Relevant bibliographies by topics / Implied volatilitie

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Academic literature on the topic 'Implied volatilitie'

Author: Grafiati
Published: 9 March 2023
Last updated: 10 March 2023

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Journal articles on the topic "Implied volatilitie"

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LEE, ROGER W. "IMPLIED AND LOCAL VOLATILITIES UNDER STOCHASTIC VOLATILITY." International Journal of Theoretical and Applied Finance 04, no. 01 (February 2001): 45–89. http://dx.doi.org/10.1142/s0219024901000870.

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For asset prices that follow stochastic-volatility diffusions, we use asymptotic methods to investigate the behavior of the local volatilities and Black–Scholes volatilities implied by option prices, and to relate this behavior to the parameters of the stochastic volatility process. We also give applications, including risk-premium-based explanations of the biases in some naïve pricing and hedging schemes. We begin by reviewing option pricing under stochastic volatility and representing option prices and local volatilities in terms of expectations. In the case that fluctuations in price and volatility have zero correlation, the expectations formula shows that local volatility (like implied volatility) as a function of log-moneyness has the shape of a symmetric smile. In the case of non-zero correlation, we extend Sircar and Papanicolaou's asymptotic expansion of implied volatilities under slowly-varying stochastic volatility. An asymptotic expansion of local volatilities then verifies the rule of thumb that local volatility has the shape of a skew with roughly twice the slope of the implied volatility skew. Also we compare the slow-variation asymptotics against what we call small-variation asymptotics, and against Fouque, Papanicolaou, and Sircar's rapid-variation asymptotics. We apply the slow-variation asymptotics to approximate the biases of two naïve pricing strategies. These approximations shed some light on the signs and the relative magnitudes of the biases empirically observed in out-of-sample pricing tests of implied-volatility and local-volatility schemes. Similarly, we examine the biases of three different strategies for hedging under stochastic volatility, and we propose ways to implement these strategies without having to specify or estimate any particular stochastic volatility model. Our approximations suggest that a number of the empirical pricing and hedging biases may be explained by a positive premium for the portion of volatility risk that is uncorrelated with asset risk.
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Kang, Byung Jin, Sohyun Kang, and Sun-Joong Yoon. "Information Content of Adjusted Implied Volatility in the KOSPI 200 Index Options Market." Journal of Derivatives and Quantitative Studies 17, no. 4 (November 30, 2009): 75–103. http://dx.doi.org/10.1108/jdqs-04-2009-b0003.

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This study examines the forecasting ability of the adjusted implied volatility (AIV), which is suggested by Kang, Kim and Yoon (2009), using the horserace competition with historical volatility, model-free implied volatility, and BS implied volatility in the KOSPI 200 index options market. The adjusted implied volatility is applicable when investors are not risk averse or when underlying returns do not follow a normal distribution. This implies that AIV is consistent with the presence of risk premia for other risk such as volatility risk and jump risk. Using KOSPI 200 index options, it is shown that the AIV outperforms other volatility estimates in terms of the unbiasedness for future realized volatilities as well as the forecasting errors.
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STEFANICA, DAN, and RADOŠ RADOIČIĆ. "AN EXPLICIT IMPLIED VOLATILITY FORMULA." International Journal of Theoretical and Applied Finance 20, no. 07 (November 2017): 1750048. http://dx.doi.org/10.1142/s0219024917500480.

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We show that an explicit approximate implied volatility formula can be obtained from a Black–Scholes formula approximation that is 2% accurate. The relative error of the approximate implied volatility is uniformly bounded for options with any moneyness and with arbitrary large or small option maturities and volatilities, including for long dated options and options on highly volatile underlying assets. For options within a large trading range, such as options with maturity less than five years and implied volatility less than 150%, the error of the approximate implied volatility relative to the Black–Scholes implied volatility is less than 10% points.
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Matić, Ivan, Radoš Radoičić, and Dan Stefanica. "Pólya-based approximation for the ATM-forward implied volatility." International Journal of Financial Engineering 04, no. 02n03 (June 2017): 1750032. http://dx.doi.org/10.1142/s2424786317500323.

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We introduce a closed form approximation for the implied volatility of ATM-forward options. The relative error of this approximation is uniformly bounded for all option maturities and implied volatilities. The approximation is extremely precise, having relative error less than [Formula: see text] for all options with integrated volatility less than [Formula: see text], such as options with maturity less than three years and implied volatility less than 100%. Moreover, the approximate implied volatilities fall within the implied volatility bid–ask spread for all the liquid options, such as options with volatility less than 200% and maturity less than nine years.
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Dennis, Patrick, Stewart Mayhew, and Chris Stivers. "Stock Returns, Implied Volatility Innovations, and the Asymmetric Volatility Phenomenon." Journal of Financial and Quantitative Analysis 41, no. 2 (June 2006): 381–406. http://dx.doi.org/10.1017/s0022109000002118.

