词条 | VIX |
释义 |
The CBOE Volatility Index, known by its ticker symbol VIX, is a popular measure of the stock market's expectation of volatility implied by S&P 500 index options. It is calculated and disseminated on a real-time basis by the Chicago Board Options Exchange (CBOE), and is commonly referred to as the fear index or the fear gauge. The concept of computing implied volatility or an implied volatility index dates back to the publication of the option valuation model by Black and Scholes in 1973. 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. In the case of VIX, the option prices are the S&P 500 index option prices. Of course, there is nothing unique about using stock index option prices. Gold option prices can be used to infer gold market volatility, bond option prices can be used to infer bond market volatility, crude oil option prices can be used to infer crude oil market volatility, and so on. In 1989, Brenner and Galai[1][2] discussed 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. The VIX was created by Robert E. Whaley of The Fuqua School of Business at Duke University (now at The Owen School of Management at Vanderbilt University) .. In 1992, the CBOE commissioned him to design a formula to compute implied stock market volatility based on prices from its S&P index options market. Based on his formula and the CBOE's historical record of index option prices, Whaley computed daily VIX levels dating back to January 1986. The VIX concept formulates a theoretical expectation of stock market volatility in the near future. 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.[3] SpecificationsThe index 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.[4] The goal is to estimate the implied volatility of S&P 500 index options at an average expiration of 30 days. 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|date=March 2018}} A variance swap can be perfectly statically replicated through vanilla puts and calls, whereas a volatility swap requires dynamic hedging. 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. The VIX is calculated and disseminated in real-time by the Chicago Board Options Exchange. On March 26, 2004, trading in futures on the VIX began on CBOE Futures Exchange (CFE). On February 24, 2006, it became possible to trade options on the VIX. Several exchange-traded funds hold mixtures of VIX futures that enable stock-like trading in volatility. InterpretationThe VIX is quoted in percentage points and represents the expected range of movement in the S&P 500 index over the next year, at a 68% confidence level (i.e. one standard deviation of the normal probability curve). For example, if the VIX is 15, this represents an expected annualized change, with a 68% probability, of less than 15% up or down. The expected volatility range for a single month can be calculated from this figure by dividing the VIX figure of 15 not by 12, but by {{sqrt|12}} which would imply a range of +/- 4.33% over the next 30-day period.[5] Similarly, expected volatility for a week would be 15 divided by {{sqrt|52}}, or +/- 2.08%. The VIX uses calendar day annualization so the conversion of 15% is 15 divided by {{sqrt|365}}, or +/- 0.79% per day. The calendar day approach does not account for the number trading days in a calendar year (that is, the fact that markets are not open on weekends or holidays). Trading days typically amount to 252 days out of a given calendar year. The price of call and put options can be used to calculate implied volatility, because volatility is one of the factors used to calculate the value of these options. Higher volatility of the underlying security makes an option more valuable, because there is a greater probability that the option will expire in the money (i.e., with a market value above zero). Thus, a higher option price implies greater volatility, other things being equal. Even though the VIX is quoted as a percentage rather than a dollar amount, multiple VIX-based derivative instruments are in existence (totaling roughly $4 Billion in AUM),[6] including:
