Volatility Is Rough

Jim Gatheral, Thibault Jaisson, Mathieu Rosenbaum · Quantitative Finance / arXiv · 2018 · quantitative-finance · 10.1080/14697688.2017.1393551 · record gatheral2018-rough-volatility
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Where this record's text came from. faceted 2026-08 by reading the locally held text (pdftext); every evidence string verified as an exact substring of that text before merging. Claim type is 'existence' because the headline claim is that a property (roughness, H ≈ 0.1) is present in observed volatility; the paper additionally contains a critique strand (spurious long memory) and a mechanism strand (Hawkes-process order splitting as the microstructural origin), neither of which the single-valued facet can carry. method is 'observational-study' since the primary evidence is estimation on market high-frequency and realized-variance data (DAX, Bund, S&P, NASDAQ and the Oxford-Man indices); the paper also uses Monte Carlo simulation for bias checks and includes short appendix proofs, so it is genuinely mixed-method. Quotes were taken from lines free of the page numbers and footnote markers that the PDF extraction interleaves into sentences. 2026-08-14, 2026-08-16 and 2026-08-25 schema-0.3 passes: every quote verified as an exact substring of the staged text and anchored at merge time; concept terms verified present; every edge endpoint an existing node. Update, 16 September 2026: EXCEPTION TO THE DATED PASS ABOVE, on this record only: this record carries 1 composite quote field - a quote assembled from two or more passages joined by an ellipsis. A COMPOSITE IS NOT AN EXACT CONTIGUOUS SUBSTRING of the staged text and is deliberately not anchored: each of its parts is verified separately at the offsets in evidence composite spans, and a part occurring more than once carries span null rather than a guessed offset. So the 'every quote verified as an exact substring' clause of the dated pass above DOES NOT HOLD for those fields, and never did - the parts were verified, the whole was not. Nothing is deleted, re-grounded or withdrawn: this writes down an exception that was always true of composites and had not been recorded, so a reader was told more than the pass had checked. 2026-09-16 the project CORRECTION TO THE EXEMPTION ABOVE, SAME DAY: THE EXEMPTION DOES NOT APPLY TO THIS RECORD. Its evidence composite spans row(s) are FOSSILS of a 2026-08-25 composite marking that was superseded by a 2026-08-26 re-slice; the quote is an exact contiguous substring of the staged text, so the dated substring claim above holds for it WITHOUT exception. The clause is left in place with this correction beside it rather than removed, so that the error and its repair are both on the record.
Some words in these quotes contain the wrong character. The PDF this text was extracted from substituted 37 characters inside a word — a currency sign or a stray accent where a letter pair belongs, as in signi¢cantly for significantly, or a single ligature glyph, as in confidence. They are valid characters in the wrong place, so they survive every encoding check. The quotes keep them for the same reason as above, and a search of this page will not find the affected words.
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Other fields define these differently the same word, defined another way in another discipline
memory 23 fields · sample-size 5 fields · integration 3 fields · linear regression 2 fields · variance 2 fields

Tags on this paper

Every tag the record carries, each linking to every other paper in the corpus that carries it. A tag appears here whether or not its words occur in the article — the spans below are only the ones a sentence in this paper licenses. Of the 125 concept tags on this paper, 122 are grounded in a quoted sentence. 116 carry the tagger's gloss of what the term means in this paper, which is not something the article can license.
