A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Study uses IMFs and neural networks to predict economic time series, enhancing interpretability.
This study applies EMD to MSCI World index and converts IMFs into graphs for GNN modeling.
Different investment strategies are adopted in short-term and long-term depending on the time scales, even though time scales are adhoc in nature. Empirical mode decomposition based Hurst exponent analysis and variance technique have been applied to identify the time scales for short-term and long-term investment from …
Paper provides exponential convergence guarantees for Iterative Markovian Fitting.
Hybrid model forecasts Bitcoin prices better than standard LSTM.
New algorithm improves on existing methods for solving transport problems.
New method solves tree-structured Schrödinger Bridge problems.
In this paper, a unified susceptible-exposed-infected-susceptible-aware (SEIS-A) framework is proposed to combine epidemic spreading with individuals' on-line self-consultation behaviors. An epidemic spreading prediction model is established based on the SEIS-A framework. The prediction process contains two phases. In …
Unfulfilled expectations from macro-economic initiatives during the Great Recession and the massive shift into globalization echo today with political upheaval, anti-establishment propaganda, and looming trade/currency wars that threaten domestic and international value chains. Once stable entities like the EU now look…
Extends diffusion-based Schrödinger bridge models to handle time-dependent potentials.
This paper is concerned with the inverse problem of recovering the unknown signal components, along with extraction of their instantaneous frequencies (IFs), governed by the adaptive harmonic model (AHM), from discrete (and possibly non-uniform) samples of the blind-source composite signal. None of the existing decompo…
This study proposes methods for multi-step-ahead stock price prediction using decomposition and neural networks.
New proof of Lie-Tresse theorem with computational advantages.
Paper forecasts tax revenues in Bulgaria during pandemic.
MSBM extends SB for multi-marginal trajectory inference.
By monitoring the time evolution of the most liquid Futures contracts traded globally as acquired using the Bloomberg API from 03 January 2000 until 15 December 2014 we were able to forecast the S&P 500 index beating the Buy and Hold trading strategy. Our approach is based on convolution computations of 42 of the most …
Python tool creates machine-learning-ready solar dataset.
The Financial Crisis of 2008 is a worldwide financial crisis causing a worldwide economic decline that is the most severe since the 1930s. According to the International Monetary Fund (IMF), the global financial crisis gave impact on USD 3.4 trillion losses from financial institutions around the world between 2007 and …
The recent financial crisis of 2008 and the 2011 indebtedness of Greece highlight the importance of understanding the structure of the global financial network. In this paper we set out to analyze and characterize this network, as captured by the IMF Coordinated Portfolio Investment Survey (CPIS), in two ways. First, t…
Systemic liquidity risk, defined by the IMF as "the risk of simultaneous liquidity difficulties at multiple financial institutions", is a key topic in macroprudential policy and financial stress analysis. Specialized models to simulate funding liquidity risk and contagion are available but they require not only banks' …
We propose a novel multi-layered nonlinear model that is able to capture and predict the housing-demographic dynamics of the real-state market by simulating the transitions of owners among price-based house layers. This model allows us to determine which parameters are most effective to smoothen the severity of a poten…
This work studies the statistical performance of Sinkhorn iterations in estimating Schrödinger bridges.
A new index CRIX for cryptocurrencies is proposed to track market changes.
New algorithm for decomposing multidimensional, non-stationary signals.