Stock markets
Korea's 2026 stock plunge came after its biggest boom in decades, not a global panic
After rising 209% in two years, the most since December 1988, Korean share prices fell 21.6% by August in monthly averages, and again in October; the BIS ties the fall to early September to exposure to AI-linked firms and turmoil in a few leveraged vehicles, crowded into two chipmakers, while world markets stayed calm and news mood was upbeat at the peak.
Key numbers
209%Source 1
Rise in Korean share prices in the two years to June 2026 (OECD monthly average), the most since December 1988; the record, 282%, came in the two years to February 1988
20.7Source 2
Highest VIX close during Korea's 2026 fall, against 79.1 during the 2007–08 fall and 82.7 in 2020
108.1Source 3
Bank of Korea news sentiment on 22 Jun 2026, the day stocks peaked; readings above the long-run average mean upbeat news
Key findings
- Korea's twelve sharp falls since 1997 had no single cause: in ten of the eleven before 2026 the VIX, Wall Street's fear gauge, closed at about double its median or more, but in 2004 it never closed above 20.0, and in 2026 it peaked at 20.7 and US shares rose 4.8% from June to AugustSource 1Source 2Source 4.
- In all eight falls since 2007, news mood about the economy was above its long-run average on the day stocks peaked, but in each it had also dipped below that average in the year before; in 2026 it went from 87.5 on 9 Mar 2026 to 108.1 at the peak and 85.0 on 18 OctSource 3.
- Korean share prices rose 209% in the two years to June 2026, the most since December 1988, as bets piled onto two chipmakers; the fall coincided with a global slide in tech shares that the BIS dates to the end of June, while Korea's chip export values, after a dip in July, were well above their June level by SeptemberSource 1Source 5Source 6.
- The fall of 21.6% to August took two months. Timed from each fall's high month to its low month, only 2020's 19.0%, also in two months, came close to that pace. Every earlier fall of a fifth or more in monthly averages took at least 11 months. Steeper two-month drops came inside the 1997–98, 2000–01 and 2007–08 falls. That speed fits selling forced by leveraged funds, but 2020's came in a global panic, and the data we can use include no daily figures on forced salesSource 1Source 5.
- Recoveries took from two months to 72 months; most followed rate cuts, but the 2007 high was regained in 2011 as rates rose, and in 2026 the Bank of Korea raised its rate 0.50 pp during the fall; a model can gauge fragility, not date a crashSource 1Source 7Source 8Source 9.
The question
The question we answered
What built up before Korea's big stock-market falls, what set them off and deepened them, what came before the market steadied, and how could a model of these stages be designed and tested on past falls, including the 2026 fall?
What we looked at
We looked at what came before, during and after Korea's big stock-market falls, from the 1997 crisis to the fall under way since June 2026, using market data and research by central banks and economists.
A note on the question. The data do not show one root cause: the 1997 fall came with a currency collapse, 2008 and 2020 with global panic, and the 2026 fall with a huge run-up and leveraged bets on two chipmakers while world markets stayed calm, as they had in 2004. None of the surveys we could use asks whether people think stocks are overpriced, so we look at mood about the economy instead, and we split 'panic selling' into selling forced by borrowing or fund rules and herd behaviour, including by foreign investors in 1997; foreign flows themselves cannot be shown.
Every fall had its own mix of causes
Korea's twelve sharp falls since 1997 share no single cause. Most came with a jump in Wall Street's fear gauge to about double its usual level. Two came with a collapse of the won, when the dollar rose by more than half against it, and two, in 2004 and 2026, with neitherSource 1Source 2Source 10.
It helps to picture four stages: the fuel that built up, the spark that set a fall off, the wind that made it worse, and what came before calm. What follows shows timing, not proof of cause.
We picked the falls on daily closes of the KOSPI: every fall of a fifth or more since 1997, except three short swings in the rebound from the 1998 low. The slide from July 2024 to April 2025, a fall of a fifth on daily closes, appears as two shorter falls, July–August 2024 and February–April 2025. The long slide from 2018 to 2020 counts as two falls, split at its August 2019 low.
To measure them we use the OECD's monthly average of Korean share prices, which smooths daily swings and so makes falls look shallower, most of all falls that happen within weeksSource 1. The deepest were 59.2% in 1997–98 and 48.8% in the 2000–01 IT bust; 2007–08 fell 46.4%Source 1. The 2026 fall, 21.6% from June to August so far, ranks mid-sized for now in monthly averages: six of the eleven earlier falls were deeperSource 1. On daily closes, though, it is already deeper than the 2018–19, 2020 and 2021–22 falls; only the 1997–98, 2000–01, 2002–03 and 2007–08 falls went deeper.
In ten of the eleven earlier falls the VIX, an index of how much US shares are expected to swing, closed at about double its median of 18.1 or moreSource 2. It reached 79.1 during the 2007–08 fall and 82.7 in 2020Source 2. The exception was 2004: Korean share prices fell 17.7% from April to July in monthly averages, yet the VIX never closed above 20.0, US shares slipped 2.4% and won per dollar rose only 0.5%Source 1Source 2Source 4Source 10. The won collapsed twice, when the dollar rose by more than half against it: by 54.3% in 1997–98 and 52.9% in 2007–08Source 10.