stochastic volatility fractional Brownian motion Hurst exponent realized volatility power law long memory Hurst parameter spot volatility volatility surface continuous semimartingales volatility process Black-Scholes framework deterministic function of time local volatility model time-inhomogeneous future volatility surfaces exotic options stochastic volatility models continuous Brownian semi-martingale local volatility dynamics stochastic volatility dynamics local-stochastic-volatility (LSV) models reasonable dynamics slow decay of the autocorrelation function not integrable power-law with exponent less than 1 asymptotic behavior of the covariance function usual time scales of observation dependence structure implied volatility volatility parameter market price of that option strike price time to expiry power-law function of time to expiry term structure of at-the-money (ATM) skew sum of decaying exponentials explosion of the volatility smile presence of jumps ATM volatility skew smoothness parameter increments of the log-volatility approximately normally distributed monofractal scaling property fractional stochastic volatility (FSV) model Rough FSV (RSFV) Rough FSV RFSV FSV Rough FSV (RFSV) RFSV model improved forecasts of realized volatility volatility persistence classical statistical procedures RFSV volatility forecasts conventional AR and HAR volatility forecasts market microstructure explanation high degree of endogeneity of the market algorithmic trading integrated variance model with uncertainty zones very short time intervals daily realized variance estimates Oxford-Man Institute of Quantitative Finance Realized Library integration biased upwards smoothness parameter sq regressing log m(q, ∆) against log ∆ fractional Ornstein-Uhlenbeck process mathematical tractability reasonableness of the model at very large times very long reversion time scale choice H < 1/2 observed smoothness of the volatility process term structure of volatility skew mean reversion by practitioners fBM like-behavior of the log-volatility stationarity property one-hour window daily eight-hour windows regularizing effect of the integral operator volatility of volatility persistent periods of high volatility low volatility periods fractal-type behavior range of observation scales volatility process over one day volatility process over a decade straight lines with slope 1.86 power law behavior of the autocorrelation function wrongly convinced classical estimation procedures spurious long memory of volatility classical power law sense RFSV forecast AR and HAR forecasts longer horizons more parsimonious forecast time horizon relevant regression window forecasting horizon volatility over the last week volatility over the last month Hawkes processes extensions of Poisson processes intensity at a given time past jumps point process kernel L1 norm power law tail degree of endogeneity of the market one given order many other orders electronic high frequency trading splitting of large orders metaorder superposition effect irregular volatility macroscopic scaling limit of Hawkes processes integrated fractional process cumulated order flow Rough Fractional Stochastic Volatility (RFSV) model FSV model one major difference THE TERM'S TWO SENSES ARE SEPARATED BY THEIR HISTORY: 'long memory' initially meant the slow decay of the autocorrelation function - anything slower than exponential - and over time acquired the more precise meaning that the function is not integrable, and more precisely still that it decays as a power law with exponent less than one THE TECHNICAL SENSE IS DEFENDED AS THE ONLY ESTIMABLE ONE: the recent literature assumes long memory in the technical sense, and the authors add that meaningful results can probably ONLY be obtained under such a specification, since the asymptotic behaviour of the covariance function cannot be estimated without assuming a specific form for it THE QUESTION IS DECLARED UNANSWERABLE AS POSED, and the authors then supply a different instrument rather than a different answer: stated in terms of the asymptotic behaviour of the autocorrelation function the long memory question simply cannot be answered, but explicit expressions still allow the dependence structure to be analysed A WIDELY ACCEPTED STYLIZED FACT IS EXPLAINED AS AN ARTEFACT OF ITS OWN DETECTOR: the model has no long memory property, and yet the classical statistical procedures designed to detect volatility persistence TEND TO CONCLUDE THAT LONG MEMORY IS PRESENT in data the model generated the evidence for the stylized fact is dated rather than dismissed: the analyses supporting it use data that PREDATE high-frequency electronic trading, and the authors note the evidence has never satisfied the remaining doubters THE NEW NAME IS CHOSEN TO CARRY THE DEPARTURE: an existing model is adopted and renamed, with the new word picked to underline the single parameter inequality that separates it from its parent in the process used, ONE PARAMETER CONTROLS BOTH PROPERTIES AT ONCE - regularity and long memory stand in one-to-one correspondence through the Hurst parameter - so a claim about smoothness is inseparably a claim about memory A WIDESPREAD BELIEF IS MET WITH A COUNTEREXAMPLE RATHER THAN AN ARGUMENT: the model is offered as a counterexample to the widespread belief that the explosion of the volatility smile at short expiries implies the presence of jumps THE MODEL IS OFFERED AGAINST TWO SEPARATE REQUIREMENTS rather than one - consistency with the empirically observed properties of the volatility time series AND consistency with the shape of the volatility surface - and the claim is stated as POTENTIAL, not as achievement the smoothness estimate is reported as a RANGE ACROSS ASSETS rather than a single fitted number, and it is accompanied by two further empirical properties of the increments - approximate normality and a monofractal scaling of the moments - which together are what licenses the modelling choice volatility fractional Brownian Hurst log-volatility exponent memory realized rough Hurst parameter H mean mean of regression linear regression sample-size sample size standard-error standard error variance observational-study

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relation to other workclaim_relationshow this paper stands to another: agrees, contradicts, extends, qualifies
claim typeclaim_typethe shape of the claim: existence, mechanism, method, critique, prediction, null
concept edgeconcept_edgesan asserted relation between two concepts, with the sentence asserting it
conceptconceptsan idea the paper works with, quoted where the paper uses it
content tagcontent_tagsa finding, definition, quantity, statistic or variable named in the paper
controlcontrolsan experiment run to eliminate a rival explanation
limitationlimitationswhat the paper says its evidence cannot support
mechanismmechanismshow the reported effect is said to come about
methodmethodhow the paper produced its evidence
phenomenonphenomenonthe effect or regularity under study
sensesensesa distinct use of a term, quoted where the paper fixes it
transfertransfersa method or concept carried in from another field
unrecordable relationunhoused_relationsa relation the paper asserts that this vocabulary cannot express, with the reason

The paper

The full text is not reproduced here. This article is not cleared for redistribution, so the page carries the tag layer only. Its evidence sentences are withheld; the grounding status remains with each tag, and the article itself is at https://doi.org/10.1080/14697688.2017.1393551. The reading view exists for the papers whose licence permits it.

