FT Cboe Vest U.S. Equity Deep Buffer ETF - August (DAUG.US)

10-Year Study

DAUG.US · US · ETF

About FT Cboe Vest U.S. Equity Deep Buffer ETF - August (DAUG.US)

Unknown

Under normal market conditions, the fund will invest substantially all of its assets in FLexible EXchange® Options (FLEX Options) that reference the price performance of the SPDR® S&P 500® ETF Trust. FLEX Options are customized equity or index option contracts that trade on an exchange, but provide investors with the ability to customize key contract terms like exercise prices, styles and expiration dates....

Source: EODHD Financial Datasets
Fundamentals updated: Sep 13, 2026

Fundamental Snapshot

FT Cboe Vest U.S. Equity Deep Buffer ETF - August (DAUG.US) charges an annual expense ratio of 0.85%, manages approximately $424.2M in net assets, and maintains a portfolio of 1 holdings. At the portfolio level, its underlying basket trades at 3.27x sales and 4.55x book value.

Executive Summary: FT Cboe Vest U.S. Equity Deep Buffer ETF - August has compounded at 6.7% annually over the last 10 years, with a maximum drawdown of 15.1% and an annualized volatility of 16.2%.

1Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+8.6%
3Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+13.6%
5Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+6.4%
10Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+6.7%

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

View full price history data
DateValue
2019-11-01$10,000
2019-12-01$10,079
2020-01-01$10,078
2020-02-01$9,747
2020-03-01$9,171
2020-04-01$9,735
2020-05-01$9,963
2020-06-01$10,012
2020-07-01$10,321
2020-08-01$10,581
2020-09-01$10,462
2020-10-01$10,335
2020-11-01$10,781
2020-12-01$10,887
2021-01-01$10,814
2021-02-01$10,920
2021-03-01$11,102
2021-04-01$11,186
2021-05-01$11,232
2021-06-01$11,299
2021-07-01$11,324
2021-08-01$11,405
2021-09-01$11,211
2021-10-01$11,475
2021-11-01$11,425
2021-12-01$11,618
2022-01-01$11,419
2022-02-01$11,272
2022-03-01$11,485
2022-04-01$10,956
2022-05-01$10,931
2022-06-01$10,627
2022-07-01$10,726
2022-08-01$10,354
2022-09-01$9,858
2022-10-01$10,225
2022-11-01$10,545
2022-12-01$10,229
2023-01-01$10,511
2023-02-01$10,364
2023-03-01$10,558
2023-04-01$10,621
2023-05-01$10,617
2023-06-01$11,186
2023-07-01$11,491
2023-08-01$11,147
2023-09-01$10,877
2023-10-01$10,732
2023-11-01$11,334
2023-12-01$11,646
2024-01-01$11,758
2024-02-01$12,027
2024-03-01$12,162
2024-04-01$12,097
2024-05-01$12,336
2024-06-01$12,442
2024-07-01$12,514
2024-08-01$12,686
2024-09-01$12,862
2024-10-01$12,797
2024-11-01$13,145
2024-12-01$13,043
2025-01-01$13,242
2025-02-01$13,186
2025-03-01$12,753
2025-04-01$12,724
2025-05-01$13,237
2025-06-01$13,694
2025-07-01$13,929
2025-08-01$14,092
2025-09-01$14,341
2025-10-01$14,441
2025-11-01$14,486
2025-12-01$14,576
2026-01-01$14,690
2026-02-01$14,670
2026-03-01$14,397
2026-07-01$15,543
2026-08-01$15,643
2026-09-01$15,578
Max DrawdownMax DrawdownThe largest peak-to-trough decline in the asset's value over the measurement period.Click for full definition →
15.1%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.33
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.52
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
8.5%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2023 · +13.8%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2022 · -12.0%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
86%

Annual Returns

View full annual returns data
YearReturn
20208.0%
20216.7%
2022-12.0%
202313.8%
202412.0%
202511.8%
20266.9%

