Sp500 volatility index

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CBOE S&P 500 3-Month Volatility Index (VXVCLS)

Source:Chicago Board Options Exchange  

Release:CBOE Market Statistics  

Units:  Index, Not Seasonally Adjusted

Frequency:  Daily, Close

Notes:

Copyright, 2016, Chicago Board Options Exchange, Inc. Reprinted with permission.

Suggested Citation:

Chicago Board Options Exchange, CBOE S&P 500 3-Month Volatility Index [VXVCLS], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/VXVCLS, October 16, 2021.

Sours: https://fred.stlouisfed.org/series/VXVCLS

Cboe Volatility Index (VIX)

What Is the Cboe Volatility Index (VIX)?

The Cboe Volatility Index (VIX) is a real-time index that represents the market's expectations for the relative strength of near-term price changes of the S&P 500 index (SPX). Because it is derived from the prices of SPX index options with near-term expiration dates, it generates a 30-day forward projection of volatility. Volatility, or how fast prices change, is often seen as a way to gauge market sentiment, and in particular the degree of fear among market participants.

The index is more commonly known by its ticker symbol and is often referred to simply as "the VIX." It was created by the Chicago Board Options Exchange (CBOE) and is maintained by Cboe Global Markets. It is an important index in the world of trading and investment because it provides a quantifiable measure of market risk and investors' sentiments.

Key Takeaways

  • The Cboe Volatility Index, or VIX, is a real-time market index representing the market's expectations for volatility over the coming 30 days.
  • Investors use the VIX to measure the level of risk, fear, or stress in the market when making investment decisions.
  • Traders can also trade the VIX using a variety of options and exchange-traded products, or use VIX values to price derivatives.

How Does the VIX Work?

For financial instruments like stocks, volatility is a statistical measure of the degree of variation in their trading price observed over a period of time. On September 27, 2018, shares of Texas Instruments Inc. (TXN) and Eli Lilly & Co. (LLY) closed around similar price levels of $107.29 and $106.89 per share, respectively.

However, a look at their price movements over the past one month (September) indicates that TXN (Blue Graph) had much wider price swings compared to that of LLY (Orange Graph). TXN had higher volatility compared to LLY over the one-month period.

Extending the observation period to the last three months (July to September) reverses the trend: LLY had a much wider range for price swings compared to that of TXN, which is completely different from the earlier observation made over one month. LLY had higher volatility than TXN during the three-month period.

Volatility attempts to measure such magnitude of price movements that a financial instrument experiences over a certain period of time. The more dramatic the price swings are in that instrument, the higher the level of volatility, and vice versa.

How Volatility Is Measured

Volatility can be measured using two different methods. First is based on performing statistical calculations on the historical prices over a specific time period. This process involves computing various statistical numbers, like mean (average), variance, and finally the standard deviation on the historical price data sets.

The resulting value of standard deviation is a measure of risk or volatility. In spreadsheet programs like MS Excel, it can be directly computed using the STDEVP() function applied on the range of stock prices. However, the standard deviation method is based on lots of assumptions and may not be an accurate measure of volatility. Since it is based on past prices, the resulting figure is called “realized volatility” or "historical volatility (HV)." To predict future volatility for the next X months, a commonly followed approach is to calculate it for the past recent X months and expect that the same pattern will follow.

The second method to measure volatility involves inferring its value as implied by option prices. Options are derivative instruments whose price depends upon the probability of a particular stock’s current price moving enough to reach a particular level (called the strike price or exercise price).

For example, say IBM stock is currently trading at a price of $151 per share. There is a call option on IBM with a strike price of $160 and has one month to expiry. The price of such a call option will depend upon the market perceived probability of IBM stock price moving from current level of $151 to above the strike price of $160 within the one month remaining to expiry. Since the possibility of such price moves happening within the given time frame is represented by the volatility factor, various option pricing methods (like Black Scholes model) include volatility as an integral input parameter. Since option prices are available in the open market, they can be used to derive the volatility of the underlying security (IBM stock in this case). Such volatility, as implied by or inferred from market prices, is called forward-looking “implied volatility (IV).”

Though none of the methods is perfect as both have their own pros and cons as well as varying underlying assumptions, they both give similar results for volatility calculation that lie in a close range.

