
Silvia Bartolucci- Associate Professor at University College London
Silvia Bartolucci
- Associate Professor at University College London
About
60
Publications
11,008
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549
Citations
Introduction
Current institution
Additional affiliations
September 2020 - present
Position
- Research Associate
October 2012 - January 2016
Education
October 2010 - July 2012
October 2007 - October 2010
Publications
Publications (60)
Using the replica method, we compute the statistics of the top eigenpair of diluted covariance matrices of the form $\bm J = \bm X^T \bm X$, where $\bm X$ is a $N\times M$ sparse data matrix, in the limit of large $N,M$ with fixed ratio and a bounded number of nonzero entries. We allow for random non-zero weights, provided they lead to an isolated...
Understanding how credit flows through inter-firm networks is critical for assessing financial stability and systemic risk. In this study, we introduce DebtStreamness, a novel metric inspired by trophic levels in ecological food webs, to quantify the position of firms within credit chains. By viewing credit as the ``primary energy source'' of the e...
Drawing from engineering systems and control theory, we introduce a framework to understand repository stability, which is a repository activity capacity to return to equilibrium following disturbances - such as a sudden influx of bug reports, key contributor departures, or a spike in feature requests. The framework quantifies stability through fou...
We analyze developer activity across 10 major Ethereum repositories (totaling 129884 commits, 40550 issues) spanning 10 years to examine how events such as technical upgrades, market events, and community decisions impact development. Through statistical, survival, and network analyses, we find that technical events prompt increased activity before...
Blockchain technology presents several sustainability challenges, such as optimization problems and excessive energy usage, which developers may overlook. This study examines how blockchain developers incorporate sustainability themes into their conversations and the specific areas they focus on. We analyze Go-Ethereum developers' issues and commen...
We analyze the stability of financial investment networks, where financial institutions hold overlapping portfolios of assets. We consider the effect of portfolio diversification and heterogeneous investments using a random matrix dynamical model driven by portfolio rebalancing. While heterogeneity generally correlates with heightened volatility, i...
Using the replica method, we compute analytically the average largest eigenvalue of diluted covariance matrices of the form $\mathbf{J} = \mathbf{X}^T \mathbf{X}$, where $\mathbf{X}$ is a $N\times M$ sparse data matrix, in the limit of large $N,M$ with fixed ratio. We allow for random non-zero weights, provided they lead to an isolated largest eige...
Ranking sectors and countries within global value chains is of paramount importance to estimate risks and forecast growth in large economies. However, this task is often non-trivial due to the lack of complete and accurate information on the flows of money and goods between sectors and countries, which are encoded in input–output (I–O) tables. In t...
Decentralized applications (DApps) built on blockchain platforms such as Ethereum and coded in languages such as Solidity, have recently gained attention for their potential to disrupt traditional centralized systems. Despite their rapid adoption, limited research has been conducted to understand the underlying code structure of these applications....
The Katz centrality of a node in a complex network is a measure of the node’s importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically because o...
We introduce a novel large-scale deep learning model for Limit Order Book mid-price changes forecasting, and we name it `HLOB'. This architecture (i) exploits the information encoded by an Information Filtering Network, namely the Triangulated Maximally Filtered Graph, to unveil deeper and non-trivial dependency structures among volume levels; and...
Debt recycling is an aggressive equity extraction strategy that potentially permits faster repayment of a mortgage. While equity progressively builds up as the mortgage is repaid monthly, mortgage holders may obtain another loan they could use to invest on a risky asset. The wealth produced by a successful investment is then used to repay the mortg...
Since the introduction of Bitcoin in 2009, the dramatic and unsteady evolution of the cryptocurrency market has also been driven by large investments by traditional and cryptocurrency-focused hedge funds. Notwithstanding their critical role, our understanding of the relationship between institutional investments and the evolution of the cryptocurre...
