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This study investigates the daily co-movements in commodity prices over the period 2006–2020 using a novel approach based on a time-varying Gerber correlation. The statistic is computed considering a set of probabilities estimated via non-traditional models that give a time-varying structure to the measure. The results indicate that there are several co-movements across commodities, that these co-movements change over time, and that they are tendentially positive. Conditional auto-regressive multithreshold logit models show higher forecasting accuracy for agricultural returns, while dynamic conditional correlation models are more accurate for energy products and metals. The proposed models are shown to be superior in terms of forecasting power to the benchmark method which is based on estimating the Gerber correlation moving a rolling window.
Bernardina Algieri; Arturo Leccadito; Pietro Toscano. A Time-Varying Gerber Statistic: Application of a Novel Correlation Metric to Commodity Price Co-Movements. Forecasting 2021, 3, 339 -354.
AMA StyleBernardina Algieri, Arturo Leccadito, Pietro Toscano. A Time-Varying Gerber Statistic: Application of a Novel Correlation Metric to Commodity Price Co-Movements. Forecasting. 2021; 3 (2):339-354.
Chicago/Turabian StyleBernardina Algieri; Arturo Leccadito; Pietro Toscano. 2021. "A Time-Varying Gerber Statistic: Application of a Novel Correlation Metric to Commodity Price Co-Movements." Forecasting 3, no. 2: 339-354.
Cyber risks and particularly data breaches constitute one of the new frontiers of risk modeling for insurers across the world. We use the cointegration methodology to uncover the relation between data breaches and Bitcoin-related variables. We perform our analyses on two different datasets of data breaches. In both cases, we provide statistical evidence of a bidirectional lead–lag relation in the short run between the variables under investigation. Moreover, the existence of a cointegrating vector suggests that this relation is likely to persist in the long run. To evaluate the quantitative implications of the relations found, we complement the study with Granger causality tests, impulse response analyses and variance decompositions of the forecasting errors.
Domenico De Giovanni; Arturo Leccadito; Marco Pirra. On the determinants of data breaches: A cointegration analysis. Decisions in Economics and Finance 2020, 44, 141 -160.
AMA StyleDomenico De Giovanni, Arturo Leccadito, Marco Pirra. On the determinants of data breaches: A cointegration analysis. Decisions in Economics and Finance. 2020; 44 (1):141-160.
Chicago/Turabian StyleDomenico De Giovanni; Arturo Leccadito; Marco Pirra. 2020. "On the determinants of data breaches: A cointegration analysis." Decisions in Economics and Finance 44, no. 1: 141-160.
This paper provides an econometric analysis aiming at evidencing the dynamics showed by the S&P 500 market index during the period of 4 January 2001–28 April 2020, in which the subprime crisis has taken place and the COVID-19 crisis has begun. In particular, we fit a three-regime switching model that allows market parameters to behave differently during economic downturns, with the regimes representative of the tranquil, volatile, and turbulent states. We document that the tranquil regime is the most frequent for the whole period, while the dominant regime is the volatile one for the crisis of 2008 and the turbulent one for the first four months of 2020. We fit the same model to the returns of the Dow Jones Industrial Average index and find that during the same period of investigation, the most frequent regime has been the tranquil one, while the volatile and turbulent regimes share the same frequencies. Additionally, we use a multinomial logit model to describe the probabilities of volatile or turbulent regimes. We show that, in the case of the S&P 500 index, the returns from the Volatility Index (VIX) index are significant for both the volatile and the turbulent regimes, while the gold, WTI oil, and the dollar indices have some explanatory power only for the turbulent regime.
Lorenzo Cerboni Baiardi; Massimo Costabile; Domenico De Giovanni; Fabio LaMantia; Arturo Leccadito; Ivar Massabó; Massimiliano Menzietti; Marco Pirra; Emilio Russo; Alessandro Staino. The Dynamics of the S&P 500 under a Crisis Context: Insights from a Three-Regime Switching Model. Risks 2020, 8, 71 .
AMA StyleLorenzo Cerboni Baiardi, Massimo Costabile, Domenico De Giovanni, Fabio LaMantia, Arturo Leccadito, Ivar Massabó, Massimiliano Menzietti, Marco Pirra, Emilio Russo, Alessandro Staino. The Dynamics of the S&P 500 under a Crisis Context: Insights from a Three-Regime Switching Model. Risks. 2020; 8 (3):71.