Extending Volatility to Market Level

In the world of investments, volatility is an indicator of how big (or small) moves a stock price, a sector-specific index, or a market-level index makes, and it represents how much risk is associated with the particular security, sector, or market. The above stock-specific example of TXN and LLY can be extended to sector-level or market-level. If the same observation is applied to the price moves of a sector-specific index, say the NASDAQ Bank Index (BANK), which consists of more than 300 banking and financial services stocks, one can assess the realized volatility of the overall banking sector. Extending it to the price observations of the broader market level index, like the S&P 500 index, will offer a peek into the volatility of the larger market. Similar results can be achieved by deducing the implied volatility from the option prices of the corresponding index.

Having a standard quantitative measure for volatility makes it easy to compare the possible price moves and the risk associated with different securities, sectors, and markets.

The VIX Index is the first benchmark index introduced by Cboe to measure the market’s expectation of future volatility. Being a forward-looking index, it is constructed using the implied volatilities on S&P 500 index options (SPX) and represents the market's expectation of 30-day future volatility of the S&P 500 index which is considered the leading indicator of the broad U.S. stock market.

Introduced in 1993, the VIX Index is now an established and globally recognized gauge of U.S. equity market volatility. It is calculated in real-time based on the live prices of the S&P 500 index. Calculations are performed and values are relayed during 3:00 a.m. CT and 9:15 a.m. CT, and between 9:30 a.m. CT and 4:15 p.m. CT. Cboe began the dissemination of the VIX Index outside of U.S. trading hours in April 2016.

Calculation of VIX Index Values

VIX index values are calculated using the Cboe-traded standard SPX options (that expire on the third Friday of each month) and using the weekly SPX options (that expire on all other Fridays). Only those SPX options are considered whose expiry period lies within 23 days and 37 days.

While the formula is mathematically complex, theoretically it works as follows. It estimates the expected volatility of the S&P 500 index by aggregating the weighted prices of multiple SPX puts and calls over a wide range of strike prices. All such qualifying options should have valid non-zero bid and ask prices that represent the market perception of which options' strike prices will be hit by the underlying stocks during the remaining time to expiry. For detailed calculations with an example, one can refer to the section “VIX Index Calculation: Step-by-Step” of the VIX whitepaper.

Evolution of VIX

During its origin in 1993, VIX was calculated as a weighted measure of the implied volatility of eight S&P 100 at-the-money put and call options, when the derivatives market had limited activity and was in its growing stages. As the derivatives markets matured, ten years later in 2003, Cboe teamed up with Goldman Sachs and updated the methodology to calculate VIX differently. It then started using a wider set of options based on the broader S&P 500 index, an expansion that allows for a more accurate view of investors' expectations on future market volatility. They then adopted a methodology that continues to remain in effect and is also used for calculating various other variants of the volatility index.

Real-World Example of the VIX

Volatility value, investors' fear, and the VIX index values move up when the market is falling. The reverse is true when the market advances—the index values, fear, and volatility decline.

A real-world comparative study of the past records since 1990 reveals several instances when the overall market, represented by S&P 500 index (Orange Graph) spiked leading to the VIX values (Blue Graph) going down around the same time, and vice versa.

One should also note that VIX movement is much more than that observed in the index. For example, when S&P 500 declined around 15% between August 1, 2008, and October 1, 2008, the corresponding rise in VIX was nearly 260%.

In absolute terms, VIX values greater than 30 are generally linked to large volatility resulting from increased uncertainty, risk, and investors’ fear. VIX values below 20 generally correspond to stable, stress-free periods in the markets.

How to Trade the VIX

VIX index has paved the way for using volatility as a tradable asset, although through derivative products. Cboe launched the first VIX-based exchange-traded futures contract in March 2004, which was followed by the launch of VIX options in Feb. 2006.

Such VIX-linked instruments allow pure volatility exposure and have created a new asset class altogether. Active traders, large institutional investors, and hedge fund managers use the VIX-linked securities for portfoliodiversification, as historical data demonstrates a strong negative correlation of volatility to the stock market returns – that is, when stock returns go down, volatility rises and vice versa.

