Automating Trading in Crypto vs Equities vs Prediction Markets: What Actually Transfers

A 0.1% Bitcoin move is noise to a spot trading bot. To a Kalshi "BTC above strike" contract with one minute left, the same move can be worth 43 cents on the dollar. That's our calculation, explained below, and it's the single most important fact for anyone moving a bot between markets.

Most "crypto vs stocks bot" guides compare APIs and fees, then stop. Those matter, and we'll cover them with 2026 numbers. But infrastructure gaps are solvable with engineering. Payoff shape isn't. Crypto and equities pay continuously: every tick moves your P&L. Prediction markets pay $1 or $0 on a date. That difference decides which strategies survive the move and which quietly die.

Key Takeaways

• Crypto trades 168 hours a week, US stocks 32.5 core hours, and Kalshi about 166. But each prediction-market contract runs on its own event clock
• Kalshi's taker fee is 3.5% of capital at 50¢ versus 0.10% on Binance spot. Held to settlement, it's cheaper per unit of risk than a short spot trade
• Payoff shape decides what transfers: momentum and arbitrage carry over in concept, mean reversion breaks hardest, and market making needs binary-aware inventory logic
• What ports cleanly is execution engineering: rate-limit handling, retries, kill switches, and legging logic. Sizing and risk limits need rebuilding for capped payoffs

Why Are Traders Porting Bots Between These Markets Now?

The three venue classes are collapsing into the same apps. Coinbase put Kalshi-powered prediction markets live in all 50 US states in January, next to crypto and stock positions (The Block, 2026). Robinhood's prediction markets out-earned its crypto business for the first time in Q2 2026 (The Block, 2026).

The convergence runs the other way too. Kalshi now lists Bitcoin perpetual futures, a continuous-payoff product, beside its binary contracts (Fortune, 2026). So a trader who automates one market now sees the other two a tap away. The natural question: will my bot work over there?

Looking for the instrument comparison instead? We covered how a binary contract stacks up against an option or a sportsbook bet in prediction markets vs options vs sports betting. This post is about the machine, not the bet. What does an algorithmic trading bot need from a venue, and does a crypto bot's logic survive as a prediction market trading bot?

APIs, Fees, and Data: What Does Each Venue Charge Your Bot?

Every venue class offers a documented API, but the price list varies wildly. Binance spot charges 0.10% to a regular taker (Binance, 2026). A commission-free stock broker charges $0 plus tiny regulatory fees, though you still pay the bid-ask spread. Kalshi charges by formula, and at 50¢ that formula costs 3.5% of the capital you put in (Kalshi, 2026). Here's the full scorecard before we unpack it.

API Throughput: Bought, Fixed, or Earned

Rate limits tell you how a venue thinks about bots. Binance's live exchange info reports 6,000 request weight per minute (each endpoint costs a set weight) and 100 orders per 10 seconds for spot (Binance, 2026). Alpaca's trading API allows 200 requests per minute per account (Alpaca, 2026). That's roughly three requests a second, fine for swing trading and tight for anything that re-quotes.

Kalshi is the odd one out. Its limits are tiered in tokens per second, a budget each request draws down. Basic gets 100 write tokens, roughly 10 orders a second at the default cost, and Prestige gets 9,600. Higher tiers are earned automatically from trading volume (Kalshi Docs, 2026). Polymarket's order endpoint allows 5,000 requests per 10 seconds in bursts (Polymarket Docs, 2026). We dug into why Kalshi's tier design favors bots in why Kalshi was built for automated trading.

Fees: Per Dollar or Per Contract?

Crypto and equities charge a percentage of notional. Coinbase Advanced's new US entry tier is 0.50% maker and 0.90% taker (Investing.com, 2026). Stock bots pay the SEC's Section 31 fee of $20.60 per million dollars sold (SEC, 2026), plus FINRA's $0.000195-per-share trading activity fee (FINRA, 2026).

