Trading Bot Strategies: What Actually Works (And What's Just Marketing)

"This bot made 500% last month!"

Cool. Show me the next month.

The trading bot industry is full of promises. Passive income. Set and forget. Let the algorithm do the work.

Most of it is garbage. Let me explain why—and what actually works.

The Bot Strategy Landscape

There are basically four types of trading bot strategies:

1. Grid Bots

Place buy orders below current price, sell orders above. Profit from oscillation.

Pros: Works in ranging markets. Simple to understand. Cons: Gets destroyed in trends. Loses money when price moves one direction.

2. DCA Bots

Dollar-cost average into positions. Buy regularly regardless of price.

Pros: Reduces timing risk. Good for accumulation. Cons: Not really "trading." Just automated buying.

3. Signal Bots

Execute trades based on technical indicators. RSI, MACD, moving averages.

Pros: Can capture trends. Systematic approach. Cons: Indicators lag. Most signal strategies underperform.

4. Conditional Order Bots

Execute based on complex, multi-factor conditions. Price + pattern + volume + timing.

Pros: Can replicate sophisticated trading logic. Flexible. Cons: Requires good strategy design. Garbage in, garbage out.

This last category is what dashpull does. And it's the only one I trust.

Why Most Bots Fail

Problem 1: Curve Fitting

Bot sellers show you backtests. Amazing returns. Perfect equity curves.

What they don't tell you: the strategy was optimized to fit historical data. It found patterns that existed in the past but won't repeat.

This is called curve fitting. It's the #1 reason bots fail in live trading.

Problem 2: Market Regime Changes

A bot optimized for 2021's bull market will fail in 2022's bear market.

Markets change. Volatility changes. Correlations change. A static bot can't adapt.

Problem 3: Execution Reality

Backtests assume perfect execution. Reality is messier.

Slippage. Fees. Latency. Liquidity issues. These eat into returns.

A strategy showing 50% annual returns in backtest might show 20% in reality. Or negative.

Problem 4: No Edge

Most bot strategies have no actual edge. They're just systematized randomness.

"Buy when RSI < 30" isn't an edge. It's a rule that sometimes works and sometimes doesn't.

An edge requires understanding WHY something works. Not just THAT it worked historically.

What Actually Works

After years of testing bots, here's what I've found:

1. Simple Strategies Beat Complex Ones

The more parameters, the more curve fitting risk.

A strategy with 3 conditions is more robust than one with 15 conditions.

Simple strategies might have lower backtested returns, but they actually work in live trading.

2. Conditional Logic Beats Indicator Signals

"RSI < 30" is a weak signal.

"RSI < 30 + price at major support + bullish engulfing + volume spike" is a strong signal.

The combination of conditions filters out noise. Each condition alone is weak. Together, they're powerful.

3. Risk Management Is the Strategy

The best entry signal in the world is worthless without risk management.

Position sizing. Stop losses. Maximum drawdown limits. These determine long-term success more than entry signals.

4. Human Oversight Matters

Fully autonomous bots are dangerous. Markets change. Bots don't adapt.

The best approach: human judgment for strategy design, automated execution for consistency.

My Bot Strategy Framework

Here's how I approach trading automation.

Step 1: Define the Edge

What's the hypothesis? Why should this work?

"Price tends to bounce at support levels, especially on the second touch with confirmation."

That's a hypothesis I can test and understand.

Step 2: Specify Conditions

Turn the hypothesis into specific, measurable conditions.

• Price within 1% of identified support
• This is the 2nd or 3rd touch
• Bullish engulfing candle forms
• Volume above 20-period average

No ambiguity. Either conditions are met or they're not.

Step 3: Define Risk Management

Before thinking about entries, define:

• Maximum risk per trade (1% of account)
• Stop loss placement (below support)
• Position sizing (based on stop distance)
• Maximum open positions (3)

Step 4: Automate with Oversight

Set up the conditions in dashpull. Let the system watch and execute.

But review regularly. Are the trades working? Do conditions need adjustment?

Step 5: Iterate

No strategy works forever. Markets change.

Review performance monthly. Adjust conditions if needed. Retire strategies that stop working.

The Strategies I Actually Run

Strategy 1: Support Bounce

Conditions:

• Price at identified support (within 1%)
• 2nd or 3rd touch of level
• Bullish confirmation candle
• Volume confirmation

This captures bounces at key levels. Simple, effective.

Strategy 2: Trend Pullback

Conditions:

• Confirmed uptrend (higher highs/lows)
• Price pulls back to 20 EMA
• RSI between 40-50
• Bullish candle at EMA

This enters trends on pullbacks. Better entries than breakouts.

Strategy 3: Funding Rate Fade

Conditions:

• Funding rate > 0.1% (extreme)
• Price at resistance
• Bearish confirmation candle

This fades overcrowded positions. Works well in crypto.

All three are set up in dashpull. They run continuously. I review weekly.

Red Flags in Bot Marketing

How to spot a scam bot:

Red Flag 1: Unrealistic Returns

"500% monthly returns!"

If it sounds too good to be true, it is. Sustainable returns are 20-50% annually, not monthly.

Red Flag 2: No Drawdown Disclosure

They show profits but hide losses. Every strategy has drawdowns. If they're not showing them, they're hiding something.

Red Flag 3: Black Box

"Our proprietary algorithm..."

If they won't explain how it works, don't trust it. You should understand what you're running.

Red Flag 4: Pressure Tactics

"Limited spots available! Sign up now!"

Good strategies don't need high-pressure sales. Scams do.

Red Flag 5: No Track Record

Backtests are not track records. Live, verified performance is.

Ask for Myfxbook, 3Commas, or exchange-verified results. Not screenshots.

The Bottom Line

Trading bots can work. But most don't.

The ones that work:

• Have simple, understandable logic
• Use conditional logic, not just indicators
• Include robust risk management
• Are monitored and adjusted by humans

dashpull is my tool for this. I define the conditions. The system executes. I maintain oversight.

It's not "set and forget." It's "set, monitor, and adjust."

That's the reality of trading automation. Anyone telling you otherwise is selling something.

Ready to build real trading automation? Try dashpull →