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AbstractWe study the dynamic relation between daily stock returns and daily innovations in optionderived implied volatilities. By simultaneously analyzing innovations in index- and firmlevel implied volatilities, we distinguish between innovations in systematic and idiosyncratic volatility in an effort to better understand the asymmetric volatility phenomenon. Our results indicate that the relation between stock returns and innovations in systematic volatility (idiosyncratic volatility) is substantially negative (near zero). These results suggest that asymmetric volatility is primarily attributed to systematic market-wide factors rather than aggregated firm-level effects. We also present evidence that supports our assumption that innovations in implied volatility are good proxies for innovations in expected stock volatility.
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SHEIKH, AAMIR M. "Stock Splits, Volatility Increases, and Implied Volatilities." Journal of Finance 44, no. 5 (December 1989): 1361–72. http://dx.doi.org/10.1111/j.1540-6261.1989.tb02658.x.

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Park, Yuen Jung. "The Information Content of the Implied Volatility in OTC Individual Stock Options Market." Journal of Derivatives and Quantitative Studies 20, no. 2 (May 31, 2012): 195–235. http://dx.doi.org/10.1108/jdqs-02-2012-b0003.

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This paper investigates the information content of implied volatilities inferred from individual stock options quoted over-the-counter (OTC). First, we examine whether the implied volatility has better explanatory power than historical volatility for forecasting future realized volatility of the underlying stock return. Next, we analyze the properties of volatility spreads, the difference between implied volatilities and realized volatilities. Using near-the-money options for 10 firms over the sample period from April 2005 to April 2010, we first demonstrate that the implied volatilities for most firms don’t have additional information beyond what are already contained in historical volatilities. However, the implied volatilities with some specific remaining maturities for two firms dominate historical volatilities in explaining the future realized volatilities. Second, we find that during the period before global financial crisis, the implied volatilities are systematically lower than the future realized volatilities whereas this reversal disappears after the year 2008. This finding suggests that there’s a possibility of the risk loving behavior of the investors in OTC individual stock options market during the pre-global crisis period. Finally, through the comparative analysis of the KOSPI200 index options quoted OTC over the same sample period, we conclude that the OTC individual stock options market has distinctive characteristics like the KRW/USD OTC currency options market.
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BRIGO, DAMIANO, and LAURENT COUSOT. "THE STOCHASTIC INTENSITY SSRD MODEL IMPLIED VOLATILITY PATTERNS FOR CREDIT DEFAULT SWAP OPTIONS AND THE IMPACT OF CORRELATION." International Journal of Theoretical and Applied Finance 09, no. 03 (May 2006): 315–39. http://dx.doi.org/10.1142/s0219024906003597.

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In this paper we investigate implied volatility patterns in the Shifted Square Root Diffusion (SSRD) model as functions of the model parameters. We begin by recalling the Credit Default Swap (CDS) options market model that is consistent with a market Black-like formula, thus introducing a notion of implied volatility for CDS options. We examine implied volatilities coming from SSRD prices and characterize the qualitative behavior of implied volatilities as functions of the SSRD model parameters. We introduce an analytical approximation for the SSRD implied volatility that follows the same patterns in the model parameters and that can be used to have a first rough estimate of the implied volatility following a calibration. We compute numerically the CDS-rate volatility smile for the adopted SSRD model. We find a decreasing pattern of SSRD implied volatilities in the interest-rate/intensity correlation. We check whether it is possible to assume zero correlation after the option maturity in computing the option price.
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Qabhobho, Thobekile, Emmanuel Asafo-Adjei, Peterson Owusu Junior, and Anokye M. Adam. "Quantifying information transfer between Commodities and Implied Volatilities in the Energy Markets: A Multi-frequency Approach." International Journal of Energy Economics and Policy 12, no. 5 (September 27, 2022): 472–81. http://dx.doi.org/10.32479/ijeep.13403.

