The use of predictive analytics in finance
November 2022
Statistical and computational methods are being increasingly integrated into Decision Support Systems to aid management and help with strategic decisions. Researchers need to fully understand the use...
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,...
Audit data analytics, machine learning, and full population testing
November 2022
Emerging technologies like data analytics and machine learning are impacting the accounting profession. In particular, significant changes are anticipated in audit and assurance procedures because of...
Credit scoring methods: Latest trends and points to consider
November 2022
Credit risk is the most significant risk by impact for any bank and financial institution. Accurate credit risk assessment affects an organisation's balance sheet and income statement, since credit...
Making it into a successful series A funding: An analysis of Crunchbase and LinkedIn data
November 2023
Startups are a key force driving economic development, and the success of these high-risk ventures can bring huge profits to venture capital firms. The ability to predict the success of startups is...
Selecting appropriate methodological framework for time series data analysis
June 2018
Economists face method selection problem while working with time series data. As time series data may possess specific properties such as trend and structural break, common methods used to analyze other...
The applications of big data in the insurance industry: A bibliometric and systematic review of relevant literature
November 2023
The insurance industry has changed rapidly over the last few decades. One factor in this change is the continuous growth of massive amounts of data that need to be processed properly to be optimally...
Short-term bitcoin market prediction via machine learning
November 2021
We analyze the predictability of the bitcoin market across prediction horizons ranging from 1 to 60 min. In doing so, we test various machine learning models and find that, while all models outperform...
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...
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...
Machine learning for cryptocurrency market prediction and trading
November 2022
We employ and analyze various machine learning models for daily cryptocurrency market prediction and trading. We train the models to predict binary relative daily market movements of the 100 largest...
CentralBankRoBERTa: A fine-tuned large language model for central bank communications
November 2023
Central bank communications are an important tool for guiding the economy and fulfilling monetary policy goals. Natural language processing (NLP) algorithms have been used to analyze central bank communications....
Symbolic Modeling for financial asset pricing
December 2025
Symbolic Regression is a machine learning technique that discovers an unknown function from its samples. Compared to conventional regression techniques (e.g., linear regression, polynomial regression,...
Machine learning portfolio allocation
November 2022
We find economically and statistically significant gains when using machine learning for portfolio allocation between the market index and risk-free asset. Optimal portfolio rules for time-varying expected...
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...
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...
Financial inclusion, technologies, and worldwide economic development: A spatial Durbin model approach
December 2025
Using panel data from 144 countries, this study constructed an inclusive financial evaluation index and depicted the inclusive finance development worldwide under digital empowerment through classification....
Fintech, financial inclusion, digital currency, and CBDC
November 2023
Dumb money? Social network attention herding, sentiment, and markets
December 2025
Wallstreetbets (WSB) is the perfect echo chamber to study retail investor behaviour and markets. We introduce a direct measure of individual stock attention and the concept of forum-wide attention herding....
Optimal rebalancing strategies reduce market variability
December 2025
The increasing fraction of passive funds influences stock market variability since passive investors behave differently than active investors. We demonstrate via simulations how portfolios that rebalance...
Stock price prediction using support vector regression on daily and up to the minute prices
September 2018
The purpose of predictive stock price systems is to provide abnormal returns for financial market operators and serve as a basis for risk management tools. Although the Efficient Market Hypothesis (EMH)...
Financial news predicts stock market volatility better than close price
June 2018
The behaviour of time series data from financial markets is influenced by a rich mixture of quantitative information from the dynamics of the system, captured in its past behaviour, and qualitative...
CapitalVX: A machine learning model for startup selection and exit prediction
November 2021
Using a big data set of venture capital financing and related startup firms from Crunchbase, this paper develops a machine-learning model called CapitalVX (for “Capital Venture eXchange”) to predict...
End-to-end large portfolio optimization for variance minimization with neural networks through covariance cleaning
December 2026
We develop a rotation-invariant neural network that provides the global minimum-variance portfolio by jointly learning how to lag-transform historical returns and marginal volatilities and how to regularise...
Finding a needle in a haystack: A machine learning framework for anomaly detection in payment systems
December 2025
We propose a flexible machine learning (ML) framework for real-time transaction monitoring in high-value payment systems (HVPS), which are central to a country’s financial infrastructure and integral...
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