31:
891:
To annualize this, you can use the "rule of 16", that is, multiply by 16 to get 16% as the annual volatility. The rationale for this is that 16 is the square root of 256, which is approximately the number of trading days in a year (252). This also uses the fact that the standard deviation of the sum
862:
One method of measuring
Volatility, often used by quant option trading firms, divides up volatility into two components. Clean volatility - the amount of volatility caused standard events like daily transactions and general noise - and dirty vol, the amount caused by specific events like earnings or
762:
For example, a lower volatility stock may have an expected (average) return of 7%, with annual volatility of 5%. Ignoring compounding effects, this would indicate returns from approximately negative 3% to positive 17% most of the time (19 times out of 20, or 95% via a two standard deviation rule). A
840:
Measures of volatility depend not only on the period over which it is measured, but also on the selected time resolution, as the information flow between short-term and long-term traders is asymmetric. As a result, volatility measured with high resolution contains information that is not covered by
1254:
Despite the sophisticated composition of most volatility forecasting models, critics claim that their predictive power is similar to that of plain-vanilla measures, such as simple past volatility especially out-of-sample, where different data are used to estimate the models and to test them. Other
853:
Some authors point out that realized volatility and implied volatility are backward and forward looking measures, and do not reflect current volatility. To address that issue an alternative, ensemble measures of volatility were suggested. One of the measures is defined as the standard deviation of
870:
Breaking down volatility into two components is useful in order to accurately price how much an option is worth, especially when identifying what events may contribute to a swing. The job of fundamental analysts at market makers and option trading boutique firms typically entails trying to assign
167:
that the instrument's price will be farther away from the initial price as time increases. However, rather than increase linearly, the volatility increases with the square-root of time as time increases, because some fluctuations are expected to cancel each other out, so the most likely deviation
1273:
expressed his disillusion with the enormous supply of empirical models unsupported by theory. 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
887:
Using a simplification of the above formula it is possible to estimate annualized volatility based solely on approximate observations. Suppose you notice that a market price index, which has a current value near 10,000, has moved about 100 points a day, on average, for many days. This would
759:), all differences are squared, so that negative and positive differences are combined into one quantity. Two instruments with different volatilities may have the same expected return, but the instrument with higher volatility will have larger swings in values over a given period of time.
1232:
1548:
Müller, Ulrich A.; Dacorogna, Michel M.; Olsen, Richard B.; Pictet, Olivier V.; Schwarz, Matthias; Morgenegg, Claude (1 December 1990). "Statistical study of foreign exchange rates, empirical evidence of a price change scaling law, and intraday analysis".
567:, or Wiener process, whose steps have finite variance. However, more generally, for natural stochastic processes, the precise relationship between volatility measures for different time periods is more complicated. Some use the Lévy stability exponent
844:
The risk parity weighted volatility of the three assets Gold, Treasury bonds and Nasdaq acting as proxy for the
Marketportfolio seems to have a low point at 4% after turning upwards for the 8th time since 1974 at this reading in the summer of 2014.
1061:
1239:(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
763:
higher volatility stock, with the same expected return of 7% but with annual volatility of 20%, would indicate returns from approximately negative 33% to positive 47% most of the time (19 times out of 20, or 95%). These estimates assume a
1214:
1134:
558:
342:
837:. Whether such large movements have the same direction, or the opposite, is more difficult to say. And an increase in volatility does not always presage a further increase—the volatility may simply go back down again.
275:
902:
The average magnitude of the observations is merely an approximation of the standard deviation of the market index. Assuming that the market index daily changes are normally distributed with mean zero and standard
401:
810:
It is common knowledge that many types of assets experience periods of high and low volatility. That is, during some periods, prices go up and down quickly, while during other times they barely move at all. In
464:
563:
The formulas used above to convert returns or volatility measures from one time period to another assume a particular underlying model or process. These formulas are accurate extrapolations of a
627:
664:
Much research has been devoted to modeling and forecasting the volatility of financial returns, and yet few theoretical models explain how volatility comes to exist in the first place.
88:
of a financial instrument for a specified period (for example 30 days or 90 days), based on historical prices over the specified period with the last observation the most recent price.
2287:
833:
Most typically, extreme movements do not appear 'out of nowhere'; they are presaged by larger movements than usual or by known uncertainty in specific future events. This is termed
899:
However importantly this does not capture (or in some cases may give excessive weight to) occasional large movements in market price which occur less frequently than once a year.
502:
2038:
Diebold, Francis X.; Hickman, Andrew; Inoue, Atsushi & Schuermannm, Til (1996) "Converting 1-Day
Volatility to h-Day Volatility: Scaling by sqrt(h) is Worse than You Think"
1407:
867:
would have clean volatility caused by people buying and selling on a daily basis but dirty (or event vol) events like quarterly earnings or a possibly anti-trust announcement.
671:. Glosten and Milgrom (1985) shows that at least one source of volatility can be explained by the liquidity provision process. When market makers infer the possibility of
117:
which refers to the volatility of a financial instrument over a specified period starting at the current time and ending at a future date (normally the expiry date of an
941:
1502:
722:
When cash flows from selling a security are needed at a specific future date to meet a known fixed liability, higher volatility means a greater chance of a shortfall;
712:
Volatility matters to investors for at least eight reasons, several of which are alternative statements of the same feature or are directly consequent on each other:
2136:
854:
ensemble returns instead of time series of returns. Another considers the regular sequence of directional-changes as the proxy for the instantaneous volatility.
2218:
834:
3078:
1143:"). Realistically, most financial assets have negative skewness and leptokurtosis, so this formula tends to be over-optimistic. Some people use the formula:
2280:
1149:
2019:
Derman, Emanuel (2011): Models.Behaving.Badly: Why
Confusing Illusion With Reality Can Lead to Disaster, on Wall Street and in Life”, Ed. Free Press.
1072:
510:
1250:
shown. Note that VIX has virtually the same predictive power as past volatility, insofar as the shown correlation coefficients are nearly identical.
297:
230:
2273:
353:
2518:
2165:
1436:
Glosten, L. R. and P. R. Milgrom (1985): "Bid, Ask and
Transaction Prices in a Specialist Market with Heterogeneously Informed Traders",
826:) are often followed by prices going down even more, or going up by an unusual amount. Also, a time when prices rise quickly (a possible
423:
3694:
3386:
3292:
3217:
2120:
1953:
Andersen, Torben G.; Bollerslev, Tim (1998). "Answering the
Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts".
191:
of a sequence of random variables, each of which is the return of the fund over some corresponding sequence of (equally sized) times.
1456:
94:
which refers to the volatility of a financial instrument over a specified period but with the last observation on a date in the past
728:
Higher volatility of returns after retirement may result in withdrawals having a larger permanent impact on the portfolio's value;
3367:
3071:
2543:
3699:
3520:
3444:
1265:
179:". Volatility is a statistical measure of dispersion around the average of any random variable such as market parameters etc.
