# Finding a reliable LLM for Polymarket trading
> Source report: https://gapforapp.com/reports/finding-a-reliable-llm-for-polymarket-trading

## 1. What we're building
Build “Polymarket Guardrailed Trader,” an LLM-assisted trading control plane that never treats an LLM as the sole decision-maker. The product should implement an explicit separation between signal synthesis and execution via hard-coded gates (regime-confidence thresholds, kill-switches tied to slippage/spread, and deterministic risk controls) and require structured, verifiable outputs rather than free-form probability numbers. It should also support safe copy-trading flows that react to on-chain/market events in real time without custody (no private-key exposure) and include guardrails to prevent blind following of unsafe wallets (e.g., timing dependence, unresolved-gains concentration, and accumulation-matching rules).

The must-have feature set should include: (1) real-time data integration so outputs reflect current pricing (not “no live data” behavior), (2) forward testing and testability that accounts for LLM drift/backtest pitfalls (prompt/version control, walk-forward evaluation, and forward-only validation), (3) aggregated alerts rather than alert overload, including links/clarity for contract resolution criteria, (4) trade execution safety including rollback/hedge fallback when multi-leg actions partially fill, (5) stop-loss / risk integration for automated behavior, and (6) sources/reasoning so users can verify the model’s claims. To directly address skepticism that “raw LLMs… can’t tell you what’s pricing right now,” include calibration tracking and continuous re-evaluation behavior, plus a mechanism to compare and benchmark multiple model variants over time (so users can “test/run different LLMs and determine which performs best”).

**Working name:** Polymarket Guardrail Trader
**Tagline:** LLM-assisted Polymarket trading control plane with real-time gates, no-custody copy rules, and forward-only tests.
**Main goal:** Enable users to approve a testable, guardrailed workflow that turns LLM signal synthesis into deterministic, verifiable execution only when risk gates pass.
**Target users:** Day traders and quant-minded Polymarket users who want mispricing scanning and safe automation without giving custody or using LLMs as the decision-maker.

**Main user result:** User gets a ranked Polymarket watchlist plus an auditable “Execute / Don’t execute” decision driven by real-time data and deterministic risk gates, not raw LLM odds.
**5-minute outcome:** User connects (read-only) to Polymarket data, runs one market scan, and sees which candidates would be executable under fixed spread/slippage/liquidity kill-switches.
**What we solve first:** We ship the guardrailed signal-to-execution pipeline with structured LLM outputs, hard gates, and aggregated alerting.
**Out of scope for MVP:**
- Multi-wallet portfolio optimization across many markets (beyond initial rule set)
- Automatic custody or private-key management
- Continuous, LLM-driven position management without deterministic policies

## 2. Why this is worth building
- Verdict: **LOW** (40/100)
- The corpus does not converge on any specific LLM as a clear “best” choice for Polymarket trading. Instead, it repeatedly argues that LLMs are unsuitable as deterministic, real-time trading engines because of hallucinations, stochasticity, latency, and poor point-in-time reliability. The most consistent requirements are around systems engineering and workflow reliability (execution gates, safe copy behavior, verification, and rigorous forward testing), not model preference. Therefore any single-model recommendation would likely be incomplete compared to a robust architecture that constrains and verifies LLM outputs.

**Current pain:** Users struggle to find a “best LLM” that trades Polymarket reliably because LLMs can’t guarantee live pricing accuracy and can hallucinate probabilities/odds. Execution also requires fast, microstructure-aware kill-switches (spread/slippage/liquidity) to avoid catastrophic outcomes.
**Current workaround:** They either run LLM-only analysis (then manually decide), rely on community bots or Discord suggestions, or try rule-based heuristics without robust forward-only testing and auditability.
**Why existing tools fail:** General LLM approaches (including sentiment/macro fusion) don’t provide live market-integrated, deterministic execution authority, and commenters emphasize slippage/spread and the need for gates. Even “AI gate” setups underperform pure rules, and many approaches lack contract-dynamic backtest continuity and forward-only validation.