Chicago/Turabian StyleLorenzo Cerboni Baiardi; Massimo Costabile; Domenico De Giovanni; Fabio LaMantia; Arturo Leccadito; Ivar Massabó; Massimiliano Menzietti; Marco Pirra; Emilio Russo; Alessandro Staino. 2020. "The Dynamics of the S&P 500 under a Crisis Context: Insights from a Three-Regime Switching Model." Risks 8, no. 3: 71.
The present study aims at modelling market risk for four commodities, namely West Texas Intermediate (WTI) crude oil, natural gas, gold and corn for the period 2007–2017. To this purpose, we use Extreme Value Theory (EVT) together with a set of Conditional Auto-Regressive Logit (CARL) models to predict risk measures for the futures return series of the considered commodities. In particular, the Peaks-Over-Threshold (POT) method has been combined with the Indicator and Absolute Value CARL models in order to predict the probability of tail events and the Value-at-Risk and the Expected Shortfall risk measures for the selected commodities. Backtesting procedures indicate that generally CARL models augmented with specific implied volatility outperform the benchmark model and thus they represent a valuable tool to anticipate and manage risks in the markets.
Bernardina Algieri; Arturo Leccadito. CARL and His POT: Measuring Risks in Commodity Markets. Risks 2020, 8, 27 .
AMA StyleBernardina Algieri, Arturo Leccadito. CARL and His POT: Measuring Risks in Commodity Markets. Risks. 2020; 8 (1):27.
Chicago/Turabian StyleBernardina Algieri; Arturo Leccadito. 2020. "CARL and His POT: Measuring Risks in Commodity Markets." Risks 8, no. 1: 27.
Bernardina Algieri; Arturo Leccadito. Ask CARL: Forecasting tail probabilities for energy commodities. Energy Economics 2019, 84, 1 .
AMA StyleBernardina Algieri, Arturo Leccadito. Ask CARL: Forecasting tail probabilities for energy commodities. Energy Economics. 2019; 84 ():1.
Chicago/Turabian StyleBernardina Algieri; Arturo Leccadito. 2019. "Ask CARL: Forecasting tail probabilities for energy commodities." Energy Economics 84, no. : 1.
Bernardina Algieri; Arturo Leccadito. Price volatility and speculative activities in futures commodity markets: A combination of combinations of p-values test. Journal of Commodity Markets 2019, 13, 40 -54.
AMA StyleBernardina Algieri, Arturo Leccadito. Price volatility and speculative activities in futures commodity markets: A combination of combinations of p-values test. Journal of Commodity Markets. 2019; 13 ():40-54.
Chicago/Turabian StyleBernardina Algieri; Arturo Leccadito. 2019. "Price volatility and speculative activities in futures commodity markets: A combination of combinations of p-values test." Journal of Commodity Markets 13, no. : 40-54.
Bernardina Algieri; Arturo Leccadito. Assessing contagion risk from energy and non-energy commodity markets. Energy Economics 2017, 62, 312 -322.
AMA StyleBernardina Algieri, Arturo Leccadito. Assessing contagion risk from energy and non-energy commodity markets. Energy Economics. 2017; 62 ():312-322.
Chicago/Turabian StyleBernardina Algieri; Arturo Leccadito. 2017. "Assessing contagion risk from energy and non-energy commodity markets." Energy Economics 62, no. : 312-322.
Theoretical models applied to option pricing should take into account the empirical characteristics of financial time series. In this paper, we show how to price basket options when the underlying asset prices follow a displaced log-normal process with jumps, capable of accommodating negative skewness and excess kurtosis. Our technique involves Hermite polynomial expansion that can match exactly the first mm moments of the model-implied basket return. This method is shown to provide superior results for basket options not only with respect to pricing but also for hedging.
Arturo Leccadito; Tommaso Paletta; Radu Tunaru. Pricing and hedging basket options with exact moment matching. Insurance: Mathematics and Economics 2016, 69, 59 -69.
AMA StyleArturo Leccadito, Tommaso Paletta, Radu Tunaru. Pricing and hedging basket options with exact moment matching. Insurance: Mathematics and Economics. 2016; 69 ():59-69.