Prediction markets charge by contract price instead. Kalshi's taker fee is 0.07 × contracts × P × (1−P), rounded up (Kalshi, 2026). Polymarket uses the same shape with category rates: 0.07 for crypto, 0.05 for sports, 0.04 for politics, and makers pay nothing (Polymarket Docs, 2026). Divide the fee by the price you pay and Kalshi costs 7% × (1−P) of your capital.

Key insight: Per dollar, Kalshi looks 35 times pricier than Binance. Per unit of risk, the ranking flips on short holds taken to settlement. A 50¢ contract held to settlement has a 50¢ standard deviation, so the 1.75¢ fee is 3.5% of the risk. A 15-minute BTC spot position at 50% annualized volatility has a 0.27% standard deviation. Binance's 0.20% taker round trip eats about 75% of that move. Fee math doesn't transfer. Re-derive it per venue.

The strategic consequence matters more than the ranking. Per contract, Kalshi's fee peaks at 50¢. Per dollar deployed, it falls as price rises: 6.3% at 10¢, 3.5% at 50¢, 0.7% at 90¢. A bot that churns around the midpoint pays near-peak fees on every trade. A bot that buys favorites and holds to settlement pays little, and Kalshi charges no settlement fee (Kalshi, 2026).

Data: Free to Stream, Expensive to Remember

Live data is cheap in crypto and prediction markets and costly in equities. Alpaca's free plan streams only the IEX exchange; consolidated data from all US exchanges costs $99 a month (Alpaca, 2026). Massive, formerly Polygon.io, charges $199 a month for real-time stock quotes (Massive, 2026). Kalshi's market data endpoints need no API key at all (Kalshi Docs, 2026).

History is the real cost, mostly for order-book depth. Binance publishes free historical trades and candles (Binance Data, 2026). Full order-book history comes from vendors like Tardis.dev, at $700 a month for individuals or $350 for academics (Tardis.dev, 2026). For stocks, Databento's standard plan runs $199 a month (Databento, 2026). Kalshi's documented historical endpoints cover markets, candlesticks, and trades, but not order-book depth (Kalshi Docs, 2026). That gap is why prediction-market backtests often assume fills they'd never get. We covered workarounds in historical prediction market data for backtesting.

Citation capsule: Crypto and stock venues charge fees as a percentage of notional. That's 0.10% for a Binance spot taker and about 0.002% in SEC fees on a stock sale. Kalshi's taker fee follows 0.07 × P × (1−P) per contract, which is 3.5% of capital at 50¢ and 0.7% at 90¢. Per unit of risk, a binary held to settlement is often cheaper than a short spot hold.

Hours, Settlement, and Rules: When Can Your Bot Trade?

Crypto never closes, US stocks trade 32.5 core hours a week, and prediction markets live on event clocks. The NYSE core session runs 9:30 a.m. to 4:00 p.m. ET (NYSE, 2026). Kalshi's exchange is open around the clock except a Thursday 3–5 a.m. ET maintenance window (Kalshi Docs, 2026). That's about 166 hours a week.

But exchange hours mislead on prediction markets. Each contract has its own open, close, and expiration time, so a Fed-decision bot has no market to trade once the decision lands. Equities are getting closer to crypto, though. Overnight 23x5 exchange trading is expected to start December 6, 2026, pending readiness of the SIPs, the feeds that publish consolidated quotes (WilmerHale, 2026). As of October 2026, it isn't live.

Settlement: T+1, Funding, or Resolution

US equities settle on T+1, the standard since May 28, 2024 (SEC, 2023). Crypto perpetuals never settle; on Binance they exchange funding every 8 hours by default (Binance, 2026). Kalshi pays $1 per winning contract, usually shortly after expiration, though Kalshi notes timing can vary (Kalshi Docs, 2026).