Every tag on this page

claim_relations 6 · claim_type 1 · concept_edges 11 · concepts 122 · content_tags 12 · controls 1 · limitations 7 · mechanisms 10 · method 1 · phenomenon 1 · senses 22 · transfers 1 · unhoused_relations 6

Relations on this page carry a quotation for the claim. Where a relation was separately evidenced — and so tested against the vocabulary for its type — the row says so; 9 of 11 relations here carry that mark. The rest are the tagger’s reading of the sentence quoted beside them.

facettagfieldconf.whose words
claim_typeexistence
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claim_typethe paper's words
phenomenonsmoothness (roughness) of the volatility process
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phenomenonthe paper's words
methodobservational-study
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methodthe paper's words
mechanismsmechanisms
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mechanisms[0]0.95the tagger's words
mechanismsmechanisms
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mechanisms[1]0.85the tagger's words
mechanismsmechanisms
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about this quote: Span re-sliced at drafting: the staged text splices footnote 1 AND a page number between 'This implies' and its own subordinate clause ('…see Section 2.1. 3 that when stated in term…'), so the quote begins after the splice. Extraction damage, not authorial. Damage class C.
mechanisms[2]0.85the tagger's words
mechanismsmechanisms
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mechanisms[3]0.95the tagger's words
mechanismsmechanisms
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mechanisms[4]0.95the tagger's words
mechanismsmechanisms
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mechanisms[5]0.85the tagger's words
mechanismsmechanisms
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mechanisms[6]0.95the tagger's words
mechanismsmechanisms
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mechanisms[7]0.85the tagger's words
mechanismsmechanisms
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mechanisms[8]0.85the tagger's words
mechanismsmechanisms
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about this quote: The span contains 'H¨older' for 'Hölder' - the diaeresis is emitted BEFORE its base letter by the PDF extraction. The quote is still an exact substring and anchors correctly; the damage is in what a reader of the tag sees, not in the provenance. None of the four shapes an internal tool looks for covers this, so it is annotated by hand.
mechanisms[9]0.95the tagger's words
limitationsthe scaling result is established at usual observation time scales
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what this limits: the scaling result, over the range examined: AT LEAST AT USUAL TIME SCALES OF OBSERVATION
limitations[0]the tagger's words
limitationsSmoothness estimates based on whole-trading-day realized variance are expected to be biased upwards because integration smooths the process.
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what this limits: the smoothness estimates specifically: WE EXPECT ESTIMATES OF THE SMOOTHNESS OF THE VOLATILITY PROCESS TO BE BIASED UPWARDS, INTEGRATION BEING A REG[ularising operation] - the direction of the bias is stated
limitations[1]the tagger's words
limitationsVolatility is never observed directly, so the key quantity m(q, Δ) can only be computed from proxies.
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what this limits: every quantity computed in the paper: THE VOLATILITY PROCESS IS NOT DIRECTLY OBSERVABLE, AND AN EXACT COMPUTATION OF m(q, delta) IS NOT POSSIBLE IN PRACTICE
limitations[2]the tagger's words
limitationsThe paper only treats the volatility time series; whether the model is consistent with observed option prices is deferred.
