DAX Wednesday-Thursday Strategy

Discover a simple DAX index trading strategy: long on Wednesday morning, exit Thursday morning. Learn how to optimize it with filters and advanced exit conditio

Published · Updated · Methodology: Technical Indicators

Part of: Swing Trading

  • Methodology: Technical Indicators
  • Content type: strategy
  • Timeframes: Daily (for backtesting and strategy improvement)
  • Markets: DAX (German index)

Indicators used

  • Keltner Channel

Source video

Decoded from: La Mejor Estrategia de Trading si tienes otro Trabajo by Estrategias Ganadoras de Trading — watch the original

Key timestamps:

  • 0:44 - Core strategy explanation
  • 1:00 - Long entry rule
  • 1:05 - Exit rule
  • 1:52 - Backtest results (profit factor, operations, profit)
  • 2:10 - No stop loss mentioned for core strategy
  • 4:10 - Strategy improvement using StrategyQuant
  • 4:40 - Adding filters and advanced exits
  • 5:00 - Advanced exit options (multipliers, fixed profit, trailing stop, bars)
  • 6:00 - Sequential exits (two or three exits)
  • 7:10 - Improved strategy results (profit increase)
  • 7:40 - Example of improved strategy with Keltner Channel filter

Strategy overview

Day-of-week strategies rest on a calendar premise: that returns are not spread evenly across the week and that a specific weekday window on a specific market carries a repeatable tilt. This entry decodes a Spanish-language video, "La Mejor Estrategia de Trading si tienes otro Trabajo" ("The Best Trading Strategy if You Have Another Job") from the channel Estrategias Ganadoras de Trading, which applies that premise to the DAX on a daily timeframe. The title states the design constraint before it states the idea — the viewer already has a job — and the midweek window named in the strategy title follows from it: one instrument, one chart per day, one decision point, nothing that requires watching an open.

What stands out about the source is how compact the teaching is. Its own chapter markers put the core explanation at 0:44, the entry at 1:00 and the exit at 1:05, so the base idea is delivered in roughly twenty seconds; the rest of the video goes to reported backtest figures and then, from 4:10, to reworking the idea in StrategyQuant, where a volatility-band filter of the Keltner type is brought in as an extra condition without the source specifying settings for it. The timeline also flags that the base version is presented with no stop loss, which means defining a maximum acceptable loss is the first thing a viewer has to supply rather than something the video hands over.

Two cautions belong with any weekday tilt. Calendar patterns are among the easiest results to find by accident — five weekdays across a handful of instruments and date ranges produce many combinations to try, so a seasonal claim carries more weight when it survives periods and markets it was not selected on. And the profit factor and trade counts cited at 1:52 are the channel's own figures from its own test window, not independently verified results. No mechanical rules were extracted for this entry, so this page indexes the concept and the source rather than a reconstructed rule set; the video remains the reference for how the setup is actually specified.

Topics

dax trading strategy · dax index strategy · trading strategy · pine script · tradingview strategy · technical indicators · keltner channel strategy · daily trading strategy · swing trading · german index trading · intraday strategy

Frequently asked questions

What is a day-of-week trading strategy?

It is a strategy whose entry condition is partly calendar-based: it only considers trades on particular weekdays, on the premise that returns are not distributed evenly across the week for a given market. The signal is a time window rather than a chart pattern, which is why these systems are usually tested on daily data over long histories.

Why would a daily-timeframe DAX strategy suit someone with another job?

Because it collapses the attention requirement. A daily chart with a fixed weekday window means one check per day, outside working hours if needed, with no intraday monitoring — which is the constraint the video's title puts front and centre before it explains any rules.

Are weekday seasonality effects reliable?

They should be treated as hypotheses, not constants. Weekday effects can appear by chance because there are many day-and-market combinations to test, and effects that were real in one regime can fade as markets and participants change. Testing on data the rule was not selected on, and accounting for spreads and costs, matters more here than for most setups.

Does this video hand over a complete, testable rule set?

No mechanical rules were extracted for this entry, so the video itself remains the source for the exact conditions, and its second half moves on to refining the idea in StrategyQuant rather than restating it. Strategy Decoder indexes video-sourced strategies like this one so you can find the concept and the original source, then test the logic on historical data before committing capital.

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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