A5057681234- Market Dynamics and Volatility
- Financial Risk and Volatility Modeling
- Complex Systems and Time Series Analysis
- Financial Markets and Investment Strategies
- Stochastic processes and financial applications
- Income, Poverty, and Inequality
- Monetary Policy and Economic Impact
- Insurance, Mortality, Demography, Risk Management
- Economic Theory and Policy
- Probability and Risk Models
- Innovation Diffusion and Forecasting
- Financial Reporting and Valuation Research
- Blockchain Technology Applications and Security
- Housing Market and Economics
- Stock Market Forecasting Methods
- Economic theories and models
- Insurance and Financial Risk Management
- Banking stability, regulation, efficiency
- Forecasting Techniques and Applications
- Wind Energy Research and Development
- Risk and Portfolio Optimization
- Energy Load and Power Forecasting
- Sports Analytics and Performance
- Capital Investment and Risk Analysis
- Simulation Techniques and Applications
Marche Polytechnic University
2018-2025
Libera Università Maria SS. Assunta
2021-2022
University of Wollongong
2019
University of Chieti-Pescara
2017
ABSTRACT In statistics, samples are drawn from a population in data‐generating process (DGP). Standard errors measure the uncertainty estimates of parameters. science, evidence is generated to test hypotheses an evidence‐generating (EGP). We claim that EGP variation across researchers adds uncertainty—nonstandard (NSEs). study NSEs by letting 164 teams same on data. turn out be sizable, but smaller for more reproducible or higher rated research. Adding peer‐review stages reduces NSEs....
How does stablecoin design affect market behavior during turbulent periods? Stablecoins attempt to maintain a "stable" peg the US dollar, but do so with widely varying structural designs. The spectacular collapse of TerraUSD (UST) and linked Terra (LUNA) token in May 2022 precipitated series reactions across major stablecoins, some experiencing fall value others gaining value. Using Baba, Engle, Kraft Kroner (1990) (BEKK) model, we examine reaction this exogenous shock find significant...
Understanding the dependencies among financial assets is critical for portfolio optimization. Traditional approaches based on correlation networks often fail to capture nonlinear and directional relationships that exist in markets. In this study, we construct directed weighted using Mixture Transition Distribution (MTD) model, offering a richer representation of asset interdependencies. We apply local assortativity measures-metrics evaluate how connect similarities or differences-to guide...
Understanding the dependencies among financial assets is critical for portfolio optimization. Traditional approaches based on correlation networks often fail to capture nonlinear and directional relationships that exist in markets. In this study, we construct directed weighted using Mixture Transition Distribution (MTD) model, offering a richer representation of asset interdependencies. We apply local assortativity measures--metrics evaluate how connect similarities or differences--to guide...
Abstract In popular Baba-Engle-Kraft-Kroner (BEKK) and dynamic conditional correlation (DCC) multivariate generalized autoregressive heteroskedasticity models, the large number of parameters requirement positive definiteness covariance matrices pose some difficulties during estimation process. To avoid these issues, we propose two modifications to BEKK DCC models that employ spherical parameterizations applied Cholesky decompositions matrices. their full specifications, introduced...
Abstract Perpetual futures, first proposed by Shiller (1993), have only seen wide use in cryptocurrency markets. We examine the contract design and market microstructure differences for behavior of Bitcoin quarterly perpetual futures prices assess implications participants policymakers. find exhibit multiple “u‐shaped” curves, seasonal effects, opening effects despite lacking closing hours. There is suggestive evidence spillover between contracts. offer cash‐and‐carry arbitrage...
Abstract Energy management of distributed energy resources has gradually become a complex problem because the intermittent nature renewable sources, such as photovoltaic power, and large use storage systems. A way to deal with these issues is operate within an community. However, efficient community in terms costs particularly relevant. Specifically, minimization costs, which consists properly utilizing shared becomes important objective. In this context, fundamental role played by demand...
