PLATFORM▸DOCS
↻🔔
DOCUMENTATION
⊞Platform Overview
◈Methodology
⊘Calculation Notes
◉Data Pipeline
◆Signal Framework
◐Module Reference
◎Research Process
⇌Hypothesis Testing
▣Thesis Builder
⊛Risk Framework
◇Research Papers
◫Roadmap
⊕API & Integrations
# SHARPE MIND DOCSV5METHODOLOGY
Complete platform reference — methodology, data pipeline, signal framework, research process, and module documentation.
# Sharpe Mind — Moneda Research & Zero Ai Labs | Docs current as of the August 30, 2026 deploy
⊞PLATFORM OVERVIEW
SHARPE MIND is a market data superintelligence terminal built by Zero Ai Labs. It integrates traditional trading data (options chains, equities, macro) with alternative intelligence sources (foot traffic, prediction markets, satellite imagery, social sentiment) to generate high-signal, cross-referenced trade ideas.
Unlike conventional terminals that present data in silos, SHARPE MIND is designed as a convergence engine — every module feeds into every other module. A foot traffic anomaly at Walmart connects to options IV surfaces, which connects to Kalshi prediction market probabilities, which connects to the signal engine thesis builder. No data point exists in isolation.
Core Principles
High Signal Only
Every feature must reduce noise, not add it. If data doesn't contribute to conviction, it doesn't ship.
Cross-Module Flow
Every data source connects to at least 2 other modules. Isolated data = low value. Connected data = alpha.
Speed Over Decoration
Sub-2-second load times on mid-tier hardware. No heavy 3D renders by default. Performance is a feature.
Hypothesis-Driven
Every interaction follows: Detect → Confirm → Structure → Execute. The platform guides decision-making, not just data display.
Module Architecture — 25 Modules
Live IntelligenceStableToday's traffic pulse (all 25 tickers), earnings radar, sector rotation heatmap, active signal scanner
Options TerminalStableφ Options Engine — gamma exposure, 13 greeks, 9 vol surfaces, dealer positioning, 9-point convergence signals
Sector MapStableDealer positioning by sector: each sector's hedging vehicle (its own ETF option book) beside how many of its constituent names sit short gamma. Breadth is a COUNT, never a sum — un-dollarised gamma tilt cannot be added across tickers of different share prices.
Kalshi PredictionStableCFTC-regulated event contracts — CPI, Fed, GDP, BTC, AI milestones — with orderbook depth and cross-ref to equities
Polymarket TerminalStableDecentralized prediction markets via Gamma API (free). Cross-ref with Kalshi for arbitrage signals. Auto-categorized into SHARPE MIND macro channels.
YFinance TerminalStableCBOE delayed quotes, OHLCV charts with 10 indicators, full options chain by strike/expiry, Black-Scholes greeks as toggleable studies and visualization charts.
Foot Traffic V5Stable25-ticker, 8-sector foot traffic intelligence with BestTime.app live data (16 live, 9 modeled), 24hr heatmaps, Kalshi bridge, supply chain pipeline
Signal EngineBeta10-source cross-reference matrix, institutional thesis builder template, indirect variable chain mapping
Alt Data HubBetaSatellite imagery, social sentiment, credit card spend, shipping, weather, job postings, CRE trends
Odds TerminalBeta10 sportsbooks via The Odds API + PropOdds — FanDuel, DraftKings, BetMGM, Pinnacle, Circa + 5 more. 7 sports, sharp line detection
YF Options TerminalStableCBOE Data — individual strike charts, full options chains with toggleable Greeks (Δ Γ Θ ν ρ σ), 10 technical indicators/studies, candlestick/line/area charts
Order Flow TerminalBetaPrediction market microstructure — 95-99¢ liquidity evaporation detector, smart money signals, Kalshi-style order book, bid/ask depth visualization, flip probability scanner
Whale TrackerStableSharp money leaderboard — hit rates, ROI, streaks, P/L tracking. Polymarket whale positions, sports sharp bettors, and prediction market big movers.
Alpha SignalsStableReal SEC Form-4 insider transactions (Alpha Vantage) over a rolling 12 months plus reported-vs-estimate EPS for the last 8 quarters; sector scan via SEC EDGAR. An acquisition covers option exercises, vestings and grants, not only open-market buying.
SeasonalityStableHistorical monthly return patterns from 1981-2026. Regime analysis, seasonal strength scoring, customizable themes across tickers and sectors.
Social SentimentStableReddit/Twitter mention velocity, meme score, viral probability, trend direction for 25 tickers. Live API with auto-refresh.
Crypto On-ChainStableExchange net flows, whale accumulation scores, reserve changes, NVT ratio, BTC correlation for 20 crypto + equity tickers via CoinGecko and DeFiLlama.
Web TrafficModeled25 digital tickers — monthly visits, bounce rate, session duration, mobile share, YoY growth. Modeled from per-ticker baselines for illustration — not measured or vendor-sourced.
S&P 500 HeatmapStableTop 100 S&P 500 constituents by index weight with live prices, % change, volume. Sector filtering, sortable columns, color-coded performance heatmap.
Wall Street ConsensusStableAggregated bank research calls, price targets, ratings from major investment banks. RSS-sourced analyst reports with sentiment scoring.
Globe GEOINTStableLeaflet map with 15+ data layers — earthquakes (USGS), wildfires (NASA FIRMS), aircraft, ships, weather, radiation, conflict events. Real-time geospatial intelligence.
Live News StreamsStableLive TV feeds from financial news networks (Bloomberg, CNBC, Fox Business) via YouTube embeds. Picture-in-picture dock for multi-stream monitoring.
Google TrendsStableReal-time search interest data for tickers and topics. BigQuery-powered trend analysis with SerpAPI fallback. Volume spikes and relative interest scoring.