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We investigate the multi-scale information transmission between two implied volatilities in the energy markets (crude oil volatility and volatility in the energy market) and energy commodities returns (global energy commodity, brent, heating oil, natural gas and petroleum). The Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) based Rényi transfer entropy approach is employed to accomplish the research objective. The study’s outcome underscores that information flow between implied volatilities and energy commodities is negative with significance being scale-dependent. Especially, significant negative information flow is found at specific intrinsic mode functions (IMFs) such as IMF1, and from IMFs 6-9 suggesting short-, upper medium and long-term energy markets dynamics. Comparatively, we find profound negative information flow with the crude oil implied volatility than the volatility in the entire energy market implying the former’s strong hedging benefits. Investors and policymakers should have knowledge about the dynamics of implied volatilities, particularly, the crude oil implied volatility when designing strategies for the energy commodities markets.
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Dash, Mihir. "Modeling of implied volatility surfaces of nifty index options." International Journal of Financial Engineering 06, no. 03 (September 2019): 1950028. http://dx.doi.org/10.1142/s2424786319500282.

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The implied volatility of an option contract is the value of the volatility of the underlying instrument which equates the theoretical option value from an option pricing model (typically, the Black–Scholes[Formula: see text]Merton model) to the current market price of the option. The concept of implied volatility has gained in importance over historical volatility as a forward-looking measure, reflecting expectations of volatility (Dumas et al., 1998). Several studies have shown that the volatilities implied by observed market prices exhibit a pattern very different from that assumed by the Black–Scholes[Formula: see text]Merton model, varying with strike price and time to expiration. This variation of implied volatilities across strike price and time to expiration is referred to as the volatility surface. Empirically, volatility surfaces for global indices have been characterized by the volatility skew. For a given expiration date, options far out-of-the-money are found to have higher implied volatility than those with an exercise price at-the-money. For short-dated expirations, the cross-section of implied volatilities as a function of strike is roughly V-shaped, but has a rounded vertex and is slightly tilted. Generally, this V-shape softens and becomes flatter for longer dated expirations, but the vertex itself may rise or fall depending on whether the term structure of at-the-money volatility is upward or downward sloping. The objective of this study is to model the implied volatility surfaces of index options on the National Stock Exchange (NSE), India. The study employs the parametric models presented in Dumas et al. (1998); Peña et al. (1999), and several subsequent studies to model the volatility surfaces across moneyness and time to expiration. The present study contributes to the literature by studying the nature of the stationary point of the implied volatility surface and by separating the in-the-money and out-of-the-money components of the implied volatility surface. The results of the study suggest that an important difference between the implied volatility surface of index call and put options: the implied volatility surface of index call options was found to have a minimum point, while that of index put options was found to have a saddlepoint. The results of the study also indicate the presence of a “volatility smile” across strike prices, with a minimum point in the range of 2.3–9.0% in-the-money for index call options and of 10.7–29.3% in-the-money for index put options; further, there was a jump in implied volatility in the transition from out-of-the-moneyness to in-the-moneyness, by 10.0% for index call options and about 1.9% for index put options.
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Dissertations / Theses on the topic "Implied volatilitie"

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PEDIO, MANUELA. "Essays on the Time Series and Cross-Sectional Predictive Power of Network-Based Volatility Spillover Measures." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/305198.

