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Samuel Tabot Enow
Pág. 197 - 203
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