Invesco EQQQ NASDAQ-100 UCITS ETF (GBP Hdg)

10-Year Study

EQGB.LSE · · GB · ETF

Executive Summary: Invesco EQQQ NASDAQ-100 UCITS ETF (GBP Hdg) has compounded at 17.5% annually over the last 10 years, with a maximum drawdown of 35.1% and an annualized volatility of 16.9%.

1Y CAGR
+25.3%
3Y CAGR
+23.2%
5Y CAGR
+13.4%
10Y CAGR
+17.5%

History & Riski10-year historical performance analysis including CAGR, Max Drawdown, Sharpe & Sortino ratios, annual returns, and rolling volatility — all computed from daily market data.

10-Year Growth of $10,000

Max DrawdownMax DrawdownThe largest peak-to-trough decline in the asset's value over the measurement period.Click for full definition →
35.1%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.79
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
1.35
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
18.9%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2023 · +53.9%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2022 · -35.1%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
78%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20260.9-2.8-6.712.8————————3.2%
20252.3-5.5-7.11.110.46.03.6-0.14.95.5-2.20.419.6%
20241.94.21.7-3.23.58.6-2.40.33.1-0.14.81.926.1%
202310.40.28.10.58.46.43.6-1.3-4.8-3.410.66.753.9%
2022-10.5-2.75.4-12.5-4.8-8.510.8-3.8-9.01.20.6-5.9-35.1%
20211.1-0.41.45.8-1.16.22.74.2-4.76.03.01.127.7%
20203.5-7.8-4.912.85.26.87.110.8-4.4-3.49.35.745.4%
20198.42.93.55.0-7.46.54.0-4.10.94.24.43.234.9%
20187.3-0.3-5.61.94.71.51.95.7-0.3-8.9-1.0-8.1-2.6%
2017——————————1.81.63.4%

Risk X-RayiA 19-factor macroeconomic risk decomposition showing exactly which market forces (equity beta, rates, inflation, credit, commodity, crypto) drive this asset's volatility. Powered by multivariate regression against daily factor returns.

Risk Profile Insight: This asset has an estimated annualized volatility of 16.9%. The dominant macroeconomic risk driver is QQQ.US, accounting for 77.8% of variance. Idiosyncratic stock-specific factors contribute 2.5%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2017-10-0110000
2017-11-0110181.340019731333
2017-12-0110341.877016986586
2018-01-0111095.49788126774
2018-02-0111065.274518465587
2018-03-0110448.639957706097
2018-04-0110645.680439926486
2018-05-0111145.739251275605
2018-06-0111311.378887058681
2018-07-0111530.39995393111
2018-08-0112189.81827890032
2018-09-0112157.632338651834
2018-10-0111075.872342426817
2018-11-0110966.75435589619
2018-12-0110073.399516835863
2019-01-0110924.363138592054
2019-02-0111241.511978209892
2019-03-0111634.248324198568
2019-04-0112213.87940927644
2019-05-0111307.91131085188
2019-06-0112041.875062891542
2019-07-0112521.759335225664
2019-08-0112002.21196018635
2019-09-0112110.205556660887
2019-10-0112613.259364238635
2019-11-0113172.862545970322
2019-12-0113591.877700291521
2020-01-0114069.798452689742
2020-02-0112967.478360675113
2020-03-0112328.15626954586
2020-04-0113900.935738202284
2020-05-0114618.798626767564
2020-06-0115612.339714333297
2020-07-0116725.262814001788
2020-08-0118539.555234773994
2020-09-0117716.84038163162
2020-10-0117110.112721438316
2020-11-0118700.56386951785
2020-12-0119766.755194711906
2021-01-0119988.63294746868
2021-02-0119915.982709840355
2021-03-0120201.47850852031
2021-04-0121366.238534496577
2021-05-0121140.041037880826
2021-06-0122444.9963872804
2021-07-0123041.906447794197
2021-08-0124005.99473632142
2021-09-0122877.363477165727
2021-10-0124239.6536086936
2021-11-0124973.617360733264
2021-12-0125239.085256067036
2022-01-0122594.22390240885
2022-02-0121993.386802023248
2022-03-0123191.13396292265
2022-04-0120283.553641840957
2022-05-0119301.40096990345
2022-06-0117659.8983034905
2022-07-0119559.800193467974
2022-08-0118810.520985928284
2022-09-0117116.00328124602
2022-10-0117316.282314707885
2022-11-0117412.49479156702
2022-12-0116387.537385026877
2023-01-0118085.982129580945
2023-02-0118127.21604823486
2023-03-0119603.78304003215
2023-04-0119699.995516891282
2023-05-0121347.388743111933
2023-06-0122719.10377033213
2023-07-0123542.604031448867
2023-08-0123240.614665307345
2023-09-0122124.549933741415
2023-10-0121369.7728703812
2023-11-0123643.13625216698
2023-12-0125223.37709657983
2024-01-0125690.302137337003
2024-02-0126763.562134300304
2024-03-0127208.10304778821
2024-04-0126325.304484607277
2024-05-0127239.519366762623
2024-06-0129585.140282189543
2024-07-0128875.524177355048
2024-08-0128961.919054534676
2024-09-0129851.786289484855
2024-10-0129809.76696285658
2024-11-0131228.213764551212
2024-12-0131810.98648152653
2025-01-0132555.55324122006
2025-02-0130774.24795537098
2025-03-0128577.069147098147
2025-04-0128904.97697639356
2025-05-0131911.125998257463
2025-06-0133835.37553544011
2025-07-0135060.611975442116
2025-08-0135009.560457108695
2025-09-0136721.74984121407
2025-10-0138732.39425557634
2025-11-0137895.93476288266
2025-12-0138041.235238139314
2026-01-0138402.52290634503
2026-02-0137318.65990172787
2026-03-0134801.42734390323
2026-04-0139258.617598397715
Annual Return Matrix
YearAnnual Return
2018-0.025960229435115556
20190.34928409000111227
20200.45430643437057583
20210.27684513757822593
2022-0.3507079508324257
20230.5391804457225018
20240.2611707924645803
20250.1958521078945743
20260.032001651698152056
Total Factor Risk
0.16946219907853038
VTI.US Exposure
0.168516404014777
VEA.US Exposure
0.014732270252608695
VWO.US Exposure
0.006953565571908258
QQQ.US Exposure
0.7783844550751227
VTV.US Exposure
-0.027596836352448317
IJR.US Exposure
-0.005292493975470655
QUAL.US Exposure
-0.050032911231594646
SHV.US Exposure
0.11494540321155756
TLT.US Exposure
0.030149801593479575
LQD.US Exposure
-0.03262849075587175
HYG.US Exposure
-0.03812985898781291
GLD.US Exposure
0.0016435746934120713
USO.US Exposure
-0.0044697956273815915
VNQ.US Exposure
0.01358857971563181
BTC-USD.CC Exposure
-0.00015692962320290396
CPER.US Exposure
0.0030345679638944167
VIX.INDX Exposure
-0.0023253068849454278
UUP.US Exposure
-0.003723922087787946
TIP.US Exposure
0.007717182289635039
Idiosyncratic Exposure
0.024690741144488906
Value Score
40.8
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
0
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
16.9%