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what this limits: the option-pricing implications: A MORE DETAILED ANALYSIS OF THE CONSISTENCY OF OUR MODEL WITH OPTION PRICES IS LEFT FOR A FUTURE ARTICLE
limitations[3]the tagger's words
limitationsThe property cannot be estimated without first assuming the functional form whose presence is at issue.
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what this limits: any estimate of long memory in volatility: the asymptotic behaviour of the covariance function cannot be estimated without assuming a specific form for it, so the specification is an input to the result rather than an output
limitations[4]1.0the tagger's words
limitationsAs the term is now defined, the field's central question about volatility cannot be answered at all.
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what this limits: the debate over whether volatility has long memory: stated in terms of the asymptotic behaviour of the autocorrelation function, the paper says the question simply cannot be answered
limitations[5]1.0the tagger's words
limitationsStandard procedures report the property in data generated by a model that does not have it, which the authors offer as the reason the field accepted it as a stylized fact.
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what this limits: the widely accepted stylized fact that volatility has long memory: classical procedures for detecting volatility persistence conclude it is present in data simulated from a model that has no long memory property at all
limitations[6]1.0the tagger's words
transfersfractional Brownian motion with a Hurst exponent below 1/2 used as the model of log-volatility, in place of the standard semimartingale volatility models of finance
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transfers[0]0.9the tagger's words
controlsa detailed test of the model against observed option prices - NOT performed, and deferred to a future article
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eliminates: the model fitting volatility time series while failing on the option prices it would be used to compute, which is the comparison the paper itself says its predecessors fail · outcome (stated by the tagger, no quotation): absent-declared-unreported
controls[0]0.85the tagger's words
conceptsfractional Brownian motion
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concepts[1]the paper's words
conceptsrealized volatility
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concepts[3]the paper's words
conceptslong memory
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also in: long memory
concepts[5]the paper's words
conceptsHurst parameter
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concepts[6]the paper's words
conceptsspot volatility
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concepts[7]the paper's words
conceptsvolatility surface
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concepts[8]the paper's words
conceptscontinuous semimartingales
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conceptsvolatility process
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conceptsBlack-Scholes framework
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conceptsdeterministic function of time
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conceptslocal volatility model
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conceptstime-inhomogeneous
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conceptsfuture volatility surfaces
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conceptsexotic options
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concepts[16]0.95the paper's words
conceptsstochastic volatility models
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conceptscontinuous Brownian semi-martingale
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conceptslocal volatility dynamics
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conceptsstochastic volatility dynamics
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conceptslocal-stochastic-volatility (LSV) models
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concepts[21]0.95the paper's words
conceptsreasonable dynamics
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conceptsslow decay of the autocorrelation function
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concepts[23]0.95the paper's words
conceptsnot integrable
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concepts[24]0.95the paper's words
conceptspower-law with exponent less than 1
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concepts[25]0.95the paper's words
conceptsasymptotic behavior of the covariance function
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concepts[26]0.95the paper's words
conceptsusual time scales of observation
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concepts[27]0.95the paper's words
conceptsdependence structure
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about this quote: PAGE FURNITURE IS SPLICED INTO THE 'evidence' QUOTE - the text of footnote 1 ('1Actually H corresponds…') and a page number, between 'This implies' and 'that when stated'. The words on either side of it were never continuous on the page; read the quote with it deleted.