Chicago/Turabian StyleArturo Leccadito; Tommaso Paletta; Radu Tunaru. 2016. "Pricing and hedging basket options with exact moment matching." Insurance: Mathematics and Economics 69, no. : 59-69.
The paper proposes a flexible and computationally efficient lattice-based approximation for evaluating European and American compound options under stochastic volatility models. In comparison with the existing evaluation procedures, the method is more flexible because it may accommodate several stochastic volatility specifications of the asset price process, and more efficient because it is computationally faster in computing accurate compound option prices. The method is obtained as an extension of Costabile et al. (2012) discretisation, which consists in approximating the stochastic volatility process by a recombining binomial lattice, and considers the asset value as an auxiliary variable whose dynamics is captured by generating subsets of representative realisations to cover the range of possible asset prices at each time slice. The backward induction scheme based on a linear interpolation technique is adapted to compute both the underlying daughter option and the compound option prices. Numerical experiments confirm the method efficiency and accuracy.
Arturo Leccadito; Emilio Russo. Compound option pricing under stochastic volatility. International Journal of Financial Markets and Derivatives 2016, 5, 97 .
AMA StyleArturo Leccadito, Emilio Russo. Compound option pricing under stochastic volatility. International Journal of Financial Markets and Derivatives. 2016; 5 (2/3/4):97.
Chicago/Turabian StyleArturo Leccadito; Emilio Russo. 2016. "Compound option pricing under stochastic volatility." International Journal of Financial Markets and Derivatives 5, no. 2/3/4: 97.
The paper proposes a flexible and computationally efficient lattice-based approximation for evaluating European and American compound options under stochastic volatility models. In comparison with the existing evaluation procedures, the method is more flexible because it may accommodate several stochastic volatility specifications of the asset price process, and more efficient because it is computationally faster in computing accurate compound option prices. The method is obtained as an extension of Costabile et al. (2012) discretisation, which consists in approximating the stochastic volatility process by a recombining binomial lattice, and considers the asset value as an auxiliary variable whose dynamics is captured by generating subsets of representative realisations to cover the range of possible asset prices at each time slice. The backward induction scheme based on a linear interpolation technique is adapted to compute both the underlying daughter option and the compound option prices. Numerical experiments confirm the method efficiency and accuracy.
Arturo Leccadito; Emilio Russo. Compound option pricing under stochastic volatility. International Journal of Financial Markets and Derivatives 2016, 5, 97 .
AMA StyleArturo Leccadito, Emilio Russo. Compound option pricing under stochastic volatility. International Journal of Financial Markets and Derivatives. 2016; 5 (2/3/4):97.
Chicago/Turabian StyleArturo Leccadito; Emilio Russo. 2016. "Compound option pricing under stochastic volatility." International Journal of Financial Markets and Derivatives 5, no. 2/3/4: 97.
Arturo Leccadito; Radu S. Tunaru; Giovanni Urga. Trading strategies with implied forward credit default swap spreads. Journal of Banking & Finance 2015, 58, 361 -375.
AMA StyleArturo Leccadito, Radu S. Tunaru, Giovanni Urga. Trading strategies with implied forward credit default swap spreads. Journal of Banking & Finance. 2015; 58 ():361-375.
Chicago/Turabian StyleArturo Leccadito; Radu S. Tunaru; Giovanni Urga. 2015. "Trading strategies with implied forward credit default swap spreads." Journal of Banking & Finance 58, no. : 361-375.
Arturo Leccadito; Pietro Toscano; Radu S. Tunaru. Value at Risk and Expected Shortfall Improved Calculation Based on the Power Transformation Method. The Journal of Derivatives 2014, 22, 67 -81.
AMA StyleArturo Leccadito, Pietro Toscano, Radu S. Tunaru. Value at Risk and Expected Shortfall Improved Calculation Based on the Power Transformation Method. The Journal of Derivatives. 2014; 22 (2):67-81.
Chicago/Turabian StyleArturo Leccadito; Pietro Toscano; Radu S. Tunaru. 2014. "Value at Risk and Expected Shortfall Improved Calculation Based on the Power Transformation Method." The Journal of Derivatives 22, no. 2: 67-81.