Polymarket adds oracle risk. Outcomes are proposed through UMA's Optimistic Oracle with a 2-hour challenge period, and disputes escalate to a token-holder vote (Polymarket Docs, 2026). Neither stocks nor crypto has an equivalent. A bot that recycles capital fast needs to model that delay. Our guide to how prediction markets resolve covers the dispute path.

Regulatory Posture: Who Polices the Bot?

In equities, the broker polices you. SEC Rule 15c3-5 requires brokers with market access to run pre-trade risk controls on every order (SEC, 2011). The big 2026 change: FINRA replaced the pattern day trader rule's $25,000 minimum with intraday margin requirements, effective June 4, 2026 (FINRA, 2026). Brokers can phase it in through October 2027.

In crypto, venues are API-first, but the rulebook depends on where you sit. The EU's MiCA bans manipulative order placement "by any available means of trading" (ESMA, 2024). In the US, the CLARITY Act, the crypto market-structure bill, failed a 49–50 Senate vote on September 15 (CoinDesk, 2026). So federal rules for US crypto venues remain unsettled.

Prediction markets are the most explicit. Kalshi's Developer Agreement limits API use to facilitating a member's "own trading on the Exchange" (Kalshi, 2026). In other words, a bot trading your own account is the intended use. The Commodity Exchange Act's anti-spoofing ban still applies on CFTC-regulated venues (Cornell LII, 2026).

Binary vs Continuous: Why Does Payoff Shape Decide What Transfers?

Everything above is plumbing. You can rewrite an API client in an afternoon. The payoff is different. On a continuous asset, your P&L moves in proportion to price, minute after minute. On a binary contract, the payoff jumps from $0 to $1 at one threshold, and its sensitivity to the underlying depends on the clock. Mathematicians have shown a digital option's delta, its price sensitivity to the underlying, can grow without bound near the strike as expiry approaches (Geiss & Gobet, 2010).

Here's what that means in practice. We priced an at-the-money Kalshi-style "BTC above strike" contract and asked one question: how much does a 0.1% Bitcoin move change its price?

With four hours left, a 0.1% move nudges the contract 3.7¢. With fifteen minutes left, it's 14.6¢. With one minute left, it's 42.6¢, most of the way to a dollar. A spot BTC position gains exactly 0.1% in all five cases. Same signal, same move, wildly different exposure, purely because of the clock.

Binary prices also pile up where continuous intuition doesn't expect them. In a study of 313,972 Kalshi contract prices, about two-thirds sat at 10¢ or less, or 90¢ or more (Bürgi, Deng & Whelan, 2026). Only 2.3% traded between 41¢ and 50¢. A bot whose filters assume prices sit near a fair midpoint meets a book that lives at the edges.

Citation capsule: A binary contract's sensitivity to its underlying depends on time to expiry. In Turbine's calculation, a 0.1% Bitcoin move shifts an at-the-money contract 3.7¢ with four hours left and 42.6¢ with one minute left. A spot position gains 0.1% either way. Strategies tuned on continuous P&L misjudge risk near expiry.

Which Strategy Archetypes Transfer, and Which Break?

Four of the classic families behave differently once the payoff turns binary. We described all five archetypes inside prediction markets in Five Strategy Archetypes. Here the question is portability: does a strategy that works on BTC spot or a stock still work as a $0/$1 contract? We skip the fifth family, news reaction, because its edge is tied to a specific feed and venue by design.

Momentum: Transfers, but the Clock Shrinks

Momentum is the most portable family. Time-series momentum showed up in all 58 futures contracts across asset classes, persisting for one to 12 months (Moskowitz, Ooi & Pedersen, 2012). Crypto has it too: market, size, and momentum factors capture cross-sectional crypto returns (Liu, Tsyvinski & Wu, 2022).

Prediction markets show momentum on a far shorter clock. A 2026 study measured how contract prices follow a benchmark probability, an outside estimate of the same event. A one-minute benchmark move shifted prices only about 0.64-for-one at first. The rest arrived as drift over the following minutes (Angelini & De Angelis, 2026). That's momentum measured in minutes, not months.