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• Questa tesi include due saggi che sono dedicati allo studio delle serie temporali e del potere predittivo a livello di cross-section di un indice di spillover di volatilità di nuova concezione basato sulle volatilità implicite delle opzioni. Nel primo saggio, ci concentriamo sulla stima dell'indice e sulla valutazione se i (cambiamenti nell'indice) possono prevedere i rendimenti in eccesso delle serie temporali di (un insieme di) singoli titoli e dello S&P 500. Si confronta il potere predittivo in-sample e out-of-sample di questo indice con quello dell'indice di spillover di volatilità proposto da Diebold e Yilmaz (2008, 2012), che si basa invece su volatilità realizzate. Sebbene entrambe le misure mostrino la prova del potere predittivo all'interno del campione, solo la misura basata sulla volatilità implicita è in grado di produrre previsioni out-of-sample che battono un semplice benchmark costituito dalla media storica. Troviamo che questo potere predittivo possa essere sfruttato da un investitore utilizzando semplici strategie di trading basate sul segno dell'eccesso di rendimento previsto e da un investitore media-varianza. Mostriamo anche che, nonostante la sovra-performance predittiva dell'indice di spillover della volatilità implicita provenga principalmente da periodi di alta volatilità, il potere previsionale aggiuntivo non è sussunto dall'inclusione del VIX (come proxy della volatilità aggregata) nelle regressioni predittive. Nel secondo saggio, indaghiamo se il rischio di spillover della volatilità (oltre al rischio di volatilità aggregata) sia valutato nella cross-section dei rendimenti delle azioni statunitensi. Per il nostro scopo, conduciamo diversi test di asset pricing (parametrici e non parametrici). In primo luogo, ordiniamo l'universo azionario in cinque portafogli quintili in base alla loro esposizione all'indice di spillover di volatilità implicita che abbiamo sviluppato nel primo saggio. In secondo luogo, utilizziamo una procedura di ordinamento condizionale per controllare le variabili che possono avere un effetto di confusione sui nostri risultati. Troviamo che i titoli con una bassa esposizione agli spillover di volatilità guadagnano in media il 6,45% all'anno in più rispetto ai titoli con un'elevata esposizione agli spillover di volatilità. Questa differenza persiste anche dopo l'aggiustamento per il rischio e quando controlliamo l'esposizione a shock di volatilità aggregata. Infine, utilizziamo un approccio Fama-Mac Beth per stimare il premio per il rischio associato al rischio di ricaduta della volatilità; questa procedura conferma in parte i risultati dell'analisi non parametrica di portfolio, sebbene il premio sia inferiore e generalmente stimato in modo impreciso.
This thesis includes two essays that are devoted to study the time-series and cross-sectional predictive power of a newly developed, forward-looking volatility spillover index based on option implied volatilities. In the first essay, we focus on the estimation of the index and on the assessment of whether the (changes in) the index can predict the time-series excess returns of (a set of) individual stocks and of the S&P 500. We also compare the in-sample and out-of-sample predictive power of this index with that of the volatility spillover index proposed by Diebold and Yilmaz (2008, 2012), which is instead based on realized, backward-looking volatilities. While both measures show evidence of in-sample predictive power, only the option-implied measure is able to produce out-of-sample forecasts that outperform a simple historical mean benchmark. We find this predictive power to be exploitable by an investor using simple trading strategies based on the sign of the predicted excess return and also by a mean-variance optimizer. We also show that, despite the predictive outperformance of the implied volatility spillover index is mostly coming from high-volatility periods, the additional forecast power is not subsumed by the inclusion of the VIX (as a proxy of aggregate volatility) in the predictive regressions. In the second essay, we investigate whether volatility spillover risk (in addition to aggregate volatility risk) is priced in the cross-section of US stock returns. To our purpose, we conduct several (parametric and non-parametric) asset pricing tests. First, we sort the stock universe into five quintile portfolios based on their exposure to the implied volatility spillover index that we have developed in the first essay. Second, we use a conditional sorting procedure to control for variables that may have a confounding effect on our results. We find that stocks with a low exposure to volatility spillovers earn an average 6.45% per annum more than stocks with a high exposure to volatility spillovers. This difference persists also after adjusting for risk and when we control for the exposure to aggregate volatility shocks. Finally, we employ a Fama-Mac Beth approach to estimate the risk premium associated with volatility spillover risk; this procedure partly confirms the results from the non-parametric, portfolio sorting analysis, although the premium is lower and generally imprecisely estimated.
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Varga, Lukáš. "Effect of Implied Volatility on FX Carry Trade." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-113592.

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This thesis aims to back-test the ability of implied volatility carry trade strategies to outperform the carry trade strategies in the FX markets. Recent research has shown that the profitability of the strategies is partly attributable to the market mispricings of the forward volatility agreements and a tendency of the forward implied volatility to overestimate the future spot implied volatility. This thesis uses a similar approach to construct portfolios containing 10 developed as well as 9 emerging market currencies. Our approach is based on the assumption that Uncovered Interest rate Parity (UIP), Forward Unbiasedness Hypothesis (FUH) and Forward Volatility Unbiasedness Hypothesis (FVUH) do not hold and therefore providing investors with several opportunities to construct trading strategies taking advantage of these market mispricings. In this thesis, we show that the foreign exchange carry trade strategy composed of the specific developed and emerging country's currencies can be outperformed by portfolio consisting of the implied volatility carry trade strategies in the FX market over the analysed period. The portfolios are adjusted to the riskiness which is accounted for by the VIX and VXY-G7 index for developed and VIX and VXY-EM index for emerging economies. The strong performance of the strategies outlined in this thesis can be of significant value to FX traders and portfolio managers.
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Hanzal, Martin. "Implikovaná volatilita a vyšší momenty rizikově neutrálního rozdělení jako předstihové indikátory realizované volatility." Master's thesis, Vysoká škola ekonomická v Praze, 2017. http://www.nusl.cz/ntk/nusl-358955.