The Katz centrality of a node in a complex network is a measure of the node's importance as far as the flow of information across the network is concerned. For ensembles of locally tree-like and undirected random graphs, this observable is a random variable. Its full probability distribution is of interest but difficult to handle analytically becau...
In recent years, decentralized applications (dApps) built on blockchain platforms such as Ethereum and coded in languages such as Solidity, have gained attention for their potential to disrupt traditional centralized systems. Despite their rapid adoption, limited research has been conducted to understand the underlying code structure of these appli...
This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach. Unlike existing tools, our toolchain combines the power of ANTLR4 and Abstract Syntax Tree (AST) traversal techniques to transform the archit...
This paper is concerned with upstreamness and downstreamness of industries and countries in global value chains. Upstreamness and downstreamness measure respectively the average distance of an industrial sector from final consumption and from primary inputs, and they are computed from based on the most used global Input-Output tables databases, e.g...
This study examines software metrics in decentralized applications (dApps) to analyze their structural and behavioral characteristics as they grow in complexity. Sixty dApps were categorized into Small (3 to 29 contracts), Medium (30 to 46 contracts), and Large (47 to 206 contracts) based on their contract count. Initial analysis showed a non-norma...
In recent years, decentralized applications (dApps) built on blockchain platforms such as Ethereum and coded in languages such as Solidity, have gained attention for their potential to disrupt traditional centralized systems. Despite the rapid adoption, limited research has been conducted to understand the underlying code structure of these applica...
Deep learning methods have demonstrated outstanding performances on classification and regression tasks on homogeneous data types (e.g., image, audio, and text data). However, tabular data still poses a challenge with classic machine learning approaches being often computationally cheaper and equally effective than increasingly complex deep learnin...
Many complex systems exhibit a natural hierarchy in which elements can be ranked according to a notion of “influence”. While the complete and accurate knowledge of the interactions between constituents is ordinarily required for the computation of nodes' influence, using a low-rank approximation we show that—in a variety of contexts—local and aggre...
This paper evaluates the capability of two state-of-the-art artificial intelligence (AI) models, GPT-3.5 and Bard, in generating Java code given a function description. We sourced the descriptions from CodingBat.com, a popular online platform that provides practice problems to learn programming. We compared the Java code generated by both models ba...
Since the introduction of Bitcoin in 2009, the dramatic and unsteady evolution of the cryptocurrency market has also been driven by large investments by traditional and cryptocurrency-focused hedge funds. Notwithstanding their critical role, our understanding of the relationship between institutional investments and the evolution of the cryptocurre...
Predicting the prices of cryptocurrencies is a notoriously challenging task due to high volatility and new mechanisms characterising the crypto markets. In this work, we focus on the two major cryptocurrencies for market capitalisation at the time of the study, Ethereum and Bitcoin, for the period 2017–2020. We present a comprehensive analysis of t...
We derive an approximate but explicit formula for the Mean First Passage Time
of a random walker between a source and a target node of a directed and
weighted network. The formula does not require any matrix inversion, and it
takes as only input the transition probabilities into the target node. It is
derived from the calculation of the average res...
Examples of sharing economy platforms are proliferating, generating new concerns on the exploitation of local resources, ethical and intellectual properties. Necessary changes are required to the regulatory frameworks of our cities. This paper proposes an application of blockchain technology for planning governance purposes. This new cutting-edge t...
We derive an approximate but explicit formula for the Mean First Passage Time of a random walker between a source and a target node of a directed and weighted network. The formula does not require any matrix inversion, and takes as only input the transition probabilities into the target node. It is derived from the calculation of the average resolv...
Predicting prices of cryptocurrencies is a notoriously hard task due to the presence of high volatility and new mechanisms characterising the crypto markets. In this work we focus on the two major cryptocurrencies for market capitalization at the time of the study, Ethereum and Bitcoin, for the period 2017-2020. We present a comprehensive analysis...
