Automated Trading
Trading bots and systematic strategies: what automation can and cannot do, how to test strategies honestly, and how to run them safely.
Start with guide 1- 1
What Are Crypto Trading Bots?
What bots can and cannot do, the honest case for automation, and the main bot categories.
- 2
Grid Trading Strategy Explained
Grid mechanics, ideal (ranging) conditions, parameter choices, and failure modes in trends.
- 3
DCA Bots: Automating Dollar-Cost Averaging
Automated accumulation, safety orders, and how DCA bots differ from simple recurring buys.
- 4
Indicator and Signal-Based Bots
Turning TA rules into bot logic, signal quality, and why most signal marketplaces disappoint.
- 5
Backtesting a Strategy Honestly
Overfitting, look-ahead bias, fees/slippage modeling — why most backtests lie and how to make yours honest.
- 6
Paper Trading Before Real Money
Forward-testing on live data with zero risk, what paper results do and don't predict.
- 7
Trailing Stop-Losses in Automated Trading
Trailing stop mechanics in bots, parameter tuning, and interaction with volatility.
- 8
Arbitrage: Theory vs Retail Reality
Cross-exchange and triangular arb, why retail arb margins are mostly gone, and what remains.
- 9
Risk Management for Bot Portfolios
Per-bot allocation, correlation across bots, kill switches, and drawdown budgets.
- 10
Copy Trading and Strategy Marketplaces
Following other traders' strategies: survivorship bias in leaderboards and due-diligence checks.
- 11
API Keys and Bot Security
Scoping keys (no withdrawal rights), IP allowlists, and key rotation for bot setups.
- 12
Choosing a Bot Platform and Exchange
Evaluation criteria: exchange API quality, fees, backtest fidelity, and platform track record.
- 13
Adapting Bot Strategies to Bull and Bear Markets
Regime detection, when to switch strategy types, and when to switch bots off entirely.
- 14
Common Mistakes New Bot Traders Make
Over-optimization, over-allocation, ignoring fees, and set-and-forget syndrome.