"...it forces us to do what we know we're supposed to do as investors, which is, add low, trim high, a version of buy low, sell high. And often when left to our own devices, we don't do that. We let the winners run. They become an outsized portion of the portfolio. And when the inevitable reversion of the mean happens, you're holding a much heavier bag than you otherwise would have," said Liz Ann Sonders, managing director & chief investment strategist of Charles Schwab. "It's really simple, basic stuff, but it's so important to hammer home, especially when you have all these rotations, which frankly give you more opportunity to use volatility to your advantage via that process of rebalancing."

Other than the standard VIX index, Cboe also offers several other variants for measuring broad market volatility. Other similar indexes include the Cboe ShortTerm Volatility Index (VXSTSM), which reflects the nine-day expected volatility of the S&P 500 Index, the Cboe S&P 500 3-Month Volatility Index (VXVSM), and the Cboe S&P 500 6-Month Volatility Index (VXMTSM). Products based on other market indexes include the Nasdaq-100 Volatility Index (VXNSM), the Cboe DJIA Volatility Index (VXDSM), and the Cboe Russell 2000 Volatility Index (RVXSM). Options and futures based on RVXSM are available for trading on Cboe and CFE platforms, respectively.

Like all indexes, one cannot buy the VIX directly. Instead, investors can take a position in VIX through futures or options contracts, or through VIX-based exchange traded products (ETP). For example, the ProShares VIX Short-Term Futures ETF (VIXY), the iPath Series B S&P 500 VIX Short Term Futures ETN (VXXB), and the VelocityShares Daily Long VIX Short-Term ETN (VIIX) are many such offerings that track certain VIX-variant index and take positions in linked futures contracts.

Active traders who employ their own trading strategies as well as advanced algorithms use VIX values to price the derivatives which are based on high beta stocks. Beta represents how much a particular stock price can move with respect to the move in a broader market index. For instance, a stock having a beta of +1.5 indicates that it is theoretically 50% more volatile than the market. Traders making bets through options of such high beta stocks utilize the VIX volatility values in appropriate proportion to correctly price their options trades.

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The S&P 500® Low Volatility Index measures performance of the 100 least volatile stocks in the S&P 500. The index benchmarks low volatility or low variance strategies for the U.S. stock market. Constituents are weighted relative to the inverse of their corresponding volatility, with the least volatile stocks receiving the highest weights.

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Why the Vix volatility index matters so much

S&P 500 12-Month Realized Volatility Index

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This index seeks to reflect the 12-Month realized volatility in the daily levels of the S&P 500. Realized volatility measures the variations in the price of a security over a given period.

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Volatility index sp500

VIX

Volatility index

For other uses, see Vix (disambiguation).

CBOE Volatility Index (VIX) 2004–2020.

VIX is the ticker symbol and the popular name for the Chicago Board Options Exchange's CBOE Volatility Index, a popular measure of the stock market's expectation of volatility based on S&P 500 index options. It is calculated and disseminated on a real-time basis by the CBOE, and is often referred to as the fear index or fear gauge.

The VIX traces its origin to the financial economics research of Menachem Brenner and Dan Galai. In a series of papers beginning in 1989, Brenner and Galai proposed the creation of a series of volatility indices, beginning with an index on stock market volatility, and moving to interest rate and foreign exchange rate volatility.[1][2][full citation needed]

In their papers, Brenner and Galai proposed, "[the] volatility index, to be named 'Sigma Index', would be updated frequently and used as the underlying asset for futures and options. ... A volatility index would play the same role as the market index plays for options and futures on the index."[This quote needs a citation] In 1992, the CBOE hired consultant Bob Whaley to calculate values for stock market volatility based on this theoretical work.[3] Whaley utilized data series in the index options market, and provided the CBOE with computations for daily VIX levels from January 1986 to May 1992.[not verified in body]

The resulting VIX index formulation provides a measure of market volatility on which expectations of further stock market volatility in the near future might be based. The current VIX index value quotes the expected annualized change in the S&P 500 index over the following 30 days, as computed from options-based theory and current options-market data.