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Implied volatility obtained from market option prices is widely regarded as an efficient predictor of future realised volatility. Implied volatility can be thought of as market's expectation of future realised volatility. We distinguish between volatility-changing events with respect to expectations - scheduled events (such as information releases) and unscheduled events. We propose a method of testing the information content of option-implied risk-neutral moments prior to volatility-changing events. Using the method introduced by Bakshi, Kapadia & Madan (2003) we extract implied volatility, skewness and kurtosis from S&P 500 options market prices and apply the proposed method in four case studies. Two are concerned with scheduled events - United Kingdom European Union membership referendum, 2016 and United States presidential election, 2016, two are concerned with unscheduled events - flash crash of August 24, 2015 and flash crash of October 15, 2014. Implied volatility indicates a rise in future realised volatility prior to both scheduled events. We find a significant rise in implied kurtosis during the last three days prior to the presidential election of 2016. Prior to unscheduled events, we find no evidence of implied moments indicating a rise in future realised volatility.
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Brodd, Tobias. "Modeling the Relation Between Implied and Realized Volatility." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273609.

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Options are an important part in today's financial market. It's therefore of high importance to be able to understand when options are overvalued and undervalued to get a lead on the market. To determine this, the relation between the volatility of the underlying asset, called realized volatility, and the market's expected volatility, called implied volatility, can be analyzed. In this thesis five models were investigated for modeling the relation between implied and realized volatility. The five models consisted of one Ornstein–Uhlenbeck model, two autoregressive models and two artificial neural networks. To analyze the performance of the models, different accuracy measures were calculated for out-of-sample forecasts. Signals from the models were also calculated and used in a simulated options trading environment to get a better understanding of how well they perform in trading applications. The results suggest that artificial neural networks are able to model the relation more accurately compared to more traditional time series models. It was also shown that a trading strategy based on forecasting the relation was able to generate significant profits. Furthermore, it was shown that profits could be increased by combining a forecasting model with a signal classification model.
Optioner är en viktig del i dagens finansiella marknad. Det är därför viktigt att kunna förstå när optioner är över- och undervärderade för att vara i framkant av marknaden. För att bestämma detta kan relationen mellan den underliggande tillgångens volatilitet, kallad realiserad volatilitet, och marknadens förväntade volatilitet, kallad implicit volatilitet, analyseras. I den här avhandlingen undersöktes fem modeller för att modellera relationen mellan implicit och realiserad volatilitet. De fem modellerna var en Ornstein–Uhlenbeck modell, två autoregressiva modeller samt två artificiella neurala nätverk. För att analysera modellernas prestanda undersöktes olika nogrannhetsmått för prognoser från modellerna. Signaler från modellerna beräknades även och användes i en simulerad optionshandelsmiljö för att få en bättre förståelse för hur väl de presterar i en handelstillämpning. Resultaten tyder på att artificiella neurala nätverk kan modellera relationen bättre än mer traditionella tidsseriemodellerna. Det visades även att en handelsstrategi baserad på prognoser av relationen kunde generera en signifikant vinst. Det visades dessutom att vinster kunde ökas genom att kombinera en prognosmodell med en modell som klassificerar signaler.
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Magnusson, Erik. "Implied Volatility Surface Construction." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-145894.

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Implied volatility surfaces are central tools used for pricing options. This thesis treats the topic of their construction. The main purpose is to uncover the most appropriate methodology for constructing implied volatility surfaces from discrete data and evaluate how well it performs. First some methods and techniques in use for such surface constructing are presented. Then the most attractive approach, chosen to contain 4 interesting models is studied. The models’ performances are tested on two price grids from the EURO STOXX 50 and Nikkei 225 indices. The found implied volatility surfaces give good and decent fits to the data, respectively. The surfaces are evaluated in terms of presence of static arbitrage and are found to have it, although mostly for strike price and time to maturity combinations which are somewhat abnormal and rarely traded. Arbitrage is found to be more prevalent in surfaces when the input data is of lower quality. The volatility surfaces’ shapes and absolute values are compared in between models but also within models for some of the best-fit producing parameter sets. The surfaces are found to differ in both cases for some strike and maturity combinations - sometimes with relative differences of more than 10%. This suggests that surfaces with good fits to the input data still can produce distinctly differing prices for some options. Calibrating the models with the chosen approach involves calculations with complex numbers in ways which potentially introduce problematic discontinuities due to branch crossings. This is investigated numerically as well as theoretically for the 4 models and found to be a significant problem in one of them. The three other models are found to avoid these problems under all valid parameter sets.
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Wang, Guan Jun. "Essays on option-implied volatility." Related electronic resource:, 2007. http://proquest.umi.com/pqdweb?did=1407687881&sid=1&Fmt=2&clientId=3739&RQT=309&VName=PQD.