X IntelligenceStableLive tweet feed with category filters (market, crypto, politics, sports). Trending topics, engagement metrics, and sentiment analysis from X/Twitter API.
◈METHODOLOGY
SHARPE MIND's methodology is built on a single thesis: alternative data, when properly cross-referenced against traditional market signals, produces a measurable information advantage. This advantage is strongest in the 2-8 week window before earnings announcements, when foot traffic and consumer behavior data leads sell-side estimates.
The Information Advantage Chain
Traditional sell-side research relies on survey data, management guidance, and historical financial models. These inputs lag reality by weeks to months. SHARPE MIND inverts this by collecting real-time physical-world signals and mapping them to financial outcomes before the consensus catches up.
Physical-World Signal→Traffic/Spend Pattern→Revenue Estimate Delta→Earnings Surprise→Options Mispricing→Trade Execution
Three Layers of Intelligence
Layer 1: Primary Data
Direct measurement of consumer behavior — GPS foot traffic, beacon signals, WiFi probe counts, satellite parking lot imagery. These are the closest signals to actual revenue. Lag: 0-2 weeks.
Sources: BestTime.app (live), GPS aggregators, satellite imagery providers, mobile app engagement data
Layer 2: Transmission Channels
Macro and market signals that cause or correlate with traffic changes — CPI, Fed funds rate, unemployment, GDP, Bitcoin price. These are the 'why' behind traffic shifts. Lag: 1-8 weeks.
Sources: Kalshi prediction markets (KXCPI, KXFED, KXGDP, KXUNRATE, KXBTC, KXAI), Federal Reserve data, BLS reports
Layer 3: Market Microstructure
Options positioning, dealer gamma exposure, vol surface topology, open interest concentration, institutional flow. These are the 'how to trade' signals. Lag: real-time to days.
Sources: OPRA options chain, φ Options Engine engine, Polygon.io market data, Massive Market Data aggregator
Convergence Scoring
No single data source is sufficient for a trade thesis. SHARPE MIND uses convergence scoring — counting the number of independent signals that align on the same directional bias. The scoring framework:
0-1 signals
NO TRADE
Insufficient convergence. Single-source signals = speculation.
2-3 signals
WATCHLIST
Emerging thesis. Monitor for additional confirmation before committing capital.
4-5 signals
MODERATE
Credible thesis. Reduced position size. Set wider stops.
6+ signals
HIGH CONVICTION
Full convergence. Full position size. Thesis template complete across all 8 sections.
⊘CALCULATION NOTES
These are the decisions that determine whether a number on this terminal can be trusted. Most are not visible in the output: they are choices about what to do when a figure cannot be computed, when a sample is too small to mean anything, or when two numbers on one screen were measured at different times. They are recorded here because a reader cannot audit them from the screen alone.
The through-line is that the terminal would rather report less than report something confident and wrong. Where a calculation has no valid answer, the page says so and gives no number.
Decisions Behind the Numbers
Unbounded risk is reported as unbounded
A short naked call loses without limit. Sampling a price grid and taking the worst point would print a specific, confident, wrong number on exactly the position where being wrong costs most. /strategy derives the tails from the payoff's SLOPE instead, so max loss reads "Unlimited" rather than a figure. RISK BUDGET then refuses to size such a structure at all: there is no worst case to divide by.
Downside is evaluated at zero, not at unbounded
The underlying cannot go below zero, so a short put reports a bounded loss rather than "unlimited". A 1x2 ratio spread is still caught as unbounded despite holding a long leg. The distinction comes from the slope, not from the leg count.
Greeks are a local approximation; the scenario grid reprices
Net delta and gamma describe the book at the point it sits at, and degrade on the large fast move you most want to survive. /portfolio RISK revalues every option with Black-Scholes across a spot-by-vol grid and draws the delta+gamma estimate ALONGSIDE it, so the divergence is visible rather than implied. On a live short straddle the two disagreed by roughly $82,000 at a 15% move.
Time decay is not theta multiplied by days
Theta accelerates into expiry, and a leg can lapse inside the horizon. IF NOTHING MOVES walks T forward and reprices, so the curve captures both. On a book holding a 6-day and a 66-day call it bled $240/day for five days and $31/day after day 30 — a linear projection of the opening rate would have been wrong by more than four times.
The contract multiplier is explicit
Journal P&L is (exit − entry) × qty × multiplier. Options rows carry 100; share rows default to 1. Without it a 2-lot closed 1.945 → 1.00 logs $1.89 instead of $189 and quietly corrupts every aggregate the moment options and share trades share a book. P&L % is deliberately multiplier-free, because it is a ratio.
Small samples do not get a verdict
WHAT IS WORKING withholds win rate below five trades, marks the bucket thin, and excludes it from best/worst. A 100% win rate on one trade is 100% by construction; shown beside a 55% on forty it invites exactly the wrong reading, because the eye takes the biggest number rather than the sturdiest.
Null is not zero
A position with no live mark is excluded from P&L and counted, never valued at zero. An undated journal row sinks below dated ones instead of sorting as though it were newest. A missing figure sorts last in BOTH directions, since a blank is not the smallest value. Where a worst case cannot be computed, the page prints a dash rather than a confident zero.
Dealer positioning is modelled, and dated
Every OI ANALYTICS figure comes from the stored options-OI snapshot refreshed by a nightly weekday cron — it is the latest STORED day, not live intraday. Where a modelled dealer figure sits beside a live one, as in YOUR Γ vs DEALER Γ, the page names the snapshot date and its age, because printing them side by side would otherwise imply a simultaneity that does not exist.
13F staleness is reported at both ends
Institutional filings are quarterly AND staggered. /ownership reports the age of the newest row and the oldest: NVDA's newest holder was 40 days old while Vanguard, its largest, had last reported 221 days earlier. Quoting only the newest date would imply the whole table is that fresh.
