Columbia Emerging Markets Consumer ETF (ECON.US)

10-Year Study

ECON.US · US · ETF

Fundamental Snapshot

Columbia Emerging Markets Consumer ETF (ECON.US) charges an annual expense ratio of low annual fee, manages approximately institutional assets in net assets, and maintains a portfolio of diversified basket of holdings.

Executive Summary: Columbia Emerging Markets Consumer ETF has compounded at 4.2% annually over the last 10 years, with a maximum drawdown of 38.6% and an annualized volatility of 18.0%.

1Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+39.0%
3Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+19.0%
5Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+6.3%
10Y CAGRCAGRCompound Annual Growth Rate — the annualized rate of return over a period, accounting for compounding.Click for full definition →
+4.2%

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
2016-06-01$10,000
2016-07-01$10,616
2016-08-01$10,590
2016-09-01$10,693
2016-10-01$10,517
2016-11-01$9,651
2016-12-01$9,612
2017-01-01$10,098
2017-02-01$10,424
2017-03-01$10,771
2017-04-01$11,122
2017-05-01$11,574
2017-06-01$11,335
2017-07-01$11,882
2017-08-01$11,908
2017-09-01$11,951
2017-10-01$11,890
2017-11-01$11,969
2017-12-01$12,252
2018-01-01$12,631
2018-02-01$11,960
2018-03-01$11,533
2018-04-01$11,355
2018-05-01$10,889
2018-06-01$10,610
2018-07-01$10,832
2018-08-01$10,031
2018-09-01$9,700
2018-10-01$8,964
2018-11-01$9,264
2018-12-01$8,960
2019-01-01$9,954
2019-02-01$9,906
2019-03-01$9,932
2019-04-01$10,192
2019-05-01$9,501
2019-06-01$10,038
2019-07-01$9,769
2019-08-01$9,585
2019-09-01$9,651
2019-10-01$9,981
2019-11-01$10,011
2019-12-01$10,503
2020-01-01$10,212
2020-02-01$9,867
2020-03-01$8,736
2020-04-01$9,264
2020-05-01$9,599
2020-06-01$10,212
2020-07-01$10,878
2020-08-01$11,406
2020-09-01$11,209
2020-10-01$11,361
2020-11-01$12,006
2020-12-01$12,691
2021-01-01$13,181
2021-02-01$13,114
2021-03-01$12,542
2021-04-01$12,506
2021-05-01$12,448
2021-06-01$12,704
2021-07-01$11,484
2021-08-01$11,777
2021-09-01$11,205
2021-10-01$11,511
2021-11-01$11,097
2021-12-01$10,900
2022-01-01$10,959
2022-02-01$10,354
2022-03-01$9,598
2022-04-01$9,548
2022-05-01$9,703
2022-06-01$9,776
2022-07-01$9,617
2022-08-01$9,657
2022-09-01$8,720
2022-10-01$8,087
2022-11-01$9,239
2022-12-01$9,156
2023-01-01$10,020
2023-02-01$9,188
2023-03-01$9,509
2023-04-01$9,318
2023-05-01$9,123
2023-06-01$9,602
2023-07-01$10,159
2023-08-01$9,597
2023-09-01$9,309
2023-10-01$9,100
2023-11-01$9,634
2023-12-01$9,846
2024-01-01$9,322
2024-02-01$9,652
2024-03-01$9,709
2024-04-01$9,676
2024-05-01$9,808
2024-06-01$9,865
2024-07-01$9,917
2024-08-01$10,058
2024-09-01$10,643
2024-10-01$10,252
2024-11-01$10,001
2024-12-01$9,866
2025-01-01$10,085
2025-02-01$10,156
2025-03-01$10,361
2025-04-01$10,323
2025-05-01$10,708
2025-06-01$11,397
2025-07-01$11,502
2025-08-01$11,792
2025-09-01$12,610
2025-10-01$13,237
2025-11-01$12,923
2025-12-01$13,234
2026-01-01$14,386
2026-02-01$15,365
2026-03-01$14,067
2026-07-01$15,936
Max DrawdownMax DrawdownThe largest peak-to-trough decline in the asset's value over the measurement period.Click for full definition →
38.6%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.11
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.17
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
16.4%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · +34.1%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2018 · -26.9%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
70%

Annual Returns

View full annual returns data
YearReturn
201727.5%
2018-26.9%
201917.2%
202020.8%
2021-14.1%
2022-16.0%
20237.5%
20240.2%
202534.1%
202620.4%

