Overview
The ETF continues to push higher, ending the session at its peak and building on a strong weekly trend. Momentum is powerful, but increasingly stretched - a signal to stay bullish but alert.
1. Last Trading Session
During the latest session, the ETF opened at its session low and climbed steadily to finish at the high of the day.
The price held a firm upward path, with no meaningful dips or volatility spikes.
It closed at the top of its intraday range, indicating strong buying interest.
RSI remained elevated, signalling persistent demand and a market that may be edging toward short-term overbought territory.
2. Weekly Trends
Over the past week, the ETF has shown a clear upward trend, rising from the mid-8.50s to just below 9.00.
Moving averages and momentum indicators have strengthened together, suggesting that recent gains are both consistent and well supported.
Support is now near 8.85, with resistance at 8.97 — the upper edge of the typical price range.
Momentum readings are unusually high. Gains may continue, but the pace could slow from here.
Overall, direction remains firmly positive.
3. Quant Metrics
Examples of quant metrics include:
• Sharpe Ratio
• volatility
• drawdowns
• moving averages
• correlation matrices
• regression models
The ETF’s Sharpe ratio is slightly above 1, meaning it has delivered returns that justify the level of risk taken.
Recent volatility has been lower than the broader US market, making it a relatively stable instrument within its category.
The worst weekly loss in recent months was just over eleven percent. Declines do occur, but they have not been excessive relative to potential upside.
4. Summary
Across all indicators, the ETF for small-cap global stocks has delivered a strong week with steady upward pressure and limited downside risk.
Short-term momentum still leans bullish, though stretched readings suggest a pause or modest pullback is possible.
Longer term, the risk–return balance looks reasonable and suggests a solid fit within a diversified portfolio.
The current outlook is cautiously optimistic: good strength in the trend, but a need to monitor whether the acceleration begins to ease.
Part I - Best TA Measures
TA metric tell you what traders are doing
Contents
1. RSI – Shows when price is overbought or oversold.
2. Intraday Range – Reveals whether buyers or sellers controlled today’s session.
3. Support Levels – Identify where buyers repeatedly step in.
4. Resistance Levels – Identify where sellers repeatedly push back.
5. Trend Direction – Shows whether the market is making higher highs or lower lows.
6. Moving Averages (MA20/50/200) – Smooth noise to reveal short- and long-term trend bias.
7. ADX (+DI / –DI) – Measures the strength and direction bias of a trend.
8. True Range (TR) – Captures the real size of price movement, including gaps.
9. Volatility (Std Dev) – Indicates whether the market is calm, unstable, or preparing for a breakout.
10. Bollinger Bands – Show volatility compression, overextension, and potential breakouts.
11. Weekly Price Channels – Map the market’s typical weekly trading corridor.
12. Confluence – Confirms signals when multiple metrics align together.
If you want, I can now turn this into:
• A blog sidebar graphic,
• A mobile-friendly Table of Contents, or
• A PDF one-pager for your TA series.
1. Relative Strength Index (RSI)
RSI measures the speed and size of recent price movements.
It identifies when an asset is overbought (buyers exhausted) or oversold (sellers exhausted).
Formula
RSI = 100 − [100 / (1 + RS)]
where RS = average gain ÷ average loss (usually over 14 days).
How to interpret
• Above 70 → short-term overbought
• Below 30 → oversold
• Between 40–60 → neutral trend zone
• Rising RSI → strengthening momentum
• Falling RSI → weakening demand
URL
https://www.investopedia.com/terms/r/rsi.asp
2. Intraday Range (High–Low Strength)
This shows where the ETF closed relative to its daily high and low.
Closing at the top of the range signals aggressive demand.
Closing at the low signals heavy selling pressure.
Formula
Position = (Close − Low) ÷ (High − Low)
Key thresholds
• > 0.70 → buyers dominate
• < 0.30 → sellers dominate
• = 1.00 → closes at the high of the day
URL
https://www.investopedia.com/terms/i/intraday.asp
3. Support and Resistance Levels
Support is where buying demand tends to appear.
Resistance is where selling pressure tends to emerge.
How levels form
They form through repeated touches of prior highs/lows, volume clustering, or psychological round numbers.