1628:
1534:
1438:
1382:
725:
Higher volatility of returns while saving for retirement results in a wider distribution of possible final portfolio values;
3727:
3101:
2537:
1955:
783:
equation assumes predictable constant volatility, this is not observed in real markets. Amongst more realistic models are
1627:
Muller, Ulrich A.; Dacorogna, Michel; Dave, Rakhal D.; Olsen, Richard; Pictet, Olivier V.; von Weizsäcker, Jakob (1997).
731:
Price volatility presents opportunities to anyone with inside information to buy assets cheaply and sell when overpriced;
577:
3237:
3202:
3020:
2960:
2756:
2662:
1255:
works have agreed, but claim critics failed to correctly implement the more complicated models. Some practitioners and
896:
independent variables (with equal standard deviations) is √n times the standard deviation of the individual variables.
3732:
3064:
2746:
2714:
2618:
2572:
2555:
2508:
751:
Volatility does not measure the direction of price changes, merely their dispersion. This is because when calculating
136:
which refers to the implied volatility observed from historical prices of the financial instrument (normally options)
69:
looks forward in time, being derived from the market price of a market-traded derivative (in particular, an option).
3398:
2531:
2525:
2056:
Excerpt from
Enhanced Call Overwriting, a report by Ryan Renicker and Devapriya Mallick at Lehman Brothers (2005).
3449:
3207:
3157:
3621:
803:
where volatility jumps to new levels with a predictable frequency, and the increasingly popular Heston model of
3232:
2920:
2595:
2158:
51:
3410:
1825:
Cumby, R.; Figlewski, S.; Hasbrouck, J. (1993). "Forecasting
Volatility and Correlations with EGARCH models".
739:
3479:
3392:
2874:
2735:
2630:
2513:
1897:
812:
3555:
3352:
3316:
3162:
3116:
2762:
1964:
1909:
1289:
1269:
papers "We Don't Quite Know What We are
Talking About When We Talk About Volatility". In a similar note,
879:
There exist several known parametrisations of the implied volatility surface, Schonbucher, SVI and gSVI.
3537:
3485:
3362:
2900:
2709:
2213:
2208:
2198:
1795:
1695:
1482:
804:
668:
472:
3689:
3633:
3302:
2955:
2720:
2704:
2667:
2549:
2492:
2460:
2234:
1724:"Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time"
1586:"Instantaneous Volatility Seasonality of High-Frequency Markets in Directional-Change Intrinsic Time"
1420:
Roll, R. (1984): "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market",
645:
644: < 2 for financial activities such as stocks, indexes and so on. This was discovered by
172:
163:, the width of the distribution increases as time increases. This is because there is an increasing
1914:
3679:
3496:
3490:
3343:
3279:
3261:
3252:
3212:
2965:
2910:
2834:
2694:
2624:
2453:
2426:
2151:
1295:
764:
649:
2814:
1969:
1056:{\displaystyle \log(1+y)=y-{\tfrac {1}{2}}y^{2}+{\tfrac {1}{3}}y^{3}-{\tfrac {1}{4}}y^{4}+\cdots }
3602:
3574:
3465:
3087:
3005:
2980:
2940:
2925:
2844:
2783:
2741:
2485:
2395:
2385:
2188:
2130:
2091:
1982:
1935:
1879:
1862:
1842:
1675:
1256:
908:
827:
823:
816:
752:
188:
126:
66:
59:
55:
2047:
1813:
2068:
1364:
788:
142:
which refers to the implied volatility observed from current prices of the financial instrument
3737:
3613:
3543:
3438:
3297:
3137:
2869:
2854:
2606:
2116:
2103:
2099:
1927:
1687:
1683:
1666:
Sarkissian, Jack (2016). "Express Measurement of Market Volatility Using Ergodicity Concept".
1648:
1566:
1401:
1240:
923:. The net effect is that this crude approach underestimates the true volatility by about 20%.
719:
Price volatility of a trading instrument can help to determine position sizing in a portfolio;
672:
148:
which refers to the implied volatility observed from future prices of the financial instrument
106:
2053:
1304: – Intraday, VIX-like volatility index for US securities and exchange traded instruments
3586:
3525:
3512:
3473:
3454:
3167:
2970:
2890:
2686:
2567:
2443:
2362:
2318:
2296:
2203:
2193:
2083:
1974:
1919:
1871:
1834:
1790:
Babak Mahdavi Damghani & Andrew Kos (2013). "De-arbitraging with a weak smile". Wilmott.
1745:
1735:
1667:
1640:
1607:
1597:
1558:
1328:
796:
735:
118:
109:, in turn calculated using the sum of squared returns divided by the number of observations.
2054:
Research paper including excerpt from report entitled Identifying Rich and Cheap Volatility
1629:"Volatilities of different time resolutions -- Analyzing the dynamics of market components"
675:, they adjust their trading ranges, which in turn increases the band of price oscillation.
3591:
3580:
3287:
3222:
3106:
3045:
3040:
2975:
2950:
2885:
2859:
2839:
2798:
2793:
2788:
2773:
2768:
2656:
2590:
2582:
2470:
2357:
2244:
1808:
1708:
1495:
1463:
1345:
1340:
830:) may often be followed by prices going up even more, or going down by an unusual amount.
800:
1765:
716:
The wider the swings in an investment's price, the harder emotionally it is to not worry;
2042:
1516:
3674:
3627:
3549:
3426:
3404:
3227:
3197:
3192:
3000:
2995:
2895:
2880:
2641:
2636:
2601:
2400:
2367:
2313:
2305:
2031:
1875:
1334:
1307:
1283:
1270:
1140:
784:
679:
637:
202:
160:
1644:
171:
Since observed price changes do not follow Gaussian distributions, others such as the
3721:
3649:
3432:
3242:
3184:
2864:
2849:
2824:
2778:
2730:
2433:
2390:
2377:
2328:
2087:
1939:
1846:
1679:
1562:
932:
780:
694:
17:
2095:
1292: – Statistical property quantifying how much a collection of data is spread out
280:
Therefore, if the daily logarithmic returns of a stock have a standard deviation of
3704:
3501:
3378:
3121:
3025:
2945:
2915:
2905:
2725:
2699:
2448:
2438:
2421:
2352:
2347:
2323:
1260:
792:
686:
683:
218:
2050:
Example based on Google daily return distribution using standard density function
1259:
seem to completely ignore or dismiss volatility forecasting models. For example,
1139:
Volatility thus mathematically represents a drag on the CAGR (formalized as the "
3684:
3654:
3531:
3329:
3142:
3030:
3010:
2990:
2985:
2930:
2819:
2751:
1244:
1209:{\displaystyle \mathrm {CAGR} \approx \mathrm {AR} -{\tfrac {1}{2}}k\sigma ^{2}}
564:
164:
156:
102:
1129:{\displaystyle \mathrm {CAGR} \approx \mathrm {AR} -{\tfrac {1}{2}}\sigma ^{2}}
553:{\displaystyle \sigma _{\text{monthly}}=0.01{\sqrt {\tfrac {252}{12}}}=0.0458.}
3421:
3152:
3147:
3111:
3015:
2935:
2612:
2475:
2001:"We Don't Quite Know What We are Talking About When We Talk About Volatility"
1931:
1652:
1570:
3324:
2651:
2646:
2561:
2480:
1838:
864:
337:{\displaystyle \sigma _{\text{annually}}=\sigma _{\text{daily}}{\sqrt {P}}.}
187:
For any fund that evolves randomly with time, volatility is defined as the
1331: – Implied volatility patterns that arise in pricing financial options
34:
CBOE Volatility Index (VIX) from December 1985 to May 2012 (daily closings)
2037:
2829:
2465:
2239:
2113:
Option Volatility and Pricing: Advanced Trading Strategies and Techniques
1740:
1723:
1671:
1602:
1585:
768:
756:
176:
153:
1750:
1612:
1286: – Expected change in price of a stock relative to the whole market
270:{\displaystyle \sigma _{\text{T}}=\sigma _{\text{annually}}{\sqrt {T}}.}
2673:
2043:
A short introduction to alternative mathematical concepts of volatility
1986:
1883:
1860:
Jorion, P. (1995). "Predicting Volatility in Foreign Exchange Market".