Some sparks were regional. US shares rose 10.8% during the 1997–98 fall, an Asian crisis rather than a global oneSource 4. Korea's political shock on 3 Dec 2024 came with a VIX of only 13.3; the fall in our table began in February 2025, and its VIX high, 52.3, came on 8 Apr 2025Source 2.
Like 2004, the 2026 fall came without a global panic: the VIX closed no higher than 20.7, US shares rose 4.8% from June to August, and won per dollar fell 8.3%, a stronger wonSource 2Source 4Source 10. Apart from swings in the flows themselves, global fear and US share returns explain far more of the money moving into and out of emerging-market funds than domestic factors do, in an IMF study that does not include KoreaSource 11. Yet from June to early September 2026 emerging-market shares as a group gainedSource 5. The table below sets the twelve falls side by side.
Figure 1
In ten of Korea's eleven big stock falls before 2026 the VIX closed at 36 or higher; in 2004 and in 2026 it stayed near 20
Korea's twelve big stock falls since 1997, side by sideChanges in % from each fall's high month to its low month (monthly averages); two-year run-up in % to the high month; VIX: highest daily close
| Fall | Korea, % | VIX high | US, % | Won/$, % | Run-up, % | High to low |
|---|---|---|---|---|---|---|
| 2026 | −21.6 | 20.7 | 4.8 | −8.3 | 209 | Jun–Aug 2026, so far |
| Feb–Apr 2025 | −4.3 | 52.3 | −5.0 | −1.3 | 7 | Mar–Apr 2025 |
| Jul–Aug 2024 | −7.8 | 38.6 | 4.4 | −3.7 | 19 | Jul–Sep 2024 |
| 2021–22 | −31.7 | 36.5 | −15.0 | 27.0 | 55 | Jun 2021–Oct 2022 |
| 2020 Covid | −19.0 | 82.7 | −23.3 | 4.3 | −12 | Jan–Mar 2020 |
| 2018–19 | −22.8 | 37.3 | −4.8 | 13.6 | 33 | Jan 2018–Aug 2019 |
| 2011 | −16.7 | 48.0 | −16.1 | 3.6 | 63 | Apr–Sep 2011 |
| 2007–08 Global crisis | −46.4 | 79.1 | −45.6 | 52.9 | 68 | Oct 2007–Nov 2008 |
| 2004 | −17.7 | 20.0 | −2.4 | 0.5 | 1 | Apr–Jul 2004 |
| 2002–03 | −38.5 | 45.1 | −24.0 | −6.1 | 14 | Apr 2002–Mar 2003 |
| 2000–01 IT bust | −48.8 | 41.8 | −13.6 | 13.8 | 152 | Dec 1999–Sep 2001 |
| 1997–98 Asian crisis | −59.2 | 38.2 | 10.8 | 54.3 | −13 | Jun 1997–Sep 1998 |
How to read this chart. One row per fall, newest first. 'Korea' and 'US' are changes in share prices, 'Run-up' the rise in Korean share prices in the two years before the high month. Read across: how far Korean share prices fell, how high Wall Street's fear gauge (the VIX) went, what US shares and the won did over the same months, and how much Korean share prices had risen in the two years before. A positive won change means a weaker won; a negative one, a stronger won.
The falls were picked on KOSPI daily closes: every fall of a fifth or more since 1997 except three short swings in the rebound from the 1998 low. The slide from July 2024 to April 2025, a fall of a fifth on daily closes, appears as two shorter falls, July–August 2024 and February–April 2025. The long slide from 2018 to 2020 counts as two falls, split at its August 2019 low. Korean and US share prices are OECD monthly averages, which smooth daily highs and lows, so the falls shown are shallower than between daily closes, most of all for falls that happen within weeks. The 2026 row stops at the lowest month so far (August 2026); prices fell again in October.
In monthly averages the 2024 slide ran from July to December 2024 (−13.1%). The Feb–Apr 2025 row shows only the March–April 2025 dip in monthly averages; its VIX high, 52.3, came on 8 Apr 2025. Korea's political shock of 3 Dec 2024 came with a VIX of only 13.3.
VIX highs are the highest daily close between the KOSPI's daily peak and low in each fall (for 2026, 22 Jun to 15 Oct 2026). The won is the New York noon rate, monthly averages. Valuations, margin loans and foreign selling are not shown: their producers' terms for republication are not cleared.
Source: OECD, Cboe and Federal Reserve Board via FRED, Federal Reserve Bank of St. Louis; datasteg calculation · Data to 16 Oct 2026Source 1Source 2Source 4Source 10
About this chart
- Definition
- OECD share price indices for Korea and the United States (all shares, monthly averages of daily prices, 2015 = 100); Cboe Volatility Index (VIX), daily close; won per US dollar, New York noon buying rate (Federal Reserve H.10), averaged by month.
- Calculation
- High and low months: highest and lowest monthly average in a fixed window around each fall. Changes = (low month ÷ high month − 1) × 100. Two-year run-up = (high month ÷ 24 months earlier − 1) × 100. VIX = highest daily close between the KOSPI's daily peak and low.