Key measures
• Breakout → price closes firmly above resistance
• Breakdown → price closes firmly below support
• Narrowing range → potential volatility expansion ahead
URL
https://www.investopedia.com/terms/s/support.asp
4. Trend Direction (Short- and Long-Term)
Trend analysis identifies the dominant direction of price movement.
How to define a trend
Higher highs + higher lows = uptrend
Lower highs + lower lows = downtrend
Key signals
• Rising trendline → sustained buying
• Flattening trendline → weakening momentum
• Steep trendline → prone to pullbacks
URL
https://www.investopedia.com/terms/t/trend.asp
5. Moving Averages (MA20, MA50, MA200)
Moving averages smooth price noise and reveal trend strength.
Formula
SMA = sum of closing prices ÷ number of periods
(e.g., 20-day SMA = average of last 20 closes)
Key interpretations
• Price > MA20 and MA50 → near-term bullish
• MA20 above MA50 → strong momentum
• MA50 above MA200 → long-term bullish cycle
• Price compressing against a rising MA → continuation pattern
URL
https://www.investopedia.com/terms/m/movingaverage.asp
6. Momentum Indicators (General)
Momentum indicators show the rate at which a price is accelerating or decelerating.
Common tools
RSI, MACD, Stochastics (not explicitly mentioned, but implied under “momentum indicators”).
Key readings
• High momentum → strong pressure in trend direction
• Divergence → potential trend reversal
• Extreme readings → risk of short-term exhaustion
URL
https://www.investopedia.com/terms/m/momentum.asp
7. Volatility (Technical)
Volatility in TA reflects the degree of price fluctuation.
Lower volatility can suggest accumulation; higher volatility can signal stress or trend transitions.
Formula
Standard deviation of returns over a period (typically 14 or 20 days).
Key interpretations
• Low volatility in an uptrend = stable demand
• Sudden volatility spikes = liquidity stress or reversal risk
• Tightening volatility bands = likely breakout
URL
https://www.investopedia.com/terms/v/volatility.asp
8. Weekly Price Channels
Weekly channels show the typical trading corridor.
How formed
Upper band = weekly resistance zone
Lower band = weekly support zone
Key signals
• Price near upper band → trend strength
• Breakout above → acceleration
• Price falling back into channel → fading momentum
URL
https://www.investopedia.com/terms/p/price-channel.asp
9. Average Directional Index (ADX) With +DI and –DI
The Average Directional Index (ADX) measures the strength of a trend.
The Directional Indicators (+DI and –DI) show the direction of that trend.
Key term: trend strength = how powerful the price movement is, regardless of direction.
How it works
• +DI shows upward pressure (buyers).
• –DI shows downward pressure (sellers).
• ADX (0–100 scale) shows whether either side is in control.
Interpretation
• ADX < 20 → weak or no trend
• ADX 20–30 → trend is forming
• ADX > 30 → strong trend
• +DI above –DI → bullish directional bias
• –DI above +DI → bearish directional bias
• ADX rising → trend strengthening
• ADX falling → trend losing power
Signals
• Bullish trend confirmation: +DI crosses above –DI and ADX rises above 20
• Bearish trend confirmation: –DI crosses above +DI and ADX rises above 20
• False moves likely when ADX is extremely low (<15)
Formula components (simplified)
• True Range (TR)
• Directional Movement (+DM / –DM)
• Smoothed averages → +DI, –DI
• ADX = smoothed average of Directional Index (DX)
(Full mathematical derivation is rarely used manually.)
URL
https://www.investopedia.com/terms/a/adx.asp
Below is a clean, blog-ready LITA-STYLE explanation of True Range (TR), written to match the style and tone of your TA Metrics section above.
Short sentences. Clear logic. Definitions included. Balanced and easy to read.
9. True Range (TR)
The True Range (TR) measures the full amount of price movement in a period, including gaps.
It captures real volatility better than simply looking at the daily high–low.
Key term: gap = when today’s price opens far above or below yesterday’s closing price.
9.1 What TR Measures
• The entire movement of the market during one bar (day, hour, week).
• It accounts for overnight jumps or sudden shocks.
• It shows whether volatility is expanding or contracting.
9.2 How TR Is Calculated
TR is the maximum of three values:
-
High − Low
-
|High − Previous Close|
-
|Low − Previous Close|
This formula ensures that TR detects:
• Hidden volatility during gaps
• Large opening moves not visible in the high–low range
• True stress points in the market
9.3 How to Interpret TR
• Rising TR → volatility increasing, energy building.