## 3. Must-have capabilities
### 3.1 Real-time Polymarket pricing + structured market snapshots (no “no live data” behavior)
**Why:** Users explicitly want outputs to reflect current pricing, not stale/hallucinated odds.
**Evidence:** post #10852 — *"Real-time data integration"*

### 3.2 Deterministic execution gates: LLM provides regime/signal, hard-coded risk gates decide execution permission
**Why:** The core requirement is never treating an LLM as the sole decision-maker; execution must be gated by thresholds and deterministic controls.
**Evidence:** post #10868 — *"I stripped the LLM of trade execution authority"*

### 3.3 Micro kill-switches tied to spread/slippage + liquidity/imbalance signals (not only PnL)
**Why:** Users asked for catastrophic-downside control and kill-switches that respond to microstructure conditions.
**Evidence:** post #10868 — *"Kill-switch tied to spread expansion and slippage"*

### 3.4 Structured, verifiable LLM outputs (regime confidence + categorical decisions), never free-form “probabilities only”
**Why:** Constrained outputs + confidence thresholds are demanded to prevent unsafe/uncertain behavior and “no number/blank card” UX.
**Evidence:** post #10868 — *"Explicit regime-confidence threshold before size-up."*

### 3.5 Aggregated alerts UI with links to contract resolution criteria
**Why:** Users want fewer, clearer alerts with resolution criteria to verify claims and avoid confusion.

### 3.6 Forward testing + testability via prompt/version control and walk-forward evaluation (forward-only validation)
**Why:** Users want trading/analysis that is genuinely testable and reliable, avoiding prompt drift and backtest pitfalls.

### 3.7 Backtest/live continuity for dynamically created/changed strikes/contracts (intraday handling)
**Why:** Polymarket contract dynamics make standard chart-based backtests unreliable; users explicitly requested this handling.

### 3.8 Stop-loss / risk management integration + additional risk metrics beyond max drawdown
**Why:** Users explicitly asked for stop-loss integration and tracking more risk metrics.

### 3.9 Safe copy-trading without custody: follow rules with anti-blind-follow guardrails (timing dependence, unresolved-gains concentration, accumulation-matching rule
**Why:** Users demanded safe copytrading that avoids blind following and reacts to on-chain/market events in real time without private keys.

### 3.10 Execution rollback / hedge fallback for multi-leg actions when partial fills occur
**Why:** Users explicitly asked for rollback/hedge fallback when first leg fills but the second doesn’t.

## 4. Use cases & user stories
A web SaaS that continuously pulls real-time Polymarket pricing, runs an LLM in synthesis mode to label a regime with categorical decisions, then allows deterministic execution only when explicit risk gates pass (kill-switches tied to spread/slippage/liquidity). It also provides aggregated alerts with contract resolution criteria links and a forward-only test harness with versioned prompt/schema c

### Use cases
**4.1 Regime-gated mispricing scanner (AI finds divergence; bot only trades when gates pass)**
A trader selects a market category and risk profile. The system continuously pulls current Polymarket odds and computes a deterministic “mispricing vs reference” shortlist. The LLM then synthesizes a regime label plus confidence (e.g., Risk-On/Risk-Off) and produces structured rationale only for explainability; however, execution permission is granted only if regime-confidence and kill-switch gates pass (spread/slippage/liquidity checks). The UI shows aggregated alerts with contract resolution criteria links and includes a traceable “why” panel that cites the specific evidence used for the regime decision.

**4.2 Safe copy-trading of a wallet with real-time anti-blind-follow rules**
A user chooses a verified wallet to follow and sets personal risk limits and maximum allowed chase behavior. The platform monitors on-chain position changes in real time (no private key custody) and decides whether to mirror trades based on guardrails: avoid chasing large moves, only copy near appropriate accumulator/entry conditions, and prevent concentration when unresolved gains are concentrated. If a multi-leg mirroring sequence partially fills, the execution engine triggers rollback/hedge fallback. The user receives aggregated daily/weekly reports plus immediate alerts when guardrails block a follow, with clear reasons and resolution-criteria links.

### User stories
- **As a Small-account day trader**, I want to receive an aggregated alert within seconds when tracked wallets open new Polymarket positions, but only if kill-switches and risk gates allow safe mirroring, *so that* I can react before the price moves without blindly copying unsafe behavior
- **As a Quant-minded Polymarket user**, I want to test a strategy forward-only using versioned prompts and deterministic code generation so results don’t break from LLM drift or backtest leakage, *so that* I can trust the edge before risking real capital

## 5. Pages & form factor
**Form factor:** Web SaaS dashboard with execution/monitoring API + optional browser extension companion
**Why:** A web SaaS lets us host the guardrailed control plane, run forward-only evaluations, and provide real-time pricing/monitoring with aggregated alerting. It also matches the product’s need for authenticated accounts, intraday backtest/live continuity, and operational visibility that’s hard to do in a browser-only or CLI-only interface.