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Marçal, Filipe Miguel Barbosa. "Earnings announcements and implied volatility." Master's thesis, Instituto Superior de Economia e Gestão, 2018. http://hdl.handle.net/10400.5/16739.

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Mestrado em Finanças
Eu analisei a reação da volatilidade implícita em opções do tipo europeu subjacentes a ações americanas num curto espaço de tempo antes e depois das divulgações de resultados trimestrais, de 2007 a 2016. Concluí que as empresas que apresentam resultados que não atingem as expetativas dos analistas têm uma menor redução de volatilidade implícita nas opções quando comparadas com empresas que apresentam resultados que atingem ou superam as expetativas dos analistas. Neste estudo encontrei também evidências de uma queda generalizada na volatilidade implícita nos três dias subsequentes às divulgações de resultados. No que corresponde às maturidades, quanto maior a maturidade, menor o impacto das divulgações de resultados no preço das opções. O Mercado de opções aparenta absorver rapidamente a informação mais recente, e contém informação útil sobre as expetativas dos investidores.
I have analyzed the reaction of the Implied Volatility on European style options regarding American equities in a short period before and after quarterly earnings announcements, from 2007 to 2016. I concluded that firms' earnings announcements that fail to meet analyst expectations produce a lower implied volatility drop on options, when compared to earnings announcements that meet/beat analyst expectations. In this study I also found evidence of a general decrease in implied volatility in a three-day window following the earnings announcements. In what regards the maturities of the options it seems the higher the maturity the less impact the earnings announcements have on the option pricing. The options market seems to absorb rapidly the new information, and contain useful information about investors' expectations.
info:eu-repo/semantics/publishedVersion
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Roome, Patrick. "Asymptotics of forward implied volatility." Thesis, Imperial College London, 2016. http://hdl.handle.net/10044/1/30764.

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We study asymptotics of forward-start option prices and the forward implied volatility smile using the theory of sharp large deviations (and refinements). In Chapter 1 we give some intuition and insight into forward volatility and provide motivation for the study of forward smile asymptotics. We numerically analyse no-arbitrage bounds for the forward smile given calibration to the marginal distributions using (martingale) optimal transport theory. Furthermore, we derive several representations of forward-start option prices, analyse various measure-change symmetries and explore asymptotics of the forward smile for small and large forward-start dates. In Chapter 2 we derive a general closed-form expansion formula (including large-maturity and 'diagonal' small-maturity asymptotics) for the forward smile in a large class of models including the Heston and Schobel-Zhu stochastic volatility models and time-changed exponential Levy models. In Chapter 3 we prove that the out-of-the-money small-maturity forward smile explodes in the Heston model and a separate model-independent analysis shows that the at-the-money small-maturity limit is well defined for any Ito diffusion. Chapter 4 provides a full characterisation of the large-maturity forward smile in the Heston model. Although the leading-order decay is provided by a fairly classical large deviations behaviour, the algebraic expansion providing the higher-order terms depends highly on the parameters, and different powers of the maturity come into play. Classical (Ito diffusions) stochastic volatility models are not able to capture the steepness of small-maturity (spot) implied volatility smiles. Models with jumps, exhibiting small-maturity exploding smiles, have historically been proposed as an alternative. A recent breakthrough was made by Gatheral, Jaisson and Rosenbaum, who proposed to replace the Brownian driver of the instantaneous volatility by a short-memory fractional Brownian motion, which is able to capture the short-maturity steepness while preserving path continuity. In Chapter 5 we suggest a different route, randomising the Black-Scholes variance by a CEV-generated distribution, which allows us to modulate the rate of explosion (through the CEV exponent) of the implied volatility for small maturities. The range of rates includes behaviours similar to exponential Levy models and fractional stochastic volatility models. As a by-product, we make a conjecture on the small-maturity forward smile asymptotics of stochastic volatility models, in exact agreement with the results in Chapter 3 for Heston.
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Ye, Hui. "A Comparison of Local Volatility and Implied Volatility." Thesis, Uppsala universitet, Analys och tillämpad matematik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154745.

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Cap, Thi Diu. "Implied volatility with HJM–type Stochastic Volatility model." Thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-54938.