- Provider
- OECD, Cboe and Federal Reserve Board via FRED
- Series
- SPASTT01KRM661N, VIXCLS, SPASTT01USM661N, DEXKOUS
- Period
- Jun 1995 – 15 Oct 2026
- Last observation
- 16 Oct 2026
- Retrieved
- 19 Oct 2026
- Licence
- FRED: OECD and Cboe series copyrighted, citation required; DEXKOUS public domain, citation requested
- Sources
- Korean share prices (OECD index, monthly average), US stock market fear gauge (VIX), US share prices (OECD index, 2015=100), Won per US dollar (New York noon rate)
The mood was upbeat at the top
None of the data we could use measures whether people felt a bubble: no survey among them asks whether people think stocks are overpriced. News mood about the economy, the closest measure, swings widely. In the year before each peak it dipped below its long-run average at some point, yet on each peak day it was above itSource 3.
The Bank of Korea's news sentiment index reads the tone of economic news each day. In all eight falls since 2007 it was above its long-run average on the day stocks peaked. In the year before each peak it had been higher at some point, and also lower: every time it fell to 93.0 or below, and before the 2020 peak to 76.5Source 3. In 2026, mood went from 125.7 on 3 Nov 2025 down to 87.5 on 9 Mar 2026, then back up to 108.1 on 22 Jun 2026, the day stocks peakedSource 3.
In each fall, counting up to three months after the low, mood sank below its dip of the year before, sometimes far below. In 2024 it did so only after stocks had hit their low, and in 2026 only after their lowest close so far, in mid-October. In the global financial crisis it fell to 57.7 on 8 Oct 2008, against 79.7 in the year before the peakSource 3.
In 2026 the gap is small: mood reached 85.0 on 18 Oct, its lowest since 11 Apr 2025, against 87.5 in MarchSource 3. The chart below compares mood on each peak day with its lowest reading from the peak to three months after the low.
Figure 2
In all eight falls since 2007, news mood was above its long-run average of 100 on the day stocks peaked, after dipping below it in the year before; its lowest readings came during or just after each fall
News mood on the day stocks peaked, and its low during and just after each fallBank of Korea news sentiment index, daily, 100 = long-run average; eight falls, Oct 2007–Oct 2026
How to read this chart. Each row is one fall: the hollow dot is news mood on the day stocks peaked, the filled dot its lowest reading from the peak to three months after the low. Right of 100 is more upbeat than usual.
Peak days are the KOSPI's daily peaks: 31 Oct 2007, 2 May 2011, 29 Jan 2018, 22 Jan 2020, 6 Jul 2021, 11 Jul 2024, 19 Feb 2025 and 22 Jun 2026. The rows for 2024 and Feb–Apr 2025 are the two pieces of the slide from July 2024 to April 2025, as in the table of falls.
The index starts in 2005, so falls before 2007 are not shown. The 2026 low (85.0, 18 Oct 2026) is the latest reading and may not be the low of this fall. The index measures the tone of economic news, not views on stock prices.
The chart shows only the peak day and the low after it, but mood swung widely in the year before too. In all eight falls, it had been higher at some point in the 12 months before the stock peak than on the peak day (for 2026, 125.7 on 3 Nov 2025), and it had also dipped below 100, each time to 93.0 or lower. The low after each peak was lower still, though only a little in 2024 (81.6 against 84.7 on 24 Oct 2023) and 2026 (85.0 against 87.5 on 9 Mar 2026). These prior highs and lows are in the table view. Consumer sentiment, a monthly survey, is in the text.
Source: Bank of Korea, ECOS; datasteg calculation · Data to 18 Oct 2026Source 3
About this chart
- Definition
- News sentiment index (experimental statistic): a daily reading of the tone of economic news articles, scaled so that 100 is the long-run average.
- Calculation
- Prior high and low: the maximum and minimum in the 12 months before the peak day. Peak day: the value on the KOSPI's daily peak. Lowest: the minimum from the peak day to three months after the KOSPI's daily low (for 2026, to 18 Oct 2026).
- Provider
- Bank of Korea, ECOS
- Series
- 523Y001/D/A001
- Period
- 10 Jul 2007 – 18 Oct 2026
- Last observation
- 18 Oct 2026
- Retrieved
- 19 Oct 2026
- Licence
- ECOS Open API terms: reuse allowed with attribution
- Sources
- Bank of Korea news sentiment index, daily
The consumer sentiment index, a monthly survey of households, fell to 67.7 in December 2008 but barely moved during the 2026 fall, with a low of 104.5 in August 2026Source 12.
Sensing a crash is common, so it is no warning by itself: US investors in long-running surveys put the chance of a crash at more than ten times its historical frequencySource 13. In an IMF study, fund flows appear to have peaked just before past large falls in asset prices, a quantity worth watching alongside moodSource 9. In Korea's data, mood was above average on each peak day; its lowest readings came during or just after the falls, though in 2024 and 2026 only a little below its dips of the year before.
2026: a run-up resting on two chipmakers
Before the 2026 fall, Korean share prices had their biggest two-year rise since the boom of 1987–89, resting on two chip stocks and leveraged betsSource 1Source 5. The fall came with a repricing of chip shares, not a fall in Korea's chip exportsSource 5Source 6.
Prices rose 209% in the two years to June 2026, the most since December 1988 but short of the record: 282% in the two years to February 1988Source 1. In data back to 1981, only two earlier run-ups doubled prices in two years: the boom of 1987–89, and the run-up of 1998–99, when prices rose 152% in the two years to December 1999Source 1. Each ended in a fall of almost half: 48.6% from March 1989 to August 1992, though the first took more than three years, and 48.8% in the IT bust that followedSource 1. Two cases are a reason for caution, not a rule.