Similar indices for bonds include the MOVE and LBPX indices. Although the VIX is often called the "fear index", a high VIX is not necessarily bearish for stocks.[7] Instead, the VIX is a measure of market perceived volatility in either direction, including to the upside. In practical terms, when investors anticipate large upside volatility, they are unwilling to sell upside call stock options unless they receive a large premium. Option buyers are willing to pay such high premiums only if similarly anticipating a large upside move. The resulting aggregate of increases in upside stock option call prices raises the VIX just as the aggregate growth in downside stock put option premiums that occurs when option buyers and sellers anticipate a likely sharp move to the downside. When the market is believed as likely to soar as to plummet, writing any option that will cost the writer in the event of a sudden large move in either direction may look equally risky. Hence high VIX readings mean investors see significant risk that the market will move sharply, whether downward or upward. The highest VIX readings occur when investors anticipate that huge moves in either direction are likely. Only when investors perceive neither significant downside risk nor significant upside potential will the VIX be low. The Black–Scholes formula uses a model of stock price dynamics to estimate how an option’s value depends on the volatility of the underlying assets. CriticismsVIX is sometimes criticized as a prediction of future volatility. It instead is a measure of the current price of index options. Despite their sophisticated composition, critics claim the predictive power of most volatility forecasting models is similar to that of plain-vanilla measures, such as simple past volatility.[8][9][10] However, other works have countered that these critiques failed to correctly implement the more complicated models.[11] Some practitioners and portfolio managers seem to ignore or dismiss volatility forecasting models. For example, Nassim Taleb famously titled one of his Journal of Portfolio Management papers We Don't Quite Know What We are Talking About When We Talk About Volatility.[12] In a similar vein, Emanuel Derman expressed his disillusion with empirical models unsupported by theory.[13] He argues that, while "theories are attempts to uncover the hidden principles underpinning the world around us, as Albert Einstein did with his theory of relativity", we should remember that "models are metaphors -- analogies that describe one thing relative to another". Michael Harris argued that VIX just tracks the inverse of price and has no predictive power.[14][15] 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). Robert J. Shiller argued that it would be circular reasoning to consider VIX to be proof of Black-Scholes, because they both express the same implied volatility. He also finds that calculating VIX retrospectively in 1929 does not predict the highest-ever volatility of the Great Depression, due to the anomalous conditions of the event, VIX cannot predict, even weakly, any future severe events.[16] 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.[17] Academic study has also examined potential methods of VIX manipulation.[18] HistoryHere is a timeline of some key events in the history of the VIX Index:
Between 1990 and October 2008, the average value of VIX was 19.04. In 2004 and 2006, VIX Futures and VIX Options, respectively, were named Most Innovative Index Product at the Super Bowl of Indexing Conference.[25] See also
Bibliography
References1. ^{{cite journal|last=Brenner|first1= Menachem |last2=Galai |first2=Dan|title=New Financial Instruments for Hedging Changes in Volatility |journal=Financial Analysts Journal |date=July–August 1989 |url= http://people.stern.nyu.edu/mbrenner/research/FAJ_articleon_Volatility_Der.pdf}} 2. ^{{cite journal|last=Brenner|first1= Menachem |last2=Galai |first2=Dan |title=Hedging Volatility in Foreign Currencies |journal=The Journal of Derivatives|date= Fall 1993 |url=http://people.stern.nyu.edu/mbrenner/research/JOD_article_of_Vol_Index_Computation.pdf}} 3. ^{{cite web|url=http://cfe.cboe.com/products/spec_vix.aspx|author=CBOE|title=Contract Specifications: CBOE Volatility Index (VX) Futures|date=26 March 2004|accessdate=7 March 2017}} 4. ^{{cite web| title= VIX White Paper| url= http://www.cboe.com/micro/vix/vixwhite.pdf| accessdate= 2010-09-20| format= PDF}} 5. ^Note that the divisor for a single month is {{sqrt|12}}, and not 12. See the definition volatility for a discussion of computing inter-period volatility. 