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A logarithmic market scoring rule agent-based model to evaluate prediction markets
Prediction Markets (PMs) are markets in which agents trade event contingent assets. Enterprises use PMs to forecast revenues and project deadlines....
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Portfolio Optimization with Prediction-Based Return Using Long Short-Term Memory Neural Networks: Testing on Upward and Downward European Markets
In recent years, artificial intelligence has helped to improve processes and performance in many different areas: in the field of portfolio...
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Uncertainty index and stock volatility prediction: evidence from international markets
This study investigates the predictability of a fixed uncertainty index (UI) for realized variances (volatility) in the international stock markets...
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Financial Fragility in Emerging Markets: Examining the Innovative Applications of Machine Learning Design Methods
Emerging economies, while exhibiting higher growth rates compared to developed countries, are susceptible to external shocks, leading to financial...
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Spillover effects of carbon, energy, and stock markets considering economic policy uncertainty
This paper uses a two-regime Markov-switching GARCH model to illustrate that the state-switching of returns in the EU carbon market and its...
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Spillover effect among independent carbon markets: evidence from China’s carbon markets
Carbon pricing is one of the key policy tools in the green recovery of the post-COVID-19 era. As linkages among ETSs worldwide are future trend, the...
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High-Frequency Trading in Bond Returns: A Comparison Across Alternative Methods and Fixed-Income Markets
A properly performing and efficient bond market is widely considered important for the smooth functioning of trading systems in general. An important...
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From the East-European Regional Day-Ahead Markets to a Global Electricity Market
The so-called black swans, COVID-19 and the invasion in Ukraine, have led to an unprecedented increase in electricity prices. Since 2021, after...
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Do artificial neural networks provide improved volatility forecasts: Evidence from Asian markets
This paper enters the ongoing volatility forecasting debate by examining the ability of a wide range of Machine Learning methods (ML), and...
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COVID-19 Impact on Stock Markets: A Multiscale Event Analysis Perspective
The existing literature primarily examined the impact of unexpected events on the stock market at a single scale, posing the challenge of a lack of...
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Long memory in volatility in foreign exchange markets: evidence from selected countries in Africa
This study examines the long memory properties in the volatility of the foreign exchange markets of Egypt, Ghana, Kenya, Nigeria and South Africa....
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Green or grey stocks? Dynamic effects of carbon markets based on Chinese practices
Carbon trading and new energy markets are two key mechanisms for carbon reduction. However, theoretical analysis cannot reveal the complex links...
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Quantile coherency of futures prices in palm and soybean oil markets
The objective of the present work is to investigate the contemporaneous price co-movement in the futures markets of soybean and palm oil. This is...
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Global liquidity effect of quantitative easing on emerging markets
Using a panel quantile vector autoregression model, we investigate the global liquidity effect of quantitative easing (QE) in the US on emerging...
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Improving Quantile Forecasts via Realized Double Hysteretic GARCH Model in Stock Markets
This research introduces a realized double hysteretic GARCH (R-dhGARCH) model with a skew Student’s t distribution designed to improve quantile...
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Efficient Markets
In the earliest descriptions of the efficient markets hypothesis asset prices were modelled as a martingale. A martingale is a stochastic process...
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The nexus between the volatility of Bitcoin, gold, and American stock markets during the COVID-19 pandemic: evidence from VAR-DCC-EGARCH and ANN models
The spread of the coronavirus has reduced the value of stock indexes, depressed energy and metals commodities prices including oil, and caused...
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The Dynamic Relationship Between Gas and Crude Oil Markets and the Causal Impact of US Shale Gas
Although the recent debate in energy economics on the importance of oil price indexation versus shale gases suggest that big data can be used in...
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Commodity markets and the global macroeconomy: evidence from machine learning and GVAR
Based on a strongly data-intensive machine learning approach, this study first identifies the most essential globally traded commodities in view of...
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The Markets of Truth
The production and the power structures of academic knowledge and truth have been widely scrutinized by Michel Foucault and his followers. Less...