concepts[28]0.95the paper's words
conceptsimplied volatility
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concepts[29]0.95the paper's words
conceptsvolatility parameter
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concepts[30]0.95the paper's words
conceptsmarket price of that option
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concepts[31]0.95the paper's words
conceptsstrike price
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also in: strike price
concepts[32]0.95the paper's words
conceptstime to expiry
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concepts[33]0.95the paper's words
conceptspower-law function of time to expiry
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concepts[34]0.95the paper's words
conceptsterm structure of at-the-money (ATM) skew
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concepts[35]0.95the paper's words
conceptssum of decaying exponentials
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concepts[36]0.95the paper's words
conceptsexplosion of the volatility smile
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concepts[37]0.95the paper's words
conceptspresence of jumps
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concepts[38]0.95the paper's words
conceptsATM volatility skew
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concepts[39]0.95the paper's words
conceptssmoothness parameter
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concepts[40]0.95the paper's words
conceptsincrements of the log-volatility
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concepts[41]0.95the paper's words
conceptsapproximately normally distributed
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concepts[42]0.95the paper's words
conceptsmonofractal scaling property
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concepts[43]0.95the paper's words
conceptsfractional stochastic volatility (FSV) model
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concepts[44]0.95the paper's words
conceptsRough FSV (RSFV)
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conceptsRough FSV
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also in: Rough FSV
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conceptsRFSV
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also in: RFSV
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conceptsFSV
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also in: FSV
concepts[48]0.95the paper's words
conceptsRough FSV (RFSV)
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concepts[49]0.95the paper's words
conceptsRFSV model
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also in: RFSV model
concepts[50]0.95the paper's words
conceptsimproved forecasts of realized volatility
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concepts[51]0.95the paper's words
conceptsvolatility persistence
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conceptsclassical statistical procedures
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conceptsRFSV volatility forecasts
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concepts[54]0.95the paper's words
conceptsconventional AR and HAR volatility forecasts
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concepts[55]0.95the paper's words
conceptsmarket microstructure explanation
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conceptshigh degree of endogeneity of the market
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conceptsalgorithmic trading
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conceptsintegrated variance
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conceptsmodel with uncertainty zones
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conceptsvery short time intervals
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conceptsdaily realized variance estimates
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conceptsOxford-Man Institute of Quantitative Finance Realized Library
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conceptsintegration
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conceptsbiased upwards
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conceptssmoothness parameter sq
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concepts[66]0.95the paper's words
conceptsregressing log m(q, ∆) against log ∆
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concepts[67]0.95the paper's words
conceptsfractional Ornstein-Uhlenbeck process
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concepts[68]0.95the paper's words
conceptsmathematical tractability
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concepts[69]0.95the paper's words
conceptsreasonableness of the model at very large times
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concepts[70]0.95the paper's words
conceptsvery long reversion time scale
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concepts[71]0.95the paper's words
conceptschoice H < 1/2
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concepts[72]0.95the paper's words
conceptsobserved smoothness of the volatility process
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concepts[73]0.95the paper's words
conceptsterm structure of volatility skew
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concepts[74]0.95the paper's words
conceptsmean reversion by practitioners
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concepts[75]0.95the paper's words
conceptsfBM like-behavior of the log-volatility
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concepts[76]0.95the paper's words
conceptsstationarity property
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concepts[77]0.95the paper's words
conceptsone-hour window
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concepts[78]0.95the paper's words
conceptsdaily eight-hour windows
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concepts[79]0.95the paper's words
conceptsregularizing effect of the integral operator
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concepts[80]0.95the paper's words
conceptsvolatility of volatility
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concepts[81]0.95the paper's words
conceptspersistent periods of high volatility
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concepts[82]0.95the paper's words
conceptslow volatility periods
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concepts[83]0.95the paper's words
conceptsfractal-type behavior
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concepts[84]0.95the paper's words
conceptsrange of observation scales
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concepts[85]0.95the paper's words
conceptsvolatility process over one day
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concepts[86]0.95the paper's words
conceptsvolatility process over a decade
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concepts[87]0.95the paper's words
conceptsstraight lines with slope 1.86
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concepts[88]0.95the paper's words
