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Lars Stentoft - One of the best experts on this subject based on the ideXlab platform.

  • what we can learn from pricing 139 879 Individual Stock options
    Journal of Derivatives, 2015
    Co-Authors: Lars Stentoft
    Abstract:

    It has long been obvious that Stock volatility is not a constant knowable parameter, as the original Black–Scholes model assumed, but no single extension to stochastic time-varying volatility has replaced it. The GARCH family of volatility models has the highly desirable feature that variance is a direct function of returns, so there is still only one source of risk, and volatility can be estimated easily from observed data. There are still unsettled issues in this framework, however, including which GARCH model to use, whether an asymmetry term should be included, and whether return shocks should be assumed to come from a normal distribution or some fatter-tailed alternative. In this article, Stentoft runs a horse race among GARCH-type models using the 30 Stocks in the Dow Jones Industrial Average. An interesting innovation is to use the relatively new theory of model confidence sets in the testing procedure. The winner is NGARCH with normal inverse Gaussian errors.

  • american option pricing with discrete and continuous time models an empirical comparison
    Journal of Empirical Finance, 2011
    Co-Authors: Lars Stentoft
    Abstract:

    Abstract This paper considers discrete time GARCH and continuous time SV models and uses these for American option pricing. We first of all show that with a particular choice of framework the parameters of the SV models can be estimated using simple maximum likelihood techniques. We then perform a Monte Carlo study to examine their differences in terms of option pricing, and we study the convergence of the discrete time option prices to their implied continuous time values. Finally, a large scale empirical analysis using Individual Stock options and options on an index is performed comparing the estimated prices from discrete time models to the corresponding continuous time model prices. The results show that, while the overall differences in performance are small, for the in the money put options on Individual Stocks the continuous time SV models do generally perform better than the discrete time GARCH specifications.

  • american option pricing with discrete and continuous time models an empirical comparison
    Research Papers in Economics, 2011
    Co-Authors: Lars Stentoft
    Abstract:

    This paper considers discrete time GARCH and continuous time SV models and uses these for American option pricing. We first of all show that with a particular choice of framework the parameters of the SV models can be estimated using simple maximum likelihood techniques. Hence the two types of models can be implemented in an internally consistent manner. We then perform a Monte Carlo study to examine their differences in terms of option pricing, and we study the convergence of the discrete time option prices to their implied continuous time values. The results show that there are differences between the two models, though the discrete time GARCH prices converge quickly to the continuous time SV values. Finally, a large scale empirical analysis using Individual Stock options and options on an index is performed comparing the estimated prices from discrete time models to the corresponding continuous time model prices. The results show that, while the overall differences in performance are small, for the in the money put options on Individual Stocks the continuous time SV models do generally perform better than the discrete time GARCH specifications.

  • american option pricing with discrete and continuous time models an empirical comparison
    Social Science Research Network, 2011
    Co-Authors: Lars Stentoft
    Abstract:

    This paper considers discrete time GARCH and continuous time SV models and uses these for American option pricing. We perform a Monte Carlo study to examine their differences in terms of option pricing, and we study the convergence of the discrete time option prices to their implied continuous time values. Finally, a large scale empirical analysis using Individual Stock options and options on an index is performed comparing the estimated prices from discrete time models to the corresponding continuous time model prices. The results indicate that, while the differences in performance are small overall, for in the money options the continuous time SV models do generally perform better than the discrete time GARCH specifications.

  • what we can learn from pricing 139 879 Individual Stock options
    CREATES Research Papers, 2011
    Co-Authors: Lars Stentoft
    Abstract:

    The GARCH framework has been used for option pricing with quite some success. While the initial work assumed conditional Gaussian innovations, recent contributions relax this assumption and allow for more flexible parametric specifications of the underlying distribution. However, until now the empirical applications have been limited to index options or options on only a few Stocks and this using only few potential distributions and variance specififications. In this paper we test the GARCH framework on 30 Stocks in the Dow Jones Industrial Average using two classical volatility specififications and 7 different underlying distributions. Our results provide clear support for using an asymmetric volatility specifification together with non-Gaussian distribution, particularly of the Normal Inverse Gaussian type, and statistical tests show that this model is most frequently among the set of best performing models.

Olivier Scaillet - One of the best experts on this subject based on the ideXlab platform.

  • factors and risk premia in Individual international Stock returns
    Journal of Financial Economics, 2021
    Co-Authors: Ines Chaieb, Hugues Langlois, Olivier Scaillet
    Abstract:

    Abstract We propose an estimation methodology tailored for large unbalanced panels of Individual Stock returns to study the factor structure and expected returns in international Stock markets. We show that the local market is necessary to capture the factor structure in both developed and emerging markets. Neither the presence of multiple world or regional risk factors, systematic currency risk factors, nor a country-specific currency subsumes the importance of the local market factor. All factors, including the local market, carry significant risk premia across a large proportion of countries. The contribution of pricing errors to total expected returns is large and time-varying.

