How Entry Filters Work
Entry filters decide when a bot is allowed to create a signal. They are the logic gate between a market idea and an actual entry attempt.
What this is
This article explains how the current product evaluates entry filters and how to build a filter set that behaves the way you expect.
When to use it
Use this article if:
- you are adding or editing rules in the Filters step
- you are getting no signals and do not understand why
- you want to understand how multiple rules combine
Before you start
Before building entry filters, make sure you already chose:
- exchange account
- market type
- symbol mode
- symbol or all-coins scope
- side
Important current behavior:
- a valid bot must contain at least one entry filter
- the editor groups filters into categories such as price, momentum, trend, volatility, volume, market data, and external
- the engine treats configured entry filters as a combined gate
Step by step
Step 1: Start with the setup idea, not with the indicator list
Before adding rules, describe the setup in plain language. For example:
- trend continuation after a pullback
- oversold reversal
- breakout confirmation with volume
That makes it easier to choose a small, coherent rule set instead of stacking unrelated indicators.
Step 2: Add only the rules needed to prove the setup
Each rule checks one condition, such as:
- price relative to a band or moving average
- momentum threshold
- crossover event
- funding or open-interest condition
- external TradingView signal
In the current engine, the rules are evaluated together. In practice:
- every configured rule must pass
- one over-restrictive rule can reduce signals to zero
Step 3: Keep the filter stack coherent
A practical structure is:
- one context rule
- one trigger rule
- one confirmation rule
Examples:
- trend + pullback + momentum turn
- breakout + volume expansion
- external signal + local confirmation
Avoid stacking many rules that all say almost the same thing.
Step 4: Understand the special cases
Some filters need extra interpretation:
- TradingView signal depends on an incoming webhook signal
- funding rate depends on funding data and ignores timeframe
- open interest change percent depends on market-data availability
- all-coins tests and backtests can surface warnings because the market universe is handled differently from a single-pair run
If you use market-data or external filters, always read the test or backtest warnings before trusting the result.
Step 5: Use Test Filters before you trust the setup
The editor includes a filter test flow. Use it every time you change the entry logic materially.
The current test flow can tell you:
- whether any signals were found
- how many signals were found
- which timestamps produced them
- which symbol produced them in all-coins mode
If the result is zero, simplify the rule set before changing grid or exits.
Step 6: Re-test after changing the basic context
If you change:
- exchange account
- market type
- symbol
- side
- symbol mode
then test the filters again. A stack that works in one context can stop making sense in another.
What you should see
By the time the Filters step is ready, you should have:
- a rule set that clearly reflects your entry idea
- a filter test result that proves the setup can produce signals
- no confusion about which rule acts as context, trigger, and confirmation
Common mistakes
- adding many indicators without defining the setup first
- forgetting that entry filters are evaluated together
- changing the symbol or side and assuming old filters still apply
- using TradingView or market-data filters without checking warnings
- treating a zero-signal test as a grid problem instead of a filter problem
Related articles
- Bot Core Fields: Exchange, Symbol, Side, Leverage, And Sizing
- Timeframe, Operator, Value, And Params
- Grid Settings
- Why Backtest Is Required Before Launch