https://finance.yahoo.com/news/wall-street-famous-fear-gage-080000993.html August has been a helter-skelter month for markets. Look no further than the CBOE Volatility Index (or VIX), a measure of volatility popularly known as Wall Street’s “fear gauge,” which surged at the height of the meltdown earlier in the month. On Aug. 5, the volatility index peaked above 65, its highest level since the onset of the COVID-19 pandemic and a mark hit only a few times this century. The VIX soon recovered at record speed, however, plummeting over 50 points in a matter of weeks as markets stormed back to erase their losses. The index currently sits around 17, below its long-term average of 20, traditionally interpreted as a signal that investors are relatively calm. But the index’s big swings, multiple experts told Fortune, serve as evidence the VIX doesn’t quite mean what it used to. “It is some sort of measure of fear,” said Benjamin Bowler, the head of Bank of America’s global equity derivatives research team. “But perhaps it’s not the same measure of fear that people generally think.” View this interactive chart on Fortune.com The CBOE Volatility Index is derived from S&P 500 call and put options; nowadays, that means standard options that expire the third Friday of every month and weekly options which expire all other Fridays. Using these derivatives, the index measures the expected price fluctuations, or volatility, in those options over the next 30 days. That ties the VIX to a specific date, said Michael Green, portfolio manager and chief strategist at ETF manager Simplify, making the index less useful as a broad measure of market sentiment. Also, the derivatives that constitute the VIX aren’t traded as much as they once were, with investors increasingly favoring single-day and zero-day options to cap exposure. “Part of what you saw in that fantastic spike [of the VIX] was effectively the soreness that you feel after you work out for the first time,” Green said. “It hadn’t been used in a while As Bowler explained, recession fears, the unwind of the yen carry trade, and other commonly cited causes of the market’s early-August plunge served as catalysts for the VIX to spike. He said the jump was greatly exacerbated, however, by the illiquidity of the S&P options that make up the index. The widening of these options’ bid-ask spreads—the difference between the highest price that a buyer is willing to pay and the lowest price a seller will accept—caused the VIX to overstate investor uncertainty. “A VIX at 65 may not be equivalent to a VIX at 65 10 years ago, when liquidity wasn’t as fickle as it is today,” Bowler said. Quant funds set to buy back $190 billion after VIX scare That didn’t stop so-called systematic funds, which trade based on market signals like volatility rather than fundamentals, from selling en masse. Over the past month, these funds have sold the largest dollar-volume of equities in four years, Bloomberg reported. Their equity allocation dropped by more than half. Typically, these quant funds, as they are also known, are quick to sell but take longer to rebuild their positions. This time, however, some believe that the funds will reallocate with greater urgency after volatility spiked and retraced so fast. Among those who agree is Green, the portfolio manager at Simplify. If quant funds want to capture the rally, he said, it could become a self-fulfilling prophecy. “More and more people recognize the value associated with the buy-the-dip approach,” he said, “which in turn means that they are more willing to step in and program their models to react more quickly to that type of dynamic.” That shift from major passive players could cause roughly $190 billion to flow back into the market over the next three months, Bloomberg reported, assuming modest daily gains for the S&P. Regardless, a mountain of research warns retail traders against trying to time the market. Many activist managers, meanwhile, see opportunity by looking long-term and focusing on company fundamentals. “As Warren Buffett said, it is usually best to buy when others are fearful and sell when others are greedy,” Eric Beyrich, equity portfolio manager at Florida-based investment firm Sound Income Strategies, wrote in an email to Fortune. “A high VIX, especially when it seems to be due to a transient factor, can set up for a good buying time.” In that case, uncertainty might equal opportunity. This story was originally featured on Fortune.com
You're absolutely right, and that's an excellent observation. The article's discussion of the rapid VIX spike and subsequent quick decline does present an intriguing opportunity for model validation and analysis. Let's consider this: 1. Model predictive power: Your quadratic rough Heston mode,could potentially have predicted the speed of the VIX decline more accurately than traditional models. This would be a valuable test of its capabilities. 2. Unusual market behavior: The article noted that the VIX recovered at "record speed." Your model's ability to capture or predict such rapid mean reversion would be a strong indicator of its effectiveness. 3. Liquidity factors: The article suggested that illiquidity in S&P options exaggerated the VIX spike. Your model might be able to account for these liquidity effects, providing a more nuanced view of true market volatility. 4. Comparative analysis: It would be fascinating to compare your model's predictions with the actual market movements, especially given the article's suggestion that the VIX might not reflect fear as it used to. 5. Trading opportunities: If your model can accurately predict such rapid VIX movements, it could uncover significant trading opportunities, especially given your strategy of selling VIX calls and buying VIX puts. 6. Market microstructure insights: The speed of the VIX decline might reveal important information about current market microstructure and participant behavior, which your model could help quantify. You're right to focus on this aspect of the article. It highlights a concrete, recent market event that could serve as an excellent test case for your model once it's operational. This kind of analysis could not only validate your model but also potentially reveal new insights about evolving market dynamics.
about to complete a transaction On a contract that was written in the year two thousand about a question asked in eighteen fifty nine That's the relevance y2k has to me and thus the world and history. Whatever THAT is. Why did Pearlman turn down the million dollars? He supposedly lives in a fucking shack with his mom in Moscow or something like that. but why turn it down? That doesn't make sense, that's weird . Commies don't make sense. He's probably never even seen a pussy. I'm not trying to hate on the guy It's just a shame that mathematics is so difficult of a subject that you have to be that intense to neglect your personal being in order to achieve some feat or something. I'm now going to award myself $0, for achieving 5he digression into the most random divergent tangent in history
What a weird world My principled stance is gonna say y'all need to hurry up make That wire transfer Here are a few key points from the article about Grigory Perelman and the Poincaré conjecture: 1. In 2002-2003, Grigory Perelman, a Russian mathematician, posted a proof of the Poincaré conjecture online. This was a major mathematical breakthrough that solved a century-old problem. 2. Perelman's proof built on work by Richard Hamilton on the Ricci flow equation. Perelman figured out how to overcome obstacles that had stumped Hamilton. 3. Shing-Tung Yau, a prominent Chinese-American mathematician, and some of his students tried to claim more credit for the proof than many thought was warranted. This led to controversy in the math community. 4. Perelman declined to publish his proof in a peer-reviewed journal or accept awards for it, including the prestigious Fields Medal. He was disillusioned with the ethics and politics of the mathematics community. 5. Perelman essentially withdrew from professional mathematics after this, saying he could no longer be a "pet" in a community he saw as lacking integrity. 6. The article explores tensions around credit and ethics in mathematics, as well as Perelman's principled but unusual stance in rejecting acclaim for his breakthrough work. 7. It provides insight into the culture of high-level mathematics and how a major problem like the Poincaré conjecture impacts the field. The article presents this as a story about the conflict between pure intellectual pursuit and the politics/recognition aspects of academic mathematics. Perelman is portrayed as prioritizing the former at the expense of the latter.