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researcher

Fabrizio Lillo

4 papers hereh-index 28 citations4 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • q-fin.CP1
  • q-fin.ST1
  • q-fin.TR1
  • stat.AP1
same name
  • Fabrizio Lillo — 5 papers, h 2
  • Fabrizio Lillo — 4 papers, h 2
  • Fabrizio Lillo — 4 papers, h 2
  • Fabrizio Lillo — 1 paper, h 1
  • Fabrizio Lillo — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators

4 papers

q-fin.ST2026

Predicting the success of new crypto-tokens: the Pump.fun case

Giulio Marino, Manuel Naviglio, Francesco Tarantelli +1

We study the dynamics of token launched on Pump.fun, a Solana-based launchpad platform, to identify the determinants of the token success. Pump.fun employs a bonding curve mechanis…

q-fin.TR2025

Why is the estimation of metaorder impact with public market data so challenging?

Manuel Naviglio, Giacomo Bormetti, Francesco Campigli +2

Estimating market impact and transaction costs of large trades (metaorders) is a very important topic in finance. However, using models of price and trade based on public market da…

q-fin.CP2025

Price manipulation schemes of new crypto-tokens in decentralized exchanges

Manuel Naviglio, Francesco Tarantelli, Fabrizio Lillo

Blockchain technology has revolutionized financial markets by enabling decentralized exchanges (DEXs) that operate without intermediaries. Uniswap V2, a leading DEX, facilitates th…

stat.AP2024

Score-Driven Exponential Random Graphs: A New Class of Time-Varying Parameter Models for Dynamical Networks

Domenico Di Gangi, Giacomo Bormetti, Fabrizio Lillo

Motivated by the increasing abundance of data describing real-world networks that exhibit dynamical features, we propose an extension of the Exponential Random Graph Models (ERGMs)…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.