FundamentalsiCompany financial health metrics: P/E valuation, dividend yield, Piotroski F-Score (9-point profitability signal), Altman Z-Score (bankruptcy risk proxy), and a radar chart across 6 fundamental dimensions. Note: ETFs may show N/A for some metrics.

Fundamental Dimensions

Core Valuation

P/E Ratio (TTM)P/E RatioPrice-to-Earnings ratio — the market price of a stock divided by its earnings per share, a key valuation measure.Click for full definition →23.1x
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →0.00%
Market Cap$564.4B
Piotroski F-ScorePiotroski F-ScoreA 9-point scoring system evaluating a company's financial strength across profitability, leverage, and operating efficiency.Click for full definition →
9-point profitability signal
0.0/ 9
Weak
Altman Z-ScoreAltman Z-ScoreA bankruptcy prediction model that combines 5 financial ratios into a single score indicating financial distress risk.Click for full definition →
Bankruptcy risk proxy
1.18
Distress Zone
Income Simulation

Based on $10,000 initial investment.

Total Income Generated
$0
Avg Yield on Cost
0.00%

Momentum & MacroiPrice momentum indicators relative to key technical levels: distance from 50-Day SMA (intermediate trend), 200-Day SMA (long-term trend), 52-Week High (bullish proximity), and Beta (market sensitivity coefficient).

vs 50-Day SMAMoving Averages (SMA)A rolling average of an asset's price over a defined window — used to identify trends and momentum signals.Click for full definition →
+6.3%
Above/below 50-day moving average
vs 200-Day SMAMoving Averages (SMA)A rolling average of an asset's price over a defined window — used to identify trends and momentum signals.Click for full definition →
+6.7%
Above/below 200-day moving average
vs 52-Week High52-Week HighThe highest price an asset reached in the past 52 weeks — a key reference for momentum and valuation context.Click for full definition →
0.0% from high
Distance from 52-week high
BetaBetaA measure of an asset's sensitivity to broad market movements relative to a benchmark (e.g. S&P 500).Click for full definition →
1.00
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Invesco EQQQ NASDAQ-100 UCITS ETF (GBP Hdg) a high-risk investment?

Invesco EQQQ NASDAQ-100 UCITS ETF (GBP Hdg) (EQGB.LSE) has an annualized volatility of 16.9% and experienced a maximum drawdown of 35.1% over the last 10 years. Its primary macro risk driver is QQQ.US.

What is the 10-year return of EQGB.LSE?

Over the past 10 years, EQGB.LSE has generated a Compound Annual Growth Rate (CAGR) of 17.5%. It has had a positive return in 78% of the years measured.

Data Methodology & Trust

The risk and return information on this page is pre-calculated mathematically using daily market data spanning a 10-year period. Fundamentals (such as P/E Ratio, Market Cap, and Dividend Yield) represent trailing averages and may not immediately reflect real-time live market fluctuations. Advanced scoring models like the Piotroski F-Score and Altman Z-Score are proxies applied to publicly available trailing-twelve-month financial statements and may not account for recent off-balance-sheet events, qualitative company shifts, or sector-specific capital structures. Macroeconomic factor exposures are estimated via multivariate regression against standard market indices. This data is provided for quantitative insight and backtesting research, and should not be misconstrued as tailored financial advice.

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