1 citations · 1 across the 6 of their papers we have counts for
6 papers
Explainable Deep Learning for Price-Trade Dynamics: From Black-Box Forecasts to Effective Parametric Models
Manuel Naviglio, Fabrizio Lillo
Understanding the joint dynamics of prices and trades is central to market microstructure, where returns and order flow interact through nonlinear and state-dependent mechanisms. L…
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…
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…
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…
Measuring price impact and information content of trades in a time-varying setting
F. Campigli, G. Bormetti, F. Lillo
We propose a non-linear observation-driven version of the Hasbrouck (1991) model for dynamically estimating trades' market impact and information content. We find that market impac…
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)…