conceptspower law behavior of the autocorrelation function
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concepts[89]0.95the paper's words
conceptswrongly convinced
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concepts[90]0.95the paper's words
conceptsclassical estimation procedures
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concepts[91]0.95the paper's words
conceptsspurious long memory of volatility
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concepts[92]0.95the paper's words
conceptsclassical power law sense
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concepts[93]0.95the paper's words
conceptsRFSV forecast
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also in: RFSV forecast
concepts[94]0.95the paper's words
conceptsAR and HAR forecasts
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concepts[95]0.95the paper's words
conceptslonger horizons
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concepts[96]0.95the paper's words
conceptsmore parsimonious
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concepts[97]0.95the paper's words
conceptsforecast time horizon
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concepts[98]0.95the paper's words
conceptsrelevant regression window
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concepts[99]0.95the paper's words
conceptsforecasting horizon
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concepts[100]0.95the paper's words
conceptsvolatility over the last week
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concepts[101]0.95the paper's words
conceptsvolatility over the last month
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concepts[102]0.95the paper's words
conceptsHawkes processes
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concepts[103]0.95the paper's words
conceptsextensions of Poisson processes
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concepts[104]0.95the paper's words
conceptsintensity at a given time
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concepts[105]0.95the paper's words
conceptspast jumps
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also in: past jumps
concepts[106]0.95the paper's words
conceptspoint process
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also in: point process
concepts[107]0.95the paper's words
conceptskernel
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also in: kernel
concepts[108]0.95the paper's words
conceptsL1 norm
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also in: L1 norm
concepts[109]0.95the paper's words
conceptspower law tail
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concepts[110]0.95the paper's words
conceptsdegree of endogeneity of the market
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concepts[111]0.95the paper's words
conceptsone given order
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concepts[112]0.95the paper's words
conceptsmany other orders
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concepts[113]0.95the paper's words
conceptselectronic high frequency trading
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concepts[114]0.95the paper's words
conceptssplitting of large orders
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concepts[115]0.95the paper's words
conceptsmetaorder
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also in: metaorder
concepts[116]0.95the paper's words
conceptssuperposition effect
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concepts[117]0.95the paper's words
conceptsirregular volatility
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concepts[118]0.95the paper's words
conceptsmacroscopic scaling limit of Hawkes processes
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concepts[119]0.95the paper's words
conceptsintegrated fractional process
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concepts[120]0.95the paper's words
conceptscumulated order flow
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concepts[121]0.95the paper's words
conceptsRough Fractional Stochastic Volatility (RFSV) model
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concepts[122]0.95the paper's words
conceptsFSV model
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also in: FSV model
concepts[123]0.95the paper's words
conceptsone major difference
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concepts[124]0.95the paper's words
unhoused_relationsRFSV model → improved forecasts of realized volatility
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The RFSV model enables improved forecasts of realized volatility. Enables is absent from the eight governed types and is not direct physical causation.
unhoused_relations[0]0.95the tagger's words
unhoused_relationsclassical statistical procedures → long memory
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Classical persistence diagnostics tend to conclude long memory in data generated by a model that has none. Misidentifies-as is absent from the edge vocabulary.
unhoused_relations[1]0.95the tagger's words
unhoused_relationsRFSV forecast → AR and HAR forecasts
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The RFSV forecast consistently outperforms AR and HAR, especially at longer horizons. Outperforms is absent from the eight types and contrast alone would discard the direction of performance.
unhoused_relations[2]0.95the tagger's words
unhoused_relationsrelevant regression window → forecasting horizon
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The relevant history window is linear in the forecasting horizon. Proportional-to is absent from the governed edge types.
unhoused_relations[3]0.95the tagger's words
unhoused_relationsmacroscopic scaling limit of Hawkes processes → integrated fractional process
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The near-critical long-tail Hawkes scaling limit can be seen as an integrated fractional process. Scaling-limit-is-represented-by is absent and a plain is-a would overstate an asymptotic result.
unhoused_relations[4]0.95the tagger's words
unhoused_relationscumulated order flow → integrated variance
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The paper reports a linear relation between cumulated order flow and integrated variance. Correlates-with/linearly-related-to is absent from the eight types.
unhoused_relations[5]0.95the tagger's words
senseslong memory - SENSE 1, THE ORIGINAL AND LOOSE ONE: slow decay of the autocorrelation function, meaning anything slower than exponential
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senses[0]1.0the tagger's words
senseslong memory - SENSE 2, THE LATER TECHNICAL ONE the field drifted to: a non-integrable autocorrelation function, more precisely one decaying as a power law with exponent below 1, and the recent literature assumes this sense
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senses[1]1.0the tagger's words
sensesvolatility - AS A PROXY, ALWAYS: the process is not directly observable, so every quantity here is computed from an estimated daily stand-in taken at a fixed time of day