### Pages
**5.1 Overview Dashboard**
Primary landing page for current scanning status, active strategies, and risk/kill-switch state.
Key elements:
- Active strategies list with current regime + confidence
- Kill-switch status indicators (spread/slippage/liquidity derived)
- Real-time market snapshot tiles (structured pricing data)
- Aggregated alerts feed (ranked, grouped by market/outcome/time window)
- Forward-test/live continuity health (dynamic strikes/contracts tracking)

**5.2 Market Scanner**
Surfaces mispriced contracts relative to a reference and produces a ranked watchlist.
Key elements:
- Reference model config (implied odds / sharp reference)
- Mispricing threshold controls (e.g., implied odds difference)
- Ranked watchlist table with regime labels
- Attached resolution criteria links for each flagged market
- Scan scheduler controls (e.g., every 4 hours) and last-run timestamps

**5.3 Execution Console**
Shows deterministic execution decisions with hard gates and provides full auditability for each attempted trade.
Key elements:
- Trade decision timeline (LLM regime output -> validity gate -> execution permission)
- Structured LLM output viewer (categorical decision + confidence + version)
- Risk gate status (spread/slippage/liquidity + stop-loss/risk metrics)
- “What would have happened” simulation panel (forward-only validation results)
- Manual override panel (only for permitted safe actions)

**5.4 Watchlists & Copy Rules**
Implements safe copytrading controls (no blind copying) and accumulator-aware guardrails.
Key elements:
- Choose source (tracked wallet/trader signal source) and monitoring targets
- Rule set for when copying is allowed (position/correlation/accumulator constraints)
- “Copy only when near average entry” toggle
- Alert preferences for wallet moves and trade lifecycle events
- Risk limits per copied position (stop-loss tightening, partial profits)

**5.5 Backtest & Forward Test**
Provides walk-forward evaluation and forward-only validation with dynamic-strike intraday handling.
Key elements:
- Prompt/version control selection for the LLM regime outputs
- Walk-forward evaluation runner (forward-only, no leakage)
- Dynamic strike/contract continuity settings (intraday changes)
- Execution simulation settings (spread/slippage models, liquidity assumptions)
- Results dashboard with edge validation metrics (regime accuracy + risk metrics)

**5.6 Alerts & Fraud Radar**
Ranked “fraud radar” style alerts and aggregated monitoring for suspicious patterns.
Key elements:
- Ranked suspicion watchlist (grouped alerts by market/time window)
- Liquidity/spread/slippage anomaly alerts (micro kill-switch triggers)
- Insider-trading-like pattern detection events (rule-based signals)
- Wallet-change alerts and why-explanations
- One-click links to resolution criteria and affected markets

**5.7 Accounts & Integrations**
Connect Polymarket accounts/wallets, configure risk defaults, and manage execution permissions.
Key elements:
- Account verification status and investor/account evaluation mode
- Polymarket API connection health (real-time snapshot integrity)
- Risk profile defaults (max spread, max slippage, liquidity thresholds)
- Notification channels (webhooks/email) with throttling controls
- Dependency/policy guardrails status (supply-chain checks indicator)

**5.8 Model & Prompt Governance**
Admin page for prompt/version control, structured output schemas, and walk-forward evaluation settings.
Key elements:
- Prompt version history with changelog
- Structured output schema viewer (regime confidence + categorical decisions)
- Confidence thresholds configuration (signal validity vs execution permission)
- Audit logs (LLM inputs/outputs hashes) for each execution attempt
- Test suite results (forward-only evaluation artifacts)