698:
690:
39:
1900:; Persand, Gita (2003). "Volatility forecasting for risk management".
396:{\displaystyle \sigma _{\text{T}}=\sigma _{\text{daily}}{\sqrt {PT}}.}
3056:
2416:
2067:
Bartram, Söhnke M.; Brown, Gregory W.; Stulz, Rene M. (August 2012).
2265:
1978:
1923:
1274:
metaphors – analogies that describe one thing relative to another".
2000:
459:{\displaystyle \sigma _{\text{annually}}=0.01{\sqrt {252}}=0.1587.}
65:
Historic volatility measures a time series of past market prices.
2339:
1457:""Riding on a Smile." RISK, 7(2) Feb.1994, pp. 139–145, pp. 32–39"
1230:
47:
29:
3415:
3269:
1316:
1298: – Academic discipline concerned with the exchange of money
701:
3060:
2269:
2147:
168:
after twice the time will not be twice the distance from zero.
3596:
2254:
2249:
1322:
1301:
1236:
1231:
30:
2143:
1814:
http://www.readcube.com/articles/10.1002/wilm.10201?locale=en
648:, who looked at cotton prices and found that they followed a
54:
of a trading price series over time, usually measured by the
1722:
Petrov, Vladimir; Golub, Anton; Olsen, Richard (June 2019).
1584:
Petrov, Vladimir; Golub, Anton; Olsen, Richard (June 2019).
1535:"Taking Advantage Of Volatility Spikes With Credit Spreads"
2032:
Graphical Comparison of Implied and Historical Volatility
1383:"Calculating Historical Volatility: Step-by-Step Example"
27:
Degree of variation of a trading price series over time
1182:
1105:
1026:
1001:
976:
656: = 1.7. (See New Scientist, 19 April 1997.)
640:
scaling relation is obtained, but some people believe
532:
483:
175:
are often used. These can capture attributes such as "
1999:
Goldstein, Daniel and Taleb, Nassim, (28 March 2007)
1152:
1075:
944:
580:
513:
475:
426:
356:
300:
233:
1312:
Pages displaying wikidata descriptions as a fallback
201:
is the standard deviation of an instrument's yearly
3667:
3642:
3612:
3565:
3511:
3464:
3377:
3351:
3342:
3315:
3278:
3260:
3251:
3183:
3176:
3130:
3094:
2807:
2682:
2581:
2501:
2409:
2376:
2337:
2303:
2227:
2181:
2048:
Volatility estimation from predicted return density
863:policy announcements. For instance, a company like
767:; in reality stock price movements are found to be
622:{\displaystyle \sigma _{T}=T^{1/\alpha }\sigma .\,}
1208:
1128:
1055:
621:
552:
496:
458:
395:
336:
269:
667:Roll (1984) shows that volatility is affected by
152:For a financial instrument whose price follows a
1406:: CS1 maint: bot: original URL status unknown (
1223:is an empirical factor (typically five to ten).
410:= 252 trading days in any given year. Then, if
1319: – Possibility of something bad happening
927:Estimate of compound annual growth rate (CAGR)
291:in trading days, the annualized volatility is
3072:
2281:
2159:
1388:. Archived from the original on 30 March 2012
835:autoregressive conditional heteroskedasticity
8:
888:constitute a 1% daily movement, up or down.
1227:Criticisms of volatility forecasting models
858:Volatility as it Relates to Options Trading
77:Volatility as described here refers to the
3348:
3257:
3180:
3079:
3065:
3057:
2288:
2274:
2266:
2166:
2152:
2144:
2135:: CS1 maint: location missing publisher (
841:low resolution volatility and vice versa.
1968:
1913:
1749:
1739:
1611:
1601:
1501:CS1 maint: multiple names: authors list (
1200:
1181:
1170:
1153:
1151:
1120:
1104:
1093:
1076:
1074:
1066:Taking only the first two terms one has:
1041:
1025:
1016:
1000:
991:
975:
943:
618:
602:
598:
585:
579:
530:
518:
512:
482:
474:
443:
431:
425:
380:
374:
361:
355:
324:
318:
305:
299:
257:
251:
238:
232:
1728:Journal of Risk and Financial Management
1590:Journal of Risk and Financial Management
1356:
2128:
1804:
1793:
1704:
1693:
1491:
1480:
1399:
819:with periods of one day and one week.
3416:Moving average convergence/divergence
417:= 0.01, the annualized volatility is
7:
2069:"Why Are U.S. Stocks More Volatile?"
822:Periods when prices fall quickly (a
1876:10.1111/j.1540-6261.1995.tb04793.x
1174:
1171:
1163:
1160:
1157:
1154:
1097:
1094:
1086:
1083:
1080:
1077:
875:Implied volatility parametrisation
849:Alternative measures of volatility
571:to extrapolate natural processes:
497:{\displaystyle T={\tfrac {1}{12}}}
287:and the time period of returns is
25:
1337: – Mathematical finance term
871:numeric values to these numbers.
2544:Electronic communication network
2088:10.1111/j.1540-6261.2012.01749.x
1551:Journal of Banking & Finance
2005:Journal of Portfolio Management
1266:Journal of Portfolio Management
815:, price changes are seasonally
3521:Accumulation/distribution line
1455:Derman, E., Iraj Kani (1994).
1439:Journal of Financial Economics
963:
951:
734:Volatility affects pricing of
650:Lévy alpha-stable distribution
194:Thus, "annualized" volatility
1:
2538:Multilateral trading facility
2115:(Second ed.). New York.
1956:International Economic Review
1645:10.1016/S0927-5398(97)00007-8
909:magnitude of the observations
697:combining volatility and the
469:The monthly volatility (i.e.
134:historical implied volatility
3597:CBOE Market Volatility Index
3238:Triple top and triple bottom
3203:Double top and double bottom
2961:Returns-based style analysis
2757:Post-modern portfolio theory
2663:Security characteristic line
1633:Journal of Empirical Finance
1563:10.1016/0378-4266(90)90009-Q
1219:for a rough estimate, where
907:, the expected value of the
406:A common assumption is that
92:actual historical volatility
2715:Efficient-market hypothesis
2619:Capital asset pricing model
2556:Straight-through processing
2111:Natenberg, Sheldon (2015).