Regime work is descriptive, not predictive
/gamma-regime reports what dealer positioning has been, not what price will do. /regime-study exists precisely so the long-versus-short-gamma tendency is TESTED against realized moves rather than assumed, and it shows its sample sizes. The cross-asset macro tilt is framed as a conditions snapshot, never a forecast or advice.
Volume above open interest does not confirm an opening trade
On /options-ratios a vol/OI ratio above 1 marks heavy activity, but closes and round-trips look identical to opens in that data. ΔOI-confirmed opening volume is a separate, T+1 measurement and lives on /oi-volume.
The earnings reaction window follows the report time
A post-market print is measured report-close to next close; a pre-market print prior-close to same close. Using one window for both mis-attributes roughly half the sample by a full session. Adjusted close guards a split or ex-dividend landing on the reaction day.
If it cannot be derived from the inputs, it is not shown
A CBOE chain snapshot carries no prior day, no price history, and no dark-pool prints. The GEX terminal once displayed all three anyway — "previous-day OI" as today × 0.95, a "historical move" as the implied move × 1.15, a Dark Pool chart of permanent zeros. An adversarial audit removed seven such fabrications in August 2026; anything that remains modelled is labelled MODELED where it renders.
Realized vol comes from actual closes, and splits are excluded, not clamped
RV is close-to-close log returns, zero-mean, annualized ×√252, from real daily prices. The close series is unadjusted, so a 2:1 split prints as a −50% "day" that alone would read as ~246% vol; returns beyond the split threshold are EXCLUDED AND COUNTED — NVDA's history shows exactly its 5 real splits — never clamped, because clamping draws a confident value exactly where the data is broken.
Vol premiums compare matched horizons
VRP is ATM IV at the expiry nearest 30 days minus RV20, and short-dated VRP pairs ~1-week IV with RV5. Averaging IV across the whole curve against a 20-session RV flips the premium's sign in a steep term structure, and the weekend-crushed 2-day front against RV20 is nonsense — live SPY read 5.5% on the front against 12% one month out on the same afternoon.
The vol surface is the market's, holes included
Every IV cell on the 3D surfaces and heatmap is a quoted contract's implied vol — the out-of-the-money side, since deep-ITM quotes carry broken marks (a live 561% "IV" was the tell). A cell with no valid quote is a visible hole with grid coverage stated, never an interpolated guess. Greeks on those tabs are Black-Scholes over each cell's market IV.
DTE is counted in calendar days, everywhere
Days-to-expiry is a difference of calendar dates, not of instants. The old rounding of (expiry midnight − right now) dropped by one after local noon, so the same expiry read 7d in the morning and 6d after lunch — and two panels on one screen could disagree. Expiry dates are read in the UTC frame they are encoded in; "today" is the user's local date.
An option expiring today is live, and an expired one is cleanup
On expiry day the naive time difference is already negative hours before the close, which once classified the most urgent position on the board as already dead — the one alert the expiry radar exists to send could never fire. dte 0 means "expires today, still trading". A row past its date is reported for cleanup, never as a deadline: it still carries its cost into every sum.
OpEx roll-off is measured spot-free, on the session that expired
Book size around expiration is gamma × open interest with no spot in it — the dollarized GEX moves when price moves even if no contract changed hands, and a test with a deliberately constant book showed price drift alone reading as 12 of 14 cycles "rolling off". Cycles anchor on the last session ON OR BEFORE the third Friday (holiday Fridays expire Thursday), offsets count trading sessions, and thin buckets are flagged with their n. Finding: gamma reliably shrinks (−17% to −42% median across the universe) while realized moves after expiration are indistinguishable from before (~1.00).
Concentration is gross, in delta dollars
Where the risk sits is measured as each name's share of GROSS |delta$| — a long in one name and a short in another do not offset the way a net figure implies, since correlated names fall together and both legs lose. Net is shown alongside, never instead. Position counts are not used (a deep-ITM and a far-OTM lot are not equal risk), unpriceable legs are named rather than zeroed, and a book under three names gets no headline at all.
Account value is what was observed, when it was observed
The account-value series records one point per VISITED local day (latest look wins), only when every position is priceable — a half-marked book records nothing rather than a fake cliff. It is net position value with no cash tracked, drawdown is labelled OBSERVED because the true peak may fall on an unvisited day, and the chart's dots are the data; the line between them is a guide for the eye.
The P/C percentile is windowed, because the ingest changed underneath it
Whole-book put/call history splits FLOW (that day's volume ratio) from the STANDING book (open interest), across ALL expiries so a hedge rolling between expiries doesn't read as a positioning change. The store's early history was backfilled with a ±25% moneyness filter while the nightly refresh captures the full chain, so far-OTM put wings STEP the OI ratio up at that boundary — the chart shows the step as real data and names it as ingest coverage, and the percentile ranks only the trailing 60 sessions so today is never ranked against the filtered-era basis. A zero-call day is null, never Infinity.
Flow tilt ranks each name against itself
FLOW TILT is the day's put/call volume percentile within the ticker's OWN trailing 60 sessions — a LEVEL ranking would re-find chronically put-heavy names (SPY, every day), and the live data made the case: GOOGL at 0.72 volume P/C, a level any screener calls call-tilted, ranked 99th because 0.72 is extremely put-heavy FOR GOOGL. Names that did not print on the latest stored day are excluded rather than ranked on stale flow; thin histories fall under a 20-session floor. The alert rule is symmetric two-tail: one threshold of 90 fires at ≥90th and ≤10th, because "tell me when flow goes extreme" means either direction.
IV is captured, and NULL means not captured
The OI store began recording each contract's implied volatility with the 2026-08-19 ingest, alongside the gamma it already carried. Rows before that date hold NULL, which is "not captured", never "no vol" — and nothing derives a backfilled IV from stored gamma, because inverting a vendor's rounded greek recovers their number through a lossy round-trip and would be a fabrication wearing maths. IV-rank features light up only as real captured sessions accumulate.