Shares of Samsung Electronics and SK Hynix, Korea's dominant memory chipmakers, more than tripled in the first half of 2026, and the wider market followed themSource 5. Bets piled up on top: assets of leveraged products on the major memory-chip stocks, Samsung, SK Hynix and the US firm Micron, rose from under a hundred million dollars in mid-2025 to more than thirty-eight billion in June 2026Source 5. In June the Bank of Korea Governor said the surge had come with "a significant increase in leveraged equity investment"Source 14.
Research shows why such a run-up matters but cannot time a fall. In US industries, the chance of a fall of two-fifths or more within two years rises from one in five to more than half as a two-year gain over the market goes from fifty to a hundred per centSource 8. Yet in run-ups that did crash, prices rose about another thirty per cent on average before the peakSource 8.
The fall coincided with a global turn in tech stocks, which the BIS dates to the end of June, days after Korean shares peaked on 22 June. Tech stocks began to falter amid the strain of a prolonged conflict in Iran, and by early September the price-earnings ratios of US-listed semiconductor makers had fallen by two-fifthsSource 5. The BIS says Korea plunged furthest because of its exposure to AI-linked firms and turmoil in a few leveraged investment vehiclesSource 5. The BIS review covers June to early September; no study we found covers the further fall to mid-October.
The chart below shows that chip export values, after a dip in July, were well above their June level by September and 268% up on a year earlier, while Korean share prices were 19.0% below JuneSource 1Source 6. The fall came with a repricing of chip shares, not a fall in chip exports.
Figure 3
Korean share prices rose to 3.5 times their December 2024 level by June 2026, then fell 21.6% by August, while chip export values and US share prices ended September above their June level
Korean share prices, chip export values and US share prices, 2024–26Index, June 2026 = 100, monthly, Jan 2024–Sep 2026
How to read this chart. All three lines are set to 100 in June 2026, the month Korean share prices peaked; above 100 means higher than then. The shaded months are the 2026 fall so far.
Korean and US share prices are OECD monthly averages, not daily closes or the KOSPI itself. Chip exports are export values in US dollars (Bank of Korea export value index for semiconductors), not company earnings or volumes; the series swings from month to month.
The latest month is September 2026; Korean prices fell again in October. Samsung Electronics and SK Hynix share prices, and a chip-sector share index, are not in the article's publishable data.
Source: OECD via FRED, Federal Reserve Bank of St. Louis; Bank of Korea, ECOS; BIS; datasteg calculation · Data to Sep 2026Source 1Source 4Source 5Source 6
About this chart
- Definition
- OECD share price indices for Korea and the United States (monthly averages of daily prices); Bank of Korea export value index for semiconductors (US dollars, 2020 = 100). Each rebased to June 2026 = 100.
- Calculation
- Each series ÷ its June 2026 value × 100. Annotation: the BIS dates the faltering of global tech stocks to the end of June 2026.
- Provider
- OECD via FRED; Bank of Korea, ECOS
- Series
- SPASTT01KRM661N, 403Y001/M/3091AA, SPASTT01USM661N
- Period
- Jan 2024 – Sep 2026
- Last observation
- Sep 2026
- Retrieved
- 19 Oct 2026
- Licence
- FRED (OECD): copyrighted, citation required; ECOS Open API terms: reuse allowed with attribution
- Sources
- Korean share prices (OECD index, monthly average), Semiconductor export value index (US dollar basis), monthly, US share prices (OECD index, 2015=100), Yields climb, yet risk appetite holds firm
Forced selling or panic? The data cannot tell
The 2026 fall was among the fastest in the dataSource 1. Some of what looks like panic may be selling that borrowing or fund rules force on investorsSource 5. The data we can use include no daily figures on forced sales, so they cannot tell the two apart.
Prices fell 21.6% in two months, by August. July 2026 alone was 17.6% below JuneSource 1. Timed from each fall's high month to its low month, only 2020's 19.0%, also in two months, came close to that paceSource 1.
Every earlier fall of a fifth or more in monthly averages took at least 11 months to reach its lowSource 1. Steeper two-month drops did come inside the 1997–98, 2000–01 and 2007–08 fallsSource 1.
When the stock behind a leveraged ETF falls, the fund's leverage rises above its target, so it must sellSource 5. For SK Hynix, the trading such funds needed after a ten per cent move reached almost five billion dollars by the June peakSource 5. Against daily turnover of under ten billion, the BIS author estimates from a model, not observed trades, that this could add two to four points to such a moveSource 5.
Hedging autocallable notes can add large trades near their barrier pricesSource 5. The author stresses concentration: "a handful of instruments referencing two stocks that dominate an index, in a market where retail participation and leverage are both unusually high"Source 5.
Borrowed money works the same way, through the margin call. In China's 2015 crash, margin investors sold heavily as their leverage neared its limit, and the stocks they held fell abnormally and later recovered, the mark of a fire saleSource 15. The authors add that the market might have corrected eventually even without that triggerSource 15.
Herding, investors copying each other, is the other suspect. Before Korea's 1997 crisis foreign investors chased recent returns, but over a day or a few days the authors find nothing that singles them out as destabilisingSource 16. Herding measures also cannot tell copying from reactions to the same newsSource 17.
A fast fall need not be irrational: in one well-known model, when investors expecting bad news cannot sell short, their information comes out during declinesSource 18. The speed of 2026 fits forced selling but does not prove it: 2020 was nearly as fast, in a global panic.