6. ^{{Cite news|url=https://www.rcmalternatives.com/2017/05/seller-beware-everybodys-short-vix-these-days/|title=Seller Beware: Everybody's Short VIX These Days|date=2017-05-09|work=RCM Alternatives|access-date=2017-09-18}} 7. ^{{cite web|url=http://www.wallstreetdaily.com/2011/08/10/picture-perfect-trade-this-market/|title=A Picture Perfect Trade for This Market|date=10 August 2011|publisher=}} 8. ^{{cite journal |last=Cumby |first=R. |first2=S. |last2=Figlewski |first3=J. |last3=Hasbrouck |year=1993 |title=Forecasting Volatility and Correlations with EGARCH models |journal=Journal of Derivatives |volume=1 |issue=2 |pages=51–63 |doi=10.3905/jod.1993.407877 }} 9. ^{{cite journal |last=Jorion |first=P. |year=1995 |title=Predicting Volatility in Foreign Exchange Market |journal=Journal of Finance |volume=50 |issue=2 |pages=507–528 |jstor=2329417 |doi=10.1111/j.1540-6261.1995.tb04793.x}} 10. ^{{cite journal |last=Adhikari |first=B. |first2=J. |last2=Hilliard|year=2014|title= The VIX, VXO and realised volatility: a test of lagged and contemporaneous relationships|journal=International Journal of Financial Markets and Derivatives|volume=3 |issue=3|pages=222–240|doi=10.1504/IJFMD.2014.059637}} 11. ^{{cite journal |first=Torben G. |last=Andersen |first2=Tim |last2=Bollerslev |title=Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts |journal=International Economic Review |year=1998 |volume=39 |issue=4 |pages=885–905 |doi= |jstor=2527343 }} 12. ^{{cite web|url=https://papers.ssrn.com/abstract=970480|title=We Don't Quite Know What We are Talking About When We Talk About Volatility|first1=Daniel G.|last1=Goldstein|first2=Nassim Nicholas|last2=Taleb|date=28 March 2007|publisher=|via=papers.ssrn.com}} 13. ^Derman, Emanuel (2011): Models.Behaving.Badly: Why Confusing Illusion With Reality Can Lead to Disaster, on Wall Street and in Life”, Ed. Free Press. 14. ^{{cite web|url=http://www.priceactionlab.com/Blog/2012/08/on-the-zero-predictive-capacity-of-vix/|title=On the Zero Predictive Capacity of VIX - Price Action Lab Blog|website=www.priceactionlab.com}} 15. ^{{cite web|url=http://www.priceactionlab.com/Blog/2012/08/further-analytical-evidence-that-vix-just-tracks-the-inverse-of-price/|title=Further Analytical Evidence that VIX Just Tracks the Inverse of Price - Price Action Lab Blog|website=www.priceactionlab.com}} 16. ^ {{Webarchive|url=https://web.archive.org/web/20160922071546/http://oyc.yale.edu/transcript/1086/econ-252-11 |date=2016-09-22 }} 17. ^https://www.ft.com/content/a89eba68-10b4-11e8-940e-08320fc2a277 18. ^{{cite web|url=https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2972979|author1=John M. Griffin|author2=Amin Shams|title=Manipulation in the VIX?|date=May 23, 2017|accessdate=May 4, 2018}} 19. ^{{Cite web|url=http://people.stern.nyu.edu/mbrenner/research/FAJ_articleon_Volatility_Der.pdf|title=|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=}} 20. ^{{Cite web|url=http://people.stern.nyu.edu/mbrenner/research/IFR_report_on_Brenner-Galai_Sigma_Index.pdf|title=|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=}} 21. ^{{Cite web|url=http://rewconsulting.files.wordpress.com/2012/09/jd93.pdf|title=|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=}} 22. ^{{cite web|url=http://statisticalideas.blogspot.com/2015/07/volatility-in-motion.html|title=Volatility in motion|publisher=}} 23. ^{{Cite web|url=http://www.cboe.com/micro/vix/vixwhite.pdf|title=|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=}} 24. ^{{cite web|url=https://www.marketwatch.com/investing/index/vix|title=CBOE Volatility Index|website=MarketWatch}} 25. ^{{cite web |title = Index Product Awards |url = https://indexbusinessassociation.org/resources_and_research/industry_awards.htm |accessdate = 2008-01-05}}{{Dead link|date=July 2018 |bot=InternetArchiveBot |fix-attempted=yes }} 26. ^{{cite web|url=http://www.policyuncertainty.com/us_monthly.html|title=Economic Policy Uncertainty|author=Scott Baker, Nick Bloom, Steven Davis|accessdate=6 July 2017}} 27. ^{{cite web|url=https://fred.stlouisfed.org/series/USEPUINDXD|title= Economic Policy Uncertainty Index for United States (USEPUINDXD)|author=Federal Reserve Bank of St. Louis|accessdate=6 July 2017}} External links
4 : American stock market indices|Derivatives (finance)|Mathematical finance|Technical analysis |
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