To summarize, VIX is a volatility index derived from S&P 500 options for the 30 days following the measurement date,[4] with the price of each option representing the market's expectation of 30-day forward-looking volatility.[4][5] The resulting VIX index formulation provides a measure of expected market volatility on which expectations of further stock market volatility in the near future might be based.[5]

Like conventional indexes, the VIX Index calculation employs rules for selecting component options and a formula to calculate index values.[5][6] Unlike other market products, VIX cannot be bought or sold directly.[7] Instead, VIX is traded and exchanged via derivative contract, derived ETFs, and ETNs which most commonly track VIX futures indexes.[8]

In addition to VIX, CBOE uses the same methodology to compute the following related products:[5][6]

  • CBOE ShortTerm Volatility Index (VIX9DSM), which reflects 9-day expected volatility of the S&P 500 Index,
  • CBOE S&P 500® 3-Month Volatility Index (VIX3MSM),
  • CBOE S&P 500® 6-Month Volatility Index (VIX6MSM)
  • CBOE S&P 500 1-Year Volatility Index (VIX1YSM).

CBOE also calculates the Nasdaq-100® Volatility Index (VXNSM), CBOE DJIA® Volatility Index (VXDSM) and the CBOE Russell 2000® Volatility Index (RVXSM).[5] There is even a VIX on VIX (VVIX) which is a volatility of volatility measure in that it represents the expected volatility of the 30-day forward price of the CBOE Volatility Index (the VIX®).[9]

Specifications[edit]

The concept of computing implied volatility or an implied volatility index dates back to the publication of the Black and Scholes' 1973 paper, "The Pricing of Options and Corporate Liabilities," published in the Journal of Political Economy, which introduced the seminal Black–Scholes model for valuing options.[10] Just as a bond's implied yield to maturity can be computed by equating a bond's market price to its valuation formula, an option-implied volatility of a financial or physical asset can be computed by equating the asset option's market price to its valuation formula.[11] In the case of VIX, the option prices used are the S&P 500 index option prices.[12]

The VIX takes as inputs the market prices of the call and put options on the S&P 500 index for near-term options with more than 23 days until expiration, next-term options with less than 37 days until expiration, and risk-free U.S. treasury bill interest rates. Options are ignored if their bid prices are zero or where their strike prices are outside the level where two consecutive bid prices are zero.[5][page needed] The goal is to estimate the implied volatility of S&P 500 index options at an average expiration of 30 days.[13]

Monthly mean of VIX volatility index, 2004-2019

The VIX is the volatility of a variance swap and not that of a volatility swap, volatility being the square root of variance, or standard deviation.[citation needed] A variance swap can be perfectly statically replicated through vanilla puts and calls,[clarification needed] whereas a volatility swap requires dynamic hedging.[citation needed] The VIX is the square root of the risk-neutral expectation of the S&P 500 variance over the next 30 calendar days and is quoted as an annualized standard deviation.[citation needed]

The VIX is calculated and disseminated in real-time by the Chicago Board Options Exchange.[citation needed] On March 26, 2004, trading in futures on the VIX began on CBOE Futures Exchange (CFE).[citation needed]

On February 24, 2006, it became possible to trade options on the VIX.[citation needed] Several exchange-traded funds hold mixtures of VIX futures that attempt to enable stock-like trading in those futures. The correlation between these ETFs and the actual VIX index is very poor, especially when the VIX is moving.[14]

VIX Formula[edit]

The VIX is a 30-day expectation of volatility given by a weighted portfolio of out-of-the-money European options on the S&P 500:[5]


{\displaystyle VIX={\sqrt {{\frac {2e^{r\,\!\tau }}{\tau }}\left(\int _{0}^{F}{\frac {P(K)}{K^{2}}}dK+\int _{F}^{\infty }{\frac {C(K)}{K^{2}}}dK\right)}}}


where {\tau } is the number of average days in a month (30 days), r is the risk-free rate, F is the 30-day forward price on the S&P 500, and {\displaystyle P(K)} and C(K) are prices for puts and calls with strike K and 30 days to maturity.[5][15]

History[edit]

The following is a timeline of key events in the history of the VIX Index:[according to whom?]