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20260.8-0.1-1.98.00.6-0.46.9%
20251.5-0.4-3.3-0.24.03.51.71.21.80.70.30.611.8%
20241.02.31.1-0.52.00.90.61.41.4-0.52.7-0.812.0%
20232.8-1.41.90.6-0.05.42.7-3.0-2.4-1.35.62.813.8%
2022-1.7-1.31.9-4.6-0.2-2.80.9-3.5-4.83.73.1-3.0-12.0%
2021-0.71.01.70.80.40.60.20.7-1.72.4-0.41.76.7%
2020-0.0-3.3-5.96.22.30.53.12.5-1.1-1.24.31.08.0%
20190.80.8%

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.

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
16.2%
View full factor risk breakdown
FactorRisk Exposure
VTI.US22.1%
VEA.US-3.4%
VWO.US0.4%
QQQ.US-1.0%
VTV.US3.5%
IJR.US-0.3%
QUAL.US-0.0%
SHV.US74.9%
TLT.US1.0%
LQD.US1.6%
HYG.US-1.3%
GLD.US-0.1%
USO.US0.2%
VNQ.US0.3%
BTC-USD.CC-0.2%
CPER.US-0.1%
VIX.INDX-0.3%
UUP.US0.8%
TIP.US-0.6%
Idiosyncratic2.4%

FT Cboe Vest U.S. Equity Deep Buffer ETF - August ETF Profile & Portfolio Fundamentals

Detailed fund structure, fee metrics, portfolio-level valuation, and asset distribution statistics.

Fund Structure & Fees

Expense Ratio
0.85%
72nd pct of 1221 ETFs · median 0.50%
Fund Size vs Peers
36th pct
larger than 36% of 1,443 ETFs we track
Holdings Count1
Distribution Yield
0.0%
10th pct of 1336 ETFs · median 1.8%

Portfolio Valuation Multiples

Portfolio P/E Ratio
Portfolio Forward P/E20.17x
Portfolio Price-to-Sales3.27x
Portfolio Price-to-Book4.55x

Market Sentiment & Squeeze Risk

Short Squeeze RiskLow

Dividend & Income Analysisi10-Year historical income simulation on a $10,000 initial investment, cumulative dividend income generated, average yield on cost, and annual payout table.

Income Simulation

Based on $10,000 initial investment.

Total Income Generated
$0
Avg Yield on Cost
0.00%

Momentum & MacroiPrice momentum indicators: distance from 50/200-Day SMA, 52-Week High proximity, Golden Cross trend signal, RSI momentum gauge, Fibonacci retracement levels, and Beta (market sensitivity).

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 →
+0.2%
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 →
+5.8%
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 →
0.8% 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 →
0.50
Market sensitivity coefficient
Trend SignalGolden Cross & Death CrossTechnical chart patterns that occur when a short-term moving average crosses over a long-term moving average.Click for full definition →
✦ Golden Cross
Bullish — 50 SMA above 200 SMA
RSI (14-Day)Relative Strength Index (RSI)A momentum oscillator that measures the speed and change of price movements to identify overbought or oversold conditions.Click for full definition →
47
OversoldNeutralOverbought
Neutral
Fibonacci LevelsFibonacci RetracementTechnical levels based on mathematical ratios that indicate potential support and resistance areas.Click for full definition →
38.2% retracement+5.4%
50.0% retracement+7.5%
61.8% retracement+9.6%
% distance of current price from each 52-week Fibonacci support level.

In-Depth Analysis

DAUG.US — 10-Year Return & Risk Profile

FT Cboe Vest U.S. Equity Deep Buffer ETF - August (DAUG.US) has delivered modest annualized growth of 6.7% over the last 10 years. A $10,000 investment at the start of the period would have grown to approximately $19,129, representing a total return of 91%. Over this period, DAUG.US generated positive annual returns in 9 out of 10 calendar years (86%).

The best single calendar year for DAUG.US was 2023, with a return of +13.8%. The worst year was 2022, when the asset declined 12.0%. This spread between best and worst year is a useful indicator of the range of outcomes an investor might have experienced in a given 12-month window.

