Trading Strategies

Named strategy walkthroughs

The directory compares six different educational topics. Short-horizon methods, multi-day methods, indicator exercises and fixed-schedule purchases serve different questions. Examples use hypothetical inputs, not documented live performance. Read each method's limitations and supporting references before interpreting a calculation.

Strategies covered

• Scalping — Capturing small price moves on the 1-5 minute timeframe.
• Swing Trading — Holding positions 2-10 days to capture intermediate moves.
• Day Trading — Opening and closing all positions within a single session.
• Dollar-Cost Averaging (DCA) — Investing equal amounts on a predetermined schedule rather than selecting each purchase date based on a price prediction.
• RSI Mean-Reversion — A conceptual comparison of RSI thresholds and later price observations.
• MACD Crossover — Trading the signal-line cross on the MACD indicator.

A simple comparison before choosing a worksheet

Consider two different teaching questions: a fixed $100 contribution made at three specified dates is a cash-flow exercise, whereas recording a MACD crossing on three observations is an indicator-definition exercise. They do not use the same denominator or imply comparable expected returns. For the contribution exercise, list total cash added and total units; for an indicator exercise, state the source, price interval and calculation before counting any signals.

Neither example needs a live trade. The choice of an exercise should follow the concept being studied, not a claim that a holding period or indicator offers a better outcome. Any comparison of observed results needs consistent date ranges, costs, valuation conventions and a clear statement that a selected sample cannot verify future performance.

What a strategy is, and what it is not

A trading rule describes a testable set of conditions and assumptions. Dollar-cost averaging is different: it schedules contributions, without requiring an active entry or exit signal. The site presents these methods for comparison, not as advice about which method is suitable for a person.

A chosen win percentage without the payoff distribution and costs is not enough to evaluate outcomes. Results from a selected historical or virtual sample are descriptive; they may change in another sample. No source-backed universal winning percentage or account-return forecast is offered.

Testing a strategy without fooling yourself

• Write down the hypothetical assumptions and observation window before reviewing outcomes.
• Avoid treating 30, 100 or any other arbitrary number of observations as a universal statistical threshold. Sample design, selection and dependence matter.
• Record cases selected by the exercise criteria, including unfavorable cases and changes to the rule.
• If using sample expectancy or drawdown, explicitly label the costs, sizes, dates and limitations of the input data.
• Check the effect of a negative-outcome sequence without asserting how often it will occur in practice.
• Compare a second specified sample without claiming that a backtest establishes future results.