• Falling TR → quiet market, possible accumulation.
• Sudden spike in TR → news, liquidity stress, or start of a breakout.
• TR is direction-neutral: it measures intensity, not trend.
9.4 Why TR Matters
TR is the foundation for:
• ATR (Average True Range) – the standard volatility gauge
• ADX – uses smoothed TR to measure trend strength
• Volatility-based stop-loss systems
• Position sizing models used by traders and funds
9.5 Practical Uses
• Identify when a trend is ready to accelerate.
• Spot false breakouts (high TR without follow-through).
• Find stable vs unstable market regimes.
• Set realistic stop-loss distances based on volatility.
URL
https://www.investopedia.com/terms/t/truerange.asp
Below is a clean, blog-ready LITA-STYLE section for Bollinger Bands, written to match the tone and structure of all your previous TA metric entries.
11. Bollinger Bands
Bollinger Bands measure volatility and identify when price stretches too far from its recent average.
They help spot overextension, breakouts, and periods of tightening pressure.
Key term: bandwidth = the distance between the upper and lower bands.
11.1 What Bollinger Bands Show
• When the market is unusually quiet or unusually volatile.
• When price is stretched far above or below its recent trend.
• When pressure is building for a breakout.
• Whether the move is likely to continue or reverse.
11.2 How Bollinger Bands Are Constructed
Three lines:
-
Middle Band – 20-day simple moving average (SMA).
-
Upper Band – SMA + 2 standard deviations.
-
Lower Band – SMA − 2 standard deviations.
The Bands automatically widen during volatile periods and contract during calm ones.
11.3 How to Interpret Bollinger Bands
• Price at the upper band → strong upward momentum, or short-term overextension.
• Price at the lower band → strong downward pressure, or short-term oversold.
• Bollinger squeeze (bands contracting) → volatility compression, often preceding a breakout.
• Bands widening suddenly → volatility surge, clear trend underway.
Important:
Touching a band ≠ buy/sell signal.
It indicates conditions, not instructions.
11.4 Practical Uses
• Detect emerging breakouts after a squeeze.
• Confirm trend strength when price walks up/down the bands.
• Spot temporary exhaustion when price repeatedly tags a band without follow-through.
• Identify volatility regimes for position sizing.
11.5 Limitations
• Bands expand with volatility, so extreme readings can occur without reversals.
• False signals occur during trending markets when price rides the band for long periods.
URL
https://www.investopedia.com/terms/b/bollingerbands.asp
A Trader Evaluates WSML - the thinking
How TA is actually applied.
1. Overview
A trader wants to understand whether SWML is building strength, weakening, or preparing for a breakout.
They decide to run through the full TA checklist, one tool at a time.
The point is not prediction.
The point is clarity and structure.
2. Step-by-Step TA Evaluation Of SWML
2.1 RSI – Momentum condition
• RSI = 62
• This is neutral-to-bullish.
• Not overbought. Not oversold.
Purpose: Check if buyers are exhausted — they are not.
2.2 Intraday Range – Daily control
• SWML closed at 0.78 of its daily range.
• Buyers controlled the session.
• No sign of intraday distribution.
Purpose: Identify which side won the day — buyers.
2.3 Support & Resistance – Battle lines
• Strong support seen at 198–200 (three prior rebounds).
• Resistance overhead at 218 (three failed attempts).
• Price currently at 214, approaching the ceiling.
Purpose: Map where buyers/sellers historically defend positions.
2.4 Trend Direction – Market structure
• Higher lows formed over the last three swings.
• Higher highs developing, but not yet breaking the key 218 level.
Purpose: Identify if the market is structurally rising — yes.
2.5 Moving Averages – Trend bias
• Price > MA20 and MA50 → short-term bullish.
• MA20 > MA50 → positive momentum.
• MA50 is rising and approaching MA200 → strengthening medium-term trend.
Purpose: Check if the trend has support from smoothed price action — yes.
2.6 ADX with +DI / –DI – Trend strength
• ADX = 24
• +DI above –DI
• Trend is forming but not yet strong; energy is building.
Purpose: Measure strength behind the move — rising but not explosive.
2.7 True Range (TR) – Underlying volatility
• TR slightly increasing over 5 sessions.