1263:famously titled one of his
883:Crude volatility estimation
747:Volatility versus direction
738:, being a parameter of the
208:The generalized volatility
3754:
3405:Know sure thing oscillator
3399:Detrended price oscillator
2532:Alternative Trading System
224:in years is expressed as:
140:current implied volatility
3387:Average directional index
682:determined the effect of
146:future implied volatility
86:actual current volatility
2596:Arbitrage pricing theory
1325: – Volatility index
1310: – French economist
1245:correlation coefficients
708:Volatility for investors
115:actual future volatility
3480:Relative strength index
3393:Commodity channel index
2875:Initial public offering
2736:Modern portfolio theory
2631:Dividend discount model
2514:List of stock exchanges
1839:10.3905/jod.1993.407877
1766:"Cleaning Implied Vols"
813:foreign exchange market
183:Mathematical definition
3117:Elliott wave principle
2763:Random walk hypothesis
1902:Journal of Forecasting
1827:Journal of Derivatives
1803:Cite journal requires
1703:Cite journal requires
1490:Cite journal requires
1462:. Risk. Archived from
1251:
1210:
1130:
1057:
623:
554:
498:
460:
397:
338:
271:
73:Volatility terminology
35:
3538:Negative volume index
3486:Stochastic oscillator
3363:Fibonacci retracement
2901:Market capitalization
2710:Dollar cost averaging
2214:Jump-diffusion models
2209:Stochastic volatility
2199:Volatility clustering
1234:
1211:
1131:
1058:
805:stochastic volatility
669:market microstructure
624:
555:
499:
461:
398:
339:
272:
81:, more specifically:
46:(usually denoted by "
33:
18:Historical volatility
3728:Mathematical finance
3690:Ralph Nelson Elliott
3634:McClellan oscillator
3622:Advance–decline line
3303:Three white soldiers
2721:Fundamental analysis
2705:Contrarian investing
2668:Security market line
2573:Liquidity aggregator
2550:Direct market access
2461:Quantitative analyst
2235:Volatility arbitrage
2182:Modelling volatility
1741:10.3390/jrfm12020054
1672:10.2139/ssrn.2812353
1603:10.3390/jrfm12020054
1150:
1073:
942:
775:Volatility over time
693:, and called it the
578:
511:
473:
424:
354:
298:
231:
3497:Ultimate oscillator
3491:True strength index
3158:Open-high-low-close
2966:Reverse stock split
2911:Market manipulation
2835:Dual-listed company
2695:Algorithmic trading
2625:Capital market line
2427:Inter-dealer broker
1365:"Levy distribution"
1296:Financial economics
1243:, resulting in the
765:normal distribution
740:Black–Scholes model
678:In September 2019,
636: = 2 the
203:logarithmic returns
99:realized volatility
97:near synonymous is
60:logarithmic returns
52:degree of variation
3733:Technical analysis
3603:Standard deviation
3575:Average true range
3556:Volume–price trend
3411:Ichimoku Kinkō Hyō
3218:Head and shoulders
3088:Technical analysis
3006:Stock market index
2845:Efficient frontier
2784:Technical analysis
2742:Momentum investing
2564:(private exchange)
2454:Proprietary trader
2396:Shares outstanding
2386:Authorised capital
2228:Trading volatility
2189:Implied volatility
2076:Journal of Finance
1863:Journal of Finance
1422:Journal of Finance
1257:portfolio managers
1252:
1241:linear regressions
1206:
1191:
1126:
1114:
1053:
1035:
1010:
985:
753:standard deviation
619:
550:
541:
494:
492:
456:
393:
334:
267:
189:standard deviation
127:implied volatility
67:Implied volatility
56:standard deviation
36:
3713:
3712:
3663:
3662:
3544:On-balance volume
3439:Smart money index
3338:
3337:
3311:
3310:
3298:Three black crows
3054:
3053:
2855:Flight-to-quality
2607:Buffett indicator
2297:Financial markets
2263:
2262:
1190:
1113:
1034:
1009:
984:
673:adverse selection
660:Volatility origin
646:Benoît Mandelbrot
542:
540:
521:
491:
448:
434:
388:
377:
364:
329:
321:
308:
262:
254:
241:
173:Lévy distribution
107:realized variance
79:actual volatility
16:(Redirected from
3745:
3587:Donchian channel
3526:Ease of movement
3474:Money flow index
3455:Vortex indicator
3349:
3317:Point and figure
3258:
3208:Flag and pennant
3181:
3163:Point and figure
3081:
3074:
3067:
3058:
2971:Share repurchase
2683:Trading theories
2568:Crossing network
2526:Over-the-counter
2363:Restricted stock
2319:Secondary market
2290:
2283:
2276:
2267:
2204:Local volatility
2194:Volatility smile
2168:
2161:
2154:
2145:
2140:
2134:
2126:
2107:
2082:(4): 1329–1370.
2073:
2020:
2017:
2011:
1997:
1991:
1990:
1972:
1950:
1944:
1943:
1917:
1894:
1888:
1887:
1857:
1851:
1850:
1822:
1816:
1812:
1806:
1801:
1799:
1791:
1787:
1781:
1780:
1778:
1776:
1762:
1756:
1755:
1753:
1743:
1719:
1713:
1712:
1706:
1701:
1699:
1691:
1663:
1657:
1656:
1639:(2–3): 213–239.
1624:
1618:
1617:
1615:
1605:
1581:
1575:
1574:
1557:(6): 1189–1208.
