Multi-Timeframe Strategy

Boost accuracy with this multi-timeframe price action strategy. Identify long-term bullish trends on the XLP ETF and enter on short-term pullbacks.

Published · Updated · Methodology: Price Action

Part of: Algorithmic & Automated Trading

  • Methodology: Price Action
  • Content type: strategy
  • Timeframes: Daily (implied by 'days ago')
  • Markets: XLP ETF

Source video

Decoded from: 73% Win Rate Multi-Timeframe Strategy (Backtested) by Quantified Strategies — watch the original

Key timestamps:

  • 0:08 - Long-term trend identification
  • 0:13 - Medium-term trend confirmation
  • 0:16 - Entry condition (pullback)
  • 0:19 - Buy rule
  • 0:20 - Sell rule

Strategy overview

A multi-timeframe strategy is one where the trade decision is split across two or more chart scales instead of taken on a single one. What makes this entry worth reading closely is that its five markers name the split explicitly and in order: long-term trend identification at 0:08, medium-term trend confirmation at 0:13, a pullback as the entry condition at 0:16, and then the buy and sell rules at 0:19 and 0:20. That is three layers doing three different jobs — direction, agreement, timing — which means the strategy is really a relationship between scales rather than a list of conditions.

The relationship is the part that does not survive being summarized. "Long-term" and "medium-term" are relative terms: their content is whatever ratio the source picked between them, and a trend filter two steps above the entry chart behaves nothing like one step above. The record here reflects that ambiguity honestly — the timeframe field reads *Daily (implied by 'days ago')*, an inference drawn from how the video phrases its lookback rather than a setting stated outright. So the scale on which any of this was measured is reconstructed, not declared.

That matters for the headline. The video, from the channel Quantified Strategies, is titled "73% Win Rate Multi-Timeframe Strategy (Backtested)" — a figure this page reports as the source's claim and does not verify. Win rate on its own also does not settle whether an approach makes money, since it says nothing about the size of the average win against the average loss, and a backtested percentage belongs to the specific market, period and timeframe pair that produced it. The methodology is recorded as Price Action with no indicators listed, which is consistent with a trend-and-pullback read taken from price alone; no rules were extracted for this entry, so what this page offers is the sequence the video lays out and a pointer to the source itself.

Topics

multi-timeframe strategy · price action · trading strategy · trend following · xlp etf · daily timeframe · tradingview strategy · pine script · etf trading strategy

Frequently asked questions

What is a multi-timeframe trading strategy?

It is a strategy that splits the decision across two or more chart scales: a higher timeframe establishes the trend direction, and a lower one is used to time the entry. The setup in this video adds a middle layer for confirmation between the two.

Why use three timeframes instead of two?

The markers in the source video assign a distinct job to each layer — long-term trend identification, medium-term confirmation, and a pullback for entry timing. The intent of a middle layer is to require agreement between scales before the entry condition is even considered, at the cost of fewer signals.

Does a 73% win rate mean a strategy is profitable?

Not by itself. Profitability depends on win rate together with the ratio of average win to average loss, plus costs — a high win rate paired with large losing trades can still lose money. A backtested figure also applies only to the market, period and timeframes it was measured on.

How do I know which timeframe pair this strategy uses?

The video describes the layers in relative terms rather than naming exact charts; the daily reference on this page is inferred from the way the source phrases its lookback. Watching the original video is the way to see how the scales are defined, and any multi-timeframe idea should be backtested on your own instrument and timeframe pair before use.

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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