How much do currency moves change returns on Asian stock markets?

Year to date as of 6 Nov 2026: Korea KOSPI is +20.1% in local currency and +26.4% in S$ (currency effect +5.3%); Taiwan TAIEX is +37.1% in local currency and +30.8% in S$ (currency effect -4.6%); India Nifty 50 is -4.2% in local currency and -8.6% in S$ (currency effect -4.5%); China Shanghai Composite is -8.1% in local currency and -3.9% in S$ (currency effect +4.5%). A market's S$ return is (1 + local return) × (1 + currency move) − 1, so the local return and the currency move compound.

What does it cost to hedge US-dollar assets back to Singapore dollars?

About 2.3% a year as of 6 Nov 2026: the US 3-month bill yields 4.11% and Singapore's 1.84%, so hedging costs that gap (roughly S$2,266 per S$100,000 a year). Bank forward spreads come on top; this is an arithmetic approximation, not a quote.

Dollar and currency moves: what they did to returns in S$ and ₹

The US dollar index, the Singapore dollar and the rupee, what currency moves added to or took from Asian stock-market returns this year, the dollar's behaviour when US stocks fall, and the cost of hedging.

Data as of 6 Nov 2026.

Open the FX summary in the cockpit Currency board Pairs table Evidence

As of 6 Nov 2026 the dollar index (DXY, the US dollar against six major currencies) stands at 102.28 and is +0.2% over 1 month and +2.5% over 3 months, at the 77th percentile of 3-month moves since 2003.
USD/SGD is 1.2818 Singapore dollars per US dollar (US dollar +0.13% over 1 month, -0.23% year to date) and USD/INR is 93.895 rupees per US dollar (-2.98% over 1 month, +4.52% year to date); SGD/INR is 73.250 rupees per Singapore dollar (+4.76% year to date).
Read as of 6 Nov 2026: USD CUSHION HOLDS. In the S&P 500's worst 10% of months since 2004 (measured on SPY), the US dollar rose a median +1.0% against the Singapore dollar and +1.9% against the Indian rupee, so a -8.0% month for a US-dollar holding was -7.3% in Singapore dollars (S$) and -6.5% in rupees (₹) (validated: both halves of the history agree).
The most unusual 3-month move against the US dollar is the Philippine peso's -2.8%, at the 16th percentile of 3-month moves since 2003.
Year to date, in S$ terms: Korea KOSPI +26.4% (+20.1% in local currency; currency leg +5.3%); Taiwan TAIEX +30.8% (+37.1% in local currency; currency leg -4.6%). A market's S$ return is (1 + local return) × (1 + currency move) − 1, so the two legs compound rather than add.
India's Nifty 50 needs about +4.8% more in rupees just to be flat in S$ this year (year to date it is -4.2% in rupees and -8.6% in S$).
Hedging US-dollar assets back to Singapore dollars with 3-month forwards costs about 2.3% a year (US 3-month bill 4.11% against 1.84% in Singapore, as of 6 Nov; roughly S$2,266 per S$100,000); hedging back to rupees earns about 1.6% a year.
USD/INR's one-month ±2σ range (two standard deviations of 20-session realised volatility) is 91.24 – 96.63; since 2004 the next month's move stayed inside it 89% of the time, against 95.4% for a normal curve.

What currencies did to market returns

Arithmetic, not a forecast. Ranked by the size of the currency effect on a holder who counts in Singapore dollars. Each market is read at its own last final session.
Market	Currency	Local YTD	In S$ YTD	In ₹ YTD	Currency effect in S$	Local YTD to be flat in S$	Local 12M	In S$ 12M	As of
Korea · KOSPI	KRW	+20.1%	+26.4%	+32.5%	+5.3%	-5.0%	+25.7%	+31.4%	6 Nov
Taiwan · TAIEX	TWD	+37.1%	+30.8%	+37.0%	-4.6%	+4.8%	+42.3%	+32.4%	6 Nov
India · Nifty 50	INR	-4.2%	-8.6%	-4.2%	-4.5%	+4.8%	-1.9%	-8.9%	6 Nov
China · Shanghai Composite	CNY	-8.1%	-3.9%	+0.7%	+4.5%	-4.3%	-8.9%	-4.5%	6 Nov
Japan · Nikkei 225	JPY	+14.1%	+12.4%	+17.8%	-1.5%	+1.5%	+12.9%	+7.3%	6 Nov
Hong Kong · Hang Seng	HKD	-4.5%	-5.4%	-0.9%	-1.0%	+1.0%	-7.6%	-9.8%	6 Nov
US · S&P 500	USD	+7.8%	+7.5%	+12.6%	-0.2%	+0.2%	+9.8%	+8.0%	6 Nov
Singapore · STI	SGD	+11.5%	+11.5%	+16.8%	0.0%	0.0%	+15.5%	+15.5%	6 Nov

