Enhancing bookkeeper decision support through graph representation learning for bank reconciliation
December 2025
The emergence of cloud-based bookkeeping platforms has made it possible to streamline decision-making in tedious accounting tasks, such as bank reconciliation. Bank reconciliation involves tracing the...
Leveraging financial interdependencies in emerging markets via graph neural networks
December 2025
This study examines the role of interdependencies in forecasting sovereign yield spreads in emerging markets using Graph Neural Networks (GNNs). Sovereign yield spreads reflect economic conditions and...
The economic impact of DeFi crime events on decentralized autonomous organizations (DAOs)
December 2025
The Decentralized Finance (DeFi) ecosystem has experienced over $10 billion in direct losses due to crime events. Beyond these immediate losses, such events often trigger broader market reactions, including...
Integrating Choquet portfolios and machine learning interpretability for robust cryptocurrency investment strategies
December 2025
This study proposes an alternative approach to portfolio optimization in the cryptocurrency market by applying the Choquet integral portfolio, positioning it within the broader context of Robo-Advisor...
Multifractal and low-dimensional representations of high-frequency return distribution sequences
December 2025
High-frequency returns are of great significance to financial risk management and investment. This study analyzes the dynamics of the high-frequency return distributions. The calculations show that...
Finding money launderers using heterogeneous graph neural networks
December 2025
The finance industry depends on effective anti-money laundering (AML) systems to ensure compliance and maintain operational efficiency. However, existing AML systems, which are predominantly rule-based,...
Informed trading and expected returns
December 2025
Does information asymmetry affect the cross-section of expected stock returns? We explore this question using representative portfolio holdings data from the Shanghai Stock Exchange. We show that institutional...
Pairs trading with time-series deep learning models
December 2025
Pairs trading is a well-studied statistical arbitrage strategy including the identification of asset pairs exhibiting correlated changes in their historical prices. This statistical arbitrage strategy...
Persistent cointegration and regime-sensitive market leadership: Evidence from international tobacco stocks
December 2025
This paper develops a data-driven framework combining fractional cointegration and structural break detection to examine long-run interdependence and market leadership among international tobacco equities....
GARCH-PDE models for option pricing under stochastic volatility and their finite difference solvers
December 2025
This paper presents numerical solvers for generative and hybrid option pricing models that unify econometric and diffusion-based approaches. These models are formulated as systems of continuous partial...
Investigating the relationship between processes and profit: A work-based assessment of process used in Australian financial planning firms
December 2024
The research explores relationship dynamics between process and profit in Australian professional practise. We analyse data collected from 134 financial planning firms located in Southeast Queensland...
Revising data collection methodology - evidence from the Australian financial sector
December 2024
Time requirements of data collection account for a significant portion of the total time required to provide financial advice. This research applies data collection software to the financial planning...
Cluster-based regression using variational inference and applications in financial forecasting
December 2024
This paper describes an approach to simultaneously identify clusters and estimate cluster-specific regression parameters from the given data. Such an approach can be useful in learning the relationship...
Deep unsupervised anomaly detection in high-frequency markets
December 2024
Inspired by recent advances in the deep learning literature, this article introduces a novel hybrid anomaly detection framework specifically designed for limit order book (LOB) data. A modified Transformer...
Research on credit card default repayment prediction model
December 2024
This study compares the predictive ability of various machine learning models for credit card default repayment within different prediction frameworks, using data from a commercial bank in China. Firstly,...
What drives liquidity in the Chinese credit bond markets?
December 2024
We study the drivers and pricing of liquidity in the Chinese credit bond markets. We document that the liquidity and liquidity effects priced into yield spreads differ significantly across the four...
China's GDP at risk: The role of housing prices
December 2024
This paper studies the impact of house prices on the distribution of GDP growth in China (the 5th, median, and 95th percentiles). We show that house price appre-ciation positively affects future GDP...
Machine learning private equity returns
December 2024
In this paper, we use two machine learning techniques to learn the aggregated return time series of complete private capital fund segments. First, we propose Stochastic Discount Factor (SDF) model combination...
Time-mixing and feature-mixing modelling for realized volatility forecast: Evidence from TSMixer model
December 2024
This study evaluates the effectiveness of the TSMixer neural network model in forecasting stock realized volatility, comparing it with traditional and contemporary benchmark models. Using data from...
NFT price and sales characteristics prediction by transfer learning of visual attributes
December 2024
Non-fungible tokens (NFTs) are unique digital assets whose possession is defined over a blockchain. NFTs can represent multiple distinct objects such as art, images, videos, etc. There was a recent...
Technical patterns and news sentiment in stock markets
December 2024
This paper explores the effectiveness of technical patterns in predicting asset prices and market movements, emphasizing the role of news sentiment. We employ an image recognition method to detect technical...
Interpretable machine learning model for predicting activist investment targets
December 2024
This research presents a predictive model to identify potential targets of activist investment funds—entities that acquire significant corporate stakes to influence strategic and operational decisions,...
Learning from AI-Finance: A selected synopsis
December 2024
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