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senses[2]1.0the tagger's words
sensesLocal volatility - exact European-option fit with time-inhomogeneous and unrealistic future dynamics
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senses[3]0.95the tagger's words
sensesConventional stochastic volatility - more realistic dynamics without exact consistency with observed European option prices
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senses[4]0.95the tagger's words
sensesLocal-stochastic volatility - market hybrid targeting both exact fit and reasonable dynamics
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senses[5]0.95the tagger's words
sensesImplied volatility - the Black-Scholes volatility input required to reproduce an option's market price
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senses[6]0.95the tagger's words
sensesVolatility surface - implied volatility plotted across strike price and time to expiry
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senses[7]0.95the tagger's words
sensesShort-maturity volatility-smile explosion - reproducible without jumps when volatility is fractionally rough
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senses[8]0.95the tagger's words
sensesRough FSV - fractional stochastic volatility with H below one half rather than the long-memory H above one half
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senses[9]0.95the tagger's words
sensesSpot-volatility observation - intrinsically latent and therefore replaced by daily fixed-time proxies
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senses[10]0.95the tagger's words
sensesWhole-day realized variance - a regularized spot proxy expected to bias smoothness upward
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senses[11]0.95the tagger's words
sensesStationary rough-volatility specification - fractional Ornstein-Uhlenbeck process with a very long reversion scale
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senses[12]0.95the tagger's words
sensesPractitioner mean reversion - unusually high volatility tends down and unusually low volatility tends up
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senses[13]0.95the tagger's words
sensesWindow-length bias - longer integration raises estimated H and lowers estimated volatility-of-volatility
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senses[14]0.95the tagger's words
sensesRFSV scale resemblance - a daily volatility path qualitatively resembles a decade-long path
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senses[15]0.95the tagger's words
sensesSpurious memory diagnosis - standard estimators report power-law memory on simulations whose model has none
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senses[16]0.95the tagger's words
sensesRFSV forecast parsimony - one H parameter rather than horizon-dependent AR/HAR coefficients
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about this quote: PAGE FURNITURE IS SPLICED INTO THE 'evidence' QUOTE - the text of footnotes 13 and 14 and a page number, between 'requires the parameter' and 'H to forecast'. The words on either side of it were never continuous on the page; read the quote with it deleted.
senses[17]0.95the tagger's words
sensesForecast-history rule - past window approximately matches the future horizon
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senses[18]0.95the tagger's words
sensesHawkes endogeneity - one order triggers many more as algorithms respond to other participants' orders
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senses[19]0.95the tagger's words
sensesOrder splitting - many observed orders belong to a slowly executed metaorder
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senses[20]0.95the tagger's words
sensesMicrostructural roughness mechanism - near-critical endogenous feedback plus long-tailed order influence produces a fractional macroscopic limit
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senses[21]0.9the tagger's words
claim_relationsbuilds-on → fractional Brownian motion (from mathematics/physics)
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claim_relations[0]the tagger's words
claim_relationsbuilds-on → the fractional stochastic volatility (FSV) model of Comte and Renault [16]
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claim_relations[1]the tagger's words
claim_relationsextends → the FSV model of Comte and Renault [16], modified to H < 1/2
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claim_relations[2]the tagger's words
claim_relationscontradicts → the accepted stylized fact of power-law long memory in volatility
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claim_relations[3]the tagger's words
claim_relationsreplicates → the stylized fact of near-Gaussian log-volatility increments reported by Andersen et al. ([2], [3])
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claim_relations[4]the tagger's words
claim_relationsbuilds-on → Fukasawa [25] on the ATM volatility skew generated by fBM-driven volatility
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claim_relations[5]the tagger's words
concept_edgeslong memory —operationalised-as→ Hurst parameter
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strength of the relation: 1
concept_edges[0]the tagger's words
concept_edgesspot volatility —operationalised-as→ realized volatility
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strength of the relation: 1 Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but the span writes 'daily spot variances' and 'daily realized variance estimates', not 'spot volatility' / 'realized volatility'.
concept_edges[1]the tagger's words
concept_edgesstochastic volatility dynamics —contrasted-with→ local volatility dynamics
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the relation itself is separately evidenced · strength of the relation: 1 · note: The stochastic dynamics are said to be more realistic than local-volatility dynamics, though still price-inconsistent.
concept_edges[2]0.95the tagger's words
concept_edgespower-law function of time to expiry —contrasted-with→ sum of decaying exponentials
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the relation itself is separately evidenced · strength of the relation: 1 · note: Observed skew is a power law, in contrast to the conventional model's constant/exponential shape.
concept_edges[3]0.95the tagger's words
concept_edgesRough FSV —same-as→ RFSV
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the relation itself is separately evidenced · strength of the relation: 1 · note: The model name is immediately followed by its acronym in parentheses.
also in: Rough FSV · RFSV
concept_edges[4]0.95the tagger's words
concept_edgesRough FSV (RFSV) —distinct-from→ FSV
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the relation itself is separately evidenced · strength of the relation: 1 · note: The paper explicitly contrasts the rough H below one-half regime with FSV.