The binary twist is the ceiling. A stock trend can run 200%. A contract bought at 70¢ can make 30¢ at most. Momentum also crashes: in March–May 2009, past equity losers rose 163% while winners gained 8% (Daniel & Moskowitz, 2016). On a binary, the equivalent is a trend that flips on resolution news, and the position goes to zero rather than giving back some gains.

Mean Reversion: The One That Breaks Hardest

Mean reversion is fragile even at home. A daily contrarian strategy on US stocks averaged 1.38% a day in 1995 and just 0.13% in 2007 (Khandani & Lo, 2007). The authors framed it as paid liquidity provision that loses when prices trend. In crypto, daily reversal shows up mostly in illiquid coins, while the largest coins show daily momentum (Zaremba et al., 2021).

Inside a liquid, range-bound prediction market, reversion can still be forgiving. But on a binary, "the mean" stops existing near expiry. The contract isn't drifting around a fair value. It's converging to $0 or $1. Fading a move with five minutes left is really a bet that the underlying recrosses the strike before the bell. Look back at the repricing chart: that bet gets more expensive every minute.

The version of reversion with the strongest evidence is structural, not temporal. Kalshi contracts priced under 10¢ lost more than 60% of their money on average, a classic favorite-longshot bias (Bürgi, Deng & Whelan, 2026). Fading longshots is mean reversion's binary cousin. It's also a different strategy with different risk, so port the idea, not the code.

From our research: In our April study of 4,904 Kalshi BTC 15-minute strategies, panic fade, a reversion family, took 93 of the top 100 slots. In a later test with a different setup and window, it lost (5,732 backtests). When we fed the same contracts a Coinbase spot signal, 78 of 100 strategies made money in a 30-day backtest. The top 10 all followed spot momentum instead of fading it (Coinbase spot edge).

Market Making: The Edge Transfers, the Model Doesn't

In equities, retail market making is mostly closed. Retail brokers route more than 90% of individual investors' marketable orders to wholesalers (SEC, 2022). Crypto is more open: Hyperliquid's perps pay maker rebates to accounts above 0.5% of maker volume (Hyperliquid Docs, 2026). Prediction markets are the most open of all.

The relative edge is real on Kalshi. Per contract, makers averaged -9.64% returns against -31.46% for takers, so makers lost about 22 points less. Makers buying at 50¢ or higher earned 2.6% (Bürgi, Deng & Whelan, 2026). Kalshi's Liquidity Incentive Program also pays $1 to $1,000 per market per day for resting orders (Kalshi, 2026).

The model is what breaks. The textbook Avellaneda–Stoikov market maker assumes the mid-price follows continuous Brownian motion (Avellaneda & Stoikov, 2008). A binary jumps to $0 or $1 on news. The same study found makers' closing-day losses on cheap contracts look more like takers', which the authors say may reflect maker over-optimism near the close. Port your quoting engine, then rebuild inventory limits around time-to-resolution. Our market-making guide covers the binary-specific version.

Arbitrage: The Idea Transfers, the Trade Changes Shape

Arbitrage exists everywhere, but each market hides it in a different place. In UK equities, latency-arbitrage races happen about once a minute per FTSE 100 stock, with a modal race lasting 5–10 microseconds (Aquilina, Budish & O'Neill, 2022). That's a game for colocated firms. Crypto's gaps have been far larger: the Korea–US Bitcoin price gap reached 40% on several days between December 2017 and February 2018 (Makarov & Schoar, 2019).

Prediction markets hand retail a constraint continuous markets rarely do: mutually exclusive, exhaustive outcomes must sum to $1. Researchers estimated about $40 million in realized arbitrage profit on Polymarket between April 2024 and April 2025 (Saguillo et al., 2025). Most came from rebalancing within single markets. Cross-market combinatorial arbitrage made only about $95,000.