  • time varying risk premium in large cross sectional equity data sets
    Econometrica, 2016
    Co-Authors: Patrick Gagliardini, Elisa Ossola, Olivier Scaillet
    Abstract:

    We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of Individual Stock returns. We estimate the time-varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset specific instruments. The estimator uses simple weighted two-pass cross-sectional regressions, and we show its consistency and asymptotic normality under increasing cross-sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no-arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi-period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousands US Stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time-invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four-factor model capturing market, size, value and momentum effects.

Tarun Chordia - One of the best experts on this subject based on the ideXlab platform.

  • liquidity and autocorrelations in Individual Stock returns
    Journal of Finance, 2006
    Co-Authors: Doron Avramov, Tarun Chordia, Amit Goyal
    Abstract:

    This paper documents a strong relationship between short-run reversals and Stock illiquidity, even after controlling for trading volume. The largest reversals and the potential contrarian trading strategy profits occur in high turnover, low liquidity Stocks, as the price pressures caused by non-informational demands for immediacy are accommodated. However, the contrarian trading strategy profits are smaller than the likely transactions costs. This lack of profitability and the fact that the overall findings are consistent with rational equilibrium paradigms suggest that the violation of the efficient market hypothesis due to short-term reversals is not so egregious after all. ASSET PRICES SHOULD FOLLOW A MARTINGALE PROCESS over short horizons as systematic short-run changes in fundamental values should be negligible in an efficient market with unpredictable information arrival. However, Lehmann (1990) and Jegadeesh (1990) show that contrarian strategies that exploit the short-run return reversals in Individual Stocks generate abnormal returns of about 1.7% per week and 2.5% per month, respectively. Subsequently, Ball, Kothari, and Wasley (1995) and Conrad, Gultekin, and Kaul (1997) suggest that much of such reversal profitability is within the bid‐ask bounce. Theoretically, the potential role of liquidity in explaining the high abnormal payoffs to short-run contrarian strategies is implied by the rational equilibrium framework of Campbell, Grossman, and Wang (1993) (henceforth, CGW). In the CGW model, non-informational trading causes price movements that, when absorbed by liquidity suppliers, cause prices to revert. Such non-informed trading is accompanied by high trading volume, whereas informed trading is accompanied by little trading volume. Thus, price changes accompanied by high (low) trading volume should (should not) revert. Empirically, Conrad, Hameed, and Niden (1994) (henceforth, CHN) find that reversal profitability increases with trading

  • asset pricing models and financial market anomalies
    Social Science Research Network, 2005
    Co-Authors: Doron Avramov, Tarun Chordia
    Abstract:

    This paper derives and implements a framework in which to test whether conditional asset pricing models, applied to single securities, can explain the size, value, turnover, and momentum effects in expected Stock returns. In this framework Individual Stock betas vary with firm level size and book-to-market as well as with macroeconomic variables. The evidence shows that under the extensively studied constant beta framework, none of the models examined capture any of the size, value, turnover, and past return effects, even when returns are risk-adjusted by size, value, liquidity, and momentum factors. In contrast, when beta is allowed to vary, the size and book to market effects are often explained, but the explanatory power of turnover and past return remains robust. The past return or momentum effect is related to model mispricing that varies with macroeconomic variables, whereas turnover shows no business cycle patterns.

  • liquidity and autocorrelations in Individual Stock returns
    Social Science Research Network, 2005
    Co-Authors: Doron Avramov, Tarun Chordia, Amit Goyal
    Abstract:

    This paper documents a strong relationship between short-run reversals and Stock return illiquidity, even after controlling for trading volume. The largest reversals and the potential contrarian trading strategy profits occur in the high turnover, low liquidity Stocks, as the price pressures caused by non-informational demands for immediacy are accommodated. Thus, the high frequency negative autocorrelations are more likely to result from stresses in the market for liquidity. The contrarian trading strategy profits are smaller than the likely transactions costs because the high turnover, low liquidity Stocks face large transaction and market impact costs. This lack of profitability and the fact that the overall findings are consistent with rational equilibrium paradigms suggest that the violation of the efficient market hypothesis due to short-term reversals is not so egregious after all.

  • order imbalance and Individual Stock returns theory and evidence
    Journal of Financial Economics, 2004
    Co-Authors: Tarun Chordia, Avanidhar Subrahmanyam
    Abstract:

    Abstract This paper studies the relation between order imbalances and daily returns of Individual Stocks. Our tests are motivated by a model which considers how market makers dynamically accommodate autocorrelated imbalances emanating from large traders who optimally choose to split their orders. Price pressures caused by autocorrelated imbalances cause a positive relation between lagged imbalances and returns, which reverses sign after controlling for the current imbalance. We find empirical evidence consistent with these implications. We also find that imbalance-based trading strategies yield statistically significant returns. Our results shed light on the role of inventory effects in daily Stock price movements.