### Key functions
- **Run market scan** *[on: Market Scanner]*
  - Trigger: User clicks “Run now” or schedules the next scan interval.
  - Fetches real-time pricing snapshots, computes mispricing vs the sharp reference, and emits a ranked watchlist for further gating.
- **Attach resolution criteria to alerts** *[on: Alerts & Fraud Radar]*
  - Trigger: When a market is flagged or added to a watchlist.
  - Shows the market’s resolution criteria text/link directly in the alert UI for operator verification.
- **Generate regime decision from structured output** *[on: Execution Console]*
  - Trigger: User enables “Auto-evaluate” for a watchlist item or runs a dry-run execution.
  - Calls the LLM in data-synthesis mode to produce a categorical regime + confidence that is never used as a direct probability for trade sizing.
- **Validate signal validity gate** *[on: Execution Console]*
  - Trigger: Before any order is created for a candidate trade.
  - Runs deterministic validity checks (strategy feature requirements, market snapshot completeness, and contract identity matching) and blocks if invalid.
- **Request execution permission from risk gate** *[on: Execution Console]*
  - Trigger: After signal validity passes and a regime is available.
  - Evaluates spread/slippage/liquidity-derived micro kill-switches and confidence thresholds to decide whether execution is allowed.
- **Execute constrained trade sizing** *[on: Execution Console]*
  - Trigger: User clicks “Execute (safe)” or when auto-execution is enabled and all gates pass.
  - Places orders using deterministic sizing/risk parameters; the LLM does not output free-form probabilities.
- **Auto-close position on next-day rule** *[on: Execution Console]*
  - Trigger: When a trade is opened under the enabled “next-day close logic” configuration.
  - Closes positions according to a deterministic hold window policy rather than LLM continuous judgment.
- **Apply long/short mispricing thresholds** *[on: Execution Console]*
  - Trigger: User configures or selects a strategy preset for mispricing thresholds.
  - Implements deterministic mapping rules: if model implied odds differ from Polymarket by more than threshold, choose direction and enforce hold/exit policy.
- **Start walk-forward evaluation** *[on: Backtest & Forward Test]*
  - Trigger: User clicks “Run forward-only evaluation” for a selected prompt/version.
  - Runs walk-forward tests and produces artifacts used to validate edge without using future information.
- **Maintain contract continuity for intraday changes** *[on: Backtest & Forward Test]*
  - Trigger: When strikes/contracts change intraday during backtest or live evaluation.
  - Automatically remaps positions and simulations across dynamically created/changed contracts to avoid evaluation discontinuities.
- **Monitor tracked wallet trade lifecycle** *[on: Watchlists & Copy Rules]*
  - Trigger: Wallet-change monitors are active; a tracked wallet executes or changes positions.
  - Detects wallet transaction/position changes and triggers copy-rule checks with operator notifications.
- **Copy only accumulator behavior** *[on: Watchlists & Copy Rules]*
  - Trigger: When a tracked signal would otherwise place a copy trade.
  - Blocks copy trades unless the target is an accumulator near average entry and not chasing large moves.
- **Run insider-pattern anomaly detection** *[on: Alerts & Fraud Radar]*
  - Trigger: Continuously evaluates event rules on wallet/position activity.
  - Raises alerts when suspicious patterns resemble insider-trading-like behavior based on defined event rules.
- **Export scan + execution audit logs** *[on: Execution Console]*
  - Trigger: User selects a run/session and clicks “Export”.
  - Exports verifiable execution audits including regime outputs, gate decisions, and market snapshot hashes for review.

### UX details
- **Execution Console decision ordering:** Always render the chain as: LLM data synthesis -> regime confidence threshold -> signal validity gate -> execution permission gate (never reverse order).
- **Kill-switch behavior:** If micro kill-switch triggers, freeze new orders and optionally reduce sizing until spread/slippage normalizes (no “only PnL” logic).
- **Alert aggregation:** Default alert view is grouped/aggregated rather than a stream of one-off alerts to reduce noise.
- **Regime output display:** Display regime decision as a categorical label with confidence; do not show raw “probability of win” as the actionable input.
- **Resolution criteria visibility:** Every market alert card must include a direct link/snippet to the market’s resolution criteria for immediate operator verification.
- **Copytrading guardrails:** When copying, disable actions that would chase after large moves and require accumulator-near-average-entry status.
- **Scanner scheduling UX:** Expose a simple scheduler preset (e.g., 4-hour loop) with visible last-run time to match user expectations of periodic screening.
- **Forward/live parity checks:** During intraday remapping, annotate the continuity method used so users can see when strikes/contracts changed between simulation slices.

