Franklin FTSE Japan ETF

10-Year Study

FLJP.US · · US · ETF

Executive Summary: Franklin FTSE Japan ETF has compounded at 7.3% annually over the last 10 years, with a maximum drawdown of 28.3% and an annualized volatility of 18.9%.

1Y CAGR
+29.6%
3Y CAGR
+19.1%
5Y CAGR
+8.5%
10Y CAGR
+7.3%

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 →
28.3%
Sharpe RatioSharpe RatioRisk-adjusted return: how much excess return you earn per unit of total risk (volatility).Click for full definition →
0.27
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 →
14.6%
Best YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2025 · +26.8%
Worst YearBest & Worst YearThe single calendar year with the highest and lowest return in the measured period.Click for full definition →
2022 · -16.6%
% Positive Years% Positive YearsThe percentage of calendar years in the measurement period where the asset delivered a positive return.Click for full definition →
78%

Annual Returns

Rolling 12-Month Returns

Rolling 12-Month Annualised Volatility

Historical Drawdowns

Monthly Returns

Monthly Returns Heatmap

YearJanFebMarAprMayJunJulAugSepOctNovDecAnn.
20266.28.3-8.65.7————————11.1%
20251.70.30.73.93.92.1-1.26.42.33.20.00.926.8%
20242.94.23.4-5.62.4-0.64.41.5-0.1-5.12.4-2.37.0%
20237.3-4.44.80.50.54.92.7-2.4-2.4-2.16.03.720.0%
2022-4.0-1.4-2.5-7.91.7-6.96.1-4.3-8.72.111.5-1.8-16.6%
2021-0.61.51.2-1.81.7-0.9-0.51.92.6-2.8-3.22.11.0%
2020-2.7-8.7-6.45.17.20.2-1.47.21.7-1.310.15.515.8%
20196.80.10.81.3-5.14.4-0.5-0.95.23.41.41.119.0%
20185.0-2.1-1.50.2-2.2-1.70.9-0.53.6-9.10.8-7.5-14.0%
2017———————————0.50.5%

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 18.9%. The dominant macroeconomic risk driver is VEA.US, accounting for 65.2% of variance. Idiosyncratic stock-specific factors contribute 6.2%.

