Nuova ricerca

Silvia MUZZIOLI

Professore Ordinario
Dipartimento di Economia "Marco Biagi"


Home | Curriculum(pdf) | Didattica |


Pubblicazioni

2022 - An OWA Analysis of the VSTOXX volatility index [Working paper]
Gambarelli., L.; Muzzioli, S.; De Baets, B.
abstract

In this paper, we analyze the information value of the VSTOXX (volatility) index as a measure of risk for the EU stock market. Employing daily data from 2007 to 2017, we inspect and contrast the properties of the VSTOXX index under various market conditions and in high- and low-volatility periods. Moreover, to evaluate the contribution of each country-specific index to the VSTOXX index, we employ the Ordered Weighted Averaging (OWA) operator, which provides a flexible aggregation procedure ranging between the minimum and the maximum of the input values. We obtain a number of useful insights. The correlation between the VSTOXX index and the volatility indices is high during the entire period only for France and Germany. Moreover, the VSTOXX index acts more like an OR-like measure than as an AND-like measure of volatility for the EU stock markets and acts as an average only during periods of extreme volatility.


2022 - Asymmetric correlations and hedging effectiveness of cryptocurrencies for the European stock market [Working paper]
Gambarelli., L.; Marchi, G.; Muzzioli, S.
abstract

The aim of the paper is twofold: first, to examine the hedging effectiveness of cryptocurrencies and cryptocurrency portfolios for European equities in bearish and bullish market conditions, and second, to contrast cryptocurrencies with gold as a safe haven asset. To this end, daily data from 2018 to 2021 were employed in a linear and nonlinear Autoregressive Distributed Lag (ARDL) framework. The findings have significant implications for investors, financial intermediaries and regulators. First, none of the cryptocurrencies under investigation acts as a safe haven for the European stock market. Second, an asymmetric relationship was found between Bitcoin / Ethereum returns on the one hand and stock market returns on the other, indicating the risk of large joint losses during periods of market turmoil. Third, cryptocurrency portfolios appear to perform better than Bitcoin and Ethereum for diversification purposes. Fourth, among cryptocurrency portfolios, the portfolio made up of the top ten cryptocurrencies appear to be the best in terms of diversification benefits and the risk-return profile. Finally, during the 2020 bear market conditions, not even gold acted as a safe haven for European stocks, highlighting the need to investigate alternative safe haven assets to mitigate portfolio risks.


2022 - Asymmetric semi-volatility spillover in a nonlinear model of interacting markets [Working paper]
Campisi, G.; Muzzioli, S.
abstract

This paper develops an heterogeneous agents model with fundamentalists and chartists trading in two different speculative markets. It examines whether investors’ behaviour is related to the volatility and its dynamics. We find that investors’ heterogeneity in price trends and trading strategies can significantly explain asymmetry in semi-volatility transmission.


2022 - Forecasting returns in the US market through fuzzy rule-based classification systems [Working paper]
Campisi, G.; De Baets, B.; Gambarelli, L.; Muzzioli, S.
abstract

The paper aims to investigate the forecasting ability of fuzzy rule-based classification systems (FRBCS) on future direction of the S&P500 index. To this end, we apply four FRBCS methods. Moreover, we compare both the forecasting accuracy and the interpretability of the results of FRBCS with the recently used machine learning techniques. Overall, among the two approaches, we prefer the FRBCS methods, since they allow a good balance between accuracy and interpretability, and provide sharper results than the machine learning techniques.


2022 - News Sentiment indicators and the Cross‐Section of Stock Returns in the European Stock Market [Working paper]
Gambarelli., L.; Muzzioli, S.
abstract

This paper investigates whether the Bloomberg investor sentiment index can provide valuable information for investors and fund managers for the purposes of stock picking and portfolio selection. The dataset consists of all the listed companies in the Euro area for the period from 2010 to 2021. By exploiting portfolio sorting strategies, the paper evaluates to what extent and how long investor sentiment can affect stock returns. Moreover, it considers whether additional factors can affect the relationship between sentiment and returns, casting light on the asymmetric effect related to positive and negative news. The findings are as follows. First, high (low) sentiment stocks exhibit high (low) returns on average. The average return of the portfolio that takes a long position in the stocks with very high sentiment and a short position in stocks with very low sentiment is statistically and economically significant and is robust to the inclusion of commonly used risk factors. Second, the predictability of stock returns using the sentiment indicator declines fast after one month. Third, evidence is found of the profitability of a long-short strategy that invests in stocks with low capitalization: profitability declines with the duration of the investment period. Finally, it is found that positive news is factored into the stock price more slowly than negative news, especially for stocks with low market capitalization.


2022 - Regional innovation in southern Europe: a poset-based analysis [Working paper]
Damiani, F.; Muzzioli, S.; De Baets, B
abstract

This paper examines the performance of regional innovation across the 60 southern European regions of Greece, Italy, Portugal and Spain. A poset-based analysis is carried out in two phases. The first phase establishes a ranking of the clusters in which regions are grouped to identify patterns of comparable regions. The second phase focuses on the country level, where the regions of each of the four countries are ranked into five different performance levels. The outcomes of the two phases are compared with the results described in the Regional Innovation Scoreboard 2019, with a view to providing insights for policymakers.


2022 - The power of deterministic option-implied trees in pricing European options [Articolo su rivista]
Elyasiani, E.; Muzzioli, S.
abstract

The aims of the current article are threefold. First, to investigate the power of deterministic option-implied trees, constructed either by forward or by backward induction, in pricing European options, in order to assess the proper representation of the smile. Second, to investigate and contrast the power of deterministic option-implied trees during tranquil and volatile market conditions. Last, to assess the correctness of the representation of the smile in different parts of the risk-neutral distribution. Three main results are obtained. First, the pricing performance of the Enhanced Derman and Kani model (EDK), based on forward induction, is superior to that of the Rubinstein model, based on backward induction. Second, the EDK model produces better results (smaller errors) on the left tail of the distribution, i.e. it is better in pricing out-of-the-money put options. Third, it performs better in turmoil periods where correct pricing a challenge, and accuracy is of greater importance than in tranquil periods. Diebold and Mariano test of equal predictive accuracy confirms the superiority of the EDK model in both sub-periods.


2021 - A TOPSIS analysis of regional competitiveness at European level [Working paper]
Ferrarini, F.; Muzzioli, S.; De Baets, B.
abstract

.


2021 - A comparison of machine learning methods for predicting stock returns in the US market [Working paper]
Muzzioli, S.; Campisi, G.; De Baets, B.
abstract


2021 - A poset-based analysis of regional innovation at European level [Working paper]
Damiani, F.; Muzzioli, S.; De Baets, B.
abstract

This paper examines the performance of regional innovation across 220 European regions. First, a cluster analysis is performed in order to detect patterns of comparable regions. Subsequently, a poset-based approach is adopted to obtain a ranking of the different clusters of European regions. The outcome is compared with the results described in the Regional Innovation Scoreboard 2019. Useful insights for policymakers are obtained.


2021 - Designing volatility indices for Austria, Finland and Spain [Articolo su rivista]
Campisi, G.; Muzzioli, S.
abstract


2021 - Existence of a fundamental solution of partial differential equations associated to Asian options [Articolo su rivista]
Anceschi, Francesca; Muzzioli, Silvia; Polidoro, Sergio
abstract

We prove the existence and uniqueness of the fundamental solution for Kolmogorov operators associated to some stochastic processes, that arise in the Black & Scholes setting for the pricing problem relevant to path dependent options. We improve previous results in that we provide a closed form expression for the solution of the Cauchy problem under weak regularity assumptions on the coefficients of the differential operator. Our method is based on a limiting procedure, whose convergence relies on some barrier arguments and uniform a priori estimates recently discovered.


2021 - Nonlinear dynamics in asset pricing: the role of a sentiment index [Articolo su rivista]
Campisi, G.; Muzzioli, S.; Zaffaroni, A.
abstract

This paper aims to contribute to the literature on the role of sentiment indices in heterogeneous asset pricing models. A new sentiment index in financial markets is proposed in which transactions take place between two groups of fundamentalists with divergent perceptions of fundamental value. It is assumed that the proportion of fundamentalists in the two groups depends on the sentiment index. After examining the analytical properties of the deterministic discrete dynamical system, stochastic components are added to the expectations of fundamentalists. First, the study measures the performance of the model in reproducing the stylized facts of financial data relying on the S&P 500 index. Second, the forecasting power of the model to predict the daily prices of the S&P 500 index is examined. For this purpose, the forecasting accuracy of the proposed dynamical model, where the sentiment index is explicitly modelled, is compared with a model where the sentiment index is not taken into account. In this case, the predictions are obtained by means of a machine learning technique (lasso regression). The results show that the sentiment index is important in explaining the stylized facts of financial returns and in forecasting prices.