Only a full backup counts as a backup
Every trade, position, board and rule lives in this browser's localStorage alone. The staleness nudge fires when records exist and the last FULL JSON export is absent or older than 14 days — a one-book CSV never stamps recency, because a partial copy silencing the warning about everything else is how data gets lost politely. Restoring a file onto another browser deliberately does not import the source browser's stamp, and a future-dated stamp reads as corrupt, not fresh.
Where the Maths Lives
Each of the above is implemented in a pure, unit-tested module rather than inside a component, so the rule holds everywhere the figure appears and can be verified without a browser: lib/optionsStrategy (payoff, unbounded detection), lib/positionSizing (risk budget and its refusals), lib/scenario (full revaluation and time decay), lib/tradeJournal and lib/journalSegments (P&L, the multiplier, the sample floor, note normalisation), lib/bookVsDealers and lib/bookImpact (exposure comparison), lib/ownership (13F staleness), lib/earningsMoves (the reaction window), lib/realizedVol (RV conventions and the split guard), lib/volSurface (the market-IV surface), lib/opexStudy (session anchoring and spot-free roll-off), lib/bookAlerts (the two-frame expiry rule), lib/concentration (gross delta-dollar shares), lib/accountValue (observed snapshots and their gate), lib/dailyBrief (actionability ranking and its caps), lib/contractLink (the calendar-date expiry bridge), lib/oiPcr (whole-book P/C, the windowed percentile, the universe tilt ranking), lib/watchlistAlerts (the symmetric two-tail tilt rule), lib/localBackup (backup recency and its full-copy-only stamp).
◉DATA PIPELINE
SHARPE MIND collects data from 16+ sources, normalizes it into a common schema, and distributes it across all 25 modules. The pipeline is designed for freshness — live API data where available, intelligent caching where API calls are expensive, and industry-modeled fallbacks where live data doesn't exist.
Data Sources
BestTime.appCachedWeekly refreshLag: 0-7 daysActiveFoot traffic heatmaps — 7 days × 24 hours per venue. 16/25 tickers have live data, 9 use industry models.
Kalshi Public APILiveOn-demandLag: Real-timeActiveCFTC-regulated prediction market contracts — CPI, Fed, GDP, unemployment, BTC, AI milestones.
Polymarket Gamma APILiveOn-demandLag: Real-timeActiveDecentralized prediction markets on Polygon L2. Free, no auth. Events, markets, prices, orderbook.
Polygon.ioLiveOn-demandLag: 15min delayActiveUS equities + options data — 80 tickers, OPRA chain, 20+ year history, aggregates.
TheRundownLiveOn-demand + WebSocketLag: Real-timeActivePrimary sports odds source (REST + WebSocket) — 33 sports, real-time lines and live line-movement tracking.
The Odds APILiveOn-demandLag: MinutesActiveFallback sports odds source when TheRundown has no data — 80+ bookmakers, moneyline/spread/totals. Free tier: 500 req/month.
PropOdds APILiveOn-demandLag: MinutesBetaSharp book odds (Pinnacle, Circa, Bookmaker) — route exists but is not wired into the Odds Terminal; requires PROPODDS_KEY.
CBOELiveOn-demandLag: 15min delayActiveOptions data, equity quotes, GEX calculations. Free public endpoints.
CoinGeckoLiveOn-demandLag: MinutesActiveCrypto prices, market data, exchange volumes for 20 crypto tickers. Free API.
DeFiLlamaLiveOn-demandLag: MinutesActiveDeFi TVL, protocol yields, chain activity. Free, no auth.
RedditLiveOn-demandLag: MinutesActiveSubreddit mention velocity, comment sentiment, viral detection for 25 tickers.
X API (official)LiveOn-demandLag: Real-timeBetaOfficial X API v2 (tweets/search/recent) — primary source for /x-intel and /consensus bank-tweet feeds. Requires X_BEARER_TOKEN; falls back to SocialData.Tools when absent or rate-limited.
X / Twitter (SocialData.Tools)LiveOn-demandLag: Real-timeDegradedOfficial X API primary, SocialData fallback — tweet feed, trending topics, engagement metrics. Requires SocialData.Tools API credits when used; feed goes dark when credits are exhausted (402).
Anthropic ClaudeLiveOn-demandLag: Real-timeActiveAI Copilot — Anthropic Claude with web search, code execution, and extended thinking (90K tokens).
USGS / NASALiveOn-demandLag: MinutesActiveEarthquake data (USGS), wildfire hotspots (NASA FIRMS) for Globe GEOINT module.
SerpAPILiveOn-demandLag: MinutesActiveGoogle Trends search interest data as API fallback for BigQuery.
Industry ModelsCachedStaticLag: N/AActiveSynthetic traffic curves for 9 tickers without BestTime data. Based on sector patterns with per-ticker noise.
Derived SignalsComputedPer-renderLag: NoneActiveYoY comparisons, sector averages, convergence scores, rotation signals — computed client-side from raw data.
Pipeline Architecture
External APIs→Next.js API Routes→Client-Side Cache→Module Components→Cross-Module Refs→Signal Engine
Caching Strategy
BestTime.app API calls cost credits ($29/month plan). Rather than calling the API on every page load, SHARPE MIND pre-fetches traffic data for all 25 tickers and stores it in a static JSON cache (besttime-cache.json). This cache is refreshed weekly or on-demand when new data is needed. For the 9 tickers without BestTime coverage (DG, DPZ, TJX, ROST, ULTA, KR, CZR, TSLA, COIN), the system generates synthetic heatmaps using sector-specific 24-hour traffic curves with deterministic per-ticker noise to ensure each ticker looks distinct.