  • 1987 - The Sigma Index was introduced in an academic paper by Brenner and Galai, published in Financial Analysts Journal, July/August 1989.[16] Brenner and Galai wrote, "Our volatility index, to be named Sigma Index, would be updated frequently and used as the underlying asset for futures and options... A volatility index would play the same role as the market index play for options and futures on the index."[This quote needs a citation]
  • 1989 - Brenner and Galai's paper is published in Financial Analysts Journal.[full citation needed] Brenner and Galai develop their research further in graduate symposia at The Hebrew University of Jerusalem[citation needed] and at the Leonard M. Stern School of Business at New York University.[citation needed]
  • 1992 - The American Stock Exchange announced it is conducting a feasibility study on a volatility index, proposed as the "Sigma Index."[17]
  • 1993 - On January 19, 1993, the Chicago Board Options Exchange held a press conference to announce the launch of real-time reporting of the CBOE Market Volatility Index or VIX. The formula that determines the VIX is tailored to the CBOE S&P 100 Index (OEX) option prices, and was developed by Professor Robert E. Whaley of Duke University (now at Vanderbilt University), whom the CBOE had commissioned.[18] This index, now known as the VXO, is a measure of implied volatility calculated using 30-day S&P 100 index at-the-money options.[19]
  • 1993 - Professors Brenner and Galai develop their 1989 proposal for a series of volatility index in their paper, "Hedging Volatility in Foreign Currencies," published in The Journal of Derivatives in the fall of 1993.[full citation needed]
  • 2003 - The CBOE introduces a new methodology for the VIX. Working with Goldman Sachs, the CBOE developed further computational methodologies, and changed the underlying index the CBOE S&P 100 Index (OEX) to the CBOE S&P 500 Index (SPX). The old methodology was renamed the VXO.[5][verification needed]
  • 2004 - On March 26, 2004, the first-ever trading in futures on the VIX Index began on the CBOE Futures Exchange (CFE).[citation needed] VIX is now proposed[clarification needed] on different trading platforms, like XTB.[citation needed]
  • 2006 - VIX options were launched in February of this year.[citation needed]
  • 2008 - On October 24, 2008, the VIX reached an intraday high of 89.53.[citation needed]
  • 2008 - On November 21, 2008, the VIX closed at a record 80.74.[20]
  • 2018 - On February 5, 2018, the VIX closed 37.32 (up 103.99% from previous close).[21]
  • 2020 - On March 9, 2020, the VIX hit 62.12, the highest level since the 2008 financial crisis due to a combination of the 2020 Russia–Saudi Arabia oil price war and the COVID-19 pandemic.[22][23]
  • 2020 - During the COVID-19 pandemic, on March 12, 2020, the VIX hit and closed at 75.47, exceeding the previous Black Monday value, as a travel ban to the US from Europe was announced by President Trump.[24]
  • 2020 - On March 16, the VIX closed at 82.69, the highest level since its inception in 1990.[25]
  • 2021 The U.S. Securities and Exchange Commission fined the S&P Dow Jones Indices for halting data on February 5, 2018.[26]

Interpretation[edit]

Performance of VIX (left) compared to past volatility (right) as 30-day volatility predictors, for the period of Jan 1990-Sep 2009. Volatility is measured as the standard deviation of S&P500 one-day returns over a month's period. The blue lines indicate linear regressions, resulting in the correlation coefficientsrshown. Note that VIX has virtually the same predictive power as past volatility, insofar as the shown correlation coefficients are nearly identical.

VIX is sometimes criticized as a prediction of future volatility. Instead it is described as a measure of the current price of index options.[according to whom?][citation needed]

Critics claim that, despite a sophisticated formulation, the predictive power of most volatility forecasting models is similar to that of plain-vanilla measures, such as simple past volatility.[27][28][29] However, other works have countered that these critiques failed to correctly implement the more complicated models.[30]

Some practitioners and portfolio managers have questioned the depth of our understanding of the fundamental concept of volatility, itself. For example, Daniel Goldstein and Nassim Taleb famously titled one of their research articles, We Don't Quite Know What We are Talking About When We Talk About Volatility.[31] Relatedly,[verification needed]Emanuel Derman has expressed disillusion with empirical models that are unsupported by theory.[clarification needed][citation needed][32][page needed] He argues that, while "theories are attempts to uncover the hidden principles underpinning the world around us... [we should remember that] models are metaphors—analogies that describe one thing relative to another."[page needed]

Michael Harris, the trader, programmer, price pattern theorist, and author, has argued that VIX just tracks the inverse of price and has no predictive power.[33][34][better source needed]