Arturo Leccadito; Omar Rachedi; Giovanni Urga. True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison. Econometric Reviews 2014, 34, 452 -479.
AMA StyleArturo Leccadito, Omar Rachedi, Giovanni Urga. True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison. Econometric Reviews. 2014; 34 (4):452-479.
Chicago/Turabian StyleArturo Leccadito; Omar Rachedi; Giovanni Urga. 2014. "True Versus Spurious Long Memory: Some Theoretical Results and a Monte Carlo Comparison." Econometric Reviews 34, no. 4: 452-479.
This paper proposes a regime-switching version of the Ohlson model (Contemp Account Res 11:661–687, ). We assume that abnormal earnings and the other information variable follow a regime-switching dynamics, which represents a simple yet rigorous way to incorporate the stochastic volatility pattern revealed by financial variables. We derive closed form formulae for market values of equity and show that the resulting model is still tractable. In our empirical investigation we consider firms from the USA stock market during the period 1980–2011 and find that the regime-switching model improves upon the traditional Ohlson model in predicting market prices.
Arturo Leccadito; Stefania Veltri. A regime switching Ohlson model. Quality & Quantity 2014, 49, 2015 -2035.
AMA StyleArturo Leccadito, Stefania Veltri. A regime switching Ohlson model. Quality & Quantity. 2014; 49 (5):2015-2035.
Chicago/Turabian StyleArturo Leccadito; Stefania Veltri. 2014. "A regime switching Ohlson model." Quality & Quantity 49, no. 5: 2015-2035.
Arturo Leccadito; Simona Boffelli; Giovanni Urga. Evaluating the accuracy of value-at-risk forecasts: New multilevel tests. International Journal of Forecasting 2014, 30, 206 -216.
AMA StyleArturo Leccadito, Simona Boffelli, Giovanni Urga. Evaluating the accuracy of value-at-risk forecasts: New multilevel tests. International Journal of Forecasting. 2014; 30 (2):206-216.
Chicago/Turabian StyleArturo Leccadito; Simona Boffelli; Giovanni Urga. 2014. "Evaluating the accuracy of value-at-risk forecasts: New multilevel tests." International Journal of Forecasting 30, no. 2: 206-216.
We present an explicit formula and a multinomial approach for pricing contingent claims under a regime-switching jump–diffusion model. The explicit formula, obtained as an expectation of Merton-type formulae for jump–diffusion processes, allows to compute the price of European options in the case of a two-regime economy with lognormal jumps, while the multinomial approach allows to accommodate an arbitrary number of regimes and a generic jump size distribution, and is suitable for pricing American-style options. The latter algorithm discretizes log-returns in each regime independently, starting from the highest volatility regime where a recombining multinomial lattice is established. In the remaining regimes, lattice nodes are the same but branching probabilities are adjusted. Derivative prices are computed by a backward induction scheme.
Massimo Costabile; Arturo Leccadito; Ivar Massabo'; Emilio Russo. Option pricing under regime-switching jump–diffusion models. Journal of Computational and Applied Mathematics 2014, 256, 152 -167.
AMA StyleMassimo Costabile, Arturo Leccadito, Ivar Massabo', Emilio Russo. Option pricing under regime-switching jump–diffusion models. Journal of Computational and Applied Mathematics. 2014; 256 ():152-167.
Chicago/Turabian StyleMassimo Costabile; Arturo Leccadito; Ivar Massabo'; Emilio Russo. 2014. "Option pricing under regime-switching jump–diffusion models." Journal of Computational and Applied Mathematics 256, no. : 152-167.
Frank J. Fabozzi; Arturo Leccadito; Radu S. Tunaru. Extracting market information from equity options with exponential Lévy processes. Journal of Economic Dynamics and Control 2014, 38, 125 -141.
AMA StyleFrank J. Fabozzi, Arturo Leccadito, Radu S. Tunaru. Extracting market information from equity options with exponential Lévy processes. Journal of Economic Dynamics and Control. 2014; 38 ():125-141.
Chicago/Turabian StyleFrank J. Fabozzi; Arturo Leccadito; Radu S. Tunaru. 2014. "Extracting market information from equity options with exponential Lévy processes." Journal of Economic Dynamics and Control 38, no. : 125-141.
The empirical characteristics of the underlying asset prices should be taken into account for the pricing and hedging of options. In this paper, we show how to price basket options when assets follow the “shifted asymmetric jump-diffusion” process. The methodology is based on the Hermite polynomial expansion that can match exactly the first m moments of the model implied-probability distribution. The resultant pricing and hedging formulae are in closed-form and similar to the Black and Scholes ones.
Tommaso Paletta; Arturo Leccadito; Radu Tunaru. Pricing and Hedging Basket Options Under Shifted Asymmetric Jump-Diffusion Processes. Mathematical and Statistical Methods for Actuarial Sciences and Finance 2014, 167 -171.
AMA StyleTommaso Paletta, Arturo Leccadito, Radu Tunaru. Pricing and Hedging Basket Options Under Shifted Asymmetric Jump-Diffusion Processes. Mathematical and Statistical Methods for Actuarial Sciences and Finance. 2014; ():167-171.
Chicago/Turabian StyleTommaso Paletta; Arturo Leccadito; Radu Tunaru. 2014. "Pricing and Hedging Basket Options Under Shifted Asymmetric Jump-Diffusion Processes." Mathematical and Statistical Methods for Actuarial Sciences and Finance , no. : 167-171.
We present a binomial approach for pricing contingent claims when the parameters governing the underlying asset process follow a regime-switching model. In each regime, the asset dynamics is discretized by a Cox–Ross–Rubinstein lattice derived by a simple transformation of the parameters characterizing the highest volatility tree, which allows a simultaneous representation of the asset value in all the regimes. Derivative prices are computed by forming expectations of their payoffs over the lattice branches. Quadratic interpolation is invoked in case of regime changes, and the switching among regimes is captured through a transition probability matrix. An econometric analysis is provided to pick reasonable volatility values for option pricing, for which we show some comparisons with the existing models to assess the goodness of the proposed approach.
Massimo Costabile; Arturo Leccadito; Ivar Massabó; Emilio Russo. A reduced lattice model for option pricing under regime-switching. Review of Quantitative Finance and Accounting 2013, 42, 667 -690.
AMA StyleMassimo Costabile, Arturo Leccadito, Ivar Massabó, Emilio Russo. A reduced lattice model for option pricing under regime-switching. Review of Quantitative Finance and Accounting. 2013; 42 (4):667-690.
Chicago/Turabian StyleMassimo Costabile; Arturo Leccadito; Ivar Massabó; Emilio Russo. 2013. "A reduced lattice model for option pricing under regime-switching." Review of Quantitative Finance and Accounting 42, no. 4: 667-690.
Edgeworth binomial trees were applied to price contingent claims when the underlying return distribution is skewed and leptokurtic, but with the limitation of working only for a limited set of skewness and kurtosis values. Recently, Johnson binomial trees were introduced to accommodate any skewness-kurtosis pair, but with the drawback of numerical convergence issues in some cases. Both techniques may suffer from non-exact matching of the moments of distribution of returns. A solution to this limitation is proposed here based on a new technique employing Hermite polynomials to match exactly the required moments. Several numerical examples illustrate the superior performance of the Hermite polynomials technique to price European and American options in the context of jump-diffusion and stochastic volatility frameworks and options with underlying asset given by the sum of two lognormally distributed random variables.
Arturo Leccadito; Pietro Toscano; Radu S. Tunaru. HERMITE BINOMIAL TREES: A NOVEL TECHNIQUE FOR DERIVATIVES PRICING. International Journal of Theoretical and Applied Finance 2012, 15, 1250058 .
AMA StyleArturo Leccadito, Pietro Toscano, Radu S. Tunaru. HERMITE BINOMIAL TREES: A NOVEL TECHNIQUE FOR DERIVATIVES PRICING. International Journal of Theoretical and Applied Finance. 2012; 15 (8):1250058.
Chicago/Turabian StyleArturo Leccadito; Pietro Toscano; Radu S. Tunaru. 2012. "HERMITE BINOMIAL TREES: A NOVEL TECHNIQUE FOR DERIVATIVES PRICING." International Journal of Theoretical and Applied Finance 15, no. 8: 1250058.