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ISSN: 2405-9188

Does one size fit all? Comparing the determinants of the FinTech market segments expansion

The paper aims to indentify and compare the determinants of the overall FinTech market expansion and its major segments – cryptocurrency and peer-to-peer lending markets – in a dataset, which covers...

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What do we learn from stock price reactions to China's first announcement of anti-corruption reforms?

China's markets gained 3.86% around December 4, 2012, when the Party announced anti-corruption reforms. State-owned enterprises (SOEs) with higher past entertainment and travel costs (ETC) gained more....

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Portfolio optimization using cellwise robust association measures and clustering methods with application to highly volatile markets

This paper introduces the minCluster portfolio, which is a portfolio optimization method combining the optimization of downside risk measures, hierarchical clustering and cellwise robustness. Using...

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The great wall of debt: Real estate, political risk, and Chinese local government financing cost

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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The cross-section of Chinese corporate bond returns

We study the relation between bond characteristics and corporate bond returns in China's two distinct and segmented bond markets—the interbank market and the exchange market—with a large cross-sectional...

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Making it into a successful series a funding: An analysis of Crunchbase and LinkedIn data

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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Hedging using reinforcement learning: Contextual k-armed bandit versus Q-learning

The construction of replication strategies for contingent claims in the presence of risk and market friction is a key problem of financial engineering. In real markets, continuous replication, such...

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The applications of big data in the insurance industry: A bibliometric and systematic review of relevant literature

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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Investigating the impact financial content structure has on consumer appreciation: An empirical study of Australian statement of advice documents

This study investigates the impact of financial content structure on consumer appreciation in Australian Statement of Advice (SOA) documents. SOAs are essential for regulatory adherence and consumer...

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Stock pledged loans and market crash risk: Evidence from China

Stock pledged loans have become prevalent among large shareholders of listed firms in China. The largest shareholder pledges a greater fraction of her holdings as collateral for credit when the firm...

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OptionNet: A multiscale residual deep learning model with confidence interval to predict option price

Option is an important financial derivative. Accurate option pricing is essential to the development of financial markets. For option pricing, existing time series models and neural networks are difficult...

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Data-driven estimation of economic indicators with search big data in discontinuous situation

Economic indicators are essential for policymaking and strategic decisions in both the public and private sectors. However, due to delays in the release of government indicators based on macroeconomic...

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Topological tail dependence: Evidence from forecasting realized volatility

This paper proposes a novel theory, coined as Topological Tail Dependence Theory, that links the mathematical theory behind Persistent Homology (PH) and the financial stock market theory. This study...

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Machine learning in classifying bitcoin addresses

The emergence of the Bitcoin cryptocurrency marked a new era of illegal transactions. Cryptocurrency provides some level of anonymity allowing its users to create an unlimited number of wallets with...

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A General Framework for Portfolio Construction Based on Generative Models of Asset Returns

In this paper, we present an integrated approach to portfolio construction and optimization, leveraging high-performance computing capabilities. We first explore diverse pairings of generative model...

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Expert Aggregation for Financial Forecasting

Machine learning algorithms dedicated to financial time series forecasting have gained a lot of interest. But choosing between several algorithms can be challenging, as their estimation accuracy may...

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A Dynamic Partial Equilibrium Model of Capital Gains Taxation

We analyze a multi-period model of capital gains taxation with endogenous prices. Relative to an economy without taxation, a capital gains tax tends to lower prices and increase returns. Abstracting...

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An Analysis of Conditional Mean-Variance Portfolio Performance Using Hierarchical Clustering: Improving Capital Allocation through Time

This paper studies portfolio optimization through improvements of ex-ante conditional covariance estimates. We use the cross-section of stock returns over a 52-year sample to analyze trading performance...

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Asset Allocation Using a Markov Process of Clustered Efficient Frontier Coefficients States

We propose a novel asset allocation model using a Markov process of states defined by clustered efficient frontier coefficients. While most research in Markov models of the market characterize regimes...

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FinLex: An effective use of word embeddings for financial lexicon generation

We present a simple and effective methodology for the generation of lexicons (word lists) that may be used in natural language scoring applications. In particular, in the finance industry, word lists...

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Persistence in factor-based supervised learning models

In this paper, we document the importance of memory in machine learning (ML)-based models relying on firm characteristics for asset pricing. We find that predictive algorithms perform best when they...

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Machine learning portfolio allocation

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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Betting against noisy beta

Strategies that overweight low beta stocks and underweight high beta stocks earn positive alphas. Price noise is known to affect high beta stocks, hence, noise trading can be expected to significantly...

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Performance attribution of machine learning methods for stock returns prediction

We analyze the performance of investable portfolios built using predicted stock returns from machine learning methods and attribute their performance to linear, marginal non-linear and interaction effects....

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Big data, accounting information, and valuation

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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