SightWhale Blog
阅读中文Deep dives into Polymarket prediction markets, whale strategies, and data insights. Updated daily.
What Whale Score Actually Is (and Why Treating It Like an Oracle Will Burn You)
Whale Score is a ranking lens: it compresses behavior, timing, and impact into something you can scan quickly. This article separates what that compression can justify from what it cannot—so you use the score as a filter, not a substitute for thinking.
Signal Half-Life in Prediction Markets: How Long Does Whale Alpha Last?
On Polymarket, the difference between riding smart money and becoming exit liquidity is measured in minutes, not days. This deep dive explains signal half-life—the time it takes for whale-driven edge to decay—and how to build trading rules around it.
From Wallets to Playbooks: How to Build Follow Strategies for Polymarket Smart Money
Copying big wallets blindly is a fast way to become exit liquidity. This deep dive shows how to classify whale behaviors on Polymarket and turn them into robust follow playbooks—with clear scopes, triggers, sizing rules, and exits.
Resolution Risk & Wording Arbitrage: The Hidden Edge (and Hidden Landmines)
In prediction markets, you can be right about reality and still lose money. The gap is resolution: wording, sources, edge cases, and oracle mechanics. This guide shows how to score resolution risk, spot “same idea, different contract” mismatches, and build a repeatable pre-trade checklist using public market metadata.
Cross-Market Price Discovery: Which Market Leads, Which Follows, and Why
In correlated Polymarket markets, not all prices are equal. Some markets lead price discovery; others follow with a delay. This post lays out a practical lead–lag workflow (cross-correlation plus a simplified causality check) you can reproduce using public price endpoints—then shows how to turn “leader flow” into actionable trades.
When Volume Is a Trap: Measuring ‘Toxic Flow’ vs Informational Flow
High volume doesn’t mean smart money. In CLOB markets, the key is flow quality: toxic (adverse selection) versus informational (price discovery). This post shows how to measure adverse selection using trades + mid-price reactions, build a followability filter for whale alerts, and reproduce it with public Polymarket APIs.
Liquidity Regimes: Detecting When a Market Turns ‘Tradable’ (Before the Crowd)
A Polymarket market can flip from untradable to efficient in hours—spread compresses, depth refills, and whales suddenly matter. This post builds a practical tradability score from spread, depth, and cancellation pressure, with a reproducible way to compute it using public order book endpoints.
Smart Collections as Portfolios: Building and Stress-Testing Thematic Whale Baskets
A Smart Collection isn’t just a list—it’s a portfolio. This post shows how to build thematic whale baskets with portfolio discipline (constraints, diversification, turnover), then stress-test them under three regimes: correlation spikes, liquidity collapses, and event shocks. Includes reproducible checks using public wallet/market data and a practical checklist.
Alert Calibration: Choosing Thresholds That Don’t Overfit (A Backtesting Playbook)
If your whale alerts feel noisy, the fix isn’t another heuristic—it’s calibration. This playbook shows how to choose alert thresholds using precision/recall, stratified backtests (by liquidity, market category, and regime), and out-of-sample validation so you don’t tune to yesterday’s tape.
Execution Alpha on Polymarket: Slippage, Spread, and Why Mid Price Lies
Most traders lose money on Polymarket without being wrong. The culprit is execution: spread, depth, and fee curves that turn the midpoint into a comforting fiction. This guide shows how to estimate execution cost from order book snapshots and how to choose maker vs taker in a way you can reproduce.
Whale Position Lifecycle: Entry → Defense → Unwind (and How to Detect Each Phase)
Whale edges don’t decay on a timer—they move through a lifecycle. This guide frames Polymarket trading as a position state machine and shows how to detect Entry, Defense, and Unwind phases using net position changes, trade structure, and closed-position PnL you can verify via Polymarket’s public APIs.
Wallet Clustering 101: When 50 Wallets Are One Trader
On Polymarket, performance can be distorted when one operator spreads activity across many wallets. This article lays out practical clustering signals—timing sync, market overlap, side consistency, and funding flows—plus the failure modes that create false positives. It also explains how clustering changes alert quality and win-rate statistics.