According to some,[who?] VIX should have predictive power as long as the prices computed by the Black-Scholes equation are valid assumptions about the volatility predicted for the future lead time (the remaining time to maturity).[citation needed]Robert J. Shiller has argued that it would be circular reasoning to consider VIX to be proof of Black-Scholes, because they both express the same implied volatility, and has found that calculating VIX retrospectively in 1929 did not predict the surpassing volatility of the Great Depression—suggesting that in the case of anomalous conditions, VIX cannot even weakly predict future severe events.[35]

An academic study from the University of Texas at Austin and Ohio State University examined potential methods of VIX manipulation.[36] On February 12, 2018, a letter was sent to the Commodity Futures Trading Commission and Securities and Exchange Commission by a law firm representing an anonymous whistleblower alleging manipulation of the VIX.[37]

Volatility of Volatility[edit]

In 2012, the CBOE introduced the "VVIX index" (also referred to as "vol of vol"), a measure of the VIX's expected volatility.[38] VVIX is calculated the same as VIX, except the inputs are market prices for VIX options, instead of stock market options.[39]

See also[edit]

References[edit]

  1. ^Brenner, Menachem; Galai, Dan (July–August 1989). "New Financial Instruments for Hedging Changes in Volatility"(PDF). Financial Analysts Journal. 45 (4): 61–65. doi:10.2469/faj.v45.n4.61.[full citation needed]
  2. ^Brenner, Menachem; Galai, Dan (Fall 1993). "Hedging Volatility in Foreign Currencies"(PDF). The Journal of Derivatives. Unknown volume (unknown issue): unknown page nos.[full citation needed]
  3. ^Bob Pisani (29 March 2020). "Father of Wall Street's 'fear gauge' sees wild volatility continuing until coronavirus cases peak". Retrieved 29 March 2020.
  4. ^ abKuepper, Justin. "CBOE Volatility Index (VIX) Definition". Investopedia. Retrieved 2020-04-10.
  5. ^ abcdefghiCBOE Staff (2019). "Whitepaper: Cboe Volatility Index"(PDF). CBOE.com. Retrieved 26 February 2020.[page needed]
  6. ^ ab"How Does the Cboe's VIX® Index Work? | Six Figure Investing". sixfigureinvesting.com. 10 July 2014. Retrieved 2020-04-10.
  7. ^Iachini, Michael. "VIX ETFs: The Facts and Risks". Schwab Brokerage. Retrieved 2020-04-10.
  8. ^Reiff, Nathan. "How to Use a VIX ETF in Your Portfolio". Investopedia. Retrieved 2020-04-10.
  9. ^"Cboe Index Dashboard". www.cboe.com. Retrieved 2020-09-02.
  10. ^Black, Fischer; Scholes, Myron (1973). "The Pricing of Options and Corporate Liabilities". Journal of Political Economy. 81 (3): 637–654. doi:10.1086/260062. ISSN 0022-3808. JSTOR 1831029. S2CID 154552078.
  11. ^Nickolas, Steven. "Implied Volatility". Investopedia. Retrieved 2020-08-18.
  12. ^"VIX Options". www.cboe.com. Retrieved 2020-08-18.
  13. ^"Cboe Tradable Products". www.cboe.com.
  14. ^Conway, Brendan (17 June 2014). "No, Your ETF Doesn't Track the VIX Volatility Index—and Here are the Numbers". Barrons.com. Retrieved 26 February 2020.
  15. ^Papanicolaou, Andrew (5 April 2016). "Identifying Links Between the S&P500 and VIX Derivatives". Institute for Pure & Applied Mathematics. UCLA. Retrieved 10 April 2020.
  16. ^"Volatility"(PDF). people.stern.nyu.edu. Retrieved 2020-02-26.
  17. ^"IFR report"(PDF). people.stern.nyu.edu. 1992. Retrieved 2020-02-26.
  18. ^"Derivatives on market volatility"(PDF). rewconsulting.files.wordpress.com. 2012. Retrieved 2020-02-26.
  19. ^Mehta, Salil (July 2015). "Volatility in motion"(blog). Statistical Ideas. Retrieved 26 February 2020 – via Statisticalideas.blogspot.com.
  20. ^Yun Li (March 16, 2020). "Wall Street's fear gauge closes at highest level ever, surpassing even financial crisis peak". MSNBC. Retrieved March 17, 2020.
  21. ^"CBOE Volatility Index". MarketWatch. February 7, 2018. Archived from the original on February 7, 2018. Retrieved August 23, 2020.
  22. ^Yakob Peterseil (March 9, 2020). "VIX Spikes to Highest Since 2008 in Manic Monday Trading". Bloomburg. Retrieved March 9, 2020.
  23. ^Pete Evans (March 9, 2020). "'This is basically panic selling': Stock markets plunge as coronavirus fear spreads". CBC. Retrieved March 9, 2020.
  24. ^Nicholas Jasinski (March 12, 2020). "The VIX Fear Gauge Is Soaring. It's Unlikely to Come Down Anytime Soon". Barron's. Retrieved March 12, 2020.
  25. ^Li, Yun (March 16, 2020). "Wall Street's fear gauge closes at highest level ever, surpassing even financial crisis peak". cnbc.com. Retrieved March 19, 2020.
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Further reading[edit]