The COVID-19 pandemic is having a strong influence in all areas of society, like wealth, economy, travel, lifestyle habits, and, amongst many others, financial and energy markets. standard energies, crude oil, renewable energies markets has been twofold: from one side, the predictability volatility strongly decreased; secondly, linkages price time series have modified. In this paper, by using DCC-GARCH Price Leadership Share methodology, we can investigate changes influences between...
We propose a dividend stock valuation model where multiple growth series and their dependencies are modelled using multivariate Markov chain. Our advances existing chain models. First, we determine assumptions that guarantee the finiteness of price risk as well fulfilment transversality conditions. Then, compute first- second-order price-dividend ratios by solving corresponding linear systems equations show different ratio is attached to each combination states process stock. Subsequently,...
Abstract We address the calibration issues of weighted-indexed semi-Markov chain (WISMC) model applied to high-frequency financial data. Specifically, we propose automate discretization price returns and volatility index by using four different approaches, two based on statistical quantities, namely, quantile sigma discretization, derived application popular machine learning algorithms, namely k-means Gaussian mixture (GMM). Moreover, comparing Bayesian information criterion (BIC) scores,...
In statistics, samples are drawn from a population in data-generating process (DGP). Standard errors measure the uncertainty sample estimates of parameters. science, evidence is generated to test hypotheses an evidence-generating (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams six on same sample. find sizeable, par with standard Their size (i) co-varies only weakly team merits, reproducibility, or peer rating, (ii)...
The energy produced by a wind farm in given location and its associated income depends both on the characteristics that location—i.e., speed direction—and dynamics of electricity spot price. Because evidence cross-correlations between speed, direction price series their lagged series, we aim to assess hypothetical located central Italy when all interactions are considered. To model these cross auto-correlations efficiently, apply high-order multivariate Markov which includes dependencies...
Sensitivity analysis of random systems may convey important information on the dynamical properties system. In this paper, we determine effects parameters' perturbation two dynamic poverty indexes: headcount ratio and income gap ratio. This is achieved by perturbing generator Markov process governing evolution in time economic agents among three classes income, initial distribution individuals vector mean for class. The paper presents bounds aforementioned indexes which show how...
Computations of risk measures in the context dividend valuation model is a crucial aspect to deal with when investors decide buy share common stock. This achieved by using Markov chain growth-dividend evolution, imposing an assumption that controls growth process and turn allows for computation moments price fulfillment set transversality conditions which avoiding presence speculative bubbles market. The probability distribution fundamental value stock recovered solving moment problem, based...
Abstract We propose the valuation of a real option in telecommunications industry. According to probabilistic present worth approach, we estimate value contract between television network and company willing advertise its business on this network. assume that depends time-dependent variable, i.e., number viewers tuned into network, which behaves like Markov process. After discretizing converting monetary through specific function, compute nth-order moment total discounted earnings. The...
This paper investigates the cryptocurrency network of FTX exchange during collapse its native token, FTT, to understand how structures adapt significant financial disruptions, by exploiting vertex centrality measures. Using proprietary data on transactional relationships between various cryptocurrencies, we construct filtered correlation matrix identify most relations in and Binance markets. By using suitable measures - closeness information assess stability FTX's bankruptcy. The findings...
In this study, we consider different poverty indexes in a dynamic framework where individuals change their rate of income randomly time. The primary objective paper is to assess the accuracy approximation that can be obtained by applying strong law large numbers an economic system composed infinite number agents. main result multivariate central limit theorem for measures, which theory U-statistics. We also show how get confidence sets considered indexes, appropriateness model. An...
We propose a dividend stock valuation model where multiple growth series and their dependencies are modelled using multivariate Markov chain. Our advances existing chain models. First, we determine assumptions that guarantee the finiteness of price risk as well fulfilment transversality conditions. Then, compute first second order price-dividend ratios by solving corresponding linear systems equations show different ratio is attached to each combination states process stock. Subsequently,...