10-Year Historical Price Series (Growth of $10,000)
DateSimulated Value
2017-11-0110000
2017-12-0110053.011659720149
2018-01-0110554.536100560936
2018-02-0110331.441414529367
2018-03-0110178.380915802501
2018-04-0110200.761509172724
2018-05-019981.033395448963
2018-06-019810.096871932745
2018-07-019896.20525659445
2018-08-019845.469589420429
2018-09-0110201.709839400275
2018-10-019274.00579429769
2018-11-019346.173724614386
2018-12-018644.219690180515
2019-01-019231.09385150097
2019-02-019239.72365657169
2019-03-019312.602834559051
2019-04-019435.6486815839
2019-05-018951.573516930064
2019-06-019341.953655101779
2019-07-019299.183961839191
2019-08-019217.4853127356
2019-09-019699.758649957086
2019-10-0110030.346567281658
2019-11-0110171.363272118617
2019-12-0110285.731897561367
2020-01-0110010.43163250307
2020-02-019140.670564303902
2020-03-018551.1410783463
2020-04-018987.752315111167
2020-05-019636.742106336267
2020-06-019653.717217409447
2020-07-019518.864659051575
2020-08-0110201.04600824099
2020-09-0110379.521757066246
2020-10-0110244.669198708374
2020-11-0111283.84946205968
2020-12-0111906.99725458399
2021-01-0111835.018990312807
2021-02-0112010.98166403505
2021-03-0112158.87376302176
2021-04-0111934.97299629677
2021-05-0112139.622659402456
2021-06-0112033.646756473538
2021-07-0111973.285537489865
2021-08-0112196.143140964547
2021-09-0112512.031939762062
2021-10-0112163.662830670895
2021-11-0111774.847437374643
2021-12-0112025.348866982462
2022-01-0111542.36428209031
2022-02-0111376.596158314247
2022-03-0111092.144506560075
2022-04-0110220.34452837167
2022-05-0110396.307202093913
2022-06-019674.48564939283
2022-07-0110266.24371138518
2022-08-019823.468328141225
2022-09-018971.061703106254
2022-10-019161.391579775911
2022-11-0110212.425970971613
2022-12-0110032.432893782272
2023-01-0110766.962071532549
2023-02-0110297.34894284888
2023-03-0110788.346918163843
2023-04-0110844.15615205527
2023-05-0110900.486967571847
2023-06-0111435.108133354195
2023-07-0111739.474719886957
2023-08-0111451.988411404618
2023-09-0111181.42979748408
2023-10-0110944.726572687141
2023-11-0111604.195412926687
2023-12-0112038.815156213697
2024-01-0112391.499167840226
2024-02-0112907.627894185314
2024-03-0113346.325457450792
2024-04-0112597.95065837826
2024-05-0112903.312991649953
2024-06-0112822.98942137631
2024-07-0113384.780248178022
2024-08-0113580.942355747118
2024-09-0113563.113747469142
2024-10-0112867.560942071248
2024-11-0113179.703836469937
2024-12-0112880.884981768353
2025-01-0113105.971161277781
2025-02-0113151.016847086492
2025-03-0113236.556233611669
2025-04-0113758.801689924465
2025-05-0114299.065420560748
2025-06-0114594.991868068299
2025-07-0114413.386629492123
2025-08-0115334.92652811562
2025-09-0115689.033035083476
2025-10-0116183.871747820027
2025-11-0116188.423732912275
2025-12-0116334.98816958041
2026-01-0117344.95986192312
2026-02-0118776.938505526396
2026-03-0117155.29381641275
2026-04-0118141.55725306666
Annual Return Matrix
YearAnnual Return
2018-0.14013631111006297
20190.18989709496226093
20200.15762275093005362
20210.009939669075921476
2022-0.16572625004435926
20230.1999896020909251
20240.06994623761791297
20250.2681572883152834
20260.11059506531204621
Total Factor Risk
0.1889980099385309
VTI.US Exposure
0.16750838624321218
VEA.US Exposure
0.652373190052137
VWO.US Exposure
0.0006598507974298587
QQQ.US Exposure
0.003873433624700213
VTV.US Exposure
-0.04947745903741989
IJR.US Exposure
-0.009587063149576566
QUAL.US Exposure
-0.10112328746213727
SHV.US Exposure
0.2860487223000336
TLT.US Exposure
-0.03663192360998799
LQD.US Exposure
0.14240079236350317
HYG.US Exposure
-0.04433903983151773
GLD.US Exposure
0.004757841113407807
USO.US Exposure
0.004691385966894123
VNQ.US Exposure
-0.025979840378252333
BTC-USD.CC Exposure
-0.005258828866442644
CPER.US Exposure
-0.03416722050450617
VIX.INDX Exposure
-0.00027702570319591884
UUP.US Exposure
-0.02867771226782492
TIP.US Exposure
0.01138996709204128
Idiosyncratic Exposure
0.06181583125750202
Value Score
50
Growth Score
50
Profit Score
37.5
Health Score
23.6
Yield Score
0
Moat Score
40

Factor Risk Decomposition

Share of annualised volatility attributable to each macro factor.

Total Est. Vol
18.9%

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 →N/A
Dividend YieldDividend YieldAnnual dividend paid per share divided by the current share price — expressed as a percentage income return.Click for full definition →0.00%
Market Cap$0
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 →
+2.0%
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 →
+11.1%
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 →
4.5% 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 →
0.82
Market sensitivity coefficient

Frequently Asked Questions & Methodology

Is Franklin FTSE Japan ETF a high-risk investment?

Franklin FTSE Japan ETF (FLJP.US) has an annualized volatility of 18.9% and experienced a maximum drawdown of 28.3% over the last 10 years. Its primary macro risk driver is VEA.US.

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

Over the past 10 years, FLJP.US has generated a Compound Annual Growth Rate (CAGR) of 7.3%. It has had a positive return in 78% 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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