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...
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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...
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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...
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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...
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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...
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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...
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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....
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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...
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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)...
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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...
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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...
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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,...
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Forecasting earnings and returns: A review of recent advancements
November 2022
We selectively review recent advancements in research on predictive models of earnings and returns. We discuss why applying statistical, econometric, and machine learning advancements to forecasting...
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The great wall of debt: Real estate, political risk, and Chinese local government financing cost
November 2023
Chengtou bond is the only asset with market prices that can capture the funding cost of Chinese local government debt. In contrast to the U.S. municipal bonds, Chengtou bonds are issued by private corporations...
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Fintech, financial inclusion, digital currency, and CBDC
November 2023
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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...
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Big data, accounting information, and valuation
November 2022
This paper reviews research that uses big data and/or machine learning methods to provide insight relevant for equity valuation. Given the huge volume of research in this area, the review focuses on...
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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...
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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...
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An overview on data representation learning: From traditional feature learning to recent deep learning
December 2016
Since about 100 years ago, to learn the intrinsic structure of data, many representation learning approaches have been proposed, either linear or nonlinear, either supervised or unsupervised, either...
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Reinforcement prompting for financial synthetic data generation
December 2024
The emergence of Large Language Models (LLMs) has unlocked unprecedented potential for comprehending and generating human-like text, fueling advances in the finance domain – a tool that can shape investment...
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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...
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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...
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Predicting bitcoin returns using high-dimensional technical indicators
September 2019
There has been much debate about whether returns on financial assets, such as stock returns or commodity returns, are predictable; however, few studies have investigated cryptocurrency return predictability....
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A hybrid stock trading framework integrating technical analysis with machine learning techniques
March 2016
In this paper, a novel decision support system using a computational efficient functional link artificial neural network (CEFLANN) and a set of rules is proposed to generate the trading decisions more...
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