1545:
1539:
1538:
1531:
1525:
1524:
1513:
1507:
1506:
1499:
1493:
1488:
1486:
1478:
1476:
1474:
1468:
1461:
1452:
1446:
1434:
1428:
1418:
1412:
1411:
1405:
1397:
1395:
1393:
1387:
1379:
1373:
1372:
1361:
1329:Volatility smile
1313:
1215:
1213:
1212:
1207:
1205:
1204:
1192:
1183:
1177:
1166:
1135:
1133:
1132:
1127:
1125:
1124:
1115:
1106:
1100:
1089:
1062:
1060:
1059:
1054:
1046:
1045:
1036:
1027:
1021:
1020:
1011:
1002:
996:
995:
986:
977:
914:
797:local volatility
628:
626:
625:
620:
611:
610:
606:
590:
589:
559:
557:
556:
551:
543:
533:
531:
523:
522:
519:
503:
501:
500:
495:
493:
484:
465:
463:
462:
457:
449:
444:
436:
435:
432:
402:
400:
399:
394:
389:
381:
379:
378:
375:
366:
365:
362:
343:
341:
340:
335:
330:
325:
323:
322:
319:
310:
309:
306:
276:
274:
273:
268:
263:
258:
256:
255:
252:
243:
242:
239:
21:
3753:
3752:
3748:
3747:
3746:
3744:
3743:
3742:
3718:
3717:
3714:
3709:
3659:
3638:
3608:
3592:Keltner channel
3581:Bollinger Bands
3561:
3507:
3460:
3373:
3354:
3334:
3307:
3288:Hikkake pattern
3274:
3247:
3223:Island reversal
3172:
3126:
3107:Dead cat bounce
3090:
3085:
3055:
3050:
3041:Voting interest
2951:Public offering
2886:Mandatory offer
2860:Government bond
2840:DuPont analysis
2803:
2799:Value investing
2794:Value averaging
2789:Trend following
2774:Style investing
2769:Sector rotation
2684:
2678:
2657:Net asset value
2583:Stock valuation
2577:
2497:
2405:
2372:
2358:Preferred stock
2333:
2299:
2294:
2264:
2259:
2245:Volatility swap
2223:
2177:
2172:
2127:
2123:
2110:
2071:
2066:
2063:
2061:Further reading
2028:
2023:
2018:
2014:
1998:
1994:
1979:10.2307/2527343
1952:
1951:
1947:
1924:10.1002/for.841
1915:10.1.1.595.9113
1896:
1895:
1891:
1859:
1858:
1854:
1824:
1823:
1819:
1802:
1792:
1789:
1788:
1784:
1774:
1772:
1764:
1763:
1759:
1721:
1720:
1716:
1702:
1692:
1665:
1664:
1660:
1626:
1625:
1621:
1583:
1582:
1578:
1547:
1546:
1542:
1533:
1532:
1528:
1521:wilmottwiki.com
1515:
1514:
1510:
1500:
1489:
1479:
1472:
1470:
1469:on 10 July 2011
1466:
1459:
1454:
1453:
1449:
1435:
1431:
1419:
1415:
1398:
1391:
1389:
1385:
1381:
1380:
1376:
1369:wilmottwiki.com
1363:
1362:
1358:
1354:
1346:Volatility beta
1341:Volatility risk
1311:
1280:
1235:Performance of
1229:
1196:
1148:
1147:
1116:
1071:
1070:
1037:
1012:
987:
940:
939:
929:
912:
903:deviation
885:
877:
860:
851:
817:heteroskedastic
801:Poisson process
777:
749:
710:
662:
594:
581:
576:
575:
514:
509:
508:
471:
470:
427:
422:
421:
416:
370:
357:
352:
351:
314:
301:
296:
295:
286:
247:
234:
229:
228:
216:
200:
185:
125:Now turning to
75:
28:
23:
22:
15:
12:
11:
5:
3751:
3749:
3741:
3740:
3735:
3730:
3720:
3719:
3711:
3710:
3708:
3707:
3702:
3697:
3692:
3687:
3682:
3677:
3675:John Bollinger
3671:
3669:
3665:
3664:
3661:
3660:
3658:
3657:
3652:
3646:
3644:
3640:
3639:
3637:
3636:
3631:
3625:
3618:
3616:
3610:
3609:
3607:
3606:
3600:
3594:
3589:
3584:
3578:
3571:
3569:
3563:
3562:
3560:
3559:
3553:
3550:Put/call ratio
3547:
3541:
3535:
3529:
3523:
3517:
3515:
3509:
3508:
3506:
3505:
3499:
3494:
3488:
3483:
3477:
3470:
3468:
3462:
3461:
3459:
3458:
3452:
3447:
3442:
3436:
3430:
3427:Moving average
3424:
3419:
3413:
3408:
3402:
3396:
3390:
3383:
3381:
3375:
3374:
3372:
3371:
3365:
3359:
3357:
3346:
3340:
3339:
3336:
3335:
3333:
3332:
3327:
3321:
3319:
3313:
3312:
3309:
3308:
3306:
3305:
3300:
3295:
3290:
3284:
3282:
3276:
3275:
3273:
3272:
3266:
3264:
3255:
3249:
3248:
3246:
3245:
3240:
3235:
3230:
3228:Price channels
3225:
3220:
3215:
3210:
3205:
3200:
3198:Cup and handle
3195:
3193:Broadening top
3189:
3187:
3178:
3174:
3173:
3171:
3170:
3165:
3160:
3155:
3150:
3145:
3140:
3134:
3132:
3128:
3127:
3125:
3124:
3119:
3114:
3109:
3104:
3098:
3096:
3092:
3091:
3086:
3084:
3083:
3076:
3069:
3061:
3052:
3051:
3049:
3048:
3043:
3038:
3033:
3028:
3023:
3018:
3013:
3008:
3003:
3001:Stock exchange
2998:
2996:Stock dilution
2993:
2988:
2983:
2978:
2973:
2968:
2963:
2958:
2953:
2948:
2943:
2938:
2933:
2928:
2923:
2921:Mean reversion
2918:
2913:
2908:
2903:
2898:
2896:Market anomaly
2893:
2888:
2883:
2878:
2872:
2867:
2862:
2857:
2852:
2847:
2842:
2837:
2832:
2827:
2822:
2817:
2815:Bid–ask spread
2811:
2809:
2805:
2804:
2802:
2801:
2796:
2791:
2786:
2781:
2776:
2771:
2766:
2760:
2754:
2749:
2744:
2739:
2733:
2728:
2723:
2718:
2712:
2707:
2702:
2697:
2691:
2689:
2680:
2679:
2677:
2676:
2671:
2665:
2660:
2654:
2649:
2644:
2642:Earnings yield
2639:
2637:Dividend yield
2634:
2628:
2622:
2616:
2610:
2604:
2599:
2593:
2587:
2585:
2579:
2578:
2576:
2575:
2570:
2565:
2559:
2553:
2547:
2541:
2535:
2529:
2528:(off-exchange)
2523:
2522:
2521:
2516:
2505:
2503:
2502:Trading venues
2499:
2498:
2496:
2495:
2490:
2489:
2488:
2478:
2473:
2468:
2463:
2458:
2457:
2456:
2451:
2441:
2436:
2431:
2430:
2429:
2424:
2413:
2411:
2407:
2406:
2404:
2403:
2401:Treasury stock
2398:
2393:
2388:
2382:
2380:
2374:
2373:
2371:
2370:
2368:Tracking stock
2365:
2360:
2355:
2350:
2344:
2342:
2335:
2334:
2332:
2331:
2326:
2321:
2316:
2314:Primary market
2310:
2308:
2301:
2300:
2295:
2293:
2292:
2285:
2278:
2270:
2261:
2260:
2258:
2257:
2252:
2247:
2242:
2237:
2231:
2229:
2225:
2224:
2222:
2221:
2219:ARCH and GARCH
2216:
2211:
2206:
2201:
2196:
2191:
2185:
2183:
2179:
2178:
2173:
2171:
2170:
2163:
2156:
2148:
2142:
2141:
2122:978-0071818773
2121:
2108:
2062:
2059:
2058:
2057:
2051:
2045:
2040:
2035:
2027:
2026:External links
2024:
2022:
2021:
2012:
1992:
1963:(4): 885–905.
1945:
1889:
1870:(2): 507–528.