2021 - The skewness index: uncovering the relation with volatility and market returns [Articolo su rivista]
Elyasiani, 2. E.; Gambarelli, L.; Muzzioli, S.
abstract


2021 - Tools and practices for LGBT+ inclusion in tertiary education: the development of the LGBT+ University Inclusion Index and its application to Italian universities [Working paper]
Russo, T.; Addabbo, T.; Muzzioli, S.; De Baets, B.
abstract

The literature provides evidence that lesbian, gay, bisexual and trans learners ore often victims of homo-bi-transphobic discrimination in educational environments. This paper outlines an index of LGBT+ inclusion for Universities. The index has a twofold aim: to help tertiary education institutions to assess their degree of inclusivenesss, and to detect the level of LGBT+ inclusion in tertiary education. Starting from the existing LGBT+ inclusion indices like the Campus Pride Index and LGBT+ Inclusive Education Index, the LGBT+ inclusive university index refers to an extended set of indicators and is based on fuzzy logic techniques to measure inclusiveness (Zadeh, 1965, 1988). Best practices in LGBTI+ inclusion, implemented by Italian universities and identified in this study, are highlighted with the aim of suggesting and recommending guidelines helpful to fighting homo-bi-transphobic discrimination in higher education institutions.


2021 - Uncertainty about fundamental and pessimistic traders: a piecewise-linear maps approach [Working paper]
Campisi, G.; Muzzioli, S.; Tramontana, F.
abstract


2021 - Uncertainty about fundamental, pessimistic and overconfident traders: a piecewise-linear maps approach [Articolo su rivista]
Campisi, G.; Muzzioli, S.; Tramontana, F.
abstract

We analyze a financial market model with heterogeneous interacting agents where fundamentalists and chartists are considered. We assume that fundamentalists are homogeneous in their trading strategy but heterogeneous in their belief about the asset’s fundamental value. On the other hand, we consider that chartists, when they are optimistic become overconfident and they trade more than when they are pessimistic. Consequently, our model dynamics are driven by a one-dimensional piecewise-linear continuous map with three linear branches. We investigate the bifurcation structures in the map’s parameter space and describe the endogenous fear and greed market dynamics arising from our asset-pricing model.


2020 - Assessing skewness in financial markets [Working paper]
Campisi, G.; La Rocca, L.; Muzzioli, S.
abstract

It is common knowledge that investors like large gains and dislike large losses. This translates into a preference for right-skewed return distributions, with right tails heavier than left tails. Skewness is thus interesting not only as a way to describe the shape of a distribution, but also for risk measurement. We review the statistical literature on skewness and provide a comprehensive framework for its assessment. We present a new measure of skewness, based on a relative comparison between above average and below average returns. We show that this measure represents a valid complement to the state of the art.


2020 - Fundamentalists heterogeneity and the role of the sentiment indicator [Working paper]
Campisi, G.; Muzzioli, S.
abstract

This paper is a contribution to the literature on the role of the sentiment indices in heterogeneous asset pricing models. We propose a new sentiment index in a financial market where we assume that transactions take place between two groups of fundamentalists that differentiate on the perception of the fundamental value. We assume that the fraction of fundamentalists in the two groups depends on the sentiment index. After studying the analytical properties of the deterministic discrete dynamical system we compare the new index with a previous index introduced in financial literature. For this purpose, by adding stochastic components to the fundamentalist' demands, we measure the performance of our model under different sentiment indices and we test its explanatory power to reproduce the stylized facts of financial data relying on the S&P500 index.


2020 - Investor sentiment and trading behavior [Working paper]
Campisi, G.; Muzzioli, S.
abstract

The aim of this paper is to model trading decisions of financial investors based on a sentiment index. For this purpose, we analyse a dynamical model which includes the sentiment index in the agents' trading behavior. We consider the set up of a Discrete Dynamical System, assuming that in financial markets transactions take place between two groups of fundamentalists that differ in their perception of fundamental value. The proportion of fundamentalists in the two groups is assumed to depend on the sentiment index. The sentiment index used is related to the risk asymmetry index (RAX) enabling us to consider both the variance and the asymmetry of the prediction error between the two groups of fundamentalists. We identify the equilibria of the model and conduct a numerical analysis in order to capture stylized facts documented empirically in the financial literature.


2020 - Investor sentiment and trading behavior [Articolo su rivista]
Campisi, G.; Muzzioli, S.
abstract

The aim of this paper is to model trading decisions of financial investors based on a sentiment index. For this purpose, we analyze a dynamical model, which includes the sentiment index in the agents' trading behavior. We consider the setup of a discrete dynamical system, assuming that in financial markets, transactions take place between two groups of fundamentalists that differ in their perception of fundamental value. This assumption is motivated by a degree of uncertainty about the true fundamental value. The proportion of fundamentalists in the two groups is assumed to depend on the sentiment index. The sentiment index used is related to the risk asymmetry index, enabling us to consider both the variance and the asymmetry of the prediction error between the two groups of fundamentalists. We identify the equilibria of the model and conduct a numerical analysis in order to capture stylized facts documented empirically in the financial literature.


2020 - Moment risk premia and the cross-section of stock returns in the European stock market [Articolo su rivista]
Elyasiani, Elyas; Gambarelli, Luca; Muzzioli, Silvia
abstract

This article investigates whether volatility, skewness, and kurtosis risks are priced in the European stock market and assess the signs and the magnitudes of the corresponding risk premia. To this end, we adopt two approaches: a model-free approach based on swap contracts, and a model-based approach built on portfolio-sorting techniques. A number of results are obtained. First, stocks with high exposure to innovations in implied market volatility (skewness) exhibit low (high) returns on average. Second, the estimated premium for bearing market volatility (skewness) risk is negative (positive), robust to the two approaches employed, and statistically and economically significant. Third, in contrast with studies on the US stock market, we identify the existence of a size premium in the European stock market: small capitalization stocks earn higher returns than high capitalization stocks.


2020 - Option implied moments obtained through fuzzy regression [Articolo su rivista]
Muzzioli, Silvia; Gambarelli, Luca; De Baets, Bernard
abstract

The aim of this paper is to investigate the potential of fuzzy regression methods for computing more reliable estimates of higher-order moments of the risk-neutral distribution. We improve upon the formula of Bakshi et al. (RFS 16(1):101–143, 2003), which is used for the computation ofmarket volatility and skewness indices (such as the VIX and the SKEW indices traded on the Chicago Board Options Exchange), through the use of fuzzy regression methods. In particular, we use the possibilistic regression method of Tanaka, Uejima and Asai, the least squares fuzzy regression method of Savic and Pedrycz and the hybrid method of Ishibuchi and Nii.We compare the fuzzy moments with those obtained by the standard methodology, based on the Bakshi et al. (2003) formula, which relies on an ex-ante choice of the option prices to be used and cubic spline interpolation.We evaluate the quality of the obtained moments by assessing their forecasting power on future realized moments. We compare the competing forecasts by using both the Model Confidence Set and Mincer–Zarnowitz regressions. We find that the forecasts for skewness and kurtosis obtained using fuzzy regression methods are closer to the subsequently realized moments than those provided by the standard methodology. In particular, the lower bound of the fuzzy moments obtained using the Savic and Pedrycz method is the best ones. The results are important for investors and policy makers who can rely on fuzzy regression methods to get a more reliable forecast for skewness and kurtosis.


2020 - The use of option prices to assess the skewness risk premium [Articolo su rivista]
Elyasiani, E.; Gambarelli, L.; Muzzioli, S.
abstract

The aims of this study are twofold. First, to determine the sign and magnitude of the skewness risk premium (SRP) in the Italian index option market using two procedures: (i) skewness swap contracts, (ii) option trading strategies consisting of positions in options and their underlying assets. Second, to investigate the term structure of the SRP for 30, 60 and 90-day maturities to provide investors with a proper time horizon for profitable skewness trading strategies. Several results are obtained. First, the SRP, defined as the difference between the physical and the risk-neutral skewness, is positive and statistically and economically significant. These findings indicate that the SRP does exist, it is positive in sign, and it can be quantified. Second, the SRP is higher in magnitude for short-term maturity (€35 for the 30-day maturity) and lower for 60-day and 90-day maturities (both about €27). Third, skewness trading strategies confirm our finding of a positive and economically significant SRP. Fourth, a strategy that sells out-of-the-money puts is more profitable for medium-term maturities compared to short-term maturities. A strategy that takes a long position on out-of-the-money calls, and a short position on out-of-the-money puts, yields a higher return, if near-term options are used.


2019 - Construction and properties of volatility indices for Austria, Finland and Spain [Working paper]
Campisi, Giovanni; Muzzioli, Silvia
abstract

The volatility index of the Chicago Board Options Exchange (VIX) is the first to have been introduced and it has attracted international imitators world-wide since it is considered as a barometer of investor fear. The aim of the paper is threefold. First, by following the VIX methodology, we construct a volatility index for three European countries (Austria, Finland and Spain) that do not have yet that piece of market information for investors. Second, we investigate the properties of the new volatility indices. In particular, we test their ability to act as fear indicators and as predictors of future returns. Moreover, we shed light on the term structure of the proposed volatility indices, by computing spot and forward implied volatility indices for different time to maturities (30, 60 and 90 days). Our results indicate that volatility indices are useful not only for investors to improve their trading decisions, but also for policy makers to choose the appropriate economic measure to guarantee stability in the market.


2019 - How do normalization schemes affect net spillovers? A replication of the Diebold and Yilmaz (2012) study [Articolo su rivista]
Giuseppe Caloia, Francesco; Cipollini, Andrea; Muzzioli, Silvia
abstract

This paper replicates the Diebold and Yilmaz (2012) study on the connectedness ofthe commodity market and three other financial markets: the stock market, the bond market, and the FX market, based on the Generalized Forecast Error Variance Decomposition, GEFVD. We show that the net spillover indices (of directional connectedness), used to assess the net contribution of one market to overall risk in the system, are sensitive to the normalization scheme applied to the GEFVD. We show that, considering data generating processes characterized by different degrees of persistence and covariance, a scalarbased normalization of the Generalized Forecast Error Variance Decomposition is preferable to the row normalization suggested by Diebold and Yilmaz since it yields net spillovers free of sign and ranking errors.


