Market Data
STFL obtains market prices, historical candles, trading volume and instrument information from exchanges, authorised market-data providers and other identified sources. Availability and update frequency may differ by dataset.
STFL Research Framework
Research Methodology
This page explains how STFL transforms available market and company information into structured analytical outputs.
Last updated: 26 October 2026
Our Approach
Multiple perspectives, clearly separated
STFL combines market data, technical calculations, fundamental information and explanatory research. Each analytical module serves a different purpose, and no single indicator or score should be treated as a complete investment decision.
Technical Trend
Trend classification considers price position relative to multiple moving averages, bullish or bearish EMA and SMA alignment, recent swing structure, breakouts or breakdowns and recent price returns.
Momentum Analysis
Momentum assessment may combine RSI, MACD, stochastic indicators and other price-velocity measurements. Momentum describes the strength and direction of recent price behaviour; it does not predict a guaranteed future movement.
Volume Analysis
Volume analysis compares current activity with historical average volume and may evaluate relative volume, accumulation, distribution and whether trading activity supports a price movement.
Support and Resistance
Support and resistance are calculated through a hybrid confluence model using recent swing points, Fibonacci retracements, Classical Pivot levels and moving averages.
Technical Bias
The technical bias summarises multiple technical modules into a directional analytical view. It is not a personalized recommendation, trade instruction, target or stop-loss.
Fundamental Research
Fundamental research may consider financial statements, profitability, growth, balance-sheet strength, cash flows, valuation ratios, peer comparisons and other company information.
Market Intelligence
Market-intelligence tools may evaluate breadth, gainers, losers, traded volume, traded value, institutional activity, market sectors and other aggregated market statistics.
Technical Methodology
How STFL identifies support and resistance
STFL uses a hybrid confluence model instead of depending on one formula. This allows the engine to recognise price zones supported by different forms of technical evidence.
Candidate levels
Potential price levels are collected from swing highs and lows, Fibonacci calculations, Classical Pivots and selected moving averages.
Confluence zones
Nearby candidate levels are grouped into zones. Zones supported by multiple methods, repeated touches or stronger structural evidence receive greater confidence.
Noise filtering
Levels extremely close to the current price may be excluded using price-distance and Average True Range thresholds.
Proximity ordering
The nearest validated level below price becomes S1 and the nearest validated level above price becomes R1.
Secondary levels
S2 and R2 are the next distinct validated zones. A minimum separation based on price and selected-timeframe ATR helps prevent nearly identical levels.
Timeframe awareness
Technical calculations use the selected chart timeframe. Daily and weekly candles contain different price structures and volatility measurements; therefore, their trend, momentum, S1, S2, R1 and R2 values can differ.
Interpretation
What the technical labels mean
LabelMeaning
BullishPositive technical structure based on the selected timeframe and available indicators.
BearishNegative technical structure based on the selected timeframe and available indicators.
NeutralMixed or insufficient directional evidence.
Trend ConfidenceThe strength and consistency of the evidence supporting the trend classification.
S1 / R1The nearest validated support and resistance zones.
S2 / R2The next distinct validated support and resistance zones.
Technical BiasA combined analytical summary, not a personalized trading recommendation.
Known Limitations
Research outputs require interpretation
Market prices and third-party datasets may be delayed, incomplete or temporarily unavailable.
Corporate actions can distort historical prices when source data has not been appropriately adjusted.
Newly listed securities may have insufficient history for reliable long-period calculations.
Low-liquidity securities can produce unstable prices, indicators and support or resistance zones.
Different timeframes can produce different trend, momentum, volatility and support or resistance results.
Automated and AI-assisted summaries can contain errors and should be independently verified.
Responsible use of STFL research
STFL research should be considered alongside company disclosures, exchange announcements, financial objectives, investment horizon, liquidity and risk tolerance. Analytical outputs do not guarantee a future result.
STFL may revise this methodology as its data sources, analytical models and research modules evolve.