Currency moves against the US dollar and where they rank in history

3-month change against the US dollar (positive = the currency strengthened) and its percentile among all 3-month moves in its own history.
Gauge	Level	Percentile of own history	History	1-year range	As of
Dollar index, 3-month move DXY	+2.5%	77th	2003 on	-3.4% to +3.4%	6 Nov
SGD/INR, 3-month move + = S$ converts to more rupees	-1.8%	16th	2003 on	-1.8% to +6.8%	6 Nov
SGD Singapore dollar	-0.1%	40th	2003 on	-1.9% to +3.6%	6 Nov
INR Indian rupee	+1.6%	79th	2003 on	-6.1% to +2.2%	6 Nov
JPY Japanese yen	+0.5%	59th	2003 on	-6.5% to +4.5%	6 Nov
KRW Korean won	+3.6%	82nd	2003 on	-6.5% to +14.7%	6 Nov
TWD Taiwan dollar	-1.7%	24th	2003 on	-4.3% to +1.6%	6 Nov
CNH Chinese yuan (offshore CNH)	+1.1%	71st	2012 on	+0.2% to +3.4%	6 Nov
THB Thai baht	-1.2%	33rd	2003 on	-5.1% to +5.5%	6 Nov
IDR Indonesian rupiah	-1.0%	45th	2003 on	-7.2% to +2.9%	6 Nov
MYR Malaysian ringgit	+0.8%	61st	2003 on	-4.4% to +6.9%	6 Nov
PHP Philippine peso	-2.8%	16th	2003 on	-6.4% to +2.0%	6 Nov

The US-dollar cushion in the S&P 500's worst months

Worst decile = the worst 10% of 21-session windows. The USD move is the median over the 21 possible start days of a monthly grid. A same-window fact, not a forecast.
Pair	Sample	SPY worst-decile month	Same, in home currency	USD move (median)	USD rose in	Gap vs all months	95% range of gap (pp)	Windows	Result
USD/SGD	2004+	-8.0%	-7.3%	+1.04%	57–82%	+1.08%	[+0.70, +1.46]	65	Validated
USD/SGD	2016+	-7.8%	-7.1%	+0.87%	38–92%	+0.86%	[+0.42, +1.26]	28	Validated
USD/INR	2004+	-8.0%	-6.5%	+1.90%	71–89%	+1.71%	[+1.19, +2.22]	65	Validated
USD/INR	2016+	-7.8%	-6.8%	+1.06%	46–92%	+0.91%	[+0.35, +1.47]	28	Validated

What hedging US-dollar assets back home would cost

Covered-interest-parity approximation from 3-month government bill yields; bank forward spreads come on top. Per 100,000 is in the home currency (S$ or ₹).
Hedge	US 3M bill	Home 3M bill	Hedge carry per year	Per 100,000 per year	As of
US$ assets hedged back to S$	4.11%	1.84%	-2.27%	-2,266	6 Nov
US$ assets hedged back to ₹	4.11%	5.75%	+1.64%	+1,642	6 Nov

One- and three-month ranges from realised volatility

σ = 20-session realised volatility scaled to the horizon. A normal curve would hold 95.4% of moves inside ±2σ. A range, not a forecast of direction.
Pair	Last	Volatility, 20 days	±1σ, 1 month	±2σ, 1 month	±2σ, 3 months	Share of months that stayed inside ±2σ	Result
USD/SGD	1.2818	2.9%	1.2711 – 1.2927	1.2604 – 1.3037	1.2449 – 1.3199	92.7%	Provisional
USD/INR	93.895	5.0%	92.56 – 95.25	91.24 – 96.63	89.34 – 98.68	89.1%	Validated
USD/JPY	158.42	5.2%	156.07 – 160.81	153.75 – 163.23	150.42 – 166.85	91.0%	Validated
USD/KRW	1,364	8.2%	1331.63 – 1396.44	1300.37 – 1430.01	1255.91 – 1480.63	93.1%	Provisional
USD/CNH (yuan)	6.6689	1.5%	6.6402 – 6.6977	6.6116 – 6.7267	6.5700 – 6.7693	88.5%	Validated

Findings and the evidence behind them

The dollar rises when US stocks fall Validated

In SPY's worst 10% of months (a 'month' = 21 trading sessions) since 2004, the US dollar rose a median +1.0% against the S$ (the median over the 21 possible start days of a monthly grid; it rose in 57–82% of those months depending on the start day) and +1.9% against the rupee. Since 2016 the figures are smaller: +0.9% vs S$ and +1.1% vs ₹. Worked example: S$100,000 of US stock in a median worst month (SPY -8.0%) lost about S$7,314 in S$, not S$8,038.