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In this thesis, we propose a new and simple approach of extending the single-factor Heston stochastic volatility model to a more flexible one in solving option pricing problems.  In this approach, the volatility process for the underlying asset dynamics depends on the time to maturity of the option. As this idea is inspired by the Heath-Jarrow-Morton framework which models the evolution of the full dynamics of forward rate curves for various maturities, we name this approach as the HJM-type stochastic volatility (HJM-SV)  model. We conduct an empirical analysis by calibrating this model to real-market option data for underlying assets including an equity  (ABB stock) and a market index (EURO STOXX 50), for two separated time spans from Jan 2017 to Dec 2017 (before the COVID-19 pandemic) and from Nov 2019 to Nov 2020 (after the start of COVID-19 pandemic). We investigate the optimal way of dividing the set of option maturities into three classes, namely, the short-maturity, middle-maturity, and long-maturity classes. We calibrate our HJM-SV model to the data in the following way, for each class a single-factor Heston stochastic volatility model is calibrated to the corresponding market data. We address the question that how well the new HJM-SV model captures the feature of implied volatility surface given by the market data.
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Books on the topic "Implied volatilitie"

1

Hafner, Reinhold. Stochastic Implied Volatility. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17117-8.

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Kanas, Angelos. Forecasting exchange rate volatility: The significance of volatilities implied in currency options premiums. Birmingham: Aston Business School, 1992.

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Dumas, Bernard. Implied volatility functions: Empirical tests. Cambridge, MA: National Bureau of Economic Research, 1996.

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Dumas, Bernard. Implied volatility functions: Empirical tests. London: Centrefor Economic Policy Research, 1996.

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Bollerslev, Tim. Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities. Washington, D.C: Federal Reserve Board, 2004.

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Ahokas, R. T. Analysis of the term structure of implied volatilities. Manchester: UMIST, 1997.

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Hafner, Reinhold. Stochastic implied volatility: A factor-based model. Berlin: Springer, 2004.

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Le, Thi. Analysing Intraday Implied Volatility for Pricing Currency Options. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71242-6.

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Andersen, Torben G. Construction and interpretation of model-free implied volatility. Cambridge, Mass: National Bureau of Economic Research, 2007.

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Skiadopoulos, Georgios. Modelling the dynamics of implied volatility smiles and surfaces. [s.l.]: typescript, 1999.

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Book chapters on the topic "Implied volatilitie"

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Hafner, Reinhold. "Implied Volatility." In Lecture Notes in Economics and Mathematical Systems, 23–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17117-8_3.

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Hol, Eugenie M. J. H. "Implied Volatility." In Dynamic Modeling and Econometrics in Economics and Finance, 63–70. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-5129-1_5.

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Brockhaus, Oliver. "Implied Volatility." In Equity Derivatives and Hybrids, 43–51. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137349491_4.

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Wickerhauser, Mladen Victor. "Implied Volatility." In Introducing Financial Mathematics, 175–90. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003329695-7.

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Farid, Jawwad Ahmed. "Forward Implied Volatilities." In An Option Greeks Primer, 125–29. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137371676_9.

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Brockhaus, Oliver. "Implied Volatility Dynamics." In Equity Derivatives and Hybrids, 95–113. London: Palgrave Macmillan UK, 2016. http://dx.doi.org/10.1057/9781137349491_7.

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Le, Thi. "Implied Volatility Forecasting Realized Volatility." In Analysing Intraday Implied Volatility for Pricing Currency Options, 51–91. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71242-6_4.

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Hafner, Reinhold. "Properties of DAX Implied Volatilities." In Lecture Notes in Economics and Mathematical Systems, 73–113. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17117-8_5.

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Fengler, Matthias R., Wolfgang Härdie, and Peter Schmidt. "The Analysis of Implied Volatilities." In Applied Quantitative Finance, 127–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-05021-7_6.

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Stojanovic, Srdjan. "Implied Volatility for European Options." In Computational Financial Mathematics using MATHEMATICA®, 197–266. Boston, MA: Birkhäuser Boston, 2003. http://dx.doi.org/10.1007/978-1-4612-0043-7_6.

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Conference papers on the topic "Implied volatilitie"

1

Cheng, Jingfei, and Guibin Lu. "Volatility Forecasting Model-Free Implied Volatility." In International Conference on Education, Management, Commerce and Society. Paris, France: Atlantis Press, 2015. http://dx.doi.org/10.2991/emcs-15.2015.101.

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He, Peng, and Stephen Shing-Toung Yau. "Forecasting Stock Market Volatility Using Implied Volatility." In 2007 American Control Conference. IEEE, 2007. http://dx.doi.org/10.1109/acc.2007.4282578.

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Zhuang, Ying, and Meiqing Wang. "Comparison of Several Implied Volatility Models." In 2017 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES). IEEE, 2017. http://dx.doi.org/10.1109/dcabes.2017.18.

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Borak, S., M. Fengler, and W. Hardle. "DSFM fitting of implied volatility surfaces." In 5th International Conference on Intelligent Systems Design and Applications (ISDA'05). IEEE, 2005. http://dx.doi.org/10.1109/isda.2005.40.