What came before the market steadied
Recoveries took from two months to 72 months. Most followed rate cuts, but the 2007 high was regained in 2011 as rates rose, and the 2022 low turned while the rate was still risingSource 1Source 7.
Prices took seven months to regain their earlier high after the 2020 peak, 39 months after 2007 and 72 months after 2011Source 1. Three months after the low, the 2020 market had regained 83% of its fall, the 2008 market only 7%Source 1.
The Bank of Korea cut its base rate during or near several falls' lows; the first cuts came on 8 Feb 2001, 9 Oct 2008 and 17 Mar 2020Source 7. But the rate rose 2.00 pp from the 2021 peak to the 2022 low, and that market still turned, if slowlySource 1Source 7. Cuts are neither the only route to calm nor a guarantee of it.
In June 2026 the Governor said the Bank needed to raise its rate before it was too late, to keep prices stableSource 14. It did so on 16 Jul 2026 and 27 Aug 2026. By 15 Oct the rate was 0.50 pp higher than at the June peakSource 7. The chart below shows the base rate through each fall.
Figure 4
The Bank of Korea raised its rate during the 2002, 2011, 2021–22 and 2026 falls; in the 2000–01, 2007–08 and 2018–19 falls it raised it first and cut later, and in 2020 it cut near the low
Bank of Korea base rate and Korea's stock falls since 1999% a year, month-end, May 1999–Oct 2026; shaded: stock falls
How to read this chart. The line is the Bank of Korea's policy rate at the end of each month; shaded periods are Korean stock falls, from the market's daily peak to its low.
Shaded: IT bust (Jan 2000–Sep 2001), 2002–03 (Apr 2002–Mar 2003), 2004 (Apr–Aug 2004), global financial crisis (Oct 2007–Oct 2008), 2011 (May–Sep 2011), 2018–19 (Jan 2018–Aug 2019), Covid (Jan–Mar 2020), 2021–22 (Jul 2021–Sep 2022) and 2026 (Jun 2026 to the 15 Oct low so far). The shading uses daily peak and low dates, which differ by a month or so from the monthly windows in the table of falls.
The series starts in May 1999, so the 1997–98 fall is not shown. Short falls (Jul–Aug 2024, Feb–Apr 2025) are left unshaded to keep the chart legible; the rate was cut after the 2024 fall (11 Oct 2024) and during the 2025 fall (25 Feb 2025). In 2004 the rate held through the fall and was cut ten days after the low (12 Aug 2004); in 2018–19 it was raised (30 Nov 2018) and then cut (18 Jul 2019), 20 days before the low. Month-end values hide the exact day of each change: rises inside the shaded falls came on 10 Feb and 5 Oct 2000, 7 May 2002 and 7 Aug 2008; first cuts on 8 Feb 2001, 9 Oct 2008 and 17 Mar 2020; the 2026 rises on 16 Jul and 27 Aug.
The chart shows timing only: it does not show that rate cuts ended falls or that rate rises deepened them.
Source: Bank of Korea, ECOS; datasteg calculation · Data to 19 Oct 2026Source 7Source 14
About this chart
- Definition
- Bank of Korea base rate (its policy rate), % a year.
- Calculation
- Value on the last day of each month in the daily series (19 Oct for October 2026). Annotation: on 12 Jun 2026 the Governor said the Bank needed to raise the base rate before it was too late.
- Provider
- Bank of Korea, ECOS
- Series
- 722Y001/D/0101000
- Period
- May 1999 – 19 Oct 2026
- Last observation
- 19 Oct 2026
- Retrieved
- 19 Oct 2026
- Licence
- ECOS Open API terms: reuse allowed with attribution
- Sources
- Bank of Korea base rate, Hyun Song Shin: Speech - 76th Anniversary of the Bank of Korea
How a crash-risk model for Korea could work
A useful model would estimate how fragile the market is, as a probability or a state, from measures of fuel, spark and wind, tested on Korea's twelve falls; it cannot date the next crashSource 8Source 9.
For the fuel, the US industry study turns a two-year run-up into a crash probability, and rising volatility and share issuance set apart the run-ups that crashedSource 8. An IMF framework adds quantities, such as trading and fund flows, to pricesSource 9. The table below sets out the design.
Figure 5
A crash-risk model for Korea would combine fuel, spark and wind measures into a probability, but much of the data it needs sits with the Korea Exchange and KOFIA or is missing from the data this article can use
A design for a Korean crash-risk modelWhat each block would measure, which public data this article uses, what is missing, and the research each block borrows from
| Block | Measure | Data used here | Missing | From research |
|---|---|---|---|---|
| Fuel | Run-up, valuation, leverage, crowding | Two-year rise; chip exports; mood | Valuations, margin loans, leveraged funds | Crash odds by run-up (NBER); prices plus quantities (IMF) |
| Spark | Global fear, US shares, the won | VIX; US shares; won per dollar | Chip-sector share index | Global drivers of emerging-market flows (IMF) |
| Wind | Forced and foreign selling, herding, speed | Speed of each fall | Foreign flows, forced sales, accounts | Fund trades vs turnover (BIS); margin-call distance (NBER); herding (OECD) |
| Before calm | Rate changes, official buying, end of forced selling | Base rate; months to recover | Investor deposits; policy dates | Fire sales reverse (NBER); bank guarantees (World Bank); short-sale bans (NY Fed) |
| Output | Crash probability or market state | Twelve falls to test on | Implied volatility (VKOSPI) | Lopsided returns (NBER); missed falls vs false alarms (IMF) |
How to read this chart. One row per block of the model, in the order a fall unfolds: what built up (fuel), what set it off (spark), what made it worse (wind) and what came before calm. The last row is what the model would produce and how to test it. The full list of missing data is in the notes.
