Equities-Short-Selling-Setup-Definition
Sources: 1 • Confidence: Medium • Updated: 2026-04-11 18:22
Key takeaways
- Stefan Stadie said he shifted from a mostly long bias to mostly short selling.
- Stefan Stadie said prediction-market prices typically start as model-driven soft lines and then move toward true probability through participant trading and liquidity, with bid-ask spreads similar to equities.
- Stadie said he targets at least about a 3% edge per market-making transaction, but with exchange fees of roughly 1% to 2% he prefers 5%+ and sometimes can capture about 10% when others leave stale prices.
- Stefan Stadie said he used tools like OddsJam to detect real-time mispriced odds and then hedged or arbitraged the outlier price against more liquid markets to lock in profits.
- Stefan Stadie said an early trading mistake was using a standard position size that could exceed 10% of his account per trade.
Sections
Equities-Short-Selling-Setup-Definition
- Stefan Stadie said he shifted from a mostly long bias to mostly short selling.
- Stefan Stadie said his short-selling edge comes from combining relative volume, liquidity events, and higher-timeframe resistance to identify downside moves after buyer exhaustion.
- Stefan Stadie said a liquidity event is a news-driven catalyst that pulls in new buyers and volume.
- Stefan Stadie said he prefers waiting for a liquidity event to exhaust and then shorting the backside rather than anticipating direction.
- Stefan Stadie said his typical short holding period ranges from about one day up to a couple of weeks and that he targets the “meat” of the move rather than small intraday scalps.
- Stefan Stadie said his approach is price-first rather than opinion-first, taking trades when the displayed price is misaligned with broader market pricing even if it conflicts with his personal preferences.
Prediction-Market-Microstructure-Price-Discovery-Liquidity
- Stefan Stadie said prediction-market prices typically start as model-driven soft lines and then move toward true probability through participant trading and liquidity, with bid-ask spreads similar to equities.
- A liquidity heuristic stated in the episode is that liquidity tends to be highest at the open and close of markets and that, in sports, the hour before an event starts is typically the most liquid and offers better fills.
- Stefan Stadie said lower liquidity periods in prediction markets lead to slippage and that higher liquidity tends to occur near the open/close in financial markets and about an hour before sports event start time in sports markets.
- Stefan Stadie said he now uses venues such as Polymarket, BetOpenly, and Pinnacle.
- Stefan Stadie said retail sportsbooks are effectively trading against the house while markets like Polymarket are peer-to-peer, where participants can stop trading if they dislike the prices rather than banning the counterparty.
- Stefan Stadie said higher liquidity improves prediction accuracy because more informed participants and higher conviction aggregate into clearer “true odds,” while low liquidity implies weaker information and noisier prices.
Market-Making-Economics-Fees-Edge-Thresholds-And-Adverse-Selection-Control
- Stadie said he targets at least about a 3% edge per market-making transaction, but with exchange fees of roughly 1% to 2% he prefers 5%+ and sometimes can capture about 10% when others leave stale prices.
- Stefan Stadie said his market-making process is to reference sharp, liquid sportsbooks (including Pinnacle, Bookmaker, and BetOnline) to infer fair pricing and then post his own bid/ask just outside those prices while avoiding negative-EV ranges.
- Stefan Stadie said a key sports-market edge comes from emotionally driven bettors posting stale or wrong prices during live events, creating short-lived mispricings that can be captured quickly.
- Stefan Stadie said psychology and short-term variance are primary challenges and recommended avoiding posting prices during nonstop live action, preferring pregame, intermissions, and halftime to reduce being adversely selected by fast-moving lines.
- Stefan Stadie said he does market making in sports markets by posting both sides to capture the spread and that anyone can be a market maker in sports prediction markets.
- Stefan Stadie said to reduce being “sniped” he removes his posted markets whenever he steps away and focuses attention on only the most important (most liquid) events at a given time.
Sports-Arbitrage-Formation-And-Decay
- Stefan Stadie said he used tools like OddsJam to detect real-time mispriced odds and then hedged or arbitraged the outlier price against more liquid markets to lock in profits.
- Stefan Stadie said large sports-odds discrepancies commonly arose near game time when news like NBA lineup changes caused rapid repricing and some sportsbooks failed to update quickly enough.
- Stefan Stadie said these sports-odds discrepancy opportunities have tightened over recent years.
- Stefan Stadie said he entered online sports betting after regulatory changes made it easier in Canada and the US, initially attracted by signup bonuses.
- Stefan Stadie said he discovered an edge in sports betting from price disconnects between sportsbooks.
Trading-Process-Upgrade-Risk-First-Position-Sizing
- Stefan Stadie said an early trading mistake was using a standard position size that could exceed 10% of his account per trade.
- Stefan Stadie said he later shifted to sizing positions using a backward risk calculation based on predefined stop levels with preplanned exits and stops.
- Stefan Stadie said he did not capitalize on the 2020 COVID crash and instead stepped back to learn because he was about a year into full-time trading.
Unknowns
- What is the methodology behind the cited Polymarket user profitability dataset (cohort selection, wallet clustering, fee treatment, realized vs unrealized PnL), and can it be replicated?
- What are the realized net returns (after all fees and slippage) of the described market-making approach across a representative sample of events, and how stable are they over time?
- How frequently do settlement disputes or ambiguous resolutions occur on the venues discussed, and what is the expected loss from settlement risk per contract category?
- How do liquidity, spreads, and slippage vary across time-to-event and across venues (Polymarket vs others), and does the “T-minus one hour” liquidity window generalize across sports and market types?
- To what extent are the claimed “reference sharp books” (e.g., Pinnacle/Bookmaker/BetOnline) truly usable as fair-value anchors under fast information updates, and how quickly do they move relative to prediction-market prices?