TradeArmor, Self-Hosted Automated Crypto Trading

A crypto strategy backtest showing an equity curve, win rate, and max drawdown on a self-hosted trading bot, with the reminder that past performance does not predict future results

How to Backtest Crypto Strategy Without Fooling Yourself

How to backtest crypto strategy honestly: what a backtest proves, the biases that fake your results, fees, slippage, and a self-hosted walkthrough.

Five technical indicators stacked into one overfit boolean rule next to a leaner three indicator rule pulling one signal from each category, on a self-hosted crypto trading bot's strategy builder

Signal Stacking vs. Overfitting: How Many Indicators Should a Crypto Bot Use

Signal stacking helps a crypto bot right up until it doesn't. Where confluence turns into overfitting, and how many indicators is actually too many.

Three candlestick charts of the same BTC/USDC move on 1-hour, 4-hour, and daily intervals, showing how the same price action produces a different number of candles and a different signal read on a self-hosted crypto trading bot

Best Timeframe for a Crypto Trading Bot: 1H vs. 4H vs. Daily

The best timeframe for a crypto trading bot depends on fees, monitoring time, and noise, not a magic interval. 1H vs 4H vs daily, and how to pick.

An in-sample backtest equity curve climbing smoothly next to a choppier, lower out-of-sample walk-forward curve for the same crypto trading strategy, illustrating how walk-forward testing exposes overfitting a normal backtest hides

Walk-Forward Testing vs. Backtesting: Why Your Crypto Strategy Backtest Lies to You

Walk-forward testing splits a crypto strategy backtest into blind out-of-sample windows, exposing the overfitting a normal single-pass backtest hides.