A design, not an estimated model: no crash or bubble model in the evidence has been tested on Korean share prices. The method column names the institution behind each study; the studies are in the references.
Missing data in full. Not cleared for republication: daily index closes, valuations, trading and foreign net purchases (Korea Exchange); margin loans and investor deposits (KOFIA). Known only from BIS estimates: leveraged-product assets and option positions. Not in the run's data: daily forced sales, flows by investor type, account-level data, Korea's implied-volatility index (VKOSPI), a publishable chip-sector share index, and dates of short-selling bans and stabilisation funds.
Source: research cited in the references; datasteg design · Data to 19 Oct 2026Source 1Source 2Source 3Source 4Source 5Source 6Source 7Source 8Source 9Source 10Source 11Source 12Source 15Source 17Source 18Source 20Source 21
About this chart
- Definition
- Blocks follow the article's four stages of a fall plus the model's output; data columns list the series this article uses and those it could not use.
- Calculation
- No calculation: a design table.
- Provider
- datasteg design from published research; data from OECD, Cboe and Federal Reserve Board via FRED and Bank of Korea, ECOS
- Series
- SPASTT01KRM661N, VIXCLS, SPASTT01USM661N, DEXKOUS, 523Y001/D/A001, 511Y002/M/FME/99988, 722Y001/D/0101000, 403Y001/M/3091AA
- Period
- Jan 1981 – 19 Oct 2026
- Last observation
- 19 Oct 2026
- Retrieved
- 19 Oct 2026
- Licence
- FRED: OECD and Cboe series copyrighted, citation required; DEXKOUS public domain; ECOS Open API terms: reuse allowed with attribution
- Sources
- Korean share prices (OECD index, monthly average), US stock market fear gauge (VIX), US share prices (OECD index, 2015=100), Won per US dollar (New York noon rate), Bank of Korea news sentiment index, daily, Composite consumer sentiment index (CCSI), monthly, Bank of Korea base rate, Semiconductor export value index (US dollar basis), monthly, Bubbles for Fama, Identifying Speculative Bubbles: A Two-Pillar Surveillance Framework, Portfolio Flows, Global Risk Aversion and Asset Prices in Emerging Markets, Yields climb, yet risk appetite holds firm, Leverage-Induced Fire Sales and Stock Market Crashes, Foreign Portfolio Investors Before and during a Crisis, Stock market responses to bank restructuring policies during the East Asian crisis, Market Declines: Is Banning Short Selling the Solution?, Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices
For the spark, it would track the won, global fear and US share returns. In an IMF study that does not include Korea, the last two explain far more of the money moving into and out of emerging-market funds than domestic factors do, apart from swings in the flows themselvesSource 11. For the wind, it would measure borrowing, leveraged-fund trades against turnover and one-sided option betsSource 5. Korea's own record is thin: only two earlier run-ups doubled prices in two years, too few cases to estimate from Korea aloneSource 1.
The output would be a probability of a large fall, a forecast of how lopsided returns will be, or a state such as calm, fragile, falling or recoveringSource 18. It would be fitted on some falls and checked on others, knowing that any warning threshold trades missed falls against false alarmsSource 9.
Much of the data such a model needs is not cleared for republication, known only from BIS estimates, or not in the data this article can use, as the table shows. And as an IMF paper puts it, "bubbles can only be identified with complete certainty ex-post"Source 9.
Terms in this article
- VIX
- An index, worked out from option prices, of how much the US stock market is expected to swing over the coming month. It is widely used as a gauge of investors' fear.Here: its highest daily close during each Korean stock fall, as a sign of whether fear came from abroad.
- news sentiment index
- A daily Bank of Korea index of how upbeat or gloomy economic news articles are, worked out from their wording. Readings above its long-run average mean news is more upbeat than usual.Here: read on the day Korean stocks peaked and at its lowest during each fall since 2007.
- consumer sentiment index
- A monthly Bank of Korea index, built from a household survey, of how people see the economy, their own finances and prices. Readings above its long-run average mean households are more optimistic than usual.
- price-earnings ratio
- A company's share price divided by its earnings per share, or a market's total value divided by its total profits. A high ratio means investors pay more for each unit of profit, often because they expect profits to grow.Here: the ratios of US-listed semiconductor makers, which fell by two-fifths from June to early September 2026, according to the BIS.
- leveraged ETF
- An exchange-traded fund that aims to deliver a multiple, such as twice, of the daily move in a stock or index, using borrowed money or derivatives. To keep that multiple it has to buy after prices rise and sell after they fall.Here: funds tied to single chip stocks, mainly SK Hynix and Samsung Electronics, in 2026.
- autocallable
- A structured note linked to a stock or index that repays early with a fixed return if the price is at or above a set level on check dates, and can lose the investor money if the price falls below a lower barrier. The banks that sell them hedge by trading the linked shares.
- margin call
- A broker's demand for more cash or collateral when shares bought with borrowed money have fallen too far in value. If the investor cannot pay, the broker sells the shares, a forced sale.
