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Industrial production over the business cycle 1919–2022: R/S and wavelet hurst analysis of multifractality and Austrian business cycle theory
The U.S. index of industrial production is examined for multifractal long memory over business cycle expansions and recessions from 1919 to 2022....
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A Comprehensive Study of Market Prediction from Efficient Market Hypothesis up to Late Intelligent Market Prediction Approaches
This paper has scrutinized the process of testing market efficiency, data generation process and the feasibility of market prediction with a...
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Benchmarking econometric and machine learning methodologies in nowcasting GDP
Nowcasting can play a key role in giving policymakers timelier insight to data published with a significant time lag, such as final GDP figures....
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Modeling Bitcoin Prices using Signal Processing Methods, Bayesian Optimization, and Deep Neural Networks
Bitcoin is a volatile financial asset that runs on a decentralized peer-to-peer Blockchain network. Investors need accurate price forecasts to...
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Develo** Hybrid Deep Learning Models for Stock Price Prediction Using Enhanced Twitter Sentiment Score and Technical Indicators
In recent years, there has been growing interest in using deep learning methods to improve the accuracy of stock price prediction, which has always...
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Strategic Studies in Develo** Countries
In the classical sense, strategy is an effort to get rid of uncertainty, a long term policy planning based on realistic evaluation, solid resources...
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Going a Step Deeper Down the Rabbit Hole: Deep Learning Model to Measure the Size of the Unregistered Economy Activity
Accurately estimating the size of unregistered economies is crucial for informed policymaking and economic analysis. However, many studies seem to...
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Volatility Spillovers and Contagion During Major Crises: An Early Warning Approach Based on a Deep Learning Model
This paper contributes to the ongoing debate on the nature and characteristics of the volatility transmission channels of major crash events in...
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Long-Term Interest Rates, the Yield Curve, and Hyperinflation
This chapter introduces the role of intertemporal expectations into our analysis. Effects of current and expected inflation on long-term interest...
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Cycles and Long-Range Behaviour in the European Stock Markets
This paper uses a modelling framework which includes two singularities (or poles) in the spectral density function, one corresponding to the long-run...
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LSTM–GARCH Hybrid Model for the Prediction of Volatility in Cryptocurrency Portfolios
In the present work, the volatility of the leading cryptocurrencies is predicted through generalised autoregressive conditional heteroskedasticity...
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Steel price index forecasting through neural networks: the composite index, long products, flat products, and rolled products
Forecasting commodity prices is a vital issue to a wide spectrum of market participants and policy makers in the metal sector. In this work, the...
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Does the Green Economy Influence Environmental Sustainability? Nexus Between Staple Food Crops Consumption and Total Factor Productivity
The investigation has examined the current state of grain productivity, using statistics concerning farm inputs and Pakistan’s major grain crops. The...
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Forecasting relative returns for S&P 500 stocks using machine learning
Forecasting changes in stock prices is extremely challenging given that numerous factors cause these prices to fluctuate. The random walk hypothesis...
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Optimal Filter Approximations for Latent Long Memory Stochastic Volatility
Estimating volatility is a challenging because it is latent, and proxies may not be efficient. Alternative to using the proxies in the conventional...
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Predicting Cryptocurrency Price Returns by Using Deep Learning Model of Technical Analysis Indicators
Over the last few years, cryptocurrencies have become a new alternative exchange currency for the global economy. Due to the high volatility in the...
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Forecasting the Stock Market Index with Dynamic ARIMA Model and LSTM Model
With the development of the machine learning method, there are a lot more time series model being invented and applied to mimic the real-world data....
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Comparative analysis of deep-learning-based models for hourly bus passenger flow forecasting
An efficient transportation system is conducive to maintaining traffic flow and safety. Passenger flow forecasting (PFF), an area of traffic...
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Bitcoin Price Prediction Using Sentiment Analysis and Empirical Mode Decomposition
Cryptocurrencies have garnered significant attention recently due to widespread investments. Additionally, researchers have increasingly turned to...
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Statistical Evaluation of Deep Learning Models for Stock Return Forecasting
Artificial intelligence applications, including algorithmic training, portfolio allocation, and stock return forecasting in the financial industry,...
