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August–November 2018: How Turkey and Argentina Shook the World's Currencies

By FinFable Research · Facts cross-checked, figures verified against market data

The 2018 Turkish lira and Argentine peso collapses triggered a cascade through emerging-market FX, with max drawdowns ranging from 1.2% on USD/CNY to 23.0% on EUR/TRY across 66 trading days.

On the morning of August 10, 2018, a single tweet from a major politician sent the Turkish lira into freefall—down 18 percent in hours. By August 22, when the data window for this cluster opens, the contagion had already begun its sweep across emerging-market currencies. Argentina was in its own freefall. The euro had slid against the lira by 13.3 percent over the following months. Yet across 66 trading days, some pairs barely flinched while others hemorrhaged. The story of this window is not one of a single crash but of differential collapse—how the same external shock exposes structural fault lines that differ sharply from currency to currency.

The two detonation points were specific. Turkey faced a toxic combination: a central bank under political pressure to keep rates low despite inflation running well into double digits, a current account deficit that required constant foreign capital, and an economy dependent on external borrowing in dollars. When diplomatic tensions with the United States added sanctions risk to the equation, foreign investors fled. The Argentine peso had been deteriorating since 2018 due to fiscal deficits, reliance on IMF financing, and loss of investor confidence after years of capital controls and monetary expansion. Both crises had domestic roots, yet both transmitted outward through correlated selling in developing-nation currencies.

Key terms

max drawdown
the largest peak-to-trough decline in a position or portfolio during a given period, expressed as a percentage loss from the highest watermark.
emerging-market currency contagion
the phenomenon where a currency crisis in one developing nation triggers selling pressure in other developing nations as investors reassess risk across the entire asset class.
single-bar move
the maximum percentage change in a currency pair occurring within a single daily candlestick, a measure of intraday shock intensity.

FinFable's scenario data for this window shows the full spectrum of outcomes across 120 member replays spanning August 22 to November 22, 2018. The USD/CNY Historical Replay: 2018-08 to 2018-11 captures 66 daily bars where the pair moved only 1.2 percent from open to close, with a max drawdown of 1.2 percent and a largest single-bar move of 1.1 percent. China's capital controls, large foreign reserves, and relatively insulated financial system insulated the renminbi from the worst of the EM selloff. The same window in the EUR/TRY Historical Replay: 2018-08 to 2018-11 tells a radically different story: a 13.3 percent close-to-close move against the lira, a maximum drawdown of 23.0 percent, and single bars swinging as much as 3.8 percent as the crisis deepened.

The distribution of outcomes across this cluster reveals something that aggregate EM indices obscure. USD/ZAR weathered a 9.7 percent maximum drawdown across the same dates, yet closed the period down only 1.7 percent. USD/TRY suffered a 21.1 percent maximum drawdown and ended down 11.9 percent. EUR/NZD—a G10 cross not directly linked to Turkey or Argentina—still absorbed a 7.3 percent drawdown as global risk appetite shifted. The common thread was not geography but vulnerability: currencies with current account deficits, external financing needs, or political uncertainty that investors had previously ignored were punished; those with reserve buffers or managed exchange rates absorbed the shock.

By the numbers

Key figures verified against market data
MetricValueSpanSource
USD/CNY max drawdown (Aug–Nov 2018)1.2%2018-08-22 → 2018-11-22verified ledger entry
EUR/TRY max drawdown (Aug–Nov 2018)23.0%2018-08-22 → 2018-11-22verified ledger entry
USD/TRY max drawdown (Aug–Nov 2018)21.1%2018-08-22 → 2018-11-22verified ledger entry
USD/ZAR max drawdown (Aug–Nov 2018)9.7%2018-08-22 → 2018-11-22verified ledger entry
EUR/NZD max drawdown (Aug–Nov 2018)7.3%2018-08-22 → 2018-11-22verified ledger entry
Number of member scenarios in cluster1202018-08-22 → 2018-12-07verified ledger entry

For traders who had positioned for EM strength going into 2018—carrying positions funded by low borrowing costs in developed markets—the shock was brutal. Carry trades unraveled as risk-off sentiment reversed capital flows. Positions that had been profitable for months evaporated within days. The lesson was not simply that emerging markets are risky; it was that risk manifests in sudden, non-linear fashion, with drawdowns far exceeding what the eventual close-to-close move would suggest. A position that ended the period with a small loss could have been stopped out at a loss five or ten times larger if volatility hit at the wrong moment.

The institutional response shaped subsequent market structure. Central banks in countries with manageable external positions—Indonesia, India, the Philippines—allowed their currencies to weaken modestly while intervening selectively to prevent disorderly moves. The Federal Reserve, then in a rate-hiking cycle, provided no relief; dollar strength was itself a headwind for EM borrowers. The IMF negotiated bailout programs with Argentina while Turkey resisted until currency pressure became unsustainable. These divergent policy responses became part of the historical record that traders now study to understand which institutional frameworks provide credible backstops and which do not.

The regulatory and market-structure implications extended beyond any single country. The episode reinforced the importance of counterparty risk monitoring in FX markets, as liquidity in EM currencies can evaporate rapidly when global risk appetite shifts. It prompted renewed attention to currency-overlay strategies that had previously been dismissed as unnecessary for well-funded institutions. The BIS noted in subsequent reports that cross-currency basis swaps had widened sharply, reflecting funding stress in dollar-denominated positions globally.

Playable slices

The following member scenarios allow you to step inside 66 daily bars of this window and navigate the same decision points that traders faced in real time. Each replay presents 12 decision points, four marked as critical, where position sizing and risk tolerance determine outcomes.

Show all 120 slices (108 more)

Every slice above can be replayed candle-by-candle on FinFable.

For decision trainers today, the core lesson from August through November 2018 is not about predicting which currency will collapse. It is about three structural insights. First, the gap between maximum drawdown and close-to-close return is where most trading accounts die—position sizing must account for the full volatility range, not the final outcome. Second, contagion operates through correlation breakdowns: assets that appear uncorrelated in calm markets can move together sharply during crises, eliminating the diversification benefit that justified the position in the first place. Third, institutional credibility is a market variable. Currencies backed by credible central banks with large reserves absorb shocks; those without do not, and the difference can be measured in multiples of volatility.

Further reading

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Disclaimer: This archive is provided for financial-history study and decision training only. It is not investment advice, an offer, or a solicitation, and it is not a recommendation to buy or sell any security. Past market episodes described here do not predict future outcomes.

Compiled by FinFable Research · Data & scenarios from finfable.com · © FinFable