossover — automated 3-minute options strategy pitchPromo for the RoboQuant platform: buy calls or puts when EMA9 crosses VWAP on the 3-minute chart, with a claimed $179k month and 79.9% prop-challenge pass rate. The…@timhutter.official · 2026-10-20 · technique
  29. CJim Simons and the Riemann Hypothesis — the benchmark for AI math claimsAnecdote about Renaissance Technologies founder Jim Simons lighting up when asked if he'd trade his fortune to solve the Riemann Hypothesis, used to argue that RH has…@ffppod · 2026-08-13 · inspiration
  30. CWave Function Collapse analogy — modeling pre-event price uncertaintyDraws analogy between quantum wave function collapse and price discovery after news events. Pre-event price is a probability distribution; the event collapses it to a…@quant.dhawan · 2026-02-28 · technique

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