BestTime.app Coverage
16 LIVE TICKERS
WMT, COST, TGT, DLTR, HD, LOW, MCD, SBUX, CMG, NKE, LULU, BBY, ACI, AMZN, DKNG, MGM
9 MODELED TICKERS
DG, DPZ, TJX, ROST, ULTA, KR, CZR, TSLA, COIN — industry-modeled from sector patterns
◆SIGNAL FRAMEWORK
SHARPE MIND uses a 10-source signal matrix. Each source has a defined lead time, connection mechanism, and confidence level. The goal is multiple independent signals converging on the same thesis — not relying on any single data point.
10-Source Intelligence Matrix
HIGHFoot TrafficLead: 2-4 wkTraffic ↑ → Revenue beat likely → IV overpriced pre-ER → Sell vol or buy directional
HIGHCredit Card SpendLead: 1-3 wkSpend shift luxury→discount → Sector rotation → Options relative value
MODERATESatellite ImageryLead: 1-2 wkParking lot density → Traffic proxy → Revenue estimate refinement
MODERATEShipping & LogisticsLead: 4-8 wkContainer volume → Restocking cycle → Same-store beat in 6-8 weeks
LOWSocial SentimentLead: Hours-daysSentiment spike → Retail flow catalyst → Gamma squeeze detection
LOWWeather DataLead: 1-2 wkSevere weather → Traffic miss ≠ demand miss → Vol overreaction → Mean reversion
MODERATEJob PostingsLead: 4-12 wkHiring surge → Store expansion → Revenue growth thesis → LEAPS calls
MODERATEApp DownloadsLead: 1-4 wkDownloads ↑ → Omnichannel engagement → Same-store traffic validation
LOWRent/CRE TrendsLead: 8-16 wkRent ↑ → Margin compression → EPS miss even with traffic ↑
STRUCTURALMacro/Fed FundsLead: ImmediateRate expectations shift → Rho surface tilt → Duration re-rate → Term structure regime
Kalshi → Traffic Transmission Channels
Each Kalshi prediction market maps to specific foot traffic tickers through economic cause-and-effect chains:
KXCPICPI / InflationLag: 1-3 wk
↑ Bullish: WMT, DG, DLTR, MCD, TJX, ROST, KR↓ Bearish: NKE, LULU, SBUX, TGT, BBY
KXFEDFed Funds RateLag: 2-8 wk
↑ Bullish: HD, LOW↓ Bearish: BBY
KXGDPGDP GrowthLag: 2-6 wk
↑ Bullish: CZR, MGM, LULU, CMG, COST, NKE↓ Bearish: DG, DLTR
KXUNRATEUnemploymentLag: 1-4 wk
↑ Bullish: DG, DLTR, WMT↓ Bearish: NKE, LULU, CZR, CMG
KXBTCBitcoin RangeLag: Hours-days
↑ Bullish: COIN, DKNG↓ Bearish: —
KXAIAI MilestonesLag: 1-4 wk
↑ Bullish: BBY, TSLA, AMZN↓ Bearish: —
◐MODULE REFERENCE
Detailed documentation for each module — what it does, what data it uses, what tabs/features are available, and how it connects to other modules.
Foot Traffic V5
The centerpiece of SHARPE MIND V5. Covers 25 retail tickers across 8 sectors with live BestTime.app data for 16 tickers. Each ticker has: YoY traffic growth, revenue per visit, conversion rate, dwell time, earnings date, Kalshi macro channel, options play thesis, and IV thesis.
TABS: OverviewEarningsTraffic Data24HR HeatSector MapKalshi XRefConvergenceSupply ChainFull Table
Connects to: Options Terminal (IV thesis), Kalshi (macro transmission), Massive (price data), Odds (gaming stocks), Signal Engine (convergence scoring)
Options Terminal (φ Options Engine)
Full Black-Scholes options analytics engine. 29 tickers, 13 greeks (delta through color), 9 interactive 3D vol surfaces via Plotly WebGL, dealer gamma exposure mapping, and 9-point directional convergence framework.
TABS: Greeks DashboardVol SurfacesGEX AnalysisConvergence Signals
Connects to: Foot Traffic (earnings thesis), Kalshi (macro overlay), Massive (underlying price), Signal Engine (greek convergence scores)
Massive Market Data
Institutional-grade US equities data. 80 tickers across 8 sectors, full OPRA options chain across 17 exchanges, 20+ years of daily OHLCV, and 5 signal detectors (momentum, reversal, breakout, volume anomaly, gap).
TABS: Equities ScannerOptions ChainHistoricalSignal Detectors
Connects to: All modules — provides underlying price and volume data for every analysis
Kalshi Prediction Markets
CFTC-regulated event contracts. 5 macro categories (CPI, Fed, GDP, Unemployment, BTC) plus AI milestones. Shows implied probabilities, YES/NO depth, bid-ask spreads, and transmission channels to equities.
TABS: Markets OverviewContract DetailOrderbookCross-Reference
Connects to: Foot Traffic (6 transmission channels), Options (macro overlay on IV surfaces), Polymarket (cross-venue arbitrage), Signal Engine (macro confirmation)
Polymarket Terminal
Decentralized prediction markets on Polygon L2 via Gamma API (free, no auth). Cross-references with Kalshi for price divergence signals. Categories auto-mapped to SHARPE MIND's macro channels. Supports multi-outcome events, orderbook data, and historical prices.
TABS: All MarketsEconomicsCryptoPoliticsSci/TechSports
Connects to: Kalshi (cross-venue arbitrage), Odds Terminal (sports overlap), Signal Engine (macro confirmation), Foot Traffic (economic predictions → traffic impact)
YFinance Terminal
CBOE Data — delayed 15min quotes with customizable OHLCV charts. 10 toggleable studies: SMA(20/50/200), EMA(9/21), Bollinger Bands, VWAP, Volume, RSI(14), MACD(12,26,9). Full options chain browser by strike/expiry with 6 greeks (Delta, Gamma, Theta, Vega, Rho, IV) as toggleable columns and dedicated visualization charts. IV smile, gamma exposure curves, theta decay bars.
