Gianna Figà-Talamanca

• PhD
• Professor (Full) at University of Perugia

This paper presents a Markov-modulated stochastic volatility model that captures the dependency of market regimes on investor sentiment. The main contribution lies in developing a modified version of the classical Heston model by allowing for a sentiment-driven bias in the volatility of the asset. Specifically, a two-factor Markov-modulated stochas...

With the availability of social networks, specialized forums, and online news, sentiment analysis has become a common and useful technique for the analysis of economic and financial scenarios. Several data‐providers have also started computing proprietary sentiment indexes on financial assets to be delivered together with market price and trading v...

The main contribution of this study is to assess whether investor sentiment, as measured through textual analysis of newspaper articles or social media posts, does have an effect on the mean returns and on the variance of financial stocks. The analysis is carried on a basket of the S &P 500 components where stock returns and volatility are modeled...

Robo-advice technology refers to services offered by a virtual financial advisor based on artificial intelligence. Research on the application of robo-advice technology already highlights the potential benefit in terms of financial inclusion. We analyze the process for adopting robo-advice through the technology acceptance model (TAM), focusing on...

The motivation of proposing and editing the Special Issue “Blockchain and cryptocurrencies” came from the inspirational invited and contributed talks at the 43rd annual A.M.A.S.E.S. conference held in Perugia in September 2019. All the papers have gone through the journal regular refereeing process under the same standards set by the journal, and n...

Empirical evidence suggests the presence of bubble effects on Bitcoin price dynamics during its lifetime, starting in 2009. Previous research, mostly empirical, focused on statistical tests in order to detect a bubble behavior at some point in time. Few exceptions suggested specific time series models capable to describe such phenomena. We contribu...

An alternative volatility index called SPIKES has been recently introduced. Like VIX, SPIKES aims to forecast S&P 500 volatility over a 30-day horizon and both indexes are based on the same theoretical formula; yet, they differ in several ways. While some differences are introduced in response to the controversy surrounding possible VIX manipulatio...

In this paper we test for regime changes and possible regime commonalities in the price dynamics of Bitcoin, Ethereum, Litecoin and Monero, as representatives of the cryptocurrencies asset class. Several parametric models are considered for the joint dynamics of the basket price where parameters are modulated through a Hidden Markov Chain with fini...

In this paper, we apply dynamic factor analysis to model the joint behaviour of Bitcoin, Ethereum, Litecoin and Monero, as a representative basket of the cryptocurrencies asset class. The empirical results suggest that the basket price is suitably described by a model with two dynamic factors. More precisely, we detect one integrated and one statio...

Bitcoin is a digital currency started in early 2009 by its inventor under the pseudonym of Satoshi Nakamoto. In the last few years, Bitcoin has received much attention and has shown a surprising price increase. Bitcoin is currently traded on many web-exchanges making it a rare example of a good for which different prices are readily available; this...

In this paper we extend the model in Cretarola, Figà-Talamanca, “Detecting bubbles in Bitcoin price dynamics via market exuberance”, Annals of Operations Research (2019), by allowing for a state-dependent correlation parameter between asset returns and market attention. We assume that the change of state is described by a continuous time latent Mar...

Finance is the language of business and as technological disruption accelerates, a fundamental change is under way. This presents both opportunities and challenges for current-day organizations and finance professionals alike. Money makes the world go around, they say; but digital money not only makes the world go around, it does it in a decentrali...

In the last few years Bitcoin price dynamics has been the subject of intense research. One of the main stream of investigation is the identification of relevant factors affecting its returns and volatility; empirical evidence suggests a positive association between returns and sentiment proxies about the Bitcoin network, such as Wikipedia inquiries...

The goal of this paper is to provide a novel quantitative framework to describe the Bitcoin price behavior, estimate model parameters and study the pricing problem for Bitcoin derivatives. To this end, we propose a continuous time model for Bitcoin price motivated by the findings in recent literature on Bitcoin, showing that price changes are affec...

In this paper, we analyze the relative impact of attention measures either on the mean or on the variance of Bitcoin returns by fitting nonlinear econometric models to historical data: Two non-overlapping subsamples are considered from January 1, 2012, to December 31, 2017. Outcomes confirm that market attention has an impact on Bitcoin returns and...

Although Bitcoin is a relatively new subject in Economics, contributions in this topic are growing very fast. Several papers evidenced a bubble behaviour in exchange rates between Bitcoin and traditional currencies. In this paper we explore and give validation to such conjecture, proving also that the bubble effect is due to confidence in Bitcoin f...

In this paper we introduce new average operators for merging any number of fuzzy numbers, without any exogenous components. The proposed n-ary operators are based on a specific adaptation of Marzullo's algorithm, and depart from the usual fuzzy arithmetic mean according to the degree of agreement or disagreement among the memberships of input fuzzy...

In this paper we introduce new disjunction and conjunction (named SMART) for merging, without any exogenous components, any number of fuzzy memberships. The present proposals are n-ary operators, based on a specific adaptation of Marzullo’s algorithm, that depart from the usual fuzzy mean on the base of the agreement/disagreement among the differen...

This chapter illustrates a continuous time model for the dynamics of Bitcoin price, which depends on an attention or sentiment factor. The model is proven arbitrage-free under mild conditions and a quasi-closed pricing formula for European style derivatives is provided.

