Franklin FTSE Brazil ETF

10-Year Study

FLBR.US · · US · ETF

Executive Summary: Franklin FTSE Brazil ETF has compounded at 7.6% annually over the last 10 years, with a maximum drawdown of 50.6% and an annualized volatility of 37.1%.

1Y CAGR
+69.8%
3Y CAGR
+23.4%
5Y CAGR
+10.8%
10Y CAGR
+7.6%

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 →
50.6%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.28
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.42
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
32.3%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · +45.7%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2024 · -27.6%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
56%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
202617.87.3-0.78.2————————35.7%
202511.0-3.59.12.81.47.0-7.49.54.70.27.3-1.945.7%
2024-5.60.3-1.3-4.2-4.0-4.91.67.00.6-7.3-6.5-6.6-27.6%
20238.4-10.40.63.42.214.94.8-8.5-0.6-3.314.46.633.2%
202212.63.914.4-13.27.1-19.36.46.5-4.09.9-3.7-4.510.4%
2021-7.5-6.44.96.59.66.3-8.1-2.8-11.5-9.2-1.54.4-16.8%
2020-8.0-12.6-38.55.39.78.312.1-8.3-6.9-3.224.112.3-20.1%
201918.6-5.1-4.61.40.96.31.4-8.32.95.9-4.613.528.5%
201815.1-1.2-1.7-5.3-16.5-9.013.3-11.14.919.5-1.4-2.4-2.1%
2017———————————5.35.3%

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 37.1%. The dominant macroeconomic risk driver is HYG.US, accounting for 22.5% of variance. Idiosyncratic stock-specific factors contribute 20.0%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2017-11-0110000
2017-12-0110529.055386269942
2018-01-0112122.889406703713
2018-02-0111972.253091951963
2018-03-0111773.57949453307
2018-04-0111151.317440401506
2018-05-019315.934755332497
2018-06-018473.418175300234
2018-07-019601.792435920415
2018-08-018537.300591503854
2018-09-018958.809822548845
2018-10-0110708.872557806057
2018-11-0110559.813586664277
2018-12-0110304.283921849796
2019-01-0112225.560136225131
2019-02-0111607.313138555297
2019-03-0111072.450259903208
2019-04-0111232.909123498835
2019-05-0111335.149668399354
2019-06-0112054.34665710701
2019-07-0112224.69976698333
2019-08-0111208.818784728444
2019-09-0111539.415665889945
2019-10-0112222.262054131565
2019-11-0111663.810718766805
2019-12-0113237.282667144653
2020-01-0112181.466212582902
2020-02-0110641.835454382506
2020-03-016542.749596701919
2020-04-016891.629324251658
2020-05-017559.204158451336
2020-06-018188.06237677003
2020-07-019175.192686861445
2020-08-018417.780964330526
2020-09-017840.616597956623
2020-10-017585.875604947122
2020-11-019411.50743860907
2020-12-0110572.28894067037
2021-01-019783.40204337695
2021-02-019160.279620003585
2021-03-019608.603692417997
2021-04-0110229.503495250045
2021-05-0111211.830077074745
2021-06-0111916.257393798172
2021-07-0110954.077791718946
2021-08-0110647.069367270122
2021-09-019425.846925972397
2021-10-018561.175837963792
2021-11-018430.90159526797
2021-12-018798.996235884566
2022-01-019910.091414231942
2022-02-0110300.483957698512
2022-03-0111781.968094640615
2022-04-0110225.416741351497
2022-05-0110956.15701738663
2022-06-018841.799605664099
2022-07-019408.998028320488
2022-08-0110017.852661767341
2022-09-019620.505466929557
2022-10-0110572.217243233556
2022-11-0110177.594550994801
2022-12-019717.870586126546
2023-01-0110530.059150385374
2023-02-019435.884567126726
2023-03-019488.438788313319
2023-04-019813.156479655852
2023-05-0110033.697795303817
2023-06-0111529.736511919698
2023-07-0112078.795483061482
2023-08-0111046.352392901954
2023-09-0110974.726653522137
2023-10-0110610.718766804088
2023-11-0112142.606201828285
2023-12-0112943.39487363327
2024-01-0112223.696002867897
2024-02-0112264.77863416383
2024-03-0112106.757483419968
2024-04-0111598.852841010934
2024-05-0111134.110055565514
2024-06-0110594.01326402581
2024-07-0110759.777737945868
2024-08-0111518.336619465854
2024-09-0111582.864312600825
2024-10-0110739.917547947662
2024-11-0110039.505287685966
2024-12-019373.005915038539
2025-01-0110399.78490768955
2025-02-0110036.493995339666
2025-03-0110945.975981358666
2025-04-0111247.607098046245
2025-05-0111406.632012905538
2025-06-0112201.684889765193
2025-07-0111294.784011471591
2025-08-0112364.724861086215
2025-09-0112941.387345402401
2025-10-0112972.71912529127
2025-11-0113917.18946047679
2025-12-0113658.36171356874
2026-01-0116088.904821652628
2026-02-0117257.573041763757
2026-03-0117128.517655493815
2026-04-0118533.78741709984
Annual Return Matrix
YearAnnual Return
2018-0.021347733122693224
20190.2846387742748002
2020-0.2013248333125709
2021-0.16773025356544624
20220.10442945145203875
20230.33191677733510416
2024-0.2758464060976691
20250.45720186644228566
20260.3569553805774279
Total Factor Risk
0.3705167154118044
VTI.US Exposure
-0.07437337201415302
VEA.US Exposure
0.000459440398978646
VWO.US Exposure
0.07267099367648479
QQQ.US Exposure
0.04488350261587106
VTV.US Exposure
0.10623570037100616
IJR.US Exposure
0.00402671928976371
QUAL.US Exposure
-0.0068258766479402724
SHV.US Exposure
0.19990506901873872
TLT.US Exposure
0.11804470734005895
LQD.US Exposure
0.06034003585689779
HYG.US Exposure
0.22451659422339737
GLD.US Exposure
0.02325517006878611
USO.US Exposure
0.013125890116298215
VNQ.US Exposure
-0.011405767695088895
BTC-USD.CC Exposure
-0.001833226562558196
CPER.US Exposure
0.02345382489239397
VIX.INDX Exposure
0.01078441916870472
UUP.US Exposure
-0.003640522403702262
TIP.US Exposure
-0.0031527755388634227
Idiosyncratic Exposure
0.19952947382492595
Value Score
46.3
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
73.4
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
37.1%

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 →9.2x
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →6.12%
Market Cap$29.4B
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 →
+9.7%
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 →
+32.5%
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 →
1.49
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Franklin FTSE Brazil ETF a high-risk investment?

Franklin FTSE Brazil ETF (FLBR.US) has an annualized volatility of 37.1% and experienced a maximum drawdown of 50.6% over the last 10 years. Its primary macro risk driver is HYG.US.

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

Over the past 10 years, FLBR.US has generated a Compound Annual Growth Rate (CAGR) of 7.6%. It has had a positive return in 56% 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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