TABS: ChartOptions ChainGreeks Visual
Connects to: Options Terminal (greeks cross-ref), Massive (quote validation), Signal Engine (technical signal source), Foot Traffic (earnings positioning)
Live Intelligence
Real-time command center. Shows today's 24-hour traffic for all 25 tickers, upcoming earnings with traffic signals, sector rotation heatmap with live data overlay, and 8+ active cross-module signals with specific trade actions.
TABS: Today's PulseEarnings RadarSector RotationActive SignalsTicker Scanner
Connects to: Pulls from all modules — synthesizes BestTime, Kalshi, and traffic data into actionable signals
YF Options Terminal
CBOE Data integration — individual strike price charting for any call or put at any expiry. Fully customizable charts with 10 technical indicators (SMA 20/50/200, EMA 9/21, Bollinger Bands, VWAP, RSI 14, MACD, Volume). Δ Γ Θ ν ρ come from the CBOE feed; the in-house Black-Scholes engine adds the higher-order greeks and IV-solver fallback. Greeks displayed as toggleable studies both in the chain and on charts. IV smile, delta curve, and OI heatmap surfaces across all strikes.
TABS: Price ChartOptions ChainStrike ChartGreeks Surface
Connects to: Options Terminal (GEX/vol surfaces use same BS engine), Massive Market Data (overlapping ticker universe), Signal Engine (IV anomalies feed convergence scoring)
Expected Move
Options-implied expected move (±1σ) per expiration, computed live from the CBOE chain. For each expiry: nearest-strike ATM implied volatility drives the estimate spot × IV × √(DTE/365), shown in dollars and percent with upper/lower price bounds, total open interest, and calendar days-to-expiration. A cone chart visualizes how the ±1σ bounds widen with time around spot. Includes CSV/JSON export and watchlist star.
TABS: Cone ChartExpiration TableExport
Connects to: Options Terminal & YF Options (shared CBOE chain + Black-Scholes lib), Massive (underlying price), Signal Engine (volatility regime)
Order Flow Terminal
Prediction market microstructure analysis — the 'cheat code'. Detects winning side via 95-99¢ liquidity evaporation pattern. When sell orders at 95-99¢ on one side are massive (winners queued to cash out) while the other side evaporates, the book reveals the outcome before the price fully adjusts. Includes Kalshi-style mirrored order book display, smart money signal engine with 10-point strength scoring, depth visualization by price level, probability price action charting with TA, and complete bid/ask/market maker mechanics guide.
TABS: Order BookFlow SignalsPrice ChartHow It Works
Connects to: Kalshi (live event data + orderbook), Polymarket (cross-venue flow comparison), Odds Terminal (sports overlap — same pattern in live games), Signal Engine (flow signals feed convergence scoring)
◎RESEARCH PROCESS
SHARPE MIND follows a structured 4-phase research process designed to minimize bias and maximize signal quality. Every trade idea must pass through all 4 phases before capital is committed.
PHASE 1: DETECTMinutes to hours
1.Check Intel page → Today's Pulse for traffic anomalies
2.Scan Sector Rotation tab for divergences (green sector + red sector = rotation)
3.Identify candidate tickers with unusual YoY changes
4.Check Kalshi for macro catalysts that explain the traffic shift
OUTPUT: 1-3 candidate tickers with preliminary directional bias
PHASE 2: CONFIRMHours to 1 day
1.Open candidate ticker in Foot Traffic → full 52-week trend, dwell, conversion
2.Check Options Terminal → IV surface topology, greek convergence score
3.Cross-reference with Kalshi transmission channel — does macro support the thesis?
4.Run Signal Engine convergence — how many of 10 sources align?
5.Check Massive for institutional volume patterns — is smart money positioning?
OUTPUT: Convergence score (0-10). If <4, move to watchlist. If ≥4, proceed to Structure.
PHASE 3: STRUCTURE30 minutes
1.Use φ Options Engine expected move cones to define price range
2.Select strike via gamma wall analysis — trade where dealers hedge
3.Choose DTE via term structure — match expiry to catalyst (earnings date)
4.Size position via theta/vega ratio — define max loss before entry
5.Fill out Thesis Builder template — all 8 sections must be complete
OUTPUT: Fully structured trade: ticker, direction, strike, DTE, size, max loss, target, invalidation level
PHASE 4: EXECUTE & REVIEWOngoing
1.Check dealer positioning for entry timing — don't fight the market maker
2.Monitor Charm/Vanna for overnight delta drift — adjust if thesis changes
3.Set stops via Speed surface — identify cascade risk zones
4.Log trade in Journal with full thesis, entry, and plan
5.Post-trade: compare actual outcome to thesis. What was right? What was missed?
OUTPUT: Trade executed + journal entry + post-mortem for continuous improvement
⇌HYPOTHESIS TESTING
Every SHARPE MIND research output is framed as a testable hypothesis. This is what separates institutional process from retail speculation. A hypothesis must be falsifiable — you must define what would prove you wrong before entering the trade.
Hypothesis Framework
OBSERVATION
Walmart foot traffic is +3.2% YoY while Target is -1.2%. MCD is +2.9% while SBUX is -0.8%.
HYPOTHESIS
Consumer trade-down is accelerating. Staples/value retailers are gaining share from discretionary/premium. This will manifest as WMT earnings beat and TGT earnings miss.
PREDICTION
WMT will beat revenue estimates by 1-2%. IV is currently overpriced for WMT (street expects bigger move than traffic suggests). Sell WMT pre-ER strangles.
FALSIFICATION
If TGT traffic reverses to positive before earnings, the trade-down thesis is weakening. If Kalshi KXCPI drops below 40¢ (inflation cooling), the catalyst for trade-down evaporates.