  • order imbalance and Individual Stock returns
    Social Science Research Network, 2002
    Co-Authors: Tarun Chordia, Avanidhar Subrahmanyam
    Abstract:

    This paper studies the relation between order imbalances and daily returns of Individual Stocks. Our tests are motivated by a theoretical framework, whose distinguishing feature is that it explicitly considers how market makers with inventory concerns dynamically accommodate autocorrelated imbalances. Persistence in imbalances arises because agents split their orders over time to minimize expected trading costs. In equilibrium, continuing price pressures caused by autocorrelated imbalances cause a positive relation between lagged imbalances and returns over daily horizons. However, this positive relation reverses sign after controlling for the current imbalance. We find empirical evidence consistent with all of these implications of the model. We also find that imbalance-based trading strategies yield statistically significant returns, the magnitude of which is moderate enough to be consistent with an equilibrium wherein intermediaries with inventory concerns accommodate persistent trader demands.

Jean Jacod - One of the best experts on this subject based on the ideXlab platform.

  • analyzing the spectrum of asset returns jump and volatility components in high frequency data
    Journal of Economic Literature, 2012
    Co-Authors: Yacine Aitsahalia, Jean Jacod
    Abstract:

    This paper reports some of the recent developments in the econometric analysis of semimartingales estimated using high frequency financial returns. It describes a simple yet powerful methodology to decompose asset returns sampled at high frequency into their base components (continuous, small jumps, large jumps), determine the relative magnitude of the components, and analyze the finer characteristics of these components such as the degree of activity of the jumps. We incorporate to effect of market microstructure noise on the test statistics, apply the methodology to high frequency Individual Stock returns, transactions and quotes, Stock index returns and compare the qualitative features of the estimated process for these different data and discuss the economic implications of the results.( JEL C58, G12, G13)

  • analyzing the spectrum of asset returns jump and volatility components in high frequency data
    Journal of Economic Literature, 2012
    Co-Authors: Yacine Aitsahalia, Jean Jacod
    Abstract:

    This paper describes a simple yet powerful methodology to decompose asset returns sampled at high frequency into their base components (continuous, small jumps, large jumps), determine the relative magnitude of the components, and analyze the finer characteristics of these components such as the degree of activity of the jumps. We extend the existing theory to incorporate to effect of market microstructure noise on the test statistics, apply the methodology to high frequency Individual Stock returns, transactions and quotes, Stock index returns and compare the qualitative features of the estimated process for these different data and discuss the economic implications of the results.

  • is brownian motion necessary to model high frequency data
    Annals of Statistics, 2010
    Co-Authors: Yacine Aitsahalia, Jean Jacod
    Abstract:

    This paper considers the problem of testing for the presence of a continuous part in a semimartingale sampled at high frequency. We provide two tests, one where the null hypothesis is that a continuous component is present, the other where the continuous component is absent, and the model is then driven by a pure jump process. When applied to high-frequency Individual Stock data, both tests point toward the need to include a continuous component in the model.

David Weinbaum - One of the best experts on this subject based on the ideXlab platform.

  • Individual Stock option prices and credit spreads
    Journal of Banking and Finance, 2008
    Co-Authors: Martijn Cremers, Joost Driessen, Pascal J Maenhout, David Weinbaum
    Abstract:

    This paper introduces measures of volatility and jump risk that are based on Individual Stock options to explain credit spreads on corporate bonds. Implied volatilities of Individual options are shown to contain useful information for credit spreads and improve on historical volatilities when explaining the cross-sectional and time-series variation in a panel of corporate bond spreads. Both the level of Individual implied volatilities and (to a lesser extent) the implied-volatility skew matter for credit spreads. Detailed principal component analysis shows that a large part of the time-series variation in credit spreads can be explained in this way.

  • Individual Stock option prices and credit spreads
    Research Papers in Economics, 2005
    Co-Authors: Martijn Cremers, Joost Driessen, Pascal J Maenhout, David Weinbaum
    Abstract:

    This paper introduces measures of volatility and skewness that are based on Individual Stock options to explain credit spreads on corporate bonds. Implied volatilities of Individual options are shown to contain important information for credit spreads and improve on both implied volatilities of index options and on historical volatilities when explaining the cross-sectional and time-series variation in a panel of corporate bond spreads. Both the level of Individual implied volatilities and the implied-volatility skew matter for credit spreads. The empirical estimates are in line with the coefficients pred

  • Individual Stock option prices and credit spreads
    Social Science Research Network, 2004
    Co-Authors: Martijn Cremers, Joost Driessen, Pascal J Maenhout, David Weinbaum
    Abstract:

    This paper introduces measures of volatility and skewness that are based on Individual Stock options to explain credit spreads on corporate bonds. Implied volatilities of Individual options are shown to contain important information for credit spreads and improve on both implied volatilities of index options and on historical volatilities when explaining the cross-sectional and time-series variation in a panel of corporate bond spreads. Both the level of Individual implied volatilities and the implied-volatility skew matter for credit spreads. The empirical estimates are in line with the coefficients predicted by a theoretical structural firm value model. Importantly, detailed principal component analysis shows that our newly constructed determinants of credit spreads reverse the finding in the literature that structural models leave a large part of the variation in credit spreads unexplained. Furthermore, our results indicate that option-market liquidity has a spillover effect on the short-maturity corporate bond market, and we show that Individual option prices contain information on the likelihood of rating migrations.