The asset's Sharpe ratio of 0.33 is considered weak on a risk-adjusted basis. The Sharpe ratio measures return earned above the risk-free rate per unit of total volatility — a higher reading indicates more efficient return generation relative to the risk taken. Investors focused on risk-adjusted outcomes should weigh this figure alongside absolute CAGR when making allocation decisions.

DAUG.US — Drawdown, Volatility & Downside Risk

DAUG.US's annualized volatility of 8.5% is classified as low relative to the long-run US equity benchmark of approximately 15%. This below-average volatility profile suggests the asset has historically experienced smaller day-to-day price swings than the broad market, which may appeal to risk-conscious or income-oriented investors.

The asset's maximum peak-to-trough decline over the study period was 15.1% — a notable pullback. Drawdown magnitude is a critical consideration for investors who may need to liquidate positions during market stress, as a larger decline requires proportionally greater subsequent gains to recover to the prior peak. A 15% drawdown, for example, requires a 18% gain just to break even.

When evaluating DAUG.US for inclusion in a diversified US portfolio, it is important to note that historical volatility and drawdown metrics are backward-looking. They capture the risk environment of the past 10 years, which included the COVID-19 market crash (2020), the 2022 Federal Reserve rate hike cycle, and various geopolitical disruptions. Future risk may differ materially, particularly in response to structural changes in US monetary policy, sector regulation, or macroeconomic regime shifts.

DAUG.US — Macroeconomic Factor Risk Exposure

The macroeconomic factor model attributes 74.9% of DAUG.US's return variance to Short-Term Interest Rates. This means that when Short-Term Interest Rates rises or falls sharply, DAUG.US tends to move in the same direction with meaningful magnitude. Investors who already hold significant exposure to this factor — through other funds or direct equity positions — should be aware of this concentration when sizing their DAUG.US allocation.

The second-largest macro driver is US Equity (broad market), contributing 22.1% of variance. 2.4% of DAUG.US's risk is attributable to idiosyncratic, stock-specific factors that are uncorrelated with the broader macro drivers. A higher idiosyncratic share generally indicates that the fund's performance is more dependent on the security selection or holdings composition of the individual underlying assets, rather than broad market forces.

For US investors building a diversified multi-asset portfolio, understanding DAUG.US's factor exposures helps assess its marginal contribution to overall portfolio risk. Adding DAUG.US alongside assets with low correlation to Short-Term Interest Rates — such as US Treasury bonds, commodities, or assets with significant developed-market ex-US exposure — can reduce the overall portfolio's sensitivity to any single macroeconomic theme.

Compare this AssetiRun a head-to-head backtest and risk analysis against similar assets.

Frequently Asked Questions & Methodology

Is FT Cboe Vest U.S. Equity Deep Buffer ETF - August a high-risk investment?

FT Cboe Vest U.S. Equity Deep Buffer ETF - August (DAUG.US) has an annualized volatility of 16.2% and experienced a maximum drawdown of 15.1% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, DAUG.US has generated a Compound Annual Growth Rate (CAGR) of 6.7%. A $10,000 investment would have grown to approximately $19,129. It has had a positive return in 86% of calendar years.

What is DAUG.US's Sharpe ratio?

DAUG.US has a Sharpe ratio of 0.33 and a Sortino ratio of 0.52 over the 10-year period. The Sharpe ratio measures risk-adjusted return — how much excess return is earned per unit of volatility. A reading below 1.0 suggests investors were not fully compensated on a risk-adjusted basis.

What is DAUG.US's dividend yield?

DAUG.US does not pay a meaningful dividend. Its returns are driven primarily by price appreciation. Investors seeking regular income may wish to consider dividend-focused alternatives.

Is DAUG.US above its 200-day moving average?

DAUG.US is currently above its 200-day moving average by 5.8%. The current trend signal is: Bullish — 50 SMA above 200 SMA. The 200-day SMA is a widely used long-term trend filter — assets trading above it tend to exhibit positive price momentum.

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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