CONFIRMATION
If WMT beats AND TGT misses AND DG/DLTR traffic accelerates → thesis confirmed. Log in journal, add to research paper, increase position sizing for similar setups.
Tracking Hypothesis Outcomes
Over time, SHARPE MIND tracks which hypotheses were confirmed vs denied, building a statistical record of which signal combinations produce the highest win rates. This feedback loop is the foundation for the platform's agentic intelligence — the system learns which data sources are most predictive for each sector and adjusts convergence weighting accordingly.
Hypothesis Logged→Trade Executed→Outcome Recorded→Win/Loss by Signal Source→Convergence Weights Updated→Better Future Predictions
▣THESIS BUILDER
The Thesis Builder is SHARPE MIND's institutional-grade trade documentation system. Every trade idea is structured into 8 sections, designed to be presentable to investment committees, portfolio managers, or internal review.
8-Section Template
1
THESIS
1-2 sentence directional bias with specific catalyst and time horizon. Must be falsifiable.
2
TRAFFIC SIGNAL
Foot traffic data: YoY trend, dwell time change, conversion rate, revenue per visit. Is the physical world confirming or denying?
3
IV SURFACE CHECK
Is implied volatility cheap or expensive at your target strike and DTE? φ Options Engine surface topology analysis.
4
GREEK CONVERGENCE
How many of the 9 convergence signals align? Gamma exposure direction, Vanna sensitivity, Charm overnight drift.
5
ALT DATA CONFIRMATION
Which indirect variables support or contradict? Credit card spend, satellite, shipping, social, job postings.
6
TRADE STRUCTURE
Exact trade: ticker, direction, strike, DTE, spread type, quantity, max loss, profit target, greeks at entry.
7
BIAS CHECK
What surfaces conflict? What would invalidate this thesis? What is the crowd doing (OI concentration)?
8
RISK MANAGEMENT
Position size as % of portfolio, stop criteria, max loss in dollars, correlation to existing positions.
Automatic Red Flags
If any of these conditions exist, the thesis requires re-evaluation before proceeding:
⚠You're long calls but Charm is negative — overnight delta erosion works against you
⚠You're selling vol but Vomma peaks near your strike — convexity risk on vol spike
⚠Only 1 data source supports thesis — insufficient convergence for conviction
⚠IV surface already expensive at your target expiry — edge already priced in
⚠OI surface shows crowd positioned same direction — consensus = no edge
⚠Speed surface shows cascade zone near your stop — gap risk through stop level
⊛RISK FRAMEWORK
Risk management is not optional — it's the foundation of every trade. SHARPE MIND enforces structured risk thinking through the thesis builder and provides tools for position sizing, stop placement, and portfolio correlation analysis.
Position Sizing Rules
HIGH CONVICTION
3-5% of portfolio
6+ signals converge
MODERATE
1-2% of portfolio
4-5 signals converge
EXPLORATORY
0.5-1% of portfolio
2-3 signals, thesis forming
NO TRADE
0%
<2 signals. Wait for more data.
◇RESEARCH PAPERS
Sharpe Mind Research publishes periodic research papers documenting findings from the platform's data collection, hypothesis testing, and signal analysis. These papers serve as both internal knowledge base and external credibility for the platform's methodology.
Published Research
Foot Traffic as a Leading Indicator for Retail Earnings SurprisesIn ProgressQ1 2026
Analysis of the predictive relationship between BestTime.app foot traffic data and subsequent retail earnings surprises. Examines 25 retail tickers across 8 sectors, measuring the accuracy of traffic-based beat/miss predictions against actual earnings outcomes. The hypothesis under test is that 2-4 week traffic trends carry directional information ahead of the print; no accuracy figure is claimed until the outcome tracking is built and run.
QSR Trade-Down Effect: MCD/SBUX Divergence as a CPI Leading IndicatorDraftingQ1 2026
Documents the observed pattern where McDonald's foot traffic accelerates relative to Starbucks during periods of elevated CPI. Examines whether this divergence precedes CPI prints and can be used as a positioning signal for inflation-sensitive options strategies.
Sector Rotation Detection via Alternative Traffic DataPlannedQ2 2026
Develops a systematic framework for identifying sector rotation using foot traffic divergences. When discount retailers show accelerating traffic while specialty retailers decelerate, the delta serves as a leading indicator for consumer spending regime changes.
Convergence Scoring Backtested: Which Signal Combinations Produce AlphaPlannedQ2 2026
Backtests the 10-source convergence scoring framework against historical earnings events. Identifies which combinations of signals (traffic + Kalshi + greek convergence + etc.) produce the highest risk-adjusted returns when used for pre-earnings options positioning.
Research Paper Pipeline
Data Collection→Hypothesis Formation→Statistical Analysis→Peer Review→Publication→Platform Integration
All research findings that prove statistically significant are integrated back into SHARPE MIND's convergence scoring weights, creating a feedback loop between research and platform intelligence.
◫PRODUCT ROADMAP
SHARPE MIND's development roadmap is driven by one question: what reduces noise and increases signal quality? Features are prioritized by their contribution to trade conviction, not by visual impressiveness.
