18 articles

Building strategies

Designing rule-based strategies for crypto and TradFi perps: triggers, filters, alternative data and risk settings.

How Much Do 52 Crypto Strategies Really Diversify?

Strategy correlation explained: why crypto trend systems move together, how to estimate effective independent bets, and how to diversify a 52-strategy agent.

6 min read

Position Size vs Allocation: Oversubscribed Trading Agents

Agent allocations are now per-strategy budgets that can add up past 100%. A worked example of which entries open, which are skipped, and when to oversubscribe.

6 min read

25 Formula Strategy Recipes for Crypto Perps

Copy-ready Trigr Expression formulas for trend, mean reversion, breakouts, volatility regimes, cross-asset signals, funding data and exits, each checked.

6 min read

Formula Graph Is Live: Build Strategies From Formulas

Trigr's new formula graph lets strategy builders write entries, filters, regimes and exits as formulas across timeframes and markets. What it does, in 5 minutes.

4 min read

Pine Script to Trigr: Convert Indicators to Formulas

A function-by-function map from Pine Script v6 to Trigr formulas: ta.crossover, request.security, ta.barssince, and what still has no direct equivalent.

6 min read

Trading Strategy Formulas: The Trigr Expression Node

Trigr's Expression node lets you write entries, filters, regimes and exits as formulas across timeframes and markets, with point-in-time backtests.

7 min read

BTC Trend-Following Strategy: Build and Test It Step by Step

Build a BTC trend following strategy step by step: a trend trigger, a strength filter, ATR trailing exits and a backtest net of slippage and funding.

7 min read

Cross-Asset Trading Signals: BTC, VIX and Gold as Filters

How cross-asset trading signals work: use BTC's trend, the VIX or gold to filter trades in other markets, without look-ahead or spurious correlations.

6 min read

DVOL Trading Strategy: Filter Crypto Trades by Implied Vol

How to use DVOL, Deribit's implied volatility index for BTC and ETH, as a filter on crypto perp strategies, and how to test it without fooling yourself.

8 min read

Liquidation Trading Strategy: Cascades and Exhaustion

How a liquidation trading strategy works on crypto perps: fading exhaustion vs riding cascades, the filters that matter, and how to test it honestly.

6 min read

Long/Short Ratio Strategy: Sentiment as a Filter

How to use the long/short ratio and on-chain or social sentiment as strategy filters on crypto perps, with realistic thresholds and point-in-time data.

7 min read

Mean Reversion Crypto Strategy: RSI and Bollinger Bands

How to build a mean reversion crypto strategy on perps with RSI and Bollinger Bands: regime filters, tight exits, fees and honest intrabar fills.

8 min read

Multi-Timeframe Trading Strategy Without Look-Ahead Bias

How to build a multi-timeframe trading strategy that only uses completed higher-timeframe bars, avoiding the repainting and resampling bugs that fake backtests.

7 min read

Crypto Position Sizing: Leverage, ATR Trails, Time Stops

A practical guide to crypto position sizing and risk settings for perps: size, leverage, stop-losses, ATR trailing stops, time stops and concurrency.

7 min read

Funding Rate Trading Strategy Ideas for Hyperliquid

How funding rate and open interest work on Hyperliquid perps, which strategy ideas are worth testing, and how to backtest them without look-ahead bias.

6 min read

Macro Data Crypto Trading: FRED, VIX, COT and EIA

How to use macro data in crypto trading strategies: which FRED, VIX, COT and EIA series help, and how to avoid release-lag and revision look-ahead.

6 min read

No-Code Trading Strategy Builder: Trigger to Risk

How a no-code trading strategy builder works: wire a trigger, filters, a signal and risk settings, then backtest honestly before paper or live trading.

9 min read

Trade Stocks on Hyperliquid? HIP-3 Perps Explained

How gold, the S&P 500 and stock perps work on Hyperliquid HIP-3, and how to backtest and paper-trade TradFi strategies on them with Trigr today.

6 min read

Put the idea to an honest test.

Describe a strategy in plain English or from your own AI assistant, backtest it on point-in-time data, and forward-test it on paper before any real money is involved.