• Market is waking up from a low-volatility regime.
Purpose: Detect whether energy is entering the system — yes, slowly.
2.8 Volatility (Standard Deviation) – Regime
• Volatility rising moderately.
• No panic spikes.
Purpose: Determine if the market is stable or stressed — stable but awakening.
2.9 Bollinger Bands – Compression and breakout risk
• Bands have tightened for 12 days — a clear “squeeze”.
• Price is now pushing the upper band.
• Classic volatility-compression setup.
Purpose: Identify breakout potential — high.
2.10 Weekly Price Channels – Higher timeframe context
• SWML is near the upper weekly channel (long-term resistance zone).
• A breakout above 220 would expand the structure.
Purpose: Place daily movement inside the weekly “river”.
2.11 Confluence – Summary of all signals
• Momentum positive (RSI, Momentum Indicators).
• Buyers in control intraday.
• Structure bullish (HH/HL).
• Trend supported by MAs.
• ADX rising from low level.
• Volatility compressing then expanding.
• Price pressing upper BB and weekly channel top.
• A multi-metric alignment.
This is precisely the type of setup TA traders look for:
quiet accumulation → compression → renewed energy → test of resistance.
3. Final Interpretation
SWML is approaching a decision point.
• If price closes above 218–220, the breakout is confirmed.
• If price rejects the resistance and falls below MA20, it becomes a failed breakout.
• The trader watches for strong intraday closes, rising ADX, and continued momentum.
This is not a prediction.
It is a structured understanding of the situation.
TA does not say “buy here”.
TA says:
“Here is where the next important move will reveal itself.”
4. Why This Worked Example Makes TA Attractive
Because readers can see:
• Clear steps
• No mysticism
• Each tool has a purpose
• Each tool sharpens the decision
• This method can be repeated on any stock or ETF
• Everything is systematic, calm, and evidence-based
It turns the market from noise into a readable landscape.
If you want, I can now generate:
✓ A diagram summarising SWML’s signals
✓ A 10-line condensed decision summary
✓ A PDF worked example
✓ A version with hypothetical price numbers and a mock chart
Test Yourself
Each question describes a purpose or market situation.
You must choose the best TA metric for that purpose.
Answers follow at the end.
1. Identify Overbought or Oversold Conditions
You want to know whether buyers are exhausted at the top of a rally, or whether sellers are exhausted at the bottom of a fall.
Which indicator is best?
• RSI
• Intraday Range
• Moving Averages
• ADX
2. Detect Buyer or Seller Dominance Within Today’s Candle
You want to understand where the market closed within the day’s high–low range.
Which metric shows the strength of intraday demand or supply?
• Intraday Range
• Volatility
• Momentum Indicator
• Support/Resistance
3. Spot Repeating Price Floors and Ceilings
You want to map the levels where buyers repeatedly appear (support) or sellers repeatedly step in (resistance).
Which metric helps?
• Trend Direction
• Support/Resistance
• ADX
• RSI
4. Determine Whether the Market Is Making Higher Highs and Higher Lows
You want to check if the trend is upward or downward based on classical price structure.
Which tool?
• Trend Direction
• RSI
• True Range
• Weekly Price Channels
5. Smooth Noise and See Short- and Long-Term Trend Bias
You want to know if the price is above MA20, MA50, or MA200 — a clear trend filter.
Which indicator?
• Momentum Indicator
• ADX
• Moving Averages
• Intraday Range
6. Measure the Strength of a Trend, Not Its Direction
You want to know whether a trend (up or down) is strong, weak, or about to fade.
Which metric provides a directional strength reading?
• Support/Resistance
• ADX (+DI / –DI)
• Volatility
• RSI
7. Identify Whether Price Movement Is Accelerating or Decelerating
You want to know if momentum is building behind the trend.
Which tool measures acceleration?
• Momentum Indicators
• Moving Averages
• Weekly Price Channels
• Support/Resistance
8. Detect Upcoming Breakouts After Tight Price Compression
You want to recognise when volatility is contracting and a breakout may be coming soon.
Which indicator is best?
• Volatility (Technical)
• Intraday Range
• ADX
• RSI
9. Visualise the Market's Typical Weekly Trading Corridor
You want to know the upper and lower bands that contain most weekly price action.
Which tool works?