1852:
1817:
1805:|journal=
1782:
1757:
1714:
1705:|journal=
1658:
1619:
1576:
1540:
1526:
1508:
1492:|journal=
1447:
1429:
1427:(4), 1127–1139
1413:
1374:
1355:
1353:
1350:
1349:
1348:
1343:
1338:
1335:Volatility tax
1332:
1326:
1320:
1314:
1308:Jules Regnault
1305:
1299:
1293:
1287:
1284:Beta (finance)
1279:
1276:
1271:Emanuel Derman
1228:
1225:
1217:
1216:
1203:
1199:
1195:
1189:
1186:
1180:
1176:
1173:
1169:
1165:
1162:
1159:
1156:
1141:volatility tax
1137:
1136:
1123:
1119:
1112:
1109:
1103:
1099:
1096:
1092:
1088:
1085:
1082:
1079:
1064:
1063:
1052:
1049:
1044:
1040:
1033:
1030:
1024:
1019:
1015:
1008:
1005:
999:
994:
990:
983:
980:
974:
971:
968:
965:
962:
959:
956:
953:
950:
947:
928:
925:
884:
881:
876:
873:
859:
856:
850:
847:
785:Emanuel Derman
776:
773:
771:(fat-tailed).
748:
745:
744:
743:
732:
729:
726:
723:
720:
717:
709:
706:
680:JPMorgan Chase
661:
658:
638:Wiener process
630:
629:
617:
614:
609:
605:
601:
597:
593:
588:
584:
561:
560:
549:
546:
539:
536:
529:
526:
517:
504:of a year) is
490:
487:
481:
478:
467:
466:
455:
452:
447:
442:
439:
430:
414:
404:
403:
392:
387:
384:
373:
369:
360:
345:
344:
333:
328:
317:
313:
304:
284:
278:
277:
266:
261:
250:
246:
237:
212:
198:
184:
181:
161:Wiener process
150:
149:
143:
137:
123:
122:
112:
111:
110:
89:
74:
71:
26:
24:
14:
13:
10:
9:
6:
4:
3:
2:
3750:
3739:
3736:
3734:
3731:
3729:
3726:
3725:
3723:
3716:
3706:
3703:
3701:
3698:
3696:
3693:
3691:
3688:
3686:
3683:
3681:
3678:
3676:
3673:
3672:
3670:
3666:
3656:
3653:
3651:
3650:Coppock curve
3648:
3647:
3645:
3641:
3635:
3632:
3629:
3626:
3623:
3620:
3619:
3617:
3615:
3611:
3604:
3601:
3598:
3595:
3593:
3590:
3588:
3585:
3582:
3579:
3576:
3573:
3572:
3570:
3568:
3564:
3557:
3554:
3551:
3548:
3545:
3542:
3539:
3536:
3533:
3530:
3527:
3524:
3522:
3519:
3518:
3516:
3514:
3510:
3503:
3500:
3498:
3495:
3492:
3489:
3487:
3484:
3481:
3478:
3475:
3472:
3471:
3469:
3467:
3463:
3456:
3453:
3451:
3448:
3446:
3443:
3440:
3437:
3434:
3433:Parabolic SAR
3431:
3428:
3425:
3423:
3420:
3417:
3414:
3412:
3409:
3406:
3403:
3400:
3397:
3394:
3391:
3388:
3385:
3384:
3382:
3380:
3376:
3369:
3366:
3364:
3361:
3360:
3358:
3356:
3353:Support &
3350:
3347:
3345:
3341:
3331:
3328:
3326:
3323:
3322:
3320:
3318:
3314:
3304:
3301:
3299:
3296:
3294:
3291:
3289:
3286:
3285:
3283:
3281:
3277:
3271:
3268:
3267:
3265:
3263:
3259:
3256:
3254:
3250:
3244:
3243:Wedge pattern
3241:
3239:
3236:
3234:
3231:
3229:
3226:
3224:
3221:
3219:
3216:
3214:
3211:
3209:
3206:
3204:
3201:
3199:
3196:
3194:
3191:
3190:
3188:
3186:
3182:
3179:
3175:
3169:
3166:
3164:
3161:
3159:
3156:
3154:
3151:
3149:
3146:
3144:
3141:
3139:
3136:
3135:
3133:
3129:
3123:
3120:
3118:
3115:
3113:
3110:
3108:
3105:
3103:
3100:
3099:
3097:
3093:
3089:
3082:
3077:
3075:
3070:
3068:
3063:
3062:
3059:
3047:
3044:
3042:
3039:
3037:
3034:
3032:
3029:
3027:
3024:
3022:
3019:
3017:
3014:
3012:
3009:
3007:
3004:
3002:
2999:
2997:
2994:
2992:
2989:
2987:
2984:
2982:
2979:
2977:
2976:Short selling
2974:
2972:
2969:
2967:
2964:
2962:
2959:
2957:
2954:
2952:
2949:
2947:
2944:
2942:
2939:
2937:
2934:
2932:
2929:
2927:
2924:
2922:
2919:
2917:
2914:
2912:
2909:
2907:
2904:
2902:
2899:
2897:
2894:
2892:
2889:
2887:
2884:
2882:
2879:
2876:
2873:
2871:
2868:
2866:
2865:Greenspan put
2863:
2861:
2858:
2856:
2853:
2851:
2850:Financial law
2848:
2846:
2843:
2841:
2838:
2836:
2833:
2831:
2828:
2826:
2825:Cross listing
2823:
2821:
2818:
2816:
2813:
2812:
2810:
2808:Related terms
2806:
2800:
2797:
2795:
2792:
2790:
2787:
2785:
2782:
2780:
2779:Swing trading
2777:
2775:
2772:
2770:
2767:
2764:
2761:
2758:
2755:
2753:
2750:
2748:
2747:Mosaic theory
2745:
2743:
2740:
2737:
2734:
2732:
2731:Market timing
2729:
2727:
2724:
2722:
2719:
2716:
2713:
2711:
2708:
2706:
2703:
2701:
2698:
2696:
2693:
2692:
2690:
2688:
2681:
2675:
2672:
2669:
2666:
2664:
2661:
2658:
2655:
2653:
2650:
2648:
2645:
2643:
2640:
2638:
2635:
2632:
2629:
2626:
2623:
2620:
2617:
2614:
2611:
2608:
2605:
2603:
2600:
2597:
2594:
2592:
2589:
2588:
2586:
2584:
2580:
2574:
2571:
2569:
2566:
2563:
2560:
2557:
2554:
2551:
2548:
2545:
2542:
2539:
2536:
2533:
2530:
2527:
2524:
2520:
2519:Trading hours
2517:
2515:
2512:
2511:
2510:
2507:
2506:
2504:
2500:
2494:
2491:
2487:
2484:
2483:
2482:
2479:
2477:
2474:
2472:
2469:
2467:
2464:
2462:
2459:
2455:
2452:
2450:
2447:
2446:
2445:
2442:
2440:
2437:
2435:
2434:Broker-dealer
2432:
2428:
2425:
2423:
2420:
2419:
2418:
2415:
2414:
2412:
2408:
2402:
2399:
2397:
2394:
2392:
2391:Issued shares
2389:
2387:
2384:
2383:
2381:
2379:
2378:Share capital
2375:
2369:
2366:
2364:
2361:
2359:
2356:
2354:
2351:
2349:
2346:
2345:
2343:
2341:
2336:
2330:
2329:Fourth market
2327:
2325:
2322:
2320:
2317:
2315:
2312:
2311:
2309:
2307:
2302:
2298:
2291:
2286:
2284:
2279:
2277:
2272:
2271:
2268:
2256:
2253:
2251:
2248:
2246:
2243:
2241:
2238:
2236:
2233:
2232:
2230:
2226:
2220:
2217:
2215:
2212:
2210:
2207:
2205:
2202:
2200:
2197:
2195:
2192:
2190:
2187:
2186:
2184:
2180:
2176:
2169:
2164:
2162:
2157:
2155:
2150:
2149:
2146:
2138:
2132:
2124:
2118:
2114:
2109:
2105:
2101:
2097:
2093:
2089:
2085:
2081:
2077:
2070:
2065:
2064:
2060:
2055:
2052:
2049:
2046:
2044:
2041:
2039:
2036:
2033:
2030:
2029:
2025:
2016:
2013:
2009:
2006:
2002:
1996:
1993:
1988:
1984:
1980:
1976:
1971:
1970:10.1.1.28.454
1966:
1962:
1958:
1957:
1949:
1946:
1941:
1937:
1933:
1929:
1925:
1921:
1916:
1911:
1907:
1903:
1899:
1898:Brooks, Chris
1893:
1890:
1885:
1881:
1877:
1873:
1869:
1865:
1864:
1856:
1853:
1848:
1844:
1840:
1836:
1832:
1828:
1821:
1818:
1815:
1810:
1797:
1786:
1783:
1771:
1770:Moontowermeta
1767:
1761:
1758:
1752:
1747:
1742:
1737:
1733:
1729:
1725:
1718:
1715:
1710:
1697:
1689:
1685:
1681:
1677:
1673:
1669:
1662:
1659:
1654:
1650:
1646:
1642:
1638:
1634:
1630:
1623:
1620:
1614:
1609:
1604:
1599:
1595:
1591:
1587:
1580:
1577:
1572:
1568:
1564:
1560:
1556:
1552:
1544:
1541:
1536:
1530:
1527:
1522:
1518:
1512:
1509:
1504:
1497:
1484:
1465:
1458:
1451:
1448:
1444:
1441:
1440:
1433:
1430:
1426:
1423:
1417:
1414:
1409:
1403:
1384:
1378:
1375:
1370:
1366:
1360:
1357:
1351:
1347:
1344:
1342:
1339:
1336:
1333:
1330:
1327:
1324:
1321:
1318:
1315:
1309:
1306:
1303:
1300:
1297:
1294:
1291:
1288:
1285:
1282:
1281:
1277:
1275:
1272:
1268:
1267:
1262:
1258:
1249:
1246:
1242:
1238:
1233:
1226:
1224:
1222:
1201:
1197:
1193:
1187:
1184:
1178:
1167:
1146:
1145:
1144:
1142:
1121:
1117:
1110:
1107:
1101:
1090:
1069:
1068:
1067:
1050:
1047:
1042:
1038:
1031:
1028:
1022:
1017:
1013:
1006:
1003:
997:
992:
988:
981:
978:
972:
969:
966:
960:
957:
954:
948:
945:
938:
937:
936:
934:
933:Taylor series
931:Consider the
926:
924:
922:
918:
910:
906:
900:
897:
895:
889:
882:
880:
874:
872:
868:
866:
857:
855:
848:
846:
842:
838:
836:
831:
829:
825:
820:
818:
814:
808:
806:
802:
798:
794:
790:
786:
782:
781:Black-Scholes
779:Although the
774:
772:
770:
769:leptokurtotic
766:
760:
758:
754:
746:
741:
737:
733:
730:
727:
724:
721:
718:
715:
714:
713:
707:
705:
703:
700:
696:
695:Volfefe index
692:
688:
685:
681:
676:
674:
670:
665:
659:
657:
655:
651:
647:
643:
639:
635:
615:
612:
607:
603:
599:
595:
591:
586:
582:
574:
573:
572:
570:
566:
547:
544:
537:
534:
527:
524:
515:
507:
506:
505:
488:
485:
479:
476:
453:
450:
445:
440:
437:
428:
420:
419:
418:
413:
409:
390:
385:
382:
371:
367:
358:
350:
349:
348:
331:
326:
315:
311:
302:
294:
293:
292:
290:
283:
264:
259:
248:
244:
235:
227:
226:
225:
223:
220:
215:
211:
206:
204:
197:
192:
190:
182:
180:
178:
174:
169:
166:
162:
158:
155:
147:
144:
141:
138:
135:
132:
131:
130:
128:
120:
116:
113:
108:
104:
100:
96:
95:
93:
90:
87:
84:
83:
82:
80:
72:
70:
68:
63:
61:
57:
53:
49:
45:
41:
32:
19:
3715:
3705:Mark Hulbert
3566:
3293:Morning star
3122:Market trend
3035:
3026:Tender offer
2946:Public float
2916:Market trend
2906:Market depth
2726:Growth stock
2700:Buy and hold
2609:(Cap-to-GDP)
2449:Floor trader
2439:Market maker
2422:Floor broker
2410:Participants
2353:Golden share
2348:Common stock
2324:Third market
2174:
2112:
2079:
2075:
2015:
2007:
2004:
1995:
1960:
1954:
1948:
1905:
1901:
1892:
1867:
1861:
1855:
1833:(2): 51–63.
1830:
1826:
1820:
1796:cite journal
1785:
1773:. Retrieved
1769:
1760:
1751:10419/239003
1731:
1727:
1717:
1696:cite journal
1661:
1636:
1632:
1622:
1613:10419/239003
1593:
1589:
1579:
1554:
1550:
1543:
1529:
1520:
1517:"Volatility"
1511:
1483:cite journal
1471:. Retrieved
1464:the original
1450:
1442:
1437:
1432:
1424:
1421:
1416:
1390:. Retrieved
1377:
1368:
1359:
1264:
1261:Nassim Taleb
1253:
1247:
1220:
1218:
1138:
1065:
930:
920:
919:= 0.798
916:
904:
901:
898:
893:
890:
886:
878:
869:
861:
852:
843:
839:
832:
821:
809:
793:Bruno Dupire
778:
761:
750:
711:
687:Donald Trump
684:US President
677:
666:
663:
653:
641:
633:
631:
568:
562:
468:
411:
407:
405:
346:
288:
281:
279:
221:
219:time horizon
213:
209:
207:
195:
193:
186:
170:
151:
145:
139:
133:
124:
114:
98:
91:
85:
78:
76:
64:
43:
37:
3700:John Murphy
3695:Bob Farrell
3685:Charles Dow
3655:Ulcer index
3532:Force index
3502:Williams %R
3368:Pivot point
3253:Candlestick
3138:Candlestick
3031:Uptick rule
3011:Stock split
2991:Squeeze-out
2986:Speculation
2931:Open outcry
2820:Block trade
2752:Pairs trade
1908:(1): 1–22.
