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The annualized volatility of Bitcoin has dropped to 46%, but the number of extreme market conditions this year has already surpassed that of the bear market in 2018

Since the beginning of 2026, Bitcoin has experienced 10 "3 standard deviation" trading days, exceeding the 8 times seen throughout the bear market of 2018. Although Bitcoin's annualized volatility has decreased from 84% in 2018 to about 46%, extreme market conditions still occur frequently relative to recent price volatility levels. "3 standard deviation" is used to measure the extent to which prices deviate from the recent normal volatility range. Data shows that the average price fluctuation for Bitcoin during such extreme conditions this year is about 7%, lower than the approximately 10% seen in 2018.Since 2024, Bitcoin's volatility has been around 47%, similar to Nvidia, but during the same period, Bitcoin has had 26 "3 standard deviation" trading days, far exceeding Nvidia's 8 times, the S&P 500's 16 times, and gold's 12 times. Market participants point out that macro shocks and the leverage and concentrated positions in the derivatives market are important factors contributing to the continued occurrence of extreme volatility. When investors sell options in large quantities, betting on market calmness, sudden news can force related concentrated positions to close, further amplifying price fluctuations.Deribit CEO Luuk Strijers stated that traditional Value at Risk (VaR) models struggle to adequately measure tail risks during extreme market conditions, and investors should pay more attention to risk indicators such as Expected Shortfall. Meanwhile, increased institutional participation, deeper liquidity, and improved risk management are also enhancing the market's ability to withstand shocks, but this does not mean that extreme volatility will disappear.

first_img Prediction market platform Kalshi releases trader composition study

The prediction market platform Kalshi's Kalshi Research released a report titled "Who Trades Prediction Markets?", with a subtitle focusing on community income, background, and probability reasoning, marked for publication in October 2026. The report studies the composition of prediction market traders, with data sourced from administrative records and surveys, and compares it to a general population sample.The administrative data covers the residential ZIP codes of each direct trader on Kalshi since January 2026, and aligns with the median household income from the American Community Survey. The survey was distributed in September 2026 to the highest profit and loss traders across various market categories, excluding sports and special categories, targeting 2,360 accounts, with 325 completed responses, resulting in a response rate of 13.8%.The report states that the median income reflected by traders' residential locations is close to the national level, with a modal range crossing $80,734, and only 6.3% residing in ZIP codes with median incomes above $150,000. Among the highest profit and loss traders, 82% have never worked full-time in investment banks, hedge funds, private equity, or proprietary trading firms, 91% are not full-time traders, and 65% claim to have learned about markets and probabilities primarily or entirely on their own. In comparison to 1,005 American adults, this group scored an average of 2.42/4 on the Berlin Mathematical Test, while the public scored 0.62, with a proportion of 93% resisting the gambler's fallacy, compared to 57% in the public.
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