Kill Switch, Average True Range (ATR)

Learn how to implement an algo trading kill switch using ATR to avoid high volatility, specifically for E-mini S&P 500 futures on daily bars.

Published · Updated · Methodology: Technical Indicators

Part of: ATR & Volatility

  • Methodology: Technical Indicators
  • Content type: educational
  • Timeframes: Daily bars (inferred from 'year's worth of volatility')
  • Markets: E-mini S&P 500 futures

Indicators used

  • ATR

Source video

Decoded from: I Improved This Strategy By $49K - Find Out This Little Used Algo Trading Trick by Algo Trading With Kevin Davey — watch the original

Key timestamps:

  • 0:25 - Introduction to kill switch concept
  • 1:00 - Theory behind the kill switch (avoid high volatility)
  • 1:45 - Code explanation for the kill switch (TradeStation)
  • 2:00 - Kill switch condition: ATR(14) vs ATR(250)
  • 2:45 - Impact on a sample strategy (before/after)
  • 3:45 - Performance improvement example
  • 4:20 - Best practices for implementing kill switches

Strategy overview

Average True Range (ATR) measures how much an instrument actually moves over a given period, which makes it the standard yardstick for volatility in systematic trading. What this entry decodes is not an ATR entry signal but an ATR *kill switch*: a filter layered on top of an existing strategy that simply stops it from taking trades when current volatility is far above its own longer-run baseline. The premise is that most systems are calibrated to normal conditions, and the outlier days — the ones where ranges explode — are where a strategy's worst losses tend to come from.

The source is Kevin Davey's video "I Improved This Strategy By $49K - Find Out This Little Used Algo Trading Trick", from the Algo Trading With Kevin Davey channel. Davey frames the kill switch as an add-on rather than a strategy: he explains the reasoning behind sitting out high-volatility regimes, walks through how the condition is coded in TradeStation, and then shows a sample strategy's equity before and after the switch is applied. The dollar figure in the title belongs to that one example on that one dataset — it is the video's illustration of the idea, not a general result you should expect from adding a volatility filter to your own system.

The honest caveat with any switch like this is that it introduces a threshold, and thresholds are easy to over-tune: set it tight and the strategy sits out too many tradeable days, set it loose and it never triggers. Davey's version keeps the sensitivity adjustable for exactly that reason. This page catalogues the concept and its source; for the coded condition and the before/after walkthrough, the video itself is the reference.

Topics

average true range · atr indicator · kill switch strategy · volatility filter · e-mini s&p 500 futures · es futures · daily timeframe strategy · algo trading strategy · tradingview strategy · pine script strategy · technical indicators · trading strategy

Frequently asked questions

What is a kill switch in algorithmic trading?

A kill switch is a condition that blocks a strategy from trading when the market is in a state the strategy was never designed for — most commonly, an unusually volatile one. It does not generate signals of its own; it only suppresses existing ones.

How is ATR used to build a volatility kill switch?

The usual approach compares a short-term ATR reading against a longer-run average of the same measure. When recent volatility is elevated relative to that baseline by more than a chosen amount, the switch trips and new entries are skipped until conditions normalize.

Will adding a volatility filter improve my strategy's results?

Not automatically. Filtering out high-volatility periods removes some large losses, but it also removes some large wins and cuts the number of trades, which weakens the statistical significance of your backtest. The improvement shown in the source video applies to the specific strategy and data Davey tested, and needs to be re-verified on your own system.

How can I test a kill switch on my own strategy?

Backtest the same system with and without the filter across multiple markets and periods, and check whether the improvement holds outside the sample you tuned it on. Strategy Decoder catalogues strategies and techniques like this one from video sources so you can evaluate them before coding anything.

About this strategy page

This trading strategy was decoded by Strategy Decoder's AI from a public YouTube trading video and turned into a structured, reviewable specification. In the interactive app this page shows the full entry and exit logic, risk management settings, the indicators involved with their parameters, AlgoWizard-compatible logic and a Pine Script export ready for TradingView backtesting — plus an automated backtest verdict when one has been computed for this strategy.

Strategy Decoder catalogs 2,229 decoded strategies. Each one is extracted with confidence scoring, cross-linked to the indicators it uses, and kept up to date as new videos are processed daily. Load this page with JavaScript enabled to use the interactive tools, or start from the strategy explorer to filter by methodology, market and timeframe.

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