## 6. Monetization
**Model:** (unspecified)

## 7. Competitors to beat
| Name | Why it fails | Price | Mentions |
|---|---|---|---|
| LLMs for macro context + AI fusion (Gemini + another LLM) | This chunk highlights risks and limitations around execution and data realism rather than proving edge; commenters emphasize slippage/spread and that paper trading may not reflect live conditions. | - | - |
| Backtesting over longer periods / with better data vendor (databento, options omega) | The criticism is that one-month or short-window backtests are too limited; also some backtests may assume mid prices or ignore execution frictions, which can mislead. | - | - |
| ChatGPT (general AI) for trade journaling and trade insights | The prediction-markets review criticizes general AI as having “No live data. No actual market integration” and sometimes “hallucinates a number” for odds, producing “2-3 generic paragraphs that don't move the needle” with “no methodology… no confidence scoring, no framework”. | - | - |
| Constrained output fields (action, confidence, reasoning, risk_level) for the LLM gate | Even with constrained output, the overall result is worse than rule-based; best AI config (V7) captured '82% of rule-based returns' and protection compliance '89%'. | - | - |
| PredictionHunt Discord (bot setups for poloymmarket) | Suggests community sharing but does not provide a concrete 'best LLM for Polymarket trading' solution in this chunk. | - | - |
| Use an LLM as an execution gate (prompting / structured reasoning / constrained output / ensemble / ML hybrid) | In the described experiments, 'rule-based systems won across every configuration I tested', with best AI capturing only '82% of rule-based returns' and protection compliance dropping to '89%'; failure modes include overriding protection rules, 2-4s latency, stochastic differing outputs, and confidence not correlating with outcomes. | - | - |
| @sightwhale_bot Telegram whale alert system | Even with zero-delay alerts, a commenter argues the core problem remains knowing "WHY the whale is betting." | - | - |
| accountable.finance AI-enabled strategy creator | Not described as an execution/trading tool; approach explicitly states not to use AI for actual analysis/execution. | - | - |

## 8. Distribution
- Top subreddits to launch in: r/Daytrading, r/Trading, r/algotrading, r/CryptoCurrency, r/options, r/quant, r/Polymarket, r/DecentralizedFinance, r/PillarLab, r/LocalLLaMA

## 9. Users & roles
**Primary persona:** Guardrailed Polymarket trader
**Secondary personas:**
- No-custody copy-follower (wants safe mirroring)

**Roles:**
- **Operator** — Configures strategies, risk gates, watchlists, and approves executions shown in the audit trail.
- **Viewer** — Views alerts, backtest/forward test artifacts, and copy-trade rule status without approval permissions.
- **Admin** — Manages prompt/schema versions and walk-forward evaluation settings with immutable audit logs.

## 10. Data model & integrations
- (no data model extracted)

## 11. States
**Empty state:** User sees a blank scan page prompting for Polymarket read-only connection and strategy/risk gate configuration.
**Error state:** User sees a red banner with the failing gate stage (data fetch vs schema validation vs risk gate) and a retry button.

## 12. Analytics & metrics
- (not synthesized for this report)

## 13. Risks & open questions
- (no risks/questions extracted)

## 14. Post-launch
- See https://gapforapp.com/reports/finding-a-reliable-llm-for-polymarket-trading for DM-able hot leads (workarounds × buying intent).
- See https://gapforapp.com/reports/finding-a-reliable-llm-for-polymarket-trading for verified key quotes you can use as landing copy.

## 15. Suggested build order (3-week MVP cut)
- Week 1: §3 must-haves + §5 page 1.
- Week 2: §5 remaining pages + auth/persistence if needed.
- Week 3: §6 monetization wiring + analytics + launch checklist.

## 16. Setup hints (your stack overrides these)
- `pnpm create next-app . --typescript --tailwind --app`
- `npx shadcn@latest init`
- The agent SHOULD ask the user before committing to a stack.

## 17. How to use this file
You're an AI coding agent reading this in AGENTS.md. Your job:
1. Confirm the stack with the user (their preferences override this file).
2. Scaffold an MVP covering §3 + §5 page-1 first.
3. Defer §6 (monetization) and §14 (post-launch) until §3 ships and works.
4. Re-fetch the live PRD anytime via:
   curl https://painfinder-api.fly.dev/api/public/reports/finding-a-reliable-llm-for-polymarket-trading/export.json?size=compact

## 18. Verbatim key quotes (top 10)
> "AI models tend to fail utterly."  
> — LLM hallucinations & limits, post #10578

> "All the newsrooms replacing reporters with AI are going to be so incredibly fucked when they realise the limitations of LLMs."  
> — News-driven trading, post #10578

