Amplify Transformational Data Sharing ETF

10-Year Study

BLOK.US · · US · ETF

Executive Summary: Amplify Transformational Data Sharing ETF has compounded at 16.9% annually over the last 10 years, with a maximum drawdown of 69.2% and an annualized volatility of 45.3%.

1Y CAGR
+24.4%
3Y CAGR
+48.0%
5Y CAGR
+9.6%
10Y CAGR
+16.9%

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 →
69.2%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.54
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
1.13
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
40.2%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2023 · +99.6%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2022 · -62.4%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
88%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20264.4-9.9-6.917.8————————3.2%
202510.8-13.1-11.48.920.418.03.40.812.63.3-9.6-8.532.6%
2024-9.924.78.6-15.37.27.23.4-3.66.17.025.1-9.053.1%
202324.9-3.56.12.81.312.914.6-15.7-9.33.416.725.499.6%
2022-18.01.62.2-21.8-13.8-21.421.3-5.3-11.22.8-11.0-10.6-62.4%
20219.831.810.3-5.2-13.44.0-6.110.6-9.824.3-0.4-17.230.8%
20200.7-5.3-14.017.06.85.014.110.5-3.61.521.717.790.2%
201912.16.20.01.8-3.05.42.7-4.2-0.41.03.81.829.5%
2018—-4.9-3.70.15.2-3.83.31.9-0.6-13.9-3.7-11.0-28.4%

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 45.3%. The dominant macroeconomic risk driver is VTI.US, accounting for 39.8% of variance. Idiosyncratic stock-specific factors contribute 8.5%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2018-01-0110000
2018-02-019506.922396133114
2018-03-019157.491474652954
2018-04-019162.257004400379
2018-05-019640.976129028266
2018-06-019277.186728309105
2018-07-019578.776682324837
2018-08-019760.671382684419
2018-09-019698.410045984268
2018-10-018353.292857275479
2018-11-018046.937373512321
2018-12-017162.157980405628
2019-01-018030.474634384846
2019-02-018527.451308045082
2019-03-018529.617457930275
2019-04-018685.27079968065
2019-05-018422.91910358529
2019-06-018873.911509682692
2019-07-019113.302016994994
2019-08-018733.297437135237
2019-09-018698.886598959012
2019-10-018781.819194563583
2019-11-019114.354146939231
2019-12-019278.05318826318
2020-01-019347.369984589392
2020-02-018847.546371080043
2020-03-017605.537916906491
2020-04-018902.009568193493
2020-05-019510.635795936305
2020-06-019985.889080747878
2020-07-0111391.782246235542
2020-08-0112583.536023072593
2020-09-0112128.27320720152
2020-10-0112311.405707495498
2020-11-0114985.92002574624
2020-12-0117644.219164856386
2021-01-0119374.354023159238
2021-02-0125538.226356474006
2021-03-0128166.199397191434
2021-04-0126688.26627552189
2021-05-0123112.014705063226
2021-06-0124045.19207560482
2021-07-0122572.3339336663
2021-08-0124968.219486684367
2021-09-0122516.818606608613
2021-10-0127979.601057081145
2021-11-0127878.720362427823
2021-12-0123072.219437172374
2022-01-0118908.07478787204
2022-02-0119206.755912041936
2022-03-0119637.510289211958
2022-04-0115364.253575694562
2022-05-0113244.83063802398
2022-06-0110413.239508098306
2022-07-0112630.262970596063
2022-08-0111964.017155907091
2022-09-0110625.769756834205
2022-10-0110918.69511130916
2022-11-019718.276734931334
2022-12-018684.40433972657
2023-01-0110849.74965496327
2023-02-0110470.673425054309
2023-03-0111113.958050960224
2023-04-0111424.088824523293
2023-05-0111573.429386608243
2023-06-0113066.773117461025
2023-07-0114973.665806395713
2023-08-0112624.507200901118
2023-09-0111447.111903303068
2023-10-0111837.637782605198
2023-11-0113819.231697580723
2023-12-0117336.19265118179
2024-01-0115622.89187198673
2024-02-0119485.013337294295
2024-03-0121163.470048336094
2024-04-0117928.541809787286
2024-05-0119223.71377114317
2024-06-0120600.147298192194
2024-07-0121308.663980640813
2024-08-0120542.032591272273
2024-09-0121790.725165091564
2024-10-0123323.98794382864
2024-11-0129183.980393249043
2024-12-0126544.310143151564
2025-01-0129414.45874103369
2025-02-0125573.25609461743
2025-03-0122666.221058690287
2025-04-0124694.356251199122
2025-05-0129734.058684094893
2025-06-0135099.42627973041
2025-07-0136297.926066209926
2025-08-0136580.6395712261
2025-09-0141202.39885627287
2025-10-0142560.63672428625
2025-11-0138461.29090155158
2025-12-0135209.21913391139
2026-01-0136750.28005223516
2026-02-0133098.770245765176
2026-03-0130827.407366147414
2026-04-0136323.23907486833
Annual Return Matrix
YearAnnual Return
20190.2954270505685941
20200.9017156731949412
20210.30763618506436563
2022-0.6235990922600686
20230.9962442987457238
20240.5311499287787429
20250.32643187726599754
20260.031640007031112694
Total Factor Risk
0.45280108853082407
VTI.US Exposure
0.39822245013250523
VEA.US Exposure
-0.0012288670603850492
VWO.US Exposure
0.0007357202702616793
QQQ.US Exposure
0.02265746163372021
VTV.US Exposure
-0.08151589881823454
IJR.US Exposure
0.1730528865949983
QUAL.US Exposure
-0.08126723880606118
SHV.US Exposure
0.24157744786226235
TLT.US Exposure
0.05098791327233712
LQD.US Exposure
-0.03255694323803056
HYG.US Exposure
-0.005771465201917973
GLD.US Exposure
0.004115356311090541
USO.US Exposure
-0.0014230214998284883
VNQ.US Exposure
-0.008394127895516289
BTC-USD.CC Exposure
0.27194381697883024
CPER.US Exposure
-0.016132608657120087
VIX.INDX Exposure
-0.02020870486887683
UUP.US Exposure
0.006855282215825263
TIP.US Exposure
-0.006534587134096665
Idiosyncratic Exposure
0.08488512790823677
Value Score
43.7
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
9.1
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
45.3%

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 →15.8x
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →0.76%
Market Cap$18.7B
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 →
+10.2%
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 →
-2.0%
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 →
20.2% 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 →
2.91
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Amplify Transformational Data Sharing ETF a high-risk investment?

Amplify Transformational Data Sharing ETF (BLOK.US) has an annualized volatility of 45.3% and experienced a maximum drawdown of 69.2% over the last 10 years. Its primary macro risk driver is VTI.US.

What is the 10-year return of BLOK.US?

Over the past 10 years, BLOK.US has generated a Compound Annual Growth Rate (CAGR) of 16.9%. It has had a positive return in 88% 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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