The engineering lesson transfers perfectly: leg risk kills arbitrage everywhere. Fill one side and miss the other, and you're holding a naked position. Our guide to automating cross-platform arbitrage walks through legging logic for Kalshi and Polymarket.

Citation capsule: Strategy families port unevenly from continuous to binary markets. Momentum transfers but compresses into minutes. Mean reversion breaks near expiry, surviving mainly as favorite-longshot fading. On Kalshi, makers averaged -9.64% against -31.46% for takers. About $40 million in Polymarket arbitrage came mostly from within-market rebalancing.

What Actually Transfers: Engineering, Not Alpha

Signals have half-lives. Engineering doesn't. Stock reversal fell from 1.38% a day to 0.13% in twelve years, one vivid example of an edge competed away (Khandani & Lo, 2007). What survives a venue move is the scaffolding around the signal, and even that needs sorting into what ports and what doesn't.

Key insight: When we added Kalshi Perps to Turbine Studio, the strategy format had to change. Perps need signed positions, leverage, funding, and take-profit and stop-loss the bot enforces itself. Event-contract keys like edge and trading_schedule don't exist there. What carried over: plain-English authoring, validation at save and deploy, paper trading, and the deploy pipeline. What didn't: backtesting, which Perps doesn't support yet, and most deployment risk limits. The plumbing ported. The risk vocabulary didn't.

Here's a porting checklist that holds across all three venue classes:

1. Re-derive your fee model. Percent-of-notional math is wrong on a P × (1−P) schedule. Recompute break-even per trade at the prices you'll actually trade.
2. Map the clock. Replace "market hours" with each contract's open, close, and expiration. Kill entries near expiry unless that's the strategy.
3. Rebuild sizing for capped payoffs. A binary's maximum loss is the premium. Size from that, not from a stop-loss that may never trigger. See our position sizing guide.
4. Re-test the signal, don't assume it. A strategy that wins on spot can lose as a contract. Treat the port as a new strategy, and watch for overfitting.
5. Keep the execution logic. Rate-limit handling, retries, legging rules, and kill switches transfer almost line for line.
6. Plan exits around resolution. Holding to settlement and selling early have different fee and risk profiles. Decide which one the strategy assumes before it trades.

Turbine Studio is built around this split. You describe a strategy in plain English, and Studio writes it for Kalshi or Polymarket event contracts, or for Kalshi Perps on the continuous side. Supported event-contract strategies can be backtested before you deploy (not on Polymarket US). Perps strategies can run as a paper Bot first, since perps backtesting isn't available yet (Turbine Docs, 2026).

Build a strategy for binary or continuous markets on Turbine Studio

The Bottom Line

Moving a bot between crypto, equities, and prediction markets is two problems. One is plumbing, and it's solvable. The other is payoff shape, and it decides whether your edge survives.

• Infrastructure: All three offer real APIs. Equities charge most for data, prediction markets least, and crypto sits in between
• Fees: Crypto and stocks charge per dollar; prediction markets charge P × (1−P) per contract, peaking at 50¢ and cheapest per dollar when buying favorites
• Clock: Crypto runs 168 hours a week, stocks 32.5 core hours, and prediction-market contracts run on event time
• Payoff: A binary's sensitivity grows as expiry nears; a 0.1% BTC move can swing an at-the-money contract 43¢ in the final minute
• Strategies: Momentum and arbitrage transfer in concept, market making transfers with new inventory logic, and mean reversion breaks hardest
• Engineering: Execution logic ports; fee models, sizing, and risk limits get rebuilt

If you're comfortable automating one market, you already have the engineering. What you need is a strategy re-derived for the new payoff, then tested before it trades.

Start building automated strategies on Turbine Studio

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This post is for informational purposes only and does not constitute financial, legal, or tax advice. Trading crypto, equities, perpetual futures, and prediction markets involves risk of loss, including total loss of capital. Backtests and calculations are illustrative and do not guarantee future results. Fees, rate limits, and regulations change; confirm current terms with each venue.