1445:(1), 71–100
565:random walk
165:probability
157:random walk
129:, we have:
103:square root
3722:Categories
3628:Arms index
3567:Volatility
3445:Trend line
3422:Mass index
3355:resistance
3344:Indicators
3168:Line break
3112:Dow theory
3036:Volatility
3016:Stock swap
2936:Order book
2687:strategies
2613:Book value
2481:Arbitrager
2476:Speculator
2175:Volatility
2010:(4), 2007.
1352:References
1290:Dispersion
50:") is the
44:volatility
3680:Ned Davis
3330:Bear trap
3325:Bull trap
2652:Fed model
2647:EV/EBITDA
2562:Dark pool
2493:Regulator
2338:Types of
2304:Types of
2131:cite book
1965:CiteSeerX
1940:154615850
1932:1099-131X
1910:CiteSeerX
1847:154028452
1734:(2): 54.
1680:168496910
1653:0927-5398
1596:(2): 54.
1571:0378-4266
1392:18 August
1198:σ
1179:−
1168:≈
1118:σ
1102:−
1091:≈
1051:⋯
1023:−
973:−
949:
865:Microsoft
789:Iraj Kani
613:σ
608:α
583:σ
516:σ
429:σ
372:σ
359:σ
316:σ
303:σ
249:σ
236:σ
177:fat tails
3738:Quantity
3668:Analysts
3466:Momentum
3389:(A.D.X.)
3233:Triangle
3177:Patterns
3102:Breakout
3095:Concepts
2981:Slippage
2941:Position
2926:Momentum
2830:Dividend
2509:Exchange
2466:Investor
2240:Straddle
2096:18587238
1402:cite web
1278:See also
791:'s and
757:variance
433:annually
307:annually
253:annually
199:annually
154:Gaussian
3614:Breadth
3280:Complex
2870:Haircut
2674:T-model
2486:Scalper
2306:markets
2104:2257549
2034:, video
1987:2527343
1884:2329417
1775:26 June
1688:2812353
911:is √(2/
736:options
699:covfefe
548:0.0458.
520:monthly
454:0.1587.
105:of the
40:finance
3630:(TRIN)
3513:Volume
3418:(MACD)
3262:Simple
3131:Charts
2891:Margin
2759:(PMPT)
2621:(CAPM)
2471:Hedger
2444:Trader
2417:Broker
2340:stocks
2119:
2102:
2094:
1985:
1967:
1938:
1930:
1912:
1882:
1845:
1686:
1678:
1651:
1569:
1473:1 June
828:bubble
691:tweets
119:option
101:, the
3643:Other
3624:(ADL)
3599:(VIX)
3577:(ATR)
3558:(VPT)
3552:(PCR)
3546:(OBV)
3540:(NVI)
3528:(EMV)
3493:(TSI)
3482:(RSI)
3476:(MFI)
3441:(SMI)
3435:(SAR)
3407:(KST)
3401:(DPO)
3395:(CCI)
3379:Trend
3185:Chart
3143:Renko
3046:Yield
3021:Trade
2956:Rally
2877:(IPO)
2765:(RMH)
2738:(MPT)
2717:(EMH)
2670:(SML)
2659:(NAV)
2633:(DDM)
2627:(CML)
2598:(APT)
2591:Alpha
2558:(STP)
2552:(DMA)
2546:(ECN)
2540:(MTF)
2534:(ATS)
2092:S2CID
2072:(PDF)
1983:JSTOR
1936:S2CID
1880:JSTOR
1843:S2CID
1676:S2CID
1467:(PDF)
1460:(PDF)
1386:(PDF)
824:crash
652:with
415:daily
376:daily
320:daily
285:daily
159:, or
3583:(BB)
3534:(FI)
3504:(%R)
3457:(VI)
3450:Trix
3429:(MA)
3370:(PP)
3270:Doji
3153:Line
3148:Kagi
2881:Long
2685:and
2615:(BV)
2602:Beta
2137:link
2117:ISBN
2100:SSRN
1928:ISSN
1809:help
1777:2024
1709:help
1684:SSRN
1649:ISSN
1567:ISSN
1503:link
1496:help
1475:2007
1408:link
1394:2011
1317:Risk
787:and
755:(or
702:meme
528:0.01
441:0.01
217:for
3605:(σ)
3213:Gap
2255:VIX
2250:IVX
2084:doi
1975:doi
1920:doi
1872:doi
1835:doi
1746:hdl
1736:doi
1668:doi
1641:doi
1608:hdl
1598:doi
1559:doi
1323:VIX
1302:IVX
1237:VIX
946:log
892:of
795:'s
689:'s
632:If
535:252
446:252
347:so
58:of
38:In
3724::
2133:}}
2129:{{
2098:.
2090:.
2080:67
2078:.
2074:.
2008:33
2003:.
1981:.
1973:.
1961:39
1959:.
1934:.
1926:.
1918:.
1906:22
1904:.
1878:.
1868:50
1866:.
1841:.
1829:.
1800::
1798:}}
1794:{{
1768:.
1744:.
1732:12
1730:.
1726:.
1700::
1698:}}
1694:{{
1682:.
1674:.
1647:.
1635:.
1631:.
1606:.
1594:12
1592:.
1588:.
1565:.
1555:14
1553:.
1519:.
1487::
1485:}}
1481:{{
1443:14
1425:39
1404:}}
1400:{{
1367:.
935::
807:.
799:,
704:.
538:12
489:12
205:.
62:.
42:,
3080:e
3073:t
3066:v
2289:e
2282:t
2275:v
2167:e
2160:t
2153:v
2139:)
2125:.
2106:.
2086::
1989:.
1977::
1942:.
1922::
1886:.
1874::
1849:.
1837::
1831:1
1811:)
1807:(
1779:.
1754:.
1748::
1738::
1711:)
1707:(
1690:.
1670::
1655:.
1643::
1637:4
1616:.
1610::
1600::
1573:.
1561::
1537:.
1523:.
1505:)
1498:)
1494:(
1477:.
1410:)
1396:.
1371:.
1248:r
1221:k
1202:2
1194:k
1188:2
1185:1
1175:R
1172:A
1164:R
1161:G
1158:A
1155:C
1122:2
1111:2
1108:1
1098:R
1095:A
1087:R
1084:G
1081:A
1078:C
1048:+
1043:4
1039:y
1032:4
1029:1
1018:3
1014:y
1007:3
1004:1
998:+
993:2
989:y
982:2
979:1
970:y
967:=
964:)
961:y
958:+
955:1
952:(
921:σ
917:σ
915:)
913:π
905:σ
894:n
742:.
654:α
642:α
634:α
616:.
604:/
600:1
596:T
592:=
587:T
569:α
545:=
525:=
486:1
480:=
477:T
451:=
438:=
412:σ
408:P
391:.
386:T
383:P
368:=
363:T
332:.
327:P
312:=
289:P
282:σ
265:.
260:T
245:=
240:T
222:T
214:T
210:σ
196:σ
121:)
48:σ
20:)
Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.
