Mysterious Trader Rakes in Over $10 Million by Predicting September Volatility Surge
September is living up to its reputation as a month of market weakness, with equities experiencing a massive loss of over $1 trillion in total market capitalization in a single session. However, one unknown trader seems to have defied the odds and made a fortune by betting on the rise in volatility.
According to a post shared on X (formerly known as Twitter) by Unusual Whales, the trader made a staggering $10 million from their bet on the CBOE Volatility Index (VIX) amid the recent sell-off. While the exact details of the trade remain a mystery, it is reported that the buyer acquired 350,000 contracts of VIX 22/30 call spreads expiring on September 18 for $0.25. These contracts saw an impressive increase of 211% and 160% respectively, resulting in the trader’s massive gain.
This impressive profit was made possible by the significant surge in the VIX at the beginning of September, coinciding with the stock market downturn. Large-cap tech stocks, including Nvidia, took a hit, with Nvidia losing over $360 billion in market capitalization, even considering its after-hours movements. Moreover, slow manufacturing activity, impacted by high interest rates, added to the market’s volatility. The upcoming release of the US August jobs report is also expected to contribute to further market fluctuations, as past unexpected unemployment readings have led to stock market downturns.
Interestingly, September has historically been a month with negative returns in the stock market. Known as the September Effect, this phenomenon has occurred consistently over the last 98 years. This negative trend is not limited to the stock market, as Bitcoin’s performance in September has also been unfavorable, with an average negative return of 4.5% from 2010 to 2023, according to CCData.
While the mysterious trader’s identity remains unknown, their impressive gain serves as a reminder of the potential profitability of predicting market volatility during historically weak periods.