also in: Rough FSV (RFSV) · FSV
concept_edges[5]0.95the tagger's words
concept_edgeschoice H < 1/2 —causes→ observed smoothness of the volatility process
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the relation itself is separately evidenced · strength of the relation: 1 · note: The choice enables the model to reproduce the observed smoothness.
concept_edges[6]0.95the tagger's words
concept_edgeschoice H < 1/2 —causes→ term structure of volatility skew
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the relation itself is separately evidenced · strength of the relation: 1 · note: The same choice enables agreement with the observed skew term structure.
concept_edges[7]0.95the tagger's words
concept_edgesone given order —causes→ many other orders
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the relation itself is separately evidenced · strength of the relation: 1 · note: The paper states that one order endogenously generates many others.
concept_edges[8]0.95the tagger's words
concept_edgessuperposition effect —causes→ irregular volatility
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the relation itself is separately evidenced · strength of the relation: 0.6 — the record marks this weak · note: The authors say they believe the combined phenomena induce irregular volatility. Audit 2026-09-28: DOUBTFUL - read against its full span and kept, but 'We believe' the two phenomena lead to the superposition effect; hedged.
concept_edges[9]0.95the tagger's words
concept_edgesRough Fractional Stochastic Volatility (RFSV) model —distinct-from→ FSV model
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the relation itself is separately evidenced · strength of the relation: 1 · note: The models are separated by the explicitly named major difference H below versus above one half.
concept_edges[10]0.95the tagger's words
content_tagsH ≈ 0.1 — Hurst exponent of log-volatility (H<1/2 means rough)
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content_tags.quantities[0]the tagger's words
content_tagsH = 1/2 — the classical Brownian-motion boundary case
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content_tags.quantities[1]the tagger's words
content_tagsLog-volatility acts essentially like fractional Brownian motion with a Hurst exponent near 0.1 at any reasonable time scale, which leads to the Rough FSV (RFSV) model with H < 1/2.
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content_tags.findings[0]0.85the tagger's words
content_tagsAlthough volatility is NOT long-memory under RFSV, classical persistence tests spuriously detect long memory in RFSV-generated data — explaining why long memory became an accepted stylized fact.
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content_tags.findings[1]the tagger's words
content_tagsHurst parameter H
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content_tags.variables[0]the tagger's words
content_tagsRFSV model
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also in: RFSV model
content_tags.definitions[0]the tagger's words
content_tagsEVIDENCE CORRECTED (RE-GROUNDED) · fractional Brownian motion
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EVIDENCE CORRECTED: RE-GROUNDED. The old span welded 'model the log of volatility using' - Gatheral's OWN model, a fBM with H < 1/2 - to 'motion (fBM for…' 5,695 characters EARLIER, which belongs to Comte and Renault's H > 1/2 model. It conflated the two Hurst regimes, which is the single distinction this paper exists to draw.
content_tags.definitions[1]the tagger's words
content_tagsmean
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about this quote: THE QUOTE STARTS INSIDE A FORMULA AND ENDS IN A TABLE: it opens on the tail of the flattened expectation symbol that its sentence defines; this copy places that sentence's last words (the period the mean is taken over) before the quote; and after the quote's last words the text runs into the labels of the forecasting results table.
also in: mean
content_tags.statistics[1]the tagger's words
content_tagsregression
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also in: regression
content_tags.statistics[2]the tagger's words
content_tagssample-size
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about this quote: QUOTE REPAIRED: the extractor split a hyphen-space and the quote was recorded faithfully with the damage in it, which made it unanchorable. The repaired string is an EXACT SUBSTRING of the staged text - that is why it was accepted, not because a rule produced it. The text as originally recorded is kept in evidence as extracted.
also in: sample-size
content_tags.statistics[3]the tagger's words
content_tagsstandard-error
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content_tags.statistics[4]the tagger's words
content_tagsvariance
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about this quote: A FOOTNOTE CALL SITS INSIDE THIS QUOTE: the '6' between 'the S&P and' and 'NASDAQ indices' is the paper's footnote marker, not part of the sentence; read the quote with it deleted.
also in: variance
content_tags.statistics[6]the tagger's words

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© 2026 Shir Sivroni · ORCID 0009-0000-2597-2824