  • Black, Fischer and Myron Scholes. "The Pricing of Options and Corporate Liabilities." Journal of Political Economy (May/June 1973), pp. 637–659.
  • Brenner, Menachem; Galai, Dan (July–August 1989). "New Financial Instruments for Hedging Changes in Volatility"(PDF). Financial Analysts Journal. Unknown volume (unknown issue): unknown page nos.[full citation needed]
  • Brenner, Menachem; Galai, Dan (Fall 1993). "Hedging Volatility in Foreign Currencies"(PDF). The Journal of Derivatives. Unknown volume (unknown issue): unknown page nos.[full citation needed]
  • "Amex Explores Volatility Options," International Financing Review, August 8, 1992.
  • Black, Keith H. "Improving Hedge Fund Risk Exposures by Hedging Equity Market Volatility, or How the VIX Ate My Kurtosis." The Journal of Trading. (Spring 2006).
  • Connors, Larry. "A Volatile Idea." Futures (July 1999): p. 36—37.
  • Connors, Larry. "Timing Your S&P Trades with the VIX." Futures (June 2002): pp. 46–47.
  • Copeland, Maggie. "Market Timing: Style and Size Rotation Using the VIX." Financial Analysts Journal, (Mar/Apr 1999); pp. 73–82.
  • Daigler, Robert T., and Laura Rossi. "A Portfolio of Stocks and Volatility." The Journal of Investing. (Summer 2006).
  • Fleming, Jeff, Barbara Ostdiek, and Robert E. Whaley, "Predicting Stock Market Volatility: A New Measure," The Journal of Futures Markets 15 (May 1995), pp. 265–302.
  • Hulbert, Mark, "The Misuse of the Stock Market's Fear Index," Barron's, October 7, 2011.
  • Mele, Antonio and Yoshiki Obayashi. "The Price of Fixed Income Market Volatility." Springer Verlag: Springer Finance Series, New York (2015).
  • Moran, Matthew T., "Review of the VIX Index and VIX Futures.," Journal of Indexes, (October/November 2004). pp. 16–19.
  • Moran, Matthew T. and Srikant Dash. "VIX Futures and Options: Pricing and Using Volatility Products to Manage Downside Risk and Improve Efficiency in Equity Portfolios." The Journal of Trading. (Summer 2007).
  • Szado, Ed. "VIX Futures and Options—A Case Study of Portfolio Diversification During the 2008 Financial Crisis." (June 2009).
  • Tan, Kopin. "The ABCs of VIX." Barron's (Mar 15, 2004): p. MW16.
  • Tracy, Tennille. "Trading Soars on Financials As Volatility Index Hits Record." Wall Street Journal. (Sept. 30, 2008) pg. C6.
  • Whaley, Robert E., "Derivatives on Market Volatility: Hedging Tools Long Overdue," The Journal of Derivatives 1 (Fall 1993), pp. 71–84.
  • Whaley, Robert E., "The Investor Fear Gauge," The Journal of Portfolio Management 26 (Spring 2000), pp. 12–17.
  • Whaley, Robert E., "Understanding the VIX." The Journal of Portfolio Management 35 (Spring 2009), pp. 98–105.

External links[edit]

Sours: https://en.wikipedia.org/wiki/VIX
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