Franklin FTSE South Korea ETF

10-Year Study

FLKR.US · · US · ETF

Executive Summary: Franklin FTSE South Korea ETF has compounded at 10.5% annually over the last 10 years, with a maximum drawdown of 49.1% and an annualized volatility of 37.6%.

1Y CAGR
+159.6%
3Y CAGR
+36.5%
5Y CAGR
+11.7%
10Y CAGR
+10.5%

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 →
49.1%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.36
Sortino RatioSortino RatioLike Sharpe, but only penalizes downside volatility — a more accurate risk measure for asymmetric return distributions.Click for full definition →
0.67
Ann. VolatilityAnnualized VolatilityThe annualized standard deviation of an asset's returns — a measure of how much prices fluctuate.Click for full definition →
28.9%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · +91.9%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2022 · -27.5%
% 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.
202625.022.5-18.719.5————————48.7%
20256.50.8-1.84.68.018.31.1-0.810.020.0-6.510.091.9%
2024-8.98.14.6-6.3-1.06.40.3-1.1-2.3-6.8-3.0-8.8-18.8%
202312.2-7.43.8-0.53.80.66.8-7.4-5.1-7.615.06.719.2%
2022-7.80.5-1.3-6.61.4-14.14.1-4.3-18.79.116.7-5.4-27.5%
20212.20.21.71.22.01.8-5.0-2.3-6.8-1.5-5.24.6-7.5%
2020-8.3-5.0-12.48.75.07.15.85.62.4-0.618.413.642.6%
201910.2-2.3-4.00.8-9.67.4-6.2-3.65.54.0-0.38.88.9%
20183.8-6.93.8-0.5-5.2-5.6-0.6-0.31.2-14.53.9-1.1-21.3%
2017———————————2.82.8%

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.

Risk Profile Insight: This asset has an estimated annualized volatility of 37.6%. The dominant macroeconomic risk driver is SHV.US, accounting for 54.1% of variance. Idiosyncratic stock-specific factors contribute 6.8%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2017-11-0110000
2017-12-0110276.490954308287
2018-01-0110670.258935973081
2018-02-019929.146145218705
2018-03-0110308.870141902764
2018-04-0110260.886526551909
2018-05-019722.53376895694
2018-06-019178.08553176964
2018-07-019118.83747013215
2018-08-019087.628614619398
2018-09-019199.931730628565
2018-10-017868.5326961525325
2018-11-018179.2558638513665
2018-12-018087.921197639829
2019-01-018910.56712342127
2019-02-018704.442385526892
2019-03-018357.24386794753
2019-04-018426.342224606233
2019-05-017618.422977519871
2019-06-018178.914516994197
2019-07-017674.306334422392
2019-08-017399.132003706051
2019-09-017803.774320963573
2019-10-018113.229628907201
2019-11-018091.285902374799
2019-12-018805.822402106596
2020-01-018078.070902618617
2020-02-017674.989028136734
2020-03-016720.875798507826
2020-04-017307.21217145365
2020-05-017669.673769932217
2020-06-018215.828741405372
2020-07-018692.05637099527
2020-08-019179.255863851367
2020-09-019401.521431706245
2020-10-019343.004827619838
2020-11-0111060.61344906617
2020-12-0112560.442775637586
2021-01-0112834.690593455893
2021-02-0112859.316331008924
2021-03-0113072.80440825084
2021-04-0113232.944848100648
2021-05-0113499.000341346857
2021-06-0113748.476130101913
2021-07-0113060.125810698784
2021-08-0112756.229580143363
2021-09-0111884.624762276295
2021-10-0111704.149802506461
2021-11-0111098.844297069292
2021-12-0111613.400302335787
2022-01-0110709.66011605793
2022-02-0110758.228897449651
2022-03-0110616.667479397278
2022-04-019914.321938850147
2022-05-0110055.444482371871
2022-06-018636.80694397035
2022-07-018989.857121958355
2022-08-018600.672940946994
2022-09-016991.856439264641
2022-10-017625.640025357195
2022-11-018901.594577461354
2022-12-018420.295508850635
2023-01-019448.52977032233
2023-02-018748.622421612132
2023-03-019081.28931584337
2023-04-019032.476715267956
2023-05-019378.114790071682
2023-06-019430.730969912713
2023-07-0110068.75700980153
2023-08-019325.888720924562
2023-09-018848.441995416197
2023-10-018174.330716340762
2023-11-019400.741210318427
2023-12-0110034.08592188033
2024-01-019140.781196664553
2024-02-019883.747013215
2024-03-0110337.445750231629
2024-04-019682.986297361875
2024-05-019583.020432047593
2024-06-0110198.420051689667
2024-07-0110225.922855610279
2024-08-0110115.862876091089
2024-09-019885.990149704978
2024-10-019209.782025649778
2024-11-018934.217584239528
2024-12-018143.902082215829
2025-01-018672.453308626322
2025-02-018737.943141366362
2025-03-018578.924269761545
2025-04-018971.814502365045
2025-05-019687.521334178573
2025-06-0111464.768127956306
2025-07-0111596.137904130297
2025-08-0111506.997610571998
2025-09-0112660.993806992734
2025-10-0115194.12883405666
2025-11-0114213.73189642561
2025-12-0115628.809674745205
2026-01-0119539.66938118691
2026-02-0123928.414687667624
2026-03-0119442.141707709558
2026-04-0123235.968205978446
Annual Return Matrix
YearAnnual Return
2018-0.21296858688431253
20190.08876214133691884
20200.4263792979327836
2021-0.07539881278219718
2022-0.27495003275164187
20230.19165484291298696
2024-0.18837628602947953
20250.9190812361158511
20260.4867394695787832
Total Factor Risk
0.37641720693454606
VTI.US Exposure
-0.11906987408715847
VEA.US Exposure
0.2721735456932476
VWO.US Exposure
-0.00750314437329792
QQQ.US Exposure
0.12187738230308535
VTV.US Exposure
0.07200358721078548
IJR.US Exposure
-0.0076383377282047814
QUAL.US Exposure
-0.0022998434105285085
SHV.US Exposure
0.5414473641480163
TLT.US Exposure
0.06528527830123065
LQD.US Exposure
-0.03211159151335125
HYG.US Exposure
-0.0013424980188498396
GLD.US Exposure
0.03199602356238493
USO.US Exposure
-0.004002017576535049
VNQ.US Exposure
0.025527700430969965
BTC-USD.CC Exposure
-0.0036553247931946273
CPER.US Exposure
0.004133006891736858
VIX.INDX Exposure
-0.00416155819112845
UUP.US Exposure
-0.01581166103955643
TIP.US Exposure
-0.004478523943003311
Idiosyncratic Exposure
0.0676304861333515
Value Score
47
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
30.4
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
37.6%

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 →7.5x
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →2.53%
Market Cap$64.7B
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 →
+10.8%
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 →
+48.6%
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 →
2.9% 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 →
1.94
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Franklin FTSE South Korea ETF a high-risk investment?

Franklin FTSE South Korea ETF (FLKR.US) has an annualized volatility of 37.6% and experienced a maximum drawdown of 49.1% over the last 10 years. Its primary macro risk driver is SHV.US.

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

Over the past 10 years, FLKR.US has generated a Compound Annual Growth Rate (CAGR) of 10.5%. 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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