V5 — ShippedShipped
◈25 intelligence modules across equities, options, predictions, sportsbook, alt data, crypto, and GEOINT
◈Full Black-Scholes options engine — 13 Greeks to 3rd order, GEX, vol surfaces, dealer positioning
◈Prediction markets — Kalshi (CFTC) + Polymarket with cross-venue arbitrage signals
◈Sports odds terminal — 10 sportsbooks, 8 sports, sharp money detection, whale tracker
◈Foot Traffic V5 with BestTime.app live data (16/25 tickers), 24hr heatmaps
◈Social sentiment — Reddit mention velocity, meme score, viral probability (live API)
◈Crypto on-chain — exchange flows, whale accumulation via CoinGecko + DeFiLlama
◈Alpha signals — real SEC Form-4 insider transactions and reported-vs-estimate EPS history (Alpha Vantage), sector scan via EDGAR
◈Wall Street Consensus — bank research, price targets, analyst ratings
◈Globe GEOINT — 15+ data layers (earthquakes, wildfires, aircraft, ships, weather, conflict)
◈Google Trends — BigQuery-powered search intelligence with SerpAPI fallback
◈X Intelligence — live tweet feed, trending topics, engagement metrics
◈AI Copilot (claude-opus-4-6) — web search, code execution, 90K token extended thinking
◈S&P 500 heatmap — top 100 by weight, live prices, sector filtering, data export
◈Multi-chart Workspace with Backtest Engine (real SPX data via CBOE)
◈Price alert engine — real-time polling with browser notifications
◈Live TV PiP — multi-window broadcast streams (Bloomberg, CNBC, Fox Business)
◈Cmd+K command palette, data export (CSV/JSON), dark/light theme toggle
◈Collapsible sidebar navigation with 8 categories and localStorage persistence
◈Deep-link support — URL params for ticker/category pre-selection across modules
V6 — NextPlanning
◈Authentication — protect the terminal with user accounts
◈Saved strategies and portfolio tracking
◈BestTime live refresh — batch auto-refresh on interval (key is configured)
◈Alerts for non-price rules — conviction score, signal fire, prediction market delta
◈Hypothesis outcome tracking — automated win/loss logging by signal source
◈Real-time WebSocket feeds for live Greeks and options flow
V7 — FutureConceptual
◈Agentic research layer — AI learns from trade journal outcomes, adjusts convergence weights
◈Additional API integrations — credit card spend, satellite imagery, job posting data
◈Multi-user collaboration — shared thesis builder and research workspace
◈Bot Monitor — read-only feed from external trading bot (separate service)
◈Stripe billing / gating — paid access tiers
⊕API & INTEGRATIONS
SHARPE MIND is designed as a modular system. New data sources can be connected through the existing API route framework, and new modules can be added without disrupting existing functionality.
Current Integrations
BestTime.appPOST/api/besttime/forecast
Foot traffic intelligence. 7-day × 24-hour forecast for any venue with Google Maps presence.
Kalshi Public APIGET/api/kalshi/[...path]
CFTC-regulated prediction market data. Event contracts, orderbook depth, series data.
Polygon.ioGET/api/massive/[...path]
US equities + options proxy. Currently UNUSED by any page — its only consumer was the old MASSIVE terminal, replaced by the Sector Map. Kept as a working Polygon proxy; /api/equity charts use Polygon directly.
The Odds APIGET/api/odds/[sport]
Fallback sports odds source when TheRundown has no data. Moneyline, spread, totals. Free: 500 req/mo.
PropOdds APIGET/api/odds/propodds
Sharp book odds — route exists but is not called by the Odds Terminal UI. Free: 100 req/day.
Polymarket Gamma APIGET/api/polymarket/[...path]
Decentralized prediction markets. Events, markets, prices, orderbook. Free, unlimited reads.
Polymarket CLOB APIGET/api/polymarket/price
Live order book pricing — price, midpoint, spread, last trade. Free public access.
CBOE Delayed QuotesGET/api/equity/[symbol]
Equity + options quotes and chains (15-min delayed) from cdn.cboe.com. Primary source for /yfinance, /yf-options, /options, and /expected-move. First-order greeks (delta/gamma/theta/vega/rho) come from the CBOE feed itself — GEX is computed from CBOE gamma; the in-house Black-Scholes engine supplies the 2nd/3rd-order greeks (vanna, charm, vomma...) and the IV solver fallback. Alpha Vantage / Polygon fallback when unavailable.
CoinGeckoGET/api/crypto/onchain
Crypto market data — prices, volumes, market caps for 20 crypto + equity tickers.
DeFiLlamaGET/api/crypto/onchain
DeFi protocol TVL, yields, chain activity. Aggregated with CoinGecko data.
Reddit APIGET/api/social/sentiment
Subreddit mention velocity and sentiment for 25 tickers across r/wallstreetbets, r/stocks, r/options.
X / Twitter (SocialData.Tools)GET/api/twitter/[action]
Live tweets, trending topics, engagement metrics via X API v2 or SocialData.Tools when a key is live. Without one, falls back to the free StockTwits public API (community posts with Bullish/Bearish stances + ranked trending symbols, labelled VIA STOCKTWITS — real social data, not X content). Actions: feed, trending, follows (follows not yet implemented).
Anthropic ClaudePOST/api/chat
AI Copilot — Anthropic Claude with web search, code execution, extended thinking. SSE streaming.
USGS EarthquakeGET/api/globe/[layer]
Real-time earthquake data for Globe GEOINT map. GeoJSON format.
TheRundownGET/api/odds/[sport] + /api/odds/ws-config
Primary sports odds source — REST lines (/api/odds/[sport]) plus a WebSocket feed for live line movement.
SerpAPIGET/api/trends/[action]
Google search trends and interest-over-time data. Fallback for BigQuery trends.
Adding New Data Sources
To integrate a new data source into SHARPE MIND: (1) Create an API route in /pages/api/ that proxies the external API, (2) Add a component or tab in the relevant module that consumes the data, (3) Define the cross-module connection — how does this data feed into convergence scoring?, (4) Update the Signal Engine matrix to include the new source.
Tech Stack
Framework
Next.js (Pages Router)
Runtime
Node.js + Vercel
Charts
Recharts (SVG)
3D Surfaces
Plotly WebGL (opt-in)
Styling
Inline styles (zero CSS)
Deployment
Vercel Edge Network
# SHARPE MIND DOCS V5.0 | Moneda Research & Zero Ai Labs CT