arXiv · arXiv · 2026
This paper compares different methods for forecasting the term structure of U.S. and European zero-coupon government bonds using both traditional econometric and Machine Learning (ML) approaches. We compare classical models (e.g., Dynamic Nelson-Siegel (DNS) and Principal Component Analysis (PCA)) with different Neural Network (NN) architectures, including those inspired by the classical models, on the U.S. Treasury …
Tobias Lausser, Joao Eduardo Vuolo, Rudi Zagst
arXiv · arXiv · 2024
We develop a liquidity-sensitive multivariate volatility framework to improve the estimation of time-varying covariance structures under market frictions. We introduce two novel portfolio-level liquidity measures, liquidity jump and liquidity diffusion, which capture magnitude and volatility of liquidity fluctuation, respectively, and construct liquidity-adjusted return and volatility that reflect real-time liquidity…
Qi Deng
arXiv · arXiv · 2012
Market liquidity plays a vital role in the field of market micro-structure, because it is the vigor of the financial market. This paper uses a variable called convexity to measure the potential liquidity provided by order-book. Based on the high-frequency data of each stock included in the SSE (Shanghai Stock Exchange) 50 Index for the year 2011, we report several statistical properties of convexity and analyze the a…
Kenan Qiao
arXiv · arXiv · 2026
Most of the autocorrelation in trade signs on decentralized exchanges comes from pairs of trades sent by different wallets. For Uniswap v3, this has been read as herding dominating order splitting -- the reverse of what equity markets show. We show that this herding share mixes two quantities: the probability $p$ that consecutive orders come from the same account, which is small when thousands of wallets are trading,…
Yichong Bai, Dingyue Kan
arXiv · arXiv · 2024
As a quantitative characterization of the complicated economy, Macroeconomic Variables (MEVs), including GDP, inflation, unemployment, income, spending, interest rate, etc., are playing a crucial role in banks' portfolio management and stress testing exercise. In recent years, especially during the COVID-19 period and the current high inflation environment, people are frequently talking about the changing "correlatio…
Garvit Arora, Shubhangi Tiwari, Ying Wu, Xuan Mei
arXiv · arXiv · 2026
We study coordinated groups of wallets on a bonding-curve launchpad (pump.fun on Solana), using a complete record of 200\,443 token launches, 15\,854\,121 curve trades and 51\,025\,958 SOL transfers over 88.3 hours. A prospective, multi-channel discovery procedure (co-buying, shared funding, joint signing, transfers, consolidation) yields 23\,710 wallet groups. Without ground-truth labels we validate them by out-of-s…
Fail Gafarov