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Kralik, Balazs, Nora Felfoeldi-Szuecs, and Kata Varadi. "Implied volatility based margin calculation on cryptocurrency markets." In 36th ECMS International Conference on Modelling and Simulation. ECMS, 2022. http://dx.doi.org/10.7148/2022-0070.

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The focus of our research is the use of implied volatility in the context of margin calculations on BTC positions. We will compare the standard deviation estimated from historical data to the implied volatility values estimated from ATM option prices. As our main result, we show that the implied volatility is a superior basis for margining purposes. Not only does it perform better in a back test, it also requires lower average margin levels to provide the same risk profile. Our results also show that the logreturns of BTC cannot be assumed to be normally distributed.
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Sun, Huiping, Meiqing Wang, Boyuan Du, and Jingyue Wang. "A Weighted Strike-Related Implied Volatility Model." In 2018 17th International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES). IEEE, 2018. http://dx.doi.org/10.1109/dcabes.2018.00062.

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Han, Henry. "Hierarchical learning for option implied volatility pricing." In Hawaii International Conference on System Sciences. Hawaii International Conference on System Sciences, 2021. http://dx.doi.org/10.24251/hicss.2021.190.

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Pranesh, K. Kiran, P. Balasubramanian, and Deepti Mohan. "The determinants of India's implied volatility index." In 2017 International Conference on Data Management, Analytics and Innovation (ICDMAI). IEEE, 2017. http://dx.doi.org/10.1109/icdmai.2017.8073532.

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Choi, Stanley, Gang Dong, and Kin Keung Lai. "Option Implied Volatility Estimation: A Computational Intelligent Approach." In 2011 Fourth International Joint Conference on Computational Sciences and Optimization (CSO). IEEE, 2011. http://dx.doi.org/10.1109/cso.2011.197.

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Sheng, Chieh-Chung, and Hsiao-Ya Chiu. "Pricing European Options with Actual Implied Volatility Distributions." In 2007 International Conference on Convergence Information Technology - ICCIT '07. IEEE, 2007. http://dx.doi.org/10.1109/iccit.2007.419.

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Reports on the topic "Implied volatilitie"

1

Dumas, Bernard, Jeff Fleming, and Robert Whaley. Implied Volatility Functions: Empirical Tests. Cambridge, MA: National Bureau of Economic Research, March 1996. http://dx.doi.org/10.3386/w5500.

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Andersen, Torben, and Oleg Bondarenko. Construction and Interpretation of Model-Free Implied Volatility. Cambridge, MA: National Bureau of Economic Research, September 2007. http://dx.doi.org/10.3386/w13449.

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Cassese, Gianluca, and Massimo Guidolin. Modelling the MIB30 Implied Volatility Surface. Does Efficiency Matter? Federal Reserve Bank of St. Louis, 2005. http://dx.doi.org/10.20955/wp.2005.008.

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Wei, Shang-Jin, and Jeffrey Frankel. Are Option-Implied Forecasts of Exchange Rate Volatility Excessively Variable? Cambridge, MA: National Bureau of Economic Research, November 1991. http://dx.doi.org/10.3386/w3910.

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Neely, Christopher J. Forecasting Foreign Exchange Volatility: Why Is Implied Volatility Biased and Inefficient? And Does It Matter? Federal Reserve Bank of St. Louis, 2002. http://dx.doi.org/10.20955/wp.2002.017.

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Graham, John, and Campbell Harvey. Market Timing Ability and Volatility Implied in Investment Newletters' Asset Allocation Recommendations. Cambridge, MA: National Bureau of Economic Research, October 1994. http://dx.doi.org/10.3386/w4890.

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Goncalves, Silvia, and Massimo Guidolin. Predictable Dynamics in the S&P 500 Index Options Implied Volatility Surface. Federal Reserve Bank of St. Louis, 2005. http://dx.doi.org/10.20955/wp.2005.010.

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Cecchetti, Stephen, Pok-sang Lam, and Nelson Mark. Testing Volatility Restrictions on Intertemporal Marginal Rates of Substitution Implied by Euler Equations and Asset Returns. Cambridge, MA: National Bureau of Economic Research, July 1992. http://dx.doi.org/10.3386/t0124.

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Neely, Christopher J. Implied Volatility from Options on Gold Futures: Do Econometric Forecasts Add Value or Simply Paint the Lilly? Federal Reserve Bank of St. Louis, 2003. http://dx.doi.org/10.20955/wp.2003.018.

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