> "ML will not find patterns by itself from candlesticks or indicators or whatever else you just throw at it (too much noise, it can't generalize well)."  
> — Strategy architecture & indicators, post #10542

> "However, this is almost always bound to fail - machine learning is NOT good at creating its own edge out of nowhere (especially LLM’s, I see that a lot too. They’ll just tell you what it thinks you want to hear."  
> — LLM hallucinations & limits, post #10542

> "Any lessons deploying RL agents into live markets?"  
> — Strategy architecture & indicators, post #10873

> "This is.. basically impossible. If you figure it out, I'll be mighty impressed (and slightly miffed)."  
> — LLM hallucinations & limits, post #10873

> "84.1% of participants were unprofitable."  
> — Uncategorized, post #10588

> "The wallets making serious money are concentrated around arbitrage, market making, and execution speed."  
> — Strategy architecture & indicators, post #10588

> "it also reads the live orderbook to detect liquidity "walls" (huge orders that can stop the price) and calculate the real-time bid/ask imbalance (buyer vs. seller pressure)."  
> — Strategy architecture & indicators, post #10557

> "It uses an LLM (Gemini, free API) to analyze the macro context."  
> — LLM model choice, post #10557

## 19. Manual workarounds users cobble together (top 15)
- (none extracted yet — see live report)

## 20. "I would pay for…" quotes (top 10)
- (none extracted yet — see live report)

## 21. Hot leads summary
- (none extracted yet — see live report)

## 22. Full competitor list (top 10)
| Name | Why it fails | Price | Mentions |
|---|---|---|---|
| LLMs for macro context + AI fusion (Gemini + another LLM) | This chunk highlights risks and limitations around execution and data realism rather than proving edge; commenters emphasize slippage/spread and that paper trading may not reflect live conditions. | - | - |
| Backtesting over longer periods / with better data vendor (databento, options omega) | The criticism is that one-month or short-window backtests are too limited; also some backtests may assume mid prices or ignore execution frictions, which can mislead. | - | - |
| ChatGPT (general AI) for trade journaling and trade insights | The prediction-markets review criticizes general AI as having “No live data. No actual market integration” and sometimes “hallucinates a number” for odds, producing “2-3 generic paragraphs that don't move the needle” with “no methodology… no confidence scoring, no framework”. | - | - |
| Constrained output fields (action, confidence, reasoning, risk_level) for the LLM gate | Even with constrained output, the overall result is worse than rule-based; best AI config (V7) captured '82% of rule-based returns' and protection compliance '89%'. | - | - |
| PredictionHunt Discord (bot setups for poloymmarket) | Suggests community sharing but does not provide a concrete 'best LLM for Polymarket trading' solution in this chunk. | - | - |
| Use an LLM as an execution gate (prompting / structured reasoning / constrained output / ensemble / ML hybrid) | In the described experiments, 'rule-based systems won across every configuration I tested', with best AI capturing only '82% of rule-based returns' and protection compliance dropping to '89%'; failure modes include overriding protection rules, 2-4s latency, stochastic differing outputs, and confidence not correlating with outcomes. | - | - |
| @sightwhale_bot Telegram whale alert system | Even with zero-delay alerts, a commenter argues the core problem remains knowing "WHY the whale is betting." | - | - |
| accountable.finance AI-enabled strategy creator | Not described as an execution/trading tool; approach explicitly states not to use AI for actual analysis/execution. | - | - |
| AI agent Kumo for pulling multiple forecasts and selecting which to trust | Not presented as a Polymarket trading LLM; only mentioned as being “pretty interesting so far” for weather/forecast selection, so evidence of trading usefulness is limited in this chunk. | - | - |
| AI agent paper-trading leaderboard (Minimax-m2, Nemotron-3-nano:30b, etc.) | Critics say conclusions are distorted because paper trading ignores costs: "Excluding fees, spreads and slippage" and the stated edge (30-80bps) may be neutralized by "new poly v2 fees"; also concerns about realistic orderbook depth and slippage. | - | - |

## 23. Where this conversation lives (top subreddits)
- r/Daytrading (59 posts)
- r/Trading (56 posts)
- r/algotrading (51 posts)
- r/CryptoCurrency (48 posts)
- r/options (40 posts)
- r/quant (39 posts)
- r/Polymarket (38 posts)
- r/DecentralizedFinance (11 posts)
- r/PillarLab (4 posts)
- r/LocalLLaMA (4 posts)