• Weekly Price Channels
• Moving Averages
• Trend Direction
• Momentum Indicators
10. Measure the Full Amount of Price Movement — Including Gaps
You want to capture the real range of movement, especially when markets open far above or below the previous close.
Which metric does this?
• True Range (TR)
• RSI
• ADX
• Support/Resistance
Answers
-
RSI
-
Intraday Range
-
Support/Resistance
-
Trend Direction
-
Moving Averages
-
ADX (+DI / –DI)
-
Momentum Indicators
-
Volatility (Technical)
-
Weekly Price Channels
-
True Range (TR)
Part II - Quant Metrics
Quant metrics tell you what the numbers say about risk and probability.
Examples of quant metrics include:
• Sharpe Ratio
• Volatility
• Drawdowns
• Moving Averages
• Correlation Matrices
• Regression Models
Below is a clean, friendly, LITA-STYLE explanation of the six quant metrics, each written in one structured block, short sentences, with definitions, purpose, interpretation, and limitations.
Perfect to pair alongside your TA Metrics section.
1. Sharpe Ratio
Definition: risk-adjusted return — how much excess return you earn for each unit of volatility.
Sharpe = (Portfolio Return − Risk-Free Rate) ÷ Volatility.
Purpose
• Compare strategies with different levels of risk.
• Identify whether high returns come from genuine skill or simply high volatility.
Interpretation
• > 1.0 → acceptable.
• > 1.5 → good.
• > 2.0 → very strong.
• Negative → investor not compensated for risk.
Limitations
• Uses standard deviation as the only definition of risk.
• Penalises upside volatility as well as downside.
• Breaks down in highly skewed or non-normal markets.
2. Volatility (Quant Version)
Definition: standard deviation of returns — a statistical measure of return dispersion.
Purpose
• Understand stability of an asset.
• Compare “behaviour” of assets with their returns removed.
Interpretation
• High volatility → unstable, noisy, large swings.
• Low volatility → smooth behaviour.
• Volatility spikes often precede regime changes.
Limitations
• Volatility ≠ risk in real life.
• Some stable assets can be fundamentally risky (e.g., pegs).
3. Drawdowns
Definition: the peak-to-trough decline during a period.
Shows the worst possible pain an investor could have suffered.
Purpose
• Evaluate downside risk.
• Understand psychological resilience required to hold a strategy.
• Compare robustness of trend followers, ETFs, or equity strategies.
Interpretation
• Max drawdown is a key robustness metric.
• Shallow drawdowns → resilient system.
• Deep drawdowns → fragile system, poor risk control.
Limitations
• Purely backward-looking.
• Does not show recovery time (another important metric).
4. Moving Averages (Quant Version)
Definition: rolling averages of returns, used to smooth noisy data.
Purpose
• Filter randomness in return series.
• Identify change of regimes in long backtests.
• Detect slow-moving cycles hidden inside raw price data.
Interpretation
• A rising moving average → improving return environment.
• A falling moving average → deteriorating conditions.
• Crossovers are used in both TA and quant trend models.
Limitations
• Lagging indicator.
• Sensitive to chosen window (20D, 50D, 200D, etc.).
5. Correlation Matrices
Definition: statistical relationships between asset returns.
Correlation ranges from −1 (perfect opposite) to +1 (perfect alignment).
Purpose
• Build diversification.
• Detect clustering behaviour in crisis regimes.
• Identify whether new assets genuinely reduce portfolio risk.
Interpretation
• Low or negative correlation → strong diversification benefits.
• Correlation spikes → crisis contagion.
• High correlation → strategies becoming crowded.
Limitations
• Correlations are unstable; they jump around.
• Correlation goes to 1 in crises (the classic warning).
6. Regression Models
Definition: statistical models that explain returns using explanatory variables (factors).
E.g., CAPM, Fama–French factors, macro regressions.
Purpose
• Understand what drives returns.
• Separate alpha (skill) from beta (market exposure).
• Test hypotheses about sensitivity to inflation, rates, volatility, etc.
Interpretation
• High R² → returns largely explained by known factors.
• Low R² → returns driven by idiosyncratic effects.
• Coefficients show exposures: market beta, value tilt, size tilt, etc.
Limitations
• Easily overfitted.
• Data-mining risk.
• Factors may stop working; regimes can change.