- fire sale
- Selling assets quickly, below what they are worth, because the seller is forced to, for example to repay debt or meet margin calls, rather than because the news about the assets has changed. Prices hit this way tend to recover once the selling stops.
- herding
- Investors copying one another's trades rather than acting on their own information. It can push prices further than news justifies, though measured herding can also reflect many investors reacting to the same news.
- base rate
- The policy interest rate a central bank sets to steer borrowing costs across the economy. In Korea it is the Bank of Korea's Base Rate.
References
Research
- 5
Abbassi, Cornelli, Lombardi, Schrimpf, Sushko; Box B by Todorov (2026). Yields climb, yet risk appetite holds firm. BIS Quarterly Review September 2026. BIS
Read the source ↗PDF ↗Cited in: ↑ Key findings, ↑ Every fall had its own mix of causes, ↑ 2026: a run-up resting on two chipmakers, ↑ Forced selling or panic? The data cannot tell, ↑ How a crash-risk model for Korea could work, ↑ Our read
- 8
Greenwood, R., Shleifer, A., You, Y. (2017). Bubbles for Fama. NBER Working Papers w23191. NBER
Read the source ↗PDF ↗Cited in: ↑ Key findings, ↑ 2026: a run-up resting on two chipmakers, ↑ How a crash-risk model for Korea could work
- 9
Jones, B. (2014). Identifying Speculative Bubbles: A Two-Pillar Surveillance Framework. IMF Working Papers WP/14/208. IMF
Read the source ↗PDF ↗Cited in: ↑ Key findings, ↑ The mood was upbeat at the top, ↑ How a crash-risk model for Korea could work
- 11
Ananchotikul, N., Zhang, L. (2014). Portfolio Flows, Global Risk Aversion and Asset Prices in Emerging Markets. IMF Working Papers 2014/156. IMF
Read the source ↗PDF ↗Cited in: ↑ Every fall had its own mix of causes, ↑ How a crash-risk model for Korea could work
- 13
Goetzmann, W. N., Kim, D., Shiller, R. J. (2024). Emotions and Subjective Crash Beliefs. NBER Working Papers w32589. NBER
Read the source ↗PDF ↗Cited in: ↑ The mood was upbeat at the top
- 15
Bian, J., He, Z., Shue, K., Zhou, H. (2018). Leverage-Induced Fire Sales and Stock Market Crashes. NBER Working Papers w25040. NBER
Read the source ↗PDF ↗Cited in: ↑ Forced selling or panic? The data cannot tell, ↑ How a crash-risk model for Korea could work
- 16
Choe, H., Kho, B.-C., Stulz, R. M. (1998). Do Foreign Investors Destabilize Stock Markets? The Korean Experience in 1997. NBER Working Papers w6661. NBER
Read the source ↗PDF ↗Cited in: ↑ Forced selling or panic? The data cannot tell
- 17
Kim, W., Wei, S.-J. (1999). Foreign Portfolio Investors Before and during a Crisis. OECD Economics Department Working Papers 210. OECD
Read the source ↗PDF ↗Cited in: ↑ Forced selling or panic? The data cannot tell, ↑ How a crash-risk model for Korea could work
- 18
Chen, J., Hong, H., Stein, J. C. (2000). Forecasting Crashes: Trading Volume, Past Returns and Conditional Skewness in Stock Prices. NBER Working Papers w7687. NBER
Read the source ↗PDF ↗Cited in: ↑ Forced selling or panic? The data cannot tell, ↑ How a crash-risk model for Korea could work
- 19
Aquilina, M., Lombardi, M., Schrimpf, A., Sushko, V. (2024). The market turbulence and carry trade unwind of August 2024. BIS Bulletin 90. BIS
Read the source ↗Cited in: ↑ What came before the market steadied
- 20
Battalio, R., Mehran, H., Schultz, P. (2011). Market Declines: Is Banning Short Selling the Solution?. Federal Reserve Bank of New York Staff Reports 518. Federal Reserve Bank of New York
Read the source ↗Cited in: ↑ What came before the market steadied, ↑ How a crash-risk model for Korea could work
- 21
Klingebiel, D., Kroszner, R., Laeven, L. et al. (2001). Stock market responses to bank restructuring policies during the East Asian crisis. Policy Research Working Papers WPS2571. World Bank
Read the source ↗PDF ↗Cited in: ↑ How a crash-risk model for Korea could work
Speeches and statements
- 14
Shin, H. S. (2026). Hyun Song Shin: Speech - 76th Anniversary of the Bank of Korea. BIS central bankers' speeches. Bank of Korea
Read the source ↗PDF ↗Cited in: ↑ 2026: a run-up resting on two chipmakers, ↑ What came before the market steadied
Data
- 1
FRED, Federal Reserve Bank of St. Louis. Korean share prices (OECD index, monthly average). SPASTT01KRM661N. Retrieved 20 Oct 2026.
Finding the series: The link opens the FRED series SPASTT01KRM661N directly. Use “Edit Graph” to change the dates or units, and “Download” for the data.
Data source ↗Cited in: ↑ Key numbers, ↑ Key findings, ↑ Every fall had its own mix of causes, ↑ 2026: a run-up resting on two chipmakers, ↑ Forced selling or panic? The data cannot tell, ↑ What came before the market steadied, ↑ How a crash-risk model for Korea could work, ↑ Our read
- 2
FRED, Federal Reserve Bank of St. Louis. US stock market fear gauge (VIX). VIXCLS. Retrieved 19 Oct 2026.