We present a baseline stochastic framework for assessing inter-sectorial relationships in a generic economy. We show that irrespective of the specific features of the technology matrix for a given country or a particular year the Leontief multipliers (and any upstreamness/downstreamness indicator computed from the Leontief inverse matrix) follow a...
The input-output balance equation is used to define rankings of constituents in the most diverse complex organizations: the very same tool that helps classify how species of an ecosystems or sectors of an economy interact with each other is useful to determine what sites of the World Wide Web -- or which nodes in a social network -- are the most in...
We propose a modelling framework for the optimal selection of crypto assets. We assume that crypto assets can be described according to two features: security (technological) and stability (governance). We simulate optimal selection decisions of investors, being driven by (i) their attitudes towards assets’ features, (ii) information about the adop...
We propose a modelling framework for the optimal selection of crypto assets. We assume that crypto assets can be described according to two features: Security (technological) and stability (governance). We simulate optimal selection decisions of investors, being driven by (i) their attitudes towards assets' features, (ii) information about the adop...
The network of developers in distributed ledgers and blockchains open source projects is essential to maintaining the platform: understanding the structure of their exchanges, analysing their activity and its quality (e.g. issues resolution times, politeness in comments) is important to determine how “healthy” and efficient a project is. The qualit...
The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide “off-chain” fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we exp...
The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we exp...
The network of developers in distributed ledgers and blockchains open-source projects is essential to maintaining the platform: understanding the structure of their exchanges, analysing their activity and its quality (e.g. issues resolution times, politeness in comments) is important to determine how "healthy" and efficient a project is. The qualit...
We propose a modelling framework for the optimal selection of crypto assets. Crypto assets differ by two essential features: security (technological) and stability (governance). Investors make choices over crypto assets similarly to how they make choices by using a recommender app: the app presents each investor with a pair of crypto assets with ce...
The Lightning Network is a so-called second-layer technology built on top of the Bitcoin blockchain to provide "off-chain" fast payment channels between users, which means that not all transactions are settled and stored on the main blockchain. In this paper, we model the emergence of the Lightning Network as a (bond) percolation process and we exp...
Recently, there has been a growing interest in using online technologies to design protocols for secure electronic voting. The main challenges include vote privacy and anonymity, ballot irrevocability and transparency throughout the vote counting process. The introduction of the blockchain as a basis for cryptocurrency protocols, provides for the e...
In this work we use belief-propagation techniques to study the equilibrium behaviour of a minimal model for the immune system comprising interacting T and B clones. We investigate the effect of the so-called idiotypic interactions among complementary B clones on the system's activation. Our result shows that B-B interactions increase the system's r...
In this work we use belief-propagation techniques to study the equilibrium behaviour of a minimal model for the immune system comprising interacting T and B clones. We investigate the effect of the so-called idiotypic interactions among complementary B clones on the system's activation. Our result shows that B-B interactions increase the system's r...
We analyse a minimal model for the primary response in the adaptive immune
system comprising three different players: antigens, T and B cells. We assume
B-T interactions to be diluted and sampled locally from heterogeneous degree
distributions, which mimic B cells receptors' promiscuity. We derive dynamical
equations for the order parameters quanti...
In this work we solve the dynamics of pattern diluted associative networks, evolving via sequential Glauber update. We derive dynamical equations for the order parameters, that quantify the simultaneous pattern recall of the system, and analyse the nature and stability of the stationary solutions by means of linear stability analysis as well as Mon...
In this work we solve the dynamics of pattern diluted associative networks,
evolving via sequential Glauber update. We derive dynamical equations for the
order parameters, that quantify the simultaneous pattern recall of the system,
and analyse the nature and stability of the stationary solutions by means of
linear stability analysis as well as Mon...
In this work, we adopt a statistical-mechanics approach to investigate basic, systemic features exhibited by adaptive immune systems. The lymphocyte network made by B cells and T cells is modeled by a bipartite spin glass, where, following biological prescriptions, links connecting B cells and T cells are sparse. Interestingly, the dilution perform...