Technical Analysis

Technical Indicators: 10 AI prompts for finance workflows

Use these Technical Indicators prompts to turn a loosely defined finance task into a clearer, copy-ready AI workflow.

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Copy-ready Technical Indicators finance prompts

Universal Technical Indicator Framework

Universal template Medium

Builds a small, context-aware indicator system and avoids stacking redundant measures that restate the same price information.

ID 151

Act as a technical-analysis educator. I trade the crypto market on 15-minute data and focus on trend/momentum/range conditions. Select nonredundant measures of trend, momentum, volume, and volatility; define settings and timeframe alignment; handle confirmation and contradiction; and state when each signal should be ignored. Finish with simple entry, exit, and invalidation rules and a plan for out-of-sample validation.

Multi-Timeframe Indicator Confluence

Medium

Aligns higher-timeframe context with lower-timeframe execution using a small set of indicators without double-counting the same evidence.

ID 152

Act as a multi-timeframe technical analyst. I want to use H4/D1 for context and M5/M15 for execution. Select two or three nonredundant indicators and define directional bias, lower-timeframe confirmation, signal timing, contradictory evidence, and clear trade, wait, and no-trade conditions. Explain how to avoid look-ahead bias and validate the rules.

Indicator Regime Filter: Trend, Range, or Noise

Beginner

Classifies market conditions before selecting an indicator and includes an uncertain state in which no trade is required.

ID 153

Act as a market-regime analyst. For instrument, design a quantitative filter that classifies the market as trend, range, noise, or uncertain. Define inputs and thresholds, explain which indicators tend to mislead in each regime, specify transition and persistence rules, and include a no-trade state. Describe how the filter will be calibrated and tested out of sample.

Trend Strength and Continuation Indicators

Beginner

Uses nonredundant measures to distinguish persistent trends from weak, late, or exhausted moves.

ID 154

Act as a trend-analysis specialist. For the crypto market, design a nonredundant set of measures for direction, strength, participation, and exhaustion. Define trend confirmation, continuation entry, invalidation, exit, and uncertain conditions. Explain how each measure adds distinct information and how the rules will be tested across trending and ranging regimes.

Three-Indicator Confluence Rule

Beginner

Requires independent evidence from trend, momentum, and volume without treating more indicators as greater certainty.

ID 155

Create a confluence rule using three different types of evidence: trend, momentum, and volume. Define exact thresholds, evaluation order, missing-data handling, timing, and an invalidation rule. Explain how to test that the indicators are not redundant and how to select and validate thresholds without fitting them to one historical period.

Indicator-Based Noise Detector

Beginner

Identifies conditions in which signals flip too frequently or volatility, spread, and liquidity make technical readings unreliable.

ID 156

Define a simple rule for identifying when a market is too noisy to trade. Combine volatility, range compression or expansion, signal-flip frequency, and spread or liquidity when available. Set measurable conditions for trading normally, reducing activity, or standing aside, and explain how to calibrate the thresholds from historical data.

False-Signal and Whipsaw Filter

Medium

Combines structure, volume, divergence, and follow-through and permits an indeterminate result when evidence is insufficient.

ID 157

Act as a signal-quality analyst. Design a rule-based filter for potential false technical signals using prior structure, divergence behavior, volume or liquidity, candle close, and subsequent follow-through. Return yes, no, or indeterminate; define the required data and timing; and explain how to test the filter without selecting only favorable examples.

Custom Indicator Concept for TradingView

Pro

Defines a custom indicator's calculations, inputs, outputs, alerts, edge cases, and validation plan before any Pine Script is written.

ID 158

Act as a TradingView indicator designer. Define a custom indicator that combines trend direction, momentum change, and volume pressure. Describe each calculation, input, normalization, output, visual state, alert condition, missing-data behavior, and edge case. Explain redundancy and overfitting risks and provide a validation plan, but do not write code.

Indicator Failure-Mode Analysis

Pro

Explains which regimes cause each indicator to degrade, which warning signs appear first, and which redundant indicators should be removed.

ID 159

Act as a technical-system diagnostics specialist. For list, explain the market regimes and data conditions in which each indicator performs poorly, early signs of deterioration, latency and parameter sensitivity, and one rule for reducing false positives or standing aside. Identify indicators that duplicate the same information and propose tests for each claimed failure mode.

Transparent Indicator Signal Score

Pro

Turns multiple technical inputs into an auditable ranking while making clear that the score is not automatically a probability of success.

ID 160

Act as a trading-system analyst. Design a 0-100 score using indicator alignment, timeframe context, volume or liquidity, and distance from key levels. Define weights, normalization, missing data, timing, minimum score, hard invalidations, and sensitivity checks. Explain that the score ranks specified conditions rather than estimating probability by itself, and include out-of-sample calibration and validation.

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How to use AI prompts to evaluate technical indicators

An indicator prompt should define the calculation and decision rule rather than rely on a familiar label. The same indicator can behave differently across assets, timeframes, parameters, and market regimes.

Specify the formula, parameters, price field, timeframe, data adjustments, signal timing, and treatment of missing observations.
Define entry, exit, invalidation, regime filters, and whether correlated indicators add information or merely repeat it.
Evaluate out-of-sample stability, parameter sensitivity, turnover, costs, and false signals before interpreting performance.