Finding the series: The link opens the FRED series VIXCLS directly. Use “Edit Graph” to change the dates or units, and “Download” for the data.
Data source ↗Cited in: ↑ Key numbers, ↑ Key findings, ↑ Every fall had its own mix of causes, ↑ What came before the market steadied, ↑ How a crash-risk model for Korea could work, ↑ Our read
- 3
Bank of Korea, ECOS. Bank of Korea news sentiment index, daily. 523Y001/D/A001. Retrieved 19 Oct 2026.
Finding the series: On ECOS (ecos.bok.or.kr), open 통계검색 (Statistics search) and type the table name “뉴스심리지수(실험적 통계)” or its code 523Y001 in the search box, or follow the statistics list 6. 심리지수 > 6.4. 뉴스심리지수(실험적 통계). In the table, select 계정항목: 뉴스심리지수. Set the cycle (주기) to daily, choose the period, and click 조회 (Search).
Data source ↗Cited in: ↑ Key numbers, ↑ Key findings, ↑ The mood was upbeat at the top, ↑ How a crash-risk model for Korea could work, ↑ Our read
- 4
FRED, Federal Reserve Bank of St. Louis. US share prices (OECD index, 2015=100). SPASTT01USM661N. Retrieved 19 Oct 2026.
Finding the series: The link opens the FRED series SPASTT01USM661N directly. Use “Edit Graph” to change the dates or units, and “Download” for the data.
Data source ↗Cited in: ↑ Key findings, ↑ Every fall had its own mix of causes, ↑ 2026: a run-up resting on two chipmakers, ↑ How a crash-risk model for Korea could work
- 6
Bank of Korea, ECOS. Semiconductor export value index (US dollar basis), monthly. 403Y001/M/3091AA. Retrieved 19 Oct 2026.
Finding the series: On ECOS (ecos.bok.or.kr), open 통계검색 (Statistics search) and type the table name “수출금액지수” or its code 403Y001 in the search box, or follow the statistics list 3. 환율/통관수출입/외환보유액 > 3.3. 무역지수/교역조건지수(2020=100) > 3.3.1. 수출입 금액/물량지수 > 3.3.1.1. 수출 금액/물량지수 > 3.3.1.1.1. 수출금액지수. In the table, select 계정코드: 반도체. Set the cycle (주기) to monthly, choose the period, and click 조회 (Search).
Data source ↗Cited in: ↑ Key findings, ↑ 2026: a run-up resting on two chipmakers, ↑ How a crash-risk model for Korea could work
- 7
Bank of Korea, ECOS. Bank of Korea base rate. 722Y001/D/0101000. Retrieved 19 Oct 2026.
Finding the series: On ECOS (ecos.bok.or.kr), open 통계검색 (Statistics search) and type the table name “한국은행 기준금리 및 여수신금리” or its code 722Y001 in the search box, or follow the statistics list 1. 통화/금융 > 1.3. 금리 > 1.3.1. 한국은행 기준금리 및 여수신금리. In the table, select 계정항목: 한국은행 기준금리. Set the cycle (주기) to daily, choose the period, and click 조회 (Search).
Data source ↗Cited in: ↑ Key findings, ↑ What came before the market steadied, ↑ How a crash-risk model for Korea could work
- 10
FRED, Federal Reserve Bank of St. Louis. Won per US dollar (New York noon rate). DEXKOUS. Retrieved 19 Oct 2026.
Finding the series: The link opens the FRED series DEXKOUS directly. Use “Edit Graph” to change the dates or units, and “Download” for the data.
Data source ↗Cited in: ↑ Every fall had its own mix of causes, ↑ How a crash-risk model for Korea could work, ↑ Our read
- 12
Bank of Korea, ECOS. Composite consumer sentiment index (CCSI), monthly. 511Y002/M/FME/99988. Retrieved 19 Oct 2026.
Finding the series: On ECOS (ecos.bok.or.kr), open 통계검색 (Statistics search) and type the table name “소비자동향조사(전국, 월, 2008.9~)” or its code 511Y002 in the search box, or follow the statistics list 6. 심리지수 > 6.2. 소비자동향조사 > 6.2.1. 소비자동향조사(전국, 월, 2008.9~). In the table, select CSI코드: 소비자심리지수; CSI분류코드: 전체. Set the cycle (주기) to monthly, choose the period, and click 조회 (Search).
Data source ↗Cited in: ↑ The mood was upbeat at the top, ↑ How a crash-risk model for Korea could work
Cite this article
If you use this article in research, a report or the news, please cite it as follows.
datasteg (2026), “Korea's 2026 stock plunge came after its biggest boom in decades, not a global panic”, datasteg articles, 20 October 2026, https://articles.datasteg.com/en/a/korea-stock-crashes.
BibTeX
@online{datasteg:korea-stock-crashes,
author = {{datasteg}},
title = {Korea's 2026 stock plunge came after its biggest boom in decades, not a global panic},
organization = {datasteg articles},
date = {2026-10-20},
url = {https://articles.datasteg.com/en/a/korea-stock-crashes}
}PDF edition. A print layout of this article, with every figure, the references and this citation. English (13 pages, 0.4 MB) · Korean (11 pages, 0.9 MB)