In recent literature it is claimed that BitCoin price behaves more likely to a volatile stock asset than a currency and that changes in its price are influenced by sentiment about the BitCoin system itself; in Kristoufek [10] the author analyses transaction based as well as popularity based potential drivers of the BitCoin price finding positive ev...

In recent literature it is claimed that BitCoin price behaves more likely to a volatile stock asset than a currency and that changes in its price are influenced by sentiment about the BitCoin system itself; in Kristoufek [10] the author analyses transaction based as well as popularity based potential drivers of the BitCoin price finding positive ev...

We endorse the idea, suggested in recent literature, that BitCoin prices are influenced by sentiment and confidence about the underlying technology; as a consequence, an excitement about the BitCoin system may propagate to BitCoin prices causing a Bubble effect, the presence of which is documented in several papers about the cryptocurrency. In this...

We endorse the idea, suggested in recent literature, that BitCoin prices are influenced by sentiment and confidence about the underlying technology; as a consequence, an excitement about the BitCoin system may propagate to BitCoin prices causing a Bubble effect, the presence of which is documented in several papers about the cryptocurrency. In this...

In this paper we extend our previous contributions on the elicitation of the fuzzy volatility membership function in option pricing models. More specifically we generalize the SMART disjunction for a multi-model volatility behavior (Uniform, LogNormal, Gamma, ...) and within a double-source (direct vs. indirect) information set. The whole procedure...

We introduce a formal test to detect whether a times series of financial log-returns is consistent with the Heston stochastic volatility model as data generating process. The test is based on the auto-covariance structure of the integrated volatility, which is available in closed form for the model under investigation. The test suggested in this co...

We illustrate a preliminary proposal of weighted fuzzy averages between two membership functions. Conflicts, as well as agreements, between the different sources of information in the two new operators are endogenously embedded inside the average weights. The proposal is motivated by the practical problem of assessing the fuzzy volatility parameter...

This chapter explains the testing of the consistency of the diffusion model with changes in the log-price of several commodities. It introduces the main issue of estimating diffusion processes by finite sample data and describes the estimation techniques to daily prices of crude oil, corn, copper and gold from May 2006 to March 2009. The chapter si...

In this work we suggest a methodology to obtain the membership of a non-observable parameter through implicit information. To this aim we profit from the interpretation of membership functions as coherent conditional probabilities. We develop full details for the well known Black and Scholes pricing model where the membership of the volatility para...

The present study analyzes the extra insights that option pricing models may achieve when uncertainty about parameters is modeled through fuzzy numbers. Specifically, the authors consider the Heston stochastic volatility model, which assumes that stock price changes and their instantaneous variance evolve as a bivariate, possibly correlated, diffus...

The aim of this work is to develop a nonparametric tool for detecting dependence in the tails of financial data. We provide a simple method to locate and measure serial dependence in the tails, based on runs tests. Our empirical investigations on many financial time series reveal a strong departure from independence for daily logreturns, which is n...

Stochastic volatility models for option pricing are suitable to explain many empirical stylized facts in financial markets. Among the other models, Heston provides a good analytical tractability because a quasi closed formula for the price of a European call option can be derived. The estimation of the Heston model parameters is nowadays a subject...

The sample autocovariance of the suitably scaled squared returns of a given stock is shown here to be a consistent and asymptotically normal estimator of the theoretical autocovariance of the mean variance, when the data is generated by the Constant Elasticity of Variance stochastic volatility (CEV SV) process. By computing explicitly the asymptoti...

Uncertainty and vagueness play a central role in financial models and fuzzy numbers can be a profitable way to manage them. In this paper we generalize the Black and Scholes option valuation model (with constant volatility) to the framework of a volatility supposed to vary in a stochastic way. The models we take under consideration belongs to the m...

The aim of this study is to evaluate some simulation schemes recently suggested for the Heston model by examining their ability in reproducing, on the simulated paths, the autocovariance function of the generated model, when discretely observed. This is done by applying the outcomes of previous research where, based on discrete equi-spaced observat...

In this note we generalize the limit results in [Genon-Catalot, Jeantheau, Laredo, 2000, Bernoulli ] for simple stochastic volatility models to the case where a non zero correlation is allowed between the Brownian mo- tion driving the main di�usion process and the Brownian motion driving the dymaics of the instantaneous variance. We also extend the...

In this paper we study the tail behaviour of eight major market indexes stratifying data according to the violation of a high threshold on the previous day. The distributional differences found can be exploited to improve VaR calculations in several settings, giving rise to what we call 'MCVaR'. We compare the performance of MCVaR with unconditione...

The aim of this paper is to introduce some methodologies for parameter estimation in Hobson and Rogers stochastic volatility model (1998). We pay a specific attention to the so-called feedback parameter, which is shown to be crucial for the model to fit correctly the smile curve of implied volatility and we introduce different procedures for the es...

In this work we refine a nonparametric methodology firstly applied in Christoffersen and Diebold [Review of Economics and Statistics 82 (2000) 12] for assessing volatility forecastability in financial time series based on discretization and on the use of runs tests. Empirical results are provided for SP500 and MIB30 indexes that lead naturally to a...