Volatility smile ≈ Volatility smile
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Hourly Oil Price Volatility: The Role of COVID-19 Open
In this paper, we study the evolution of hourly oil price volatility. Using multiple measures of oil price volatility, we conclude that volatility increased following the onset of COVID-19. After controlling for conventional predictors of …
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On the return-volatility relationship in the Bitcoin market around the price crash of 2013 Open
The authors examine the relation between price returns and volatility changes in the Bitcoin market using a daily database denominated in US dollar. The results for the entire period provide no evidence of an asymmetric return-volatility r…
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Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis Open
We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure…
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Good Volatility, Bad Volatility, and the Cross Section of Stock Returns Open
Based on intraday data for a large cross section of individual stocks and newly developed econometric procedures, we decompose the realized variation for each of the stocks into separate so-called realized up and down semi-variance measure…
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Volatility impulse response analysis for DCC‐GARCH models: The role of volatility transmission mechanisms Open
This study introduces volatility impulse response functions (VIRF) for dynamic conditional correlation–generalized autoregressive conditional heteroskedasticity (DCC‐GARCH) models. In addition, the implications with respect to network anal…
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Short‐Term Market Risks Implied by Weekly Options Open
We study short‐maturity (“weekly”) S&P 500 index options, which provide a direct way to analyze volatility and jump risks. Unlike longer‐dated options, they are largely insensitive to the risk of intertemporal shifts in the economic enviro…
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Deep learning volatility: a deep neural network perspective on pricing and calibration in (rough) volatility models Open
We present a neural network-based calibration method that performs the calibration task within a few milliseconds for the full implied volatility surface. The framework is consistently applicable throughout a range of volatility models—inc…
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Volatility Spillover Effect between Stock and Exchange Rate in Oil Exporting Countries Open
This paper proposes the volatility spillover effect between stock and foreign exchange markets in both directions in oil exporting countries – Russia and Brazil. The data sample consists of daily observations. The method is based on FIGARC…
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Stabilizing effect of volatility in financial markets Open
In financial markets, greater volatility is usually considered to be synonymous with greater risk and instability. However, large market downturns and upturns are often preceded by long periods where price returns exhibit only small fluctu…
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Volatility Spillovers between Equity and Green Bond Markets Open
This study examines the market for green bonds, which have been in the spotlight as an eco-friendly investment product. We analyze the volatility dynamics and spillovers between the equity and green bond markets. As the return dynamics of …
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Price volatility in the carbon market in China Open
China is the world’s largest developing country and a carbon dioxide emitter. A functional carbon market can effectively reduce carbon emissions. This paper uses the Markov chain Monte Carlo-stochastic volatility model and the wavelet mult…
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Are shocks on the returns and volatility of cryptocurrencies really persistent? Open
This letter questions the true nature (true versus spurious) of the Long Range Dependence (LRD) behavior observed in the returns and volatility series of four Cryptocurrencies (CC). Using a robust approach, this letter shows that the LRD b…
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Rough volatility: Evidence from option prices Open
It has been recently shown that spot volatilities can be closely modeled by rough stochastic volatility-type dynamics. In such models, the log-volatility follows a fractional Brownian motion with Hurst parameter smaller than half. This res…
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Growth options and firm valuation Open
This paper studies the relationship between firm value and a firm's growth options. We find strong empirical evidence that Tobin's Q increases with firm‐level volatility. The significance mainly comes from R&D firms, which have more growth…
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Volatility persistence in cryptocurrency markets under structural breaks Open
This paper deals with the analysis of volatility persistence in 12 main cryptocurrencies (Bitcoin, Bitshare, Bytecoin, Dash, Ether, Litecoin, Monero, Nem, Ripple, Siacoin, Stellar and Tether) taking into account the possibility of structur…
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Asset volatility Open
We examine whether fundamental measures of volatility are incremental to market-based measures of volatility in (i) predicting bankruptcies (out of sample), (ii) explaining cross-sectional variation in credit spreads, and (iii) explaining …
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Modeling Exchange Rate Volatility: Application of the GARCH and EGARCH Models Open
Policy makers need accurate forecasts about future values of exchange rates. This is due to the fact that exchange rate volatility is a useful measure of uncertainty about the economic environment of a country. This paper applies univariat…
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Time-Varying Periodicity in Intraday Volatility Open
We develop a nonparametric test for whether return volatility exhibits time-varying intraday periodicity using a long time series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatil…
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Short-time near-the-money skew in rough fractional volatility models Open
We consider rough stochastic volatility models where the driving noise of volatility has fractional scaling, in the ‘rough’ regime of Hurst parameter H<1/2. This regime recently attracted a lot of attention both from the statistical and op…
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Modelling and Estimation of Volatility Using ARCH/GARCH Models in Jordan’s Stock Market Open
Financials have been concerned constantly with factors that have impact on both taking and assessing various financial decisions in firms. Hence modelling volatility in financial markets is one of the factors that have direct role and effe…
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Implied volatility directional forecasting: a machine learning approach Open
This study investigates whether the direction of U.S. implied volatility, VIX index, can be forecast. Multiple forecasts are generated based on standard econometric models, but, more importantly, on several machine learning techniques. The…
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A Generative Adversarial Network Approach to Calibration of Local Stochastic Volatility Models Open
We propose a fully data-driven approach to calibrate local stochastic volatility (LSV) models, circumventing in particular the ad hoc interpolation of the volatility surface. To achieve this, we parametrize the leverage function by a famil…
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Can we forecast the implied volatility surface dynamics of equity options? Predictability and economic value tests Open
We examine whether the dynamics of the implied volatility surface of individual equity options contains exploitable predictability patterns. Predictability in implied volatilities is expected due to the learning behavior of agents in optio…
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The Impact of COVID-19 on Gold Price Volatility Open
Purpose: This article investigates the implications of the spread of COVID-19 on gold spot prices.Design/Methodology/Approach: We use GARCH and GJR-GARCH models based on daily gold returns over the period 2012-2020 to analyze the impact of…
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Can we use volatility to diagnose financial bubbles? lessons from 40 historical bubbles Open
We inspect the price volatility before, during, and after financial asset bubbles in orderto uncover possible commonalities and check empirically whether volatility might be used as anindicator or an early warning signal of an unsustainabl…
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Randomness, Informational Entropy, and Volatility Interdependencies among the Major World Markets: The Role of the COVID-19 Pandemic Open
The main purpose of our paper is to evaluate the impact of the COVID-19 pandemic on randomness in volatility series of world major markets and to examine its effect on their interconnections. The data set includes equity (Bitcoin and Stand…
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Shifts in volatility driven by large stock market shocks Open
This paper presents an extension of the stochastic volatility model which allows for level shifts in volatility of stock market returns, known as structural breaks. These shifts are endogenously driven by large return shocks (innovations),…
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Forecasting realized volatility: The role of implied volatility, leverage effect, overnight returns, and volatility of realized volatility Open
We forecast realized volatility extending the heterogeneous autoregressive model (HAR) to include implied volatility (IV), the leverage effect, overnight returns, and the volatility of realized volatility. We analyze 10 international stock…
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Do collective emotions drive bitcoin volatility? A triple regime-switching vector approach Open
In this paper, we build an empirical specification that helps to explain bitcoin volatility and to characterize phases of the bitcoin bubble using information derived from investors' emotions and sentiment that captures investment intentio…
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Learning from History: Volatility and Financial Crises Open
We study the effects of volatility on financial crises by constructing a cross-country database spanning over 200 years. Volatility is not a significant predictor of crises whereas unusually high and low volatilities are. Low volatility is…