Core Signals to Include in a High‑Probability Pipeline

1. Liquidity & Exchange Listing Filters

Set minimum daily volume (e.g., $500k–$2M) and minimum order book depth (e.g., ability to buy/sell 0.5% of circulating supply without 1% slippage). Prefer assets listed on reputable exchanges — for Canadians, exchanges like Bitbuy and Newton can be starting points for spot liquidity, but add global venues for cross‑exchange signals. Low liquidity assets create false breakouts and extreme slippage.

2. Volume & Volume Z‑Score

Volume spikes are often the earliest, reliable confirmation of interest. Compute a z‑score for volume (current volume minus 20‑period mean divided by standard deviation) and flag tickers with z > 2.5 for further review. Visual: imagine a price chart where a daily candle bursts above a consolidation zone with a 3x volume spike — that’s a high‑priority candidate.

3. Volatility Filters (ATR & Range Expansion)

Use ATR to ensure the asset has tradable volatility. Filter out coins with very low ATR relative to price (e.g., ATR/price < 0.5%) for day trades. For breakouts, look for range expansion: current candle range / 20‑period average range > 2.

4. Technical Confluence

Combine simple technical checks: price > 20 EMA (trend), pullback to a support (moving average, previous consolidation, VWAP or a supply zone), and momentum confirmation (e.g., RSI between 45–70 for continuation). Confluence raises hit rate compared to single indicator screens.

5. Funding Rates & Perps Basis

For perpetual futures arbitrage or directional perps trades, include funding rate divergence — unusually high positive funding can indicate crowded long positions and mean reversion risk. Track basis (spot vs. perp price) to spot cheap hedged carry trades.

6. On‑Chain Flow Signals

Exchange inflows/outflows, large transfers (whale movement), and stablecoin mint/reserve flows often precede moves. Screen for items like sudden exchange outflows (accumulation), exchange inflows (potential selling pressure), or large transfers into known custodial wallets. Combine these with on‑chain volume for stronger signals.

7. Token Event and Supply Filters

Filter out tokens with imminent large unlocks or token unlocks in the filter so you don’t take momentum against significant supply pressure. Alternatively, flag assets with scheduled positive catalysts (protocol upgrades, airdrops, exchange listings) and increase rank if other signals support them.

8. Social & Sentiment Triggers

Short‑term retail surges often show up on social platforms. Use a sentiment score combined with volume and on‑chain flow to avoid false positives caused by pump noise. Require sentiment > neutral and a corresponding volume confirmation before acting.

From Signal to Trade: Rules, Execution & Risk

Entry & Confirmation Rules

Convert a screen hit into a trade with a concise rule: e.g., after a screener hit confirm on the 1‑hour close above prior consolidation high with volume z > 2, then enter on a retest to the breakout zone (or enter on breakout with tighter stop). Never trade only on the screen without a contextual price confirmation.

Position Sizing & Stop Placement

Use fixed risk per trade (e.g., 0.5–1% of equity). Calculate position size by distance to stop: position size = risk capital / (entry price - stop price). Consider volatility scaling: larger ATR > wider stops and proportionally smaller size. For leverage products, cap effective leverage and use partial scaling into the trade.

Execution Considerations

Account for slippage and fees. For small cap altcoins, split orders or use limit post‑only orders to reduce slippage. For DEX trades, simulate or estimate gas and routing costs; MEV and slippage can kill a trade. Prefer pairs with stablecoin depth (USDT/USDC) for predictable fills. On CEXs, use IOC or post‑only where appropriate and watch maker/taker fee tiers.

Common Pitfalls & Maintenance

Screener drift is real: signals that worked in one regime may fail in another. Regularly re‑calibrate thresholds every quarter or after major regime changes. Avoid overfitting — prefer simple, explainable rules. Beware of data hygiene: APIs, timezones, and missing data can cause false triggers. Keep a test environment running live paper trades for at least 3 months before allocating real capital to a new pipeline.