Evidence: +1.08% versus a baseline of -0.10%; 95% range +0.70% to +1.46% (65 separate windows, 46 episodes, both halves of history agree). Today: SPY -5.0% over the last 21 sessions (worst-decile line -4.4%): inside a worst-decile month now. The condition holds today.

What currencies did to market returns Fact

The return in S$ compounds the local index return with the currency's move against the S$ (the 'currency effect'): (1 + local) × (1 + currency) − 1, so the two do not simply add. Year to date, local → S$: KOSPI (Korea) +20.1% → +26.4%; TAIEX (Taiwan) +37.1% → +30.8%; Nifty 50 (India) -4.2% → -8.6%; Shanghai Composite (China) -8.1% → -3.9%. For India: the Nifty's -4.2% in rupees is -8.6% in S$ because S$ converts to +4.8% more rupees than on 2025-12-31.

Today: YTD as of 2026-11-06; largest currency effect: the KOSPI (Korea) +20.1% YTD in local currency is +26.4% in S$ (the S$ leg alone: +5.3%; the two legs compound, they do not add). The condition holds today.

Currency ranges have fatter tails than textbook Validated

A realised-vol range takes how much a currency swung over the last 20 sessions (realised volatility, annualised) and projects a one-month band of ±2σ (two standard deviations). A bell curve says 95% of months end inside it. Measured since 2004 the share that did: SGD 93%, INR 89%, JPY 91%, KRW 93%, CNH 89%. Today USD/INR's ±2σ one-month band is 91.24 – 96.63 (vol 5.0% a year).

Evidence: -6.4 pp versus a baseline of 95.5%; 95% range -8.8 pp to -3.9 pp (283 separate windows, both halves of history agree). Today: USD/INR 93.89, ±1σ 1M 92.56 – 95.25. The condition holds today.

Strong-currency markets did not outperform next No edge

We ranked 7 Asian markets every day since 2004 by how much their currency rose against the US dollar over 3 months, then compared the 3 strongest-currency markets with the 3 weakest over the next month (in US$): -0.19% a month on average (95% range -0.49% to +0.12%, 283 non-overlapping months). No edge.

Evidence: -0.19% versus a baseline of 0.00%; 95% range -0.49% to +0.12% (283 separate windows, both halves of history agree). Today: Strongest currencies now: Korea, India, Japan; weakest: Indonesia, Thailand, Taiwan. The condition does not hold today.

PHP 3-month move at 16th percentile Descriptive

The Philippine peso is -2.8% against the US dollar over 3 months, weaker than 84% of 3-month moves since 2003. When any of 6 Asian currencies rose 5%+ in 3 months, that market returned +4.0% in US$ over the next 3 months vs +2.6% normally (95% range of the gap -1.4% to +4.3%; label DESCRIPTIVE).

Evidence: +1.44% versus a baseline of 2.60%; 95% range -1.39% to +4.25% (39 separate windows, 23 episodes, both halves of history agree). Today: PHP -2.8% vs USD over 3M as of 2026-11-06. The condition does not hold today.

Sources: TradingView FX_IDC interbank composite daily closes, index closes and 3-month government bill yields. Evidence and the rules that found no edge are on the Evidence page.

Questions

Does a stronger US dollar cushion falls in US stocks for investors in Singapore dollars or rupees?: Historically yes. In the S&P 500's worst 10% of months since 2004 the US dollar rose a median +1.0% against the Singapore dollar (it rose in 57–82% of those months, depending on the start day) and +1.9% against the rupee, so a -8.0% month in US dollars was -7.3% in S$ and -6.5% in rupees. The same holds from 2016 on (+0.9% vs S$ and +1.1% vs rupees). It is a same-window fact, not a forecast.
How much do currency moves change returns on Asian stock markets?: Year to date as of 6 Nov 2026: Korea KOSPI is +20.1% in local currency and +26.4% in S$ (currency effect +5.3%); Taiwan TAIEX is +37.1% in local currency and +30.8% in S$ (currency effect -4.6%); India Nifty 50 is -4.2% in local currency and -8.6% in S$ (currency effect -4.5%); China Shanghai Composite is -8.1% in local currency and -3.9% in S$ (currency effect +4.5%). A market's S$ return is (1 + local return) × (1 + currency move) − 1, so the local return and the currency move compound.
What does it cost to hedge US-dollar assets back to Singapore dollars?: About 2.3% a year as of 6 Nov 2026: the US 3-month bill yields 4.11% and Singapore's 1.84%, so hedging costs that gap (roughly S$2,266 per S$100,000 a year). Bank forward spreads come on top; this is an arithmetic approximation, not a quote.

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