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20268.76.8-8.413.320.4%
20252.20.72.0-0.43.76.40.92.56.95.0-2.42.434.1%
2024-5.33.50.6-0.31.40.60.51.45.8-3.7-2.4-1.40.2%
20239.4-8.33.5-2.0-2.15.25.8-5.5-3.0-2.25.92.27.5%
20220.5-5.5-7.3-0.51.60.8-1.60.4-9.7-7.314.2-0.9-16.0%
20213.9-0.5-4.4-0.3-0.52.1-9.62.5-4.92.7-3.6-1.8-14.1%
2020-2.8-3.4-11.56.03.66.46.54.9-1.71.45.75.720.8%
201911.1-0.50.32.6-6.85.6-2.7-1.90.73.40.34.917.2%
20183.1-5.3-3.6-1.5-4.1-2.62.1-7.4-3.3-7.63.4-3.3-26.9%
20175.13.23.33.34.1-2.14.80.20.4-0.50.72.427.5%
20166.2-0.21.0-1.7-8.2-0.4-3.9%

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
18.0%
View full factor risk breakdown
FactorRisk Exposure
VTI.US-20.5%
VEA.US-3.0%
VWO.US88.2%
QQQ.US3.4%
VTV.US3.4%
IJR.US0.9%
QUAL.US12.4%
SHV.US0.4%
TLT.US1.2%
LQD.US3.6%
HYG.US2.4%
GLD.US0.4%
USO.US-0.1%
VNQ.US-0.2%
BTC-USD.CC1.1%
CPER.US-3.0%
VIX.INDX3.6%
UUP.US-2.5%
TIP.US-0.7%
Idiosyncratic9.1%

Columbia Emerging Markets Consumer ETF ETF Profile & Portfolio Fundamentals

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

Fund Structure & Fees

Distribution Yield
0.0%

Portfolio Valuation Multiples

Portfolio P/E Ratio
Portfolio Forward P/E
Portfolio Price-to-Sales
Portfolio Price-to-Book

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 →
+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 →
+20.9%
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 →
8.0% 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 →
0.94
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 →
63
OversoldNeutralOverbought
Neutral
Fibonacci LevelsFibonacci RetracementTechnical levels based on mathematical ratios that indicate potential support and resistance areas.Click for full definition →
38.2% retracement+12.3%
50.0% retracement+20.5%
61.8% retracement+30.0%
% distance of current price from each 52-week Fibonacci support level.

In-Depth Analysis

ECON.US — 10-Year Return & Risk Profile

Columbia Emerging Markets Consumer ETF (ECON.US) has delivered modest annualized growth of 4.2% over the last 10 years. A $10,000 investment at the start of the period would have grown to approximately $15,102, representing a total return of 51%. Over this period, ECON.US generated positive annual returns in 7 out of 10 calendar years (70%).

The best single calendar year for ECON.US was 2025, with a return of +34.1%. The worst year was 2018, when the asset declined 26.9%. 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 0.11 is considered poor 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.

ECON.US — Drawdown, Volatility & Downside Risk

ECON.US's annualized volatility of 16.4% is classified as moderate relative to the long-run US equity benchmark of approximately 15%. This above-average volatility means investors in ECON.US have historically experienced larger day-to-day price swings than the broader market, which requires a higher tolerance for short-term portfolio fluctuations.

The asset's maximum peak-to-trough decline over the study period was 38.6% — a severe bear-market collapse. 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 39% drawdown, for example, requires a 63% gain just to break even.

When evaluating ECON.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.

ECON.US — Macroeconomic Factor Risk Exposure

The macroeconomic factor model attributes 88.2% of ECON.US's return variance to Emerging Market Equities. This means that when Emerging Market Equities rises or falls sharply, ECON.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 ECON.US allocation.

The second-largest macro driver is US Equity (broad market), contributing 20.5% of variance. 9.1% of ECON.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 ECON.US's factor exposures helps assess its marginal contribution to overall portfolio risk. Adding ECON.US alongside assets with low correlation to Emerging Market Equities — 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 Columbia Emerging Markets Consumer ETF a high-risk investment?

Columbia Emerging Markets Consumer ETF (ECON.US) has an annualized volatility of 18.0% and experienced a maximum drawdown of 38.6% over the last 10 years. Its primary macro risk driver is VWO.US.

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

Over the past 10 years, ECON.US has generated a Compound Annual Growth Rate (CAGR) of 4.2%. A $10,000 investment would have grown to approximately $15,102. It has had a positive return in 70% of calendar years.

What is ECON.US's Sharpe ratio?

ECON.US has a Sharpe ratio of 0.11 and a Sortino ratio of 0.17 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 ECON.US's dividend yield?

ECON.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 ECON.US above its 200-day moving average?

ECON.US is currently above its 200-day moving average by 20.9%. 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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