2019 - Risk-asymmetry indices in Europe [Working paper]
Gambarelli, Luca; Muzzioli, Silvia
abstract

The objectives of this study are threefold. First, we introduce for the first time a skewness index (SKEW) for each European country. Second, we compute an alternative measure of asymmetry (RAX) based on corridor implied volatilities to assess whether it outperforms the standard skewness index in measuring tail risk. Third, we investigate the properties of the proposed indices by uncovering the contemporaneous linear relationship among skewness, volatility, and returns and the information content of skewness on future returns, which is highly debated in the literature. Last, we propose two aggregate indices of asymmetry to monitor the risk of the EU financial market as a whole. To deal with the limited availability of option-based data for European countries, that represent the main obstacle for the construction of such indices in the EU, we delineate a country-specific procedure. Several results are obtained. First, all the asymmetry indices are on average higher than 100, indicating that the risk-neutral distribution is in general left-skew for the 12 EU countries under investigation. Second, the relation between changes in asymmetry indices and contemporaneous market returns in positive, indicating that asymmetry indices are not able to capture the same fear effect captured by volatility indices. Third, the results for the relationship between asymmetry and volatility (future returns) are mixed both in terms of magnitude and significance and do not allow us to delineate general conclusions. Last, the aggregate asymmetry index based on the RAX methodology is the only one able to forecast future negative returns for all the EU countries in our dataset when it reaches very high levels.


2019 - The Future of Fuzzy Sets in Finance: New Challenges in Machine Learning and Explainable AI [Capitolo/Saggio]
Muzzioli, Silvia
abstract

Traditional statistical analysis is oriented towards finding linear relationships between the variables under investigation, often accompanied by strict assump-tions about the problem and data distributions. Moreover, traditional analysis en-dorses data reduction as much as possible before modeling, and, as a result, part of the original information is lost. On the other hand, machine learning does not impose rigid pre-assumptions about the problem and data distributions since the underlying ratio is to “learn from data”, without the need for data reduction or a priori knowledge before the learning. For these reasons machine learning has ex-perienced a rapid dissemination in a large number of sectors including healthcare, finance, transportation, retail and social media services industry. Machine learn-ing is the core technology of the new age of AI applications. Machine learning methods offer tremendous benefits, but are limited by their opaqueness, non-intuitiveness and difficulty to understand. In finance in particular, machine learning methods have played a crucial role in improving the forecasting ability of financial models and trading systems, due to their ability to process a large amount of data and the peculiarity of capturing also non-linear relationships between variables. In recent years, the availability of sample data at very high frequencies (intraday or tick by tick) resulted in a fertile domain for their application, especially in the coding of indicators and patterns of technical analysis. Deep learning systems are the most advanced form of machine learning. They can match humans in recognizing images or driving a car, but why they come up with the solutions remains difficult to tell exactly. Businesses would have used machine learning more widely if they could understand how machines come up with their recommendations on trading, fraud detection, insur-ance and banking. A challenge for AI in finance is the need to analyze and aggregate a large amount of information obtained from different sources. In the financial literature, the use of artificial intelligence (AI) and machine learning techniques is often lim-ited to the coding of technical analysis indicators (such as moving averages or the flag pattern) for trading strategy purposes. As pointed out in [1], most of the con-tributions investigating machine learning methods in financial markets propose trading strategies that rely mainly on technical analysis and focus on a single stock market or market index. Moreover, financial markets are generally treated as compartmentalized and most of the contributions investigate only a single mar-ket or a specific asset [2]. On the other hand, investors and regulators need com-prehensive risk measures able to aggregate and synthesize different types of in-formation in a single indicator. Another challenge is represented by the increasing dominance of computerized trading, which may cause more volatility during market downturns. The rising frequency of 'flash crashes' across many major markets, the increasing incidents of volatility such as the VIX spike on Feb. 5, 2018, the 10-year Treasury bond on Oct. 15, 2014, and the British pound on Oct. 6, 2016, are an important early warning sign that machines have to be closely supervised and understood. New measures and tools to control the volatility of financial markets [3,4,5] should be developed. The semantic properties of linguistic fuzzy sets, their good coverage even in the case of lack of data, their management of the uncertainty, especially in Big Data, make them a very interesting tool for nowadays applications, especially when the practitioner need to understand why a given decision has been made.


2019 - Towards a fuzzy index of skewness [Capitolo/Saggio]
Muzzioli, Silvia; Gambarelli, L.; De baets, Bernard
abstract

The aim of this paper is to investigate the potential of fuzzy regression methods for computing a measure of skewness for the market. A quadratic version of the Ishibuchi and Nii hybrid fuzzy regression method is used to estimate the third order moment. The obtained fuzzy estimates are compared with the one provided by standard market practice. The proposed approach allows us to cope with the limited availability of data and to use all the information that is present in the market. In the Italian market, the results suggest that the fuzzy-regression based skewness measure is closer to the subsequently realized measure of skewness than the one provided by the standard methodology. In particular, the upper bound of the Ishibuchi and Nii method provides the best forecast. The results are important for investors and policy makers who can rely on fuzzy regression methods to get a more reliable forecast of skewness.


2018 - Asymmetric semi-volatility spillover effects in EMU stock markets [Articolo su rivista]
Giuseppe Caloia, Francesco; Cipollini, Andrea; Muzzioli, Silvia
abstract

The aim of this paper is to quantify the strength and the direction of semi-volatility spillovers between five EMU stock markets over the 2000-2016 period. We use upside and downside semi-volatilities as proxies for downside risk and upside opportunities. In this way, we aim to complement the literature, which has focused mainly on the contemporaneous correlation between positive and negative returns, with the evidence of asymmetry also in semi-volatility transmission. For this purpose, we apply the Diebold and Yilmaz (2012) methodology, based on a generalized forecast error variance decomposition, to downside and upside realized semi-volatility series. While the analysis of Diebold and Yilmaz (2012) is based on a stationary VAR, we take into account the long-memory behaviour of the series, by using the multivariate extension of the HAR model (named VHAR model). Moreover, we cast light on how the choice of the normalization scheme can bias the net-spillover computation in a full sample as well as in a rolling sample analysis.


2018 - INDICES FOR FINANCIAL MARKET VOLATILITY OBTAINED THROUGH FUZZY REGRESSION [Articolo su rivista]
Muzzioli, Silvia; Gambarelli, Luca; De Baets, Bernard
abstract

The measurement of volatility is of fundamental importance in finance. Standard market practice adopted for volatility estimation from option prices leads to a considerable loss of information and the introduction of an element of arbitrariness in the volatility index computation. We propose to resort to fuzzy regression methods in order to include all the available information from option prices and obtain an informative volatility index. In fact, the obtained fuzzy volatility indices do not only offer a most possible value, but also a lower and an upper bound for the interval of possible values, providing investors with an additional source of information. We also propose a defuzzification procedure in order to select a representative value within this interval. Moreover, we investigate the occurrence of truncation and discretization errors in the volatility index computation by resorting to an interpolation-extrapolation method. We also test the forecasting power of each volatility index on future realized volatility.


2018 - On the financial connectedness of the commodity market: a replication of the Diebold and Yilmaz (2012) study [Working paper]
Caloia, F.; Cipollini, A.; Muzzioli, S.
abstract

In this paper we replicate the Diebold and Yilmaz (2012) study on the connectedness of the Commodity market and three other financial markets: the stock market, the bond market, and the FX market. We show that both the row and the column normalization schemes of the Generalized Forecast Error Variance Decomposition, suggested by the authors, lead to inaccurate measures of net contribution to risk transmission, in terms of ranking and sign. We show that, considering data generating processes characterized by different degrees of comovement and persistence, a scalar based normalization of the Generalized Forecast Error Variance Decomposition yields consistent (free of sign and ranking errors) net spillovers.


2018 - Risk aversion connectedness in five European countries [Articolo su rivista]
Cipollini, Andrea; Lo Cascio, Iolanda; Muzzioli, Silvia
abstract

In this paper we compute an aggregate index of risk aversion and indices of vulnerability and the contribution to systemic risk aversion for five European countries. The variance risk premium proxies risk aversion. The contribution to the literature is twofold. First, this is the first study estimating not only the common component, but also indices of directional connectedness among variance risk premia. Second, it is the first to estimate the interconnections by means of a FIVAR model, in order to account for long memory. Our analysis indicates measures of total and directional connectedness unlike those that would be obtained with the use of a short memory VAR. These differences arise when the focus is on market turmoil periods and on forecast horizons of thirty days. Future research evaluating spillovers among long memory series can benefit from our results. Policy-makers should take these interconnections into account when adopting effective macroeconomic policies.


2018 - The Risk-Asymmetry Index as a New Measure of Risk [Articolo su rivista]
Elyasiani, E.; Gambarelli, L.; Muzzioli, S.
abstract

The aim of this paper is to propose a simple and unique measure of risk that subsumes the conflicting information contained in volatility and skewness indices and overcomes the limitations of these indices in accurately measuring future fear or greed in the market. To this end, the concept of upside and downside corridor implied volatility, which accounts for the asymmetry in the risk-neutral distribution, is exploited. The risk-asymmetry index is intended to capture the investors’ pricing asymmetry towards upside gains and downside losses. The results show that the proposed risk-asymmetry index can play a crucial role in predicting future returns, at various forecast horizons, since it subsumes the information embedded in both the volatility and skewness indices. Furthermore, the risk-asymmetry index is the only index that, at very high values, possesses the ability to clearly highlight a risky situation for the aggregate stock market.


2018 - The properties of a skewness index and its relation with volatility and returns [Working paper]
Elyasiani, E.; Gambarelli, L.; Muzzioli, Silvia
abstract

The objective of this study is threefold. First, we investigate the properties of a skewness index in order to determine whether it captures fear (fear of losing money), or greed in the market (fear of losing opportunities). Second, we uncover the combined relationship among skewness, volatility and returns. Third, we provide further evidence and possible explanations for the relationship between skewness and future returns, which is highly debated in the literature. The stock market investigated is the Italian one, for which a skewness index is not traded yet. The methodology proposed for the construction of the Italian skewness index can be adopted for other European and non-European countries characterized by a limited number of option prices traded. Several results are obtained. First, we find that in the Italian market the skewness index acts as measures of market greed, as opposed to market fear. Second, for almost 70% of the daily observations, the implied volatility and the skewness index move together but in opposite directions. Increases (decreases) in volatility and decreases (increases) in the skewness index are associated with negative (positive) returns. Last, we find strong evidence that positive returns are reflected both in a decrease in the implied volatility index and in an increase in the skewness index the following day. Implications for investors and policy makers are drawn.


2018 - The use of option prices in order to evaluate the skewness risk premium [Working paper]
Elyasiani, E.; Gambarelli, L.; Muzzioli, Silvia
abstract


2017 - Fuzzy approaches to option price modelling [Articolo su rivista]
Muzzioli, Silvia; De Baets, Bernard
abstract

The aim of this paper is to review the literature that has addressed direct and inverse problems in option pricing in a fuzzy setting. In a direct problem, the stochastic process for the underlying asset is assumed and the option prices are derived by no-arbitrage or equilibrium conditions. In an inverse problem, the option prices are taken as given and used to infer the underlying asset process. Models are divided into discrete-time and continuous-time ones. Special attention is paid to real options, a particular class of non-financial options that are used to evaluate real investments. Directions for future research are outlined. In particular in inverse problems, there is still room for promising research, both in discrete time and in continuous time. Moreover, given that many proposed methods remain difficult to use in practice, there is mainly the need to apply the fuzzy models obtained on real market data and to compare the results with non-fuzzy techniques in order to assess the usefulness and the improvements in the modeling of imprecise data with fuzzy sets and fuzzy random variables.


2017 - The information content of corridor volatility measures during calm and turmoil periods [Articolo su rivista]
Elyasiani, E.; Gambarelli, L.; Muzzioli, S.
abstract

Measurement of volatility is of paramount importance in finance because of the effects on risk measurement and risk management. Corridor implied volatility measures allow us to disentangle the volatility of positive returns from that of negative returns, providing investors with additional information beyond standard market volatility. The aim of the paper is twofold. First, to propose different types of corridor implied volatility and some combinations of them as risk indicators, in order to provide useful information about investors’ sentiment and future market returns. Second, to investigate their usefulness in prediction of market returns under different market conditions (with a particular focus on the subprime crisis and the European debt crisis). The data set consists of daily index options traded on the Italian market and covers the 2005-2014 period. We find that upside corridor implied volatility measure embeds the highest information content about contemporaneous market returns, claiming the superiority of call options in measuring current sentiment in the market. Moreover, both upside and downside volatilities can be considered as barometers of investors’ fear. The volatility measures proposed have forecasting power on future returns only during high volatility periods and in particular during the European debt crisis. The explanatory power on future market returns improves when two of the proposed volatility measures are combined together in the same model.


2017 - Towards a Fuzzy Volatility Index for the Italian Market [Relazione in Atti di Convegno]
Muzzioli, Silvia; Gambarelli, Luca; De Baets, Bernard
abstract

The measurement of volatility is of fundamental importance in finance. The standard market practice adopted for the computation of a volatility index imposes to discard some option prices quoted in the market, resulting in a considerable loss of information. To overcome this drawback, we propose to resort to fuzzy regression methods in order to include all the available information and obtain an informative volatility index for the Italian stock market.


2016 - A note on normalization schemes: The case of generalized forecast error variance decompositions [Working paper]
Caloia, F. G.; Cipollini, A.; Muzzioli, S.
abstract

The aim of this paper is to propose new normalization schemes for the values obtained from the generalized forecast error variance decomposition, in order to obtain more reliable net spillover measures. We provide a review of various matrix normalization schemes used in different application domains. The intention is to contribute to the financial econometrics literature aimed at building a bridge between different approaches able to detect spillover effects, such as spatial regressions and network analyses. Considering DGPs characterized by different degrees of correlation and persistence, we show that the popular row normalization scheme proposed by Diebold and Yilmaz (2012), as well as the alternative column normalization scheme, may lead to inaccurate measures of net contributions (NET spillovers) in terms of risk transmission. Results are based on simulations and show that the number of errors increases as the correlation between the variable increases. The normalization schemes we suggest overcome these limits.


2016 - Fear or greed? What does a skewness index measure? [Working paper]
Elyasiani, E.; Gambarelli, L.; Muzzioli, S.
abstract

The ℎ ℎ (CBOE) SKEW index is designed to capture investors’ fear in the US stock market. In this paper we pursue two objectives. First, we investigate the properties of the CBOE SKEW index in order to assess whether it captures fear or greed in the market. Second, we introduce and compare three measures of asymmetry of the Italian index options return distribution. These measures include: (i) the CBOE SKEW index adapted to the Italian market (we call it ITSKEW) and (ii) two model-free measures of skewness based on comparison of a bear and a bull index. Finally, we explore the existence and sign of the skewness risk premium. Several results are obtained. First, the Italian skewness index (ITSKEW) presents many advantages compared to the two model-free measures: it has a significant contemporaneous relation with market index returns and with model-free implied volatility. Both the ITSKEW and the CBOE SKEW indices act as measures of market greed (the opposite of market fear), since returns react positively to an increase in the skewness indices. Trading strategies show that the Italian market is characterized by a significant positive skewness risk premium.


2016 - Forecasting and pricing powers of option-implied tree models: Tranquil and volatile market conditions [Working paper]
Elyasiani, E.; Muzzioli, S.; Ruggieri, A.
abstract

The aims of this paper are twofold. First, to investigate the accuracy of different option-implied trees in pricing European options in order to assess the power of implied trees in replicating the market information. Second, to compare deterministic volatility implied trees and stochastic implied volatility models (Bakshi et al. (2003)) in assessing the forecasting power of implied moments on subsequently realised moments, and ascertaining the existence, magnitude and sign of variance, skewness, and kurtosis risk-premia. The analysis is carried out using the Italian daily market data covering the period 2005-2014. This enables us to contrast the pricing performance of implied trees and to assess the magnitude and sign of risk premia in both a tranquil and a turmoil period. The findings are as follows. First, the pricing performance of the Enhanced Derman and Kani (EDK, Moriggia et al. 2009) model is superior to that of the Rubinstein (1994) model. This superiority is stronger especially in the high volatility period due to a better estimation of the left tail of the distribution describing bad market conditions. Second, the Bakshi et al. (2003) formula is the most accurate for forecasting skewness and kurtosis, while for variance it yields upwardly biased forecasts. All models agree on the signs of the risk premia: negative for variance and kurtosis, and positive for skewness, but differ in magnitude. Overall, the results suggest that selling (buying) variance and kurtosis (skewness) is profitable in both high and low volatility periods.


2016 - Moment Risk Premia and the Cross-Section of Stock Returns [Working paper]
Elyasiani, E.; Gambarelli, L.; Muzzioli, S.
abstract

The aim of this paper is to assess the existence and the sign of moment risk premia. To this end, we use methodologies ranging from swap contracts to portfolio sorting techniques in order to obtain robust estimates. We provide empirical evidence for the European stock market for the 2008-2015 time period. Evidence is found of a negative volatility risk premium and a positive skewness risk premium, which are robust to the different techniques and cannot be explained by common risk-factors such as market excess return, size, book-to-market and momentum. Kurtosis risk is not priced in our dataset. Furthermore, we find evidence of a positive risk premium in relation to the firm’s size.


2016 - The Risk-Asymmetry Index [Working paper]
Elyasiany, E.; Gambarelli, L.; Muzzioli, S.
abstract

The aim of this paper is to propose a simple and unique measure of risk, that subsumes the conflicting information in volatility and skewness indices and overcomes the limits of these indices in correctly measuring future fear or greed in the market. To this end, we exploit the concept of upside and downside corridor implied volatility, which accounts for the asymmetry in risk-neutral distribution, i.e. the fact that investors like positive spikes in returns, while they dislike negative ones. We combine upside and downside implied volatilities in a single asymmetry index called the risk-asymmetry index (ܴܣ .(ܺThe risk-asymmetry index ሺܴܣܺሻ plays a crucial role in predicting future returns, since it subsumes all the information embedded in both the Italian skewness index ܫܵܶܧܭ ܹand the Italian volatility index (ܫܸܶܫ .(ܺThe ܴܣ ܺindex is the only index that is able to indicate (when reaching very high values) a clearly risky situation for the aggregate stock market, which is detected neither by the ܫܸܶܫ ܺindex nor by the ܫܵܶܧܭ ܹindex.


2015 - A comparison of fuzzy regression methods for the estimation of the implied volatility smile function [Articolo su rivista]
Muzzioli, Silvia; Ruggieri, A.; De Baets, B.
abstract

The information content of option prices on the underlying asset has a special importance in finance. In particular, with the use of option implied trees, market participants may price other derivatives, estimate and forecast volatility (see e.g. the volatility index VIX), or higher moments of the underlying asset distribution. A crucial input of option implied trees is the estimation of the smile (implied volatility as a function of the strike price), which boils down to fitting a function to a limited number of existing knots. However, standard techniques require a one-to-one mapping between volatility and strike price, which is not met in the reality of financial markets, where, to a given strike price, two different implied volatilities are usually associated (coming from different types of options: call and put). In this paper we compare the widely used methodology of discarding some implied volatilities and interpolating the remaining knots with cubic splines, to a fuzzy regression approach which does not require an a-priori choice of implied volatilities. To this end, we first extend some linear fuzzy regression methods to a polynomial form and we apply them to the financial problem. The fuzzy regression methods used range from the possibilistic regression method of Tanaka et al.[28], to theleast squares fuzzy regression method of Savic and Pedrycz [27]and to the hybrid method of Ishibuchi and Nii[11].


2015 - Financial connectedness among European volatility risk premia [Working paper]
Cipollini, A.; Lo Cascio, I.; Muzzioli, S.
abstract

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to estimate the contribution and the vulnerability to systemic risk of volatility risk premia for five European stock markets: France, Germany, UK, Switzerland and the Netherlands. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. Therefore, we estimate and invert a Fractionally Integrated VAR model to compute the cross forecast error variance shares necessary to obtain the index of total and directional connectedness.


2015 - The optimal corridor for implied volatility: From periods of calm to turmoil [Articolo su rivista]
Muzzioli, Silvia
abstract

Corridor implied volatility is obtained from model-free impliedvolatility by truncating the integration domain between two barri-ers. Empirical evidence on volatility forecasting in various marketspoints to the utility of trimming the risk-neutral distribution ofthe underlying stock price, in order to obtain unbiased measuresof future realized volatility. The aim of this paper is to investigatethe optimal corridor of strike prices for volatility forecasting in theItalian market, by analyzing numerous symmetric and asymmet-ric corridors in a dataset for the years 2005–2010 spanning both arelatively calm period and a period of turmoil. The results indicatethat put prices, providing information on the probability of a down-turn of the underlying asset, provide the best indication of futurerealized volatility, particularly in a period of turmoil.


2015 - Towards a skewness index for the Italian stock market [Working paper]
Elyasiani, E.; Gambarelli, L.; Muzzioli, S.
abstract

The present paper is a first attempt of computing a skewness index for the Italian stock market. We compare and contrast different measures of asymmetry of the distribution: an index computed with the CBOE SKEW index formula and two other asymmetry indexes, the SIX indexes, as proposed in Faff and Liu (2014). We analyze the properties of the skewness indexes, by investigating their relationship with model-free implied volatility and the returns on the underlying stock index. Moreover, we assess the profitability of skewness trades and disentangle the contribution of the left and the right part of the risk neutral distribution to the profitability of the latter strategies. The data set consists of FTSE MIB index options data and covers the years 2011-2014, allowing us to address the behavior of skewness measures both in bullish and bearish market periods. We find that the Italian SKEW index presents many advantages with respect to other asymmetry measures: it has a significant contemporaneous relation with both returns, model-free implied volatility and has explanatory power on returns, after controlling for volatility. We find a negative relation between volatility changes and changes in the Italian SKEW index: an increase in model-free implied volatility is associated with a decrease in the Italian SKEW index. Moreover, the SKEW index acts as a measure of market greed, since returns react more negatively to a decrease in the SKEW index (increase in risk neutral skewness) than they react positively to an increase of the latter (decrease in risk neutral skewness). The results of the paper point to the existence of a skewness risk premium in the Italian market. This emerges both from the fact that implied skewness is more negative than physical one in the sample period and from the profitability of skewness trading strategies. In addition, the higher performance of the portfolio composed by only put options indicates that the mispricing of options is mainly focused on the left part of the distribution.


2015 - Volatility co-movements: a time-scale decomposition analysis [Articolo su rivista]
Cipollini, Andrea; Lo Cascio, Iolanda; Muzzioli, Silvia
abstract

In this paper we are interested in detecting contagion from US to European stock market volatilities in the period immediately after the Lehman Brothers collapse. The analysis is based on a factor decomposition of the covariance matrix, in the time and frequency domain, using wavelets. The analysis aims to disentangle two components of volatility contagion (anticipated and unanticipated by the market). Once we control for heteroskedasticity, the results show no evidence of contagion (from the US) in market expectations (coming from implied volatility) and evidence of unanticipated contagion (coming from the volatility risk premium) for almost any European country. Finally, the estimation of a three-factor model specification shows that a European common shock plays an important role in determining volatility co-movements mainly in the tranquil period, while in the period of financial turmoil the US common shock is the main driver of volatility co-movements.


2014 - Volatility risk premia and financial connectedness [Working paper]
Cipollini, A.; Lo Cascio, I.; Muzzioli, S.
abstract

In this paper we use the Diebold Yilmaz (2009 and 2012) methodology to construct an index of connectedness among five European stock markets: France, Germany, UK, Switzerland and the Netherlands, by using volatility risk premia. The volatility risk premium, which is a proxy of risk aversion, is measured by the difference between the implied volatility and expected realized volatility of the stock market for next month. While Diebold and Yilmaz focus is on the forecast error variance decomposition of stock returns or range based volatilities employing a stationary VAR in levels, we account for the (locally) long memory stationary properties of the levels of volatility risk premia series. Therefore, we estimate and invert a Fractionally Integrated VAR model to compute the cross forecast error variance shares necessary to obtain the index of total connectedness and the net contribution of each series to total connectedness. The results show that, over January 2000-August 2013, the index of total connectedness among volatility risk premia has been relatively stable with an increasing role played by France and with a positive (but decreasing) role played by Germany and the Netherlands. Non EMU countries such as the UK and Switzerland are negative net contributors to the index.


2013 - A comparative assessment of different fuzzy regression methods for volatility forecasting [Articolo su rivista]
Muzzioli, Silvia; B., De Baets
abstract

The aim of this paper is to compare different fuzzy regression methods in the assessment of the information content on future realised volatility of option-based volatility forecasts. These methods offer a suitable tool to handle both imprecision of measurements and fuzziness of the relationship among variables. Therefore, they are particularly useful for volatility forecasting, since the variable of interest (realised volatility) is unobservable and a proxy for it is used. Moreover, measurement errors in both realised volatility and volatility forecasts may affect the regression results. We compare both the possibilistic regression method of Tanaka, Uejima and Asai (1982) and the least squares fuzzy regression method of Savic and Pedrycz (1991). In our case study, based on intra-daily data of the DAX-index options market, both methods have proved to have advantages and disadvantages. Overall, among the two methods, we prefer the Savic and Pedricz (1991) method, since it contains as special case (the central line) the ordinary least squares regression, is robust to the analysis of the variables in logarithmic terms or in levels, and provides sharper results than the Tanaka, Uejima and Asai (1982) method.


2013 - A comparison of fuzzy regression methods for the estimation of the implied volatility smile function [Working paper]
Muzzioli, S.; Ruggieri, A.; De Baets, B.
abstract

The information content of option prices on the underlying asset has a special importance in finance. In particular, with the use of option implied trees, market participants may price other derivatives, estimate and forecast volatility (see e.g. the volatility index VIX), or higher moments of the underlying asset distribution. A crucial input of option implied trees is the estimation of the smile (implied volatility as a function of the strike price), which boils down to fitting a function to a limited number of existing knots. However, standard techniques require a one-to-one mapping between volatility and strike price, which is not met in the reality of financial markets, where, to a given strike price, two different implied volatilities are usually associated (coming from different types of options: call and put). In this paper we compare the widely used methodology of discarding some implied volatilities and interpolating the remaining knots with cubic splines, to a fuzzy regression approach which does not require an a-priori choice of implied volatilities. To this end, we first extend some linear fuzzy regression methods to a polynomial form and we apply them to the financial problem. The fuzzy regression methods used range from the possibilistic regression method of Tanaka, Uejima and Asai [14], the least squares fuzzy regression method of Savic and Pedrycz [13] and the hybrid method of Ishibuchi and Nii [4].


2013 - Option implied trees and implied moments [Working paper]
Muzzioli, S.; Ruggieri, A.
abstract

Implied trees are simple non-parametric discretizations of one- or two-dimension diffusions, aimed at introducing non-constant volatility in an option pricing model. The aim of the paper is twofold. First we investigate the ability of different option implied trees in pricing European options. Second, we compare the implied moments obtained with the use of option implied trees with the risk–neutral moments obtained with the use of Bakshi et al. (2003) formula and with realised physical moments. The comparison is pursued in the Italian market by analysing a data set which covers the years 2005-2009 and span both a relatively tranquil and a turmoil period. Keywords:


2013 - The forecasting performance of corridor implied volatility in the Italian market [Articolo su rivista]
Muzzioli, Silvia
abstract

Corridor implied volatility introduced in Carr and Madan (1998) and recently implemented in Andersen and Bondarenko (2007) is obtained from model-free implied volatility by truncating the integration domain between two barriers. Corridor implied volatility is implicitly linked with the concept that the tails of the risk-neutral distribution are estimated with less precision than central values, due to the lack of liquid options for very high and very low strikes. However, there is no golden choice for the barrier levels, which are likely to change depending on the underlying asset risk neutral distribution. The latter feature renders its forecasting performance mainly an empirical question. The aim of the paper is to investigate the forecasting performance of corridor implied volatility by choosing different corridors with symmetric and asymmetric cuts, and compare the results with the preliminary findings in Muzzioli (2010b). Moreover, we shed light on the information content of different parts of the risk neutral distribution of the stock price, by using a model-independent approach based on corridor measures. To this end we compute both realized and model-free variance measures accounting for both falls and increases in the underlying asset price. The forecasting performance of volatility measures is evaluated both in a statistical and an economic setting. The economic significance is assessed by employing trading strategies based on delta-neutral straddles. The comparison is pursued by using intra-day synchronous prices between the options and the underlying asset.


2013 - The information content of option based forecasts of volatility: evidence from the Italian stock market [Articolo su rivista]
Muzzioli, Silvia
abstract

The aim of this paper is to comprehensively compare option-based measures of volatility, with the ultimate plan of devising a new volatility index for the Italian stock market. The performance of the different implied volatility measures in forecasting future volatility is evaluated both in a statistical and in an economic setting. The properties of the implied volatility measures are also explored, by looking at both the contemporaneous relationship between implied volatility changes and market returns and the usefulness of the proposed index in forecasting future market returns. The results of the paper are of practical importance for both policy-makers and investors. The volatility index, based on corridor measures, could be used to forecast market volatility, for Value at Risk purposes, in order to determine trading strategies on the underlying index and as an early warning for future market conditions.


2013 - The optimal corridor for implied volatility: from calm to turmoil periods [Working paper]
Muzzioli, S.
abstract

Corridor implied volatility is obtained from model-free implied volatility by truncating the integration domain between two barriers. Empirical evidence on volatility forecasting, in various markets, points to the utility of trimming the risk-neutral distribution of the underlying stock price, in order to obtain unbiased measures of future realised volatility (see e.g. [9], [3]). The aim of the paper is to investigate, both in a statistical and in an economic setting, the optimal corridor of strike prices to use for volatility forecasting in the Italian market, by analysing a data set which covers the years 2005-2010 and span both a relatively tranquil and a turmoil period.


2013 - Volatility co-movements: a time scale decomposition analysis [Working paper]
Cipollini, A.; Lo Cascio, I.; Muzzioli, S.
abstract

In this paper we investigate short-run co-movements before and after the Lehman Brothers’ collapse among the volatility series of US and a number of European countries. The series under investigation (implied and realized volatility) exhibit long-memory and, in order to avoid miss-specification errors related to the parameterization of a long memory multivariate model, we rely on wavelet analysis. More specifically, we retrieve the time series of wavelet coefficients for each volatility series for high frequency scales, using the Maximal Overlapping Discrete Wavelet transform and we apply Maximum Likelihood for a factor decomposition of the short-run covariance matrix. The empirical evidence shows an increased interdependence in the post-break period and points at an increasing (decreasing) role of the common shock underlying the dynamics of the implied (realized) volatility series, once we move from the 2-4 days investment time horizon to the 8-16 days. Moreover, there is evidence of contagion from the US to Europe immediately after the Lehman Brothers’ collapse, only for realized volatilities over an investment time horizon between 8 and 16 days.


2012 - Corridor implied volatility and the variance risk premium in the Italian market [Relazione in Atti di Convegno]
Muzzioli, Silvia
abstract

Corridor implied volatility introduced in Carr and Madan (1998) and recently implemented in Andersen and Bondarenko (2007) is obtained from model-free implied volatility by truncating the integration domain between two barriers. Corridor implied volatility is implicitly linked with the concept that the tails of the risk-neutral distribution are estimated with less precision than central values, due to the lack of liquid options for very high and very low strikes. However, there is no golden choice for the barriers levels’, which will probably change depending on the underlying asset risk neutral distribution. The latter feature renders its forecasting performance mainly an empirical question.The aim of the paper is twofold. First we investigate the forecasting performance of corridor implied volatility by choosing different corridors with symmetric and asymmetric cuts, and compare the results with the preliminary findings in Muzzioli (2010b). Second, we examine the nature of the variance risk premium and shed light on the information content of different parts of the risk neutral distribution of the stock price, by using a model-independent approach based on corridor measures. To this end we compute both realised and model-free variance measures which accounts for drops versus increases in the underlying asset price. The comparison is pursued by using intra-daily synchronous prices between the options and the underlying asset.


2012 - Put-Call Parity and options’ forecasting power [Articolo su rivista]
Muzzioli, Silvia
abstract

Numerous papers have investigated the forecasting power of Black-Scholes volatility versus a time series volatility forecast (see e.g. Poon (2005)). However, as far as we know, little is the evidence about the different information content of implied volatilities obtained from options with different type (call or put). Even if theoretically call and put options with the very same strike price and expiration date should yield the same implied volatility due to no arbitrage considerations, empirically there are many reasons that may cause call and put implied volatilities to differ (see e.g. Hentshle (2003), Buraschi and Jackwerth (2001)). The aim of this paper is twofold: to investigate how the information content of implied volatility varies according to option type and to compare the latter option based forecasts with historical volatility in order to see if they subsume all the information contained in the latter. Two hypotheses are tested: unbiasedness and efficiency of the different volatility forecasts w.r.t. historical volatility. The investigation is pursued in the Dax index options market. Differently from previous studies, that use settlement prices, we are using the more informative synchronous prices, matched in a one minute interval. This is very important to stress, since our implied volatilities are real “prices”, as determined by synchronous no-arbitrage relations.


2011 - Assessing the information content of option-based volatility forecastsusing fuzzy regression methods [Working paper]
Muzzioli, Silvia; B., De Baets
abstract

Volatility is a key variable for portfolio selection models, option pricing models and risk management techniques. Volatility can be estimated and forecasted by using either historical information or option prices. The present paper focuses on option-based volatility forecasts for three main reasons. First, for the forward looking nature of option-based forecasts (as opposed to the backward looking nature of historical information); second, for the average superiority, documented in the literature, of option-based estimates in forecasting future realized volatility; third, for the widespread use of option prices in the computation of the most important market volatility indexes (see e.g. the VIX index for the Chicago Board Options Exchange). The aim of this paper is to assess the information content on future realised volatility of different option-based volatility forecasts, through the use of fuzzy regression methods. The latter methods offer a suitable tool to handle both imprecision in measurements and fuzziness of the relationship among variables. Therefore, they are particularly useful for volatility forecasting, since the variable of interest (realised volatility) is unobservable and a proxy for it is used. Moreover, measurement errors in both realised volatility and volatility forecasts may affect the regression results. Fuzzy regression methods have not yet been used in volatility forecasting. Our case study is based on intra-daily data on the DAX-index options market.


2011 - Corridor Implied Volatility and the Variance Risk Premium in the Italian Market [Working paper]
Muzzioli, S.
abstract

Corridor implied volatility introduced in Carr and Madan (1998) and recently implemented in Andersen and Bondarenko (2007) is obtained from model-free implied volatility by truncating the integration domain between two barriers. Corridor implied volatility is implicitly linked with the concept that the tails of the risk-neutral distribution are estimated with less precision than central values, due to the lack of liquid options for very high and very low strikes. However, there is no golden choice for the barriers levels’, which will probably change depending on the underlying asset risk neutral distribution. The latter feature renders its forecasting performance mainly an empirical question.The aim of the paper is twofold. First we investigate the forecasting performance of corridor implied volatility by choosing different corridors with symmetric and asymmetric cuts, and compare the results with the preliminary findings in Muzzioli (2010b). Second, we examine the nature of the variance risk premium and shed light on the information content of different parts of the risk neutral distribution of the stock price, by using a model-independent approach based on corridor measures. To this end we compute both realised and model-free variance measures which accounts for drops versus increases in the underlying asset price. The comparison is pursued by using intra-daily synchronous prices between the options and the underlying asset.


2011 - The Skew Pattern of Implied Volatility in the DAX Index Options Market [Articolo su rivista]
Muzzioli, Silvia
abstract

The aim of this paper is twofold: to investigate how the information content of implied volatility varies according to moneyness and option type and to compare option-based forecasts with historical volatility. The different information content of implied volatility is examined for the most liquid at-the-money and out-of-the-money options: put (call) options for strikes below (above) the current underlying asset price. Two hypotheses are tested: unbiasedness and efficiency of the different volatility forecasts. The investigation is pursued in the Dax index options market, by using synchronous prices matched in a one-minute interval. It was found that the information content of implied volatility has a humped shape, with out-of-the-money options being less informative than at-the-money ones. Overall, the best forecast is at-the-money put implied volatility: it is unbiased (after a constant adjustment) and efficient, in that it subsumes all the information contained in historical volatility.


2011 - Towards a volatility index for the Italian stock market [Relazione in Atti di Convegno]
Muzzioli, Silvia
abstract

The aim of this paper is to analyse and empirically test how to unlock volatility information from option prices. The information content of three option based forecasts of volatility: Black-Scholes implied volatility, model-free implied volatility and corridor implied volatility is addressed, with the ultimate plan of proposing a new volatility index for the Italian stock market. As for model-free implied volatility, two different extrapolation techniques are implemented. As for corridor implied volatility, five different corridors are compared.Our results, which point to a better performance of corridor implied volatilities with respect to both Black-Scholes implied volatility and model-free implied volatility, are in favour of narrow corridors. The volatility index proposed is obtained with an overall 50% cut of the risk neutral distribution. The properties of the volatility index are explored by analysing both the contemporaneous relationship between implied volatility changes and market returns and the usefulness of the proposed index in forecasting future market returns.


2010 - Option-based forecasts of volatility: An empirical study in the DAX-index options market [Articolo su rivista]
Muzzioli, Silvia
abstract

Volatility estimation and forecasting are essential for both the pricing and the risk management of derivative securities. Volatility forecasting methods can be divided into option-based ones, that use prices of traded options in order to unlock volatility expectations, and time series volatility models that use historical information in order to predict future volatility. Among option-based volatility forecasts we distinguish between the “model-dependent” Black-Scholes implied volatility and the “model-free” implied volatility proposed by Britten-Jones and Neuberger (2000) that does not rely on a particular option pricing model.The aim of this paper is to investigate the unbiasedness and efficiency, with respect to past realised volatility, of the two option-based volatility forecasts. The comparison is pursued by using intra-daily data on the DAX-index options market. Our results suggest that Black-Scholes implied volatility subsumes all the information contained in past realised volatility and is a better predictor for future realised volatility than model-free implied volatility.


2010 - The relation between implied and realised volatility in the DAX index options market [Capitolo/Saggio]
Muzzioli, Silvia
abstract

The aim of this paper is to investigate the relation between implied volatility, historical volatility and realised volatility in the DAX index options market. Since implied volatility varies across option type (call versus put) we run a horse race of different implied volatility estimates: implied call and implied put. Two hypotheses are tested in the DAX index options market: unbiasedness and efficiency of the different volatility forecasts. Our results suggest that both implied volatility forecasts are unbiased (after a constant adjustment) and efficient forecasts of future realised volatility in that they subsume all the information contained in historical volatility.


2010 - Towards a volatility index for the Italian stock market [Working paper]
Muzzioli, S.
abstract

The aim of this paper is to analyse and empirically test how to unlock volatility information from option prices. The information content of three option based forecasts of volatility: BlackScholes implied volatility, model-free implied volatility and corridor implied volatility is addressed, with the ultimate plan of proposing a new volatility index for the Italian stock market. As for model-free implied volatility, two different extrapolation techniques are implemented. As for corridor implied volatility, five different corridors are compared. Our results, which point to a better performance of corridor implied volatilities with respect to both Black-Scholes implied volatility and model-free implied volatility, are in favour of narrow corridors. The volatility index proposed is obtained with an overall 50% cut of the risk neutral distribution. The properties of the volatility index are explored by analysing both the contemporaneous relationship between implied volatility changes and market returns and the usefulness of the proposed index in forecasting future market returns


2009 - On the no arbitrage condition in option implied trees [Articolo su rivista]
V., Moriggia; Muzzioli, Silvia; Torricelli, Costanza
abstract

The aim of this paper is to discuss the no-arbitrage condition in option implied trees based on forward induction and to propose a no-arbitrage test that rules out the negative probabilities problem and hence enhances the pricing performance. The no-arbitrage condition takes into account two main features: the position of the node in the tree and the relation between the dividend yield and the risk-free rate. The proposed methodology is tested in and out of sample with Italian index options data and findings support a good pricing performance.


2009 - The skew pattern of implied volatility in the DAX index options market [Working paper]
Muzzioli, S.
abstract

The aim of this paper is twofold: to investigate how the information content of implied volatility varies according to moneyness and option type, and to compare option-based forecasts with historical volatility in order to see if they subsume all the information contained in historical volatility. The different information content of implied volatility is examined for the most liquid at-the-money and out-of-the-money options: put (call) options for strikes below (above) the current underlying asset price, i.e. the ones that are usually used as inputs for the computation of the smile function. In particular, since at-the-money implied volatilities are usually inserted in the smile function by computing some average of both call and put implied ones, we investigate the performance of a weighted average of at-the-money call and put implied volatilities with weights proportional to trading volume. Two hypotheses are tested: unbiasedness and efficiency of the different volatility forecasts. The investigation is pursued in the Dax index options market, by using synchronous prices matched in a one-minute interval. It was found that the information content of implied volatility has a humped shape, with out-of-the-money options being less informative than at-the-money ones. Overall, the best forecast is at-the-money put implied volatility: it is unbiased (after a constant adjustment) and efficient, in that it subsumes all the information contained in historical volatility.


2009 - The skew pattern of implied volatility in the DAX-index options market [Working paper]
Muzzioli, Silvia
abstract

The aim of this paper is twofold: to investigate how the information content of implied volatility varies according to moneyness and option type, and to compare option-based forecasts with historical volatility in order to see if they subsume all the information contained in historical volatility. The different information content of implied volatility is examined for the most liquid at-the-money and out-of-the-money options: put (call) options for strikes below (above) the current underlying asset price, i.e. the ones that are usually used as inputs for the computation of the smile function. In particular, since at-the-money implied volatilities are usually inserted in the smile function by computing some average of both call and put implied ones, we investigate the performance of a weighted average of at-the-money call and put implied volatilities with weights proportional to trading volume. Two hypotheses are tested: unbiasedness and efficiency of the different volatility forecasts. The investigation is pursued in the Dax index options market, by using synchronous prices matched in a one-minute interval. It was found that the information content of implied volatility has a humped shape, with out-of-the-money options being less informative than at-the-money ones. Overall, the best forecast is at-the-money put implied volatility: it is unbiased (after a constant adjustment) and efficient, in that it subsumes all the information contained in historical volatility.


2008 - American Option Pricing with Imprecise Risk-Neutral Probabilities [Articolo su rivista]
Muzzioli, Silvia; H., Reynaerts
abstract

The aim of this paper is to price an American option in a multiperiod binomial model,when there is uncertainty on the volatility of the underlying asset.American option valuation is usually performed, under the risk-neutralvaluation paradigm, by using numerical procedures such as the binomialoption pricing model of Cox, Ross, Rubinstein (1979). A key input of themultiperiod binomial model is the volatility of the underlying asset,that is an unobservable parameter.As it is hard to give a precise estimate forthe volatility, in this paper we use a possibility distribution in order to modelthe uncertainty on the volatility. Possibility distributions are one of the mostpopular mathematical tools for modelling uncertainty. The standard risk-neutralvaluation paradigm requires the derivation of the risk-neutral probabilities, thatin a one period binomial model boils down to the solution of a linear system ofequations. As a consequence of the uncertainty in the volatility, we obtain apossibility distribution on the risk-neutral probabilities. Under these measures,we perform the risk-neutral valuation of the American option.


2008 - Option based forecasts of volatility: An empirical study in the DAX index options market [Working paper]
Muzzioli, S.
abstract

Option based volatility forecasts can be divided into “model dependent” forecast, such as implied volatility, that is obtained by inverting the Black and Scholes formula, and “model free” forecasts, such as model free volatility, proposed by Britten-Jones and Neuberger (2000), that do not rely on a particular option pricing model. The aim of this paper is to investigate the unbiasedness and efficiency in predicting future realized volatility of the two option based volatility forecasts: implied volatility and model free volatility. The comparison is pursued by using intradaily data on the Dax-index options market. Our results suggest that Black-Scholes volatility subsumes all the information contained in historical volatility and is a better predictor than model free volatility.


2007 - American option pricing with imprecise risk neutral probabilities: from plain intervals to fuzzy sets [Working paper]
Muzzioli, Silvia; H., Reynaerts
abstract

The aim f this paper is to price an American style option when there is uncertainty on the underlying asset volatility.


2007 - Call and put implied volatilities and the derivation of option implied trees [Articolo su rivista]
Moriggia, V; Muzzioli, Silvia; Torricelli, Costanza
abstract

The aim of this paper is to discuss the no-arbitrage condition in option implied trees based on forward induction and to propose a no-arbitrage test that rules out the negative probabilities problem and hence enhances the pricing performance. The no-arbitrage condition takes into account two main features: the position of the node in the tree and the relation between the dividend yield and the risk-free rate. The proposed methodology is tested in and out of sample with Italian index options data and findings support a good pricing performance.


2007 - Option pricing in the presence of uncertainty [Capitolo/Saggio]
Muzzioli, Silvia; H., Reynaerts
abstract

In this chapter we investigate the derivation of the European option price in the Cox-Ross-Rubinstein binomial model in the presence of uncertainty on the volatility of the underlying asset. We propose two different approaches to the issue that concentrate on the fuzzification of one or both the two jump factors.


2007 - Solving parametric fuzzy linear systems by a non linear programming method [Articolo su rivista]
Muzzioli, Silvia; H., Reynaerts
abstract

Linear systems of equations, with uncertainty on the parameters,play a major role in various problems in economics and finance. In this paperparametric fuzzy linear systems of the general formA_1x+b_1=A_2x+b_2, with A_1, A_2, b_1 and b_2 matrices with fuzzy elements,are solved by means of a nonlinear programming method.The relationbetween this methodology and the algorithm proposed in Muzzioli and Reynaerts (2006a)is highlighted.The methodology is finally applied to an economic and afinancial problem.


2007 - The relation between implied and realised volatility: are call options more informative than put options? Evidence from the DAX index options market [Working paper]
Muzzioli, S.
abstract

The aim of this paper is to investigate the relation between implied volatility, historical volatility and realised volatility in the Dax index options market. Since implied volatility varies across option type (call versus put) we run a horse race of different implied volatility estimates: implied call, implied put and average implied that is a weighted average of call and put implied volatility with weights proportional to traded volume. Two hypotheses are tested in the Dax index options market: unbiasedness and efficiency of the different volatility forecasts. Our results suggest that all the three implied volatility forecasts are unbiased (after a constant adjustment) and efficient forecasts of future realised volatility in that they subsume all the information contained in historical volatility.


2007 - The solution of fuzzy linear systems by non-linear programming: a financial application [Articolo su rivista]
Muzzioli, Silvia; H., Reynaerts
abstract

Fuzzy linear systems of equations play a major role in various financial applications. In this paper we analyse a particular fuzzy linear system: the derivation of the risk neutral probabilities in a fuzzy binary tree. This system has previously been investigated and different solutions to different forms of the same system have been proposed. The aim of this paper is twofold. First, we highlight that the different solutions proposed, arise from different forms of the same system. Second, in order to find a unique vector solution for the system, we propose a practical algorithm that boils down to the solution of a non-linear optimization problem. (c) 2005 Elsevier B.V. All rights reserved.


2006 - Fuzzy binary tree model for European options [Capitolo/Saggio]
Muzzioli, Silvia; H., Reynaerts
abstract

The derivation of the risk-neutral probabilities in a binary tree, in the presence of uncertainty on the underlying asset moves, boils down to the solution of dual fuzzy linear systems. The issue has previously been addressed and different solutions to the dual systems have been found. The aim of this paper is to apply a methodology which leads to a unique solution for the dual systems.


2006 - Fuzzy linear systems of the form A(1)x plus b(1) = A(2)x plus b(2) [Articolo su rivista]
Muzzioli, Silvia; H., Reynaerts
abstract

Linear systems of equations, with uncertainty on the parameters, play a major role in several applications in various areas such as economics, finance, engineering and physics. This paper investigates fuzzy linear systems of the form A(1) x + b(1) = A(2)x + b(2) with A(1), A(2) square matrices of fuzzy coefficients and b(1), b(2) fuzzy number vectors. The aim of this paper is twofold. First, we clarify the link between interval linear systems and fuzzy linear systems. Second, a generalization of the vector solution of Buckley and Qu [Solving systems of linear fuzzy equations, Fuzzy Sets and Systems 43 (1991) 33-43] to the fuzzy system A(1) x + b(1) = A(2)x + b(2) is provided. In particular, we give the conditions under which the system has a vector solution and we show that the linear systems Ax = b and A(1)x + b(1) = A(2)x + b(2), with A = A(1) - A(2) and b = b(2) - b(1), have the same vector solutions. Moreover, in order to find the vector solution, a simple algorithm is proposed.


2005 - Fuzzy up and down probabilities in a financial problem [Working paper]
Muzzioli, Silvia; H., Reynaerts
abstract

The aim of this paper is to solve a fuzzy linear system of equation that arises in the computation of the risk neutral probabilities.


2005 - Solving fuzzy systems of linear equations by a nonlinear programming method [Relazione in Atti di Convegno]
H., Reynaerts; Muzzioli, Silvia
abstract

Linear systems of equations with uncertainty on the parameters play a major role in various problems in economics and finance. In this paper fuzzy linear systems of the most general form A_1x+b_1=A_2x+b_2, with A_1, A_2, b_1, and b_2 matrices with fuzzy elements are solved by means of a nonlinear programming method. The methodology is finally applied to an economic and a financial problem.


2005 - The pricing of options on an interval binomial tree. An application to the DAX-index option market [Articolo su rivista]
Muzzioli, Silvia; Torricelli, Costanza
abstract

This paper implements a model setup in Muzzioli and Torricelli [Int. J. Intell. Syst. 17 (6) (2002) 577-594] for deriving implied trees and pricing options when the put-call parity is not fulfilled. The model basically extends Derman and Kani´s [Risk 7 (2) (1994) 32-39], whereby call (put) prices are also used in the lower (upper) part of the tree thus exploiting the information content of both call and put prices. The DAX-index option market is chosen for this application because it is a relatively new European market where short-selling restrictions may induce put-call parity violations and the nature of the option (European) and of the underlying (dividends reinvested in the index) avoid some estimation problems. In order to test the pricing fit of the model, a non-linear optimisation procedure is proposed to estimate a unique implied tree which allows a comparison between the model prices, Derman and Kani´s and market prices. The results suggest that the MT model improves the pricing.


2004 - A multiperiod binomial model for pricing options in a vague world [Articolo su rivista]
Muzzioli, Silvia; Torricelli, Costanza
abstract

The aim of this paper is the pricing of European options in a multiperiod binomial model characterised by ill-defined states of the world. The pricing methodology is still the risk-neutral valuation approach. However, the vagueness in the stock price movements implies that both the risk-neutral probabilities and the stock price are weighted intervals. An empirical validation of the model with DAX-index option data is also provided.


2004 - Fuzzy binary tree model for European style vanilla options [Relazione in Atti di Convegno]
Muzzioli, Silvia; H., Reynaerts
abstract

The derivation of the risk neutral probabilities in a binary tree, in the presence of uncertainty on the underlying asset moves, boils down to the solution of dual fuzzy linear systems. The issue has previously been addressed and different solutions to the dual systems have been found. The aim of this paper is to apply a methodology which leads to a unique solution for the dual systems.


2003 - A note on fuzzy linear systems [Working paper]
Muzzioli, Silvia
abstract

The aim of this paper is to analyse the solution of a fuzzy system when the classical solution based on standard fuzzy mathematics fails to exist. In particular we analyse the solution of the system Ax=b with A squared matrix with positive fuzzy coefficients and y crisp vector of positive elements. This system is particularly important for financial applications. We propose two different solution methods that are based respectively on the work of Buckley et al. (2002) and Friedman, Ming and Kandel (1998). An application to an important financial problem, the derivation of the artificial probabilities in a lattice framework, is provided.


2002 - Implied trees in illiquid markets: A Choquet pricing approach [Articolo su rivista]
Muzzioli, Silvia; Torricelli, Costanza
abstract

Implied trees are necessary to implement the risk neutral valuation approach, and standard methodologies for their derivation are based on the validity of the put call parity. However, in illiquid markets the put call parity fails to hold, and the uniqueness of the artificial probabilities leaves room for an interval. The contribution of this article is twofold. First we propose a methodology for the derivation of implied trees in illiquid markets. Such a methodology, by contrast with standard ones, takes into account the information stemming both from call and put prices. Second, we set up a framework for pricing derivatives written on an underlying asset traded on an illiquid market. To this end we have extended the Choquet integral definition to account for interval payoffs of the underlying asset. The price interval we obtain may be interpreted as a bid-ask price quoted by the intermediary issuing the derivative security.


2001 - A Multiperiod Binomial Model for Pricing Options in an Uncertain World [Relazione in Atti di Convegno]
Muzzioli, Silvia; Torricelli, Costanza
abstract

The aim of this paper is to price an option in a multiperiod binomial model, when there is uncertainty on the states of the world at each node of the tree. As a consequence, also the stock price at each state takes imprecise values. Possibility distributions are used to handle this type of problems. The pricing methodology is still based on a risk neutral valuation approach, but, as a consequence of the uncertainty on the two jumps of the stock, we obtain weighted intervals for risk-neutral probabilities. The distinctive feature of our model is that it tracks back the arising of these probability intervals to the imprecision of the value of the stock price in the up and down states. This paper provides a generalization of the standard binomial option pricing model. We obtain an expected value interval for the option price within which it is possible to find a crisp representative value and an index of the uncertainty present in the model.


2001 - A model for pricing an option with a fuzzy payoff [Articolo su rivista]
Muzzioli, Silvia; Torricelli, Costanza
abstract

This paper sets up a one period model for pricing an option with a fuzzy payoff. The option is written on an underlying asset that has a fuzzy price at the end of the period, modelled by means of triangular fuzzy numbers. The pricing methodology used is the standard one for pricing derivatives, i.e. the so called risk neutral valuation. Combining the standard Binomial Option Pricing Model with a fuzzy representation of the option payoff offers some advantages. First it provides an intuitive way of looking at the future price of an asset. Second it includes the results of the Standard Binomial Model, allowing the market to have different levels of information.


2001 - A multiperiod binomial model for ricing options in an uncertain world [Abstract in Atti di Convegno]
Muzzioli, Silvia; Torricelli, Costanza
abstract

The aim of this paper is to price an option in a multiperiod binomial tree, when there is uncertainty on the states of the world at each node of the tree.


1999 - Pricing options on a vague asset [Relazione in Atti di Convegno]
Muzzioli, Silvia; Torricelli, Costanza
abstract

This paper deals with the problem of pricing an option in a one-period model when the price of the underlyng asset is vague. The vagueness is modelled by the use of triangular fuzzy numbers and the pricing methodlogy is based on the no-arbitrage principle. A comparison with the corresponding binomial option pricing model is provided, in particular we show that it can be viewed as a special case of our model.


1998 - Note on ranking fuzzy triangular numbers [Articolo su rivista]
Facchinetti, Gisella; R., Ghiselli Ricci; Muzzioli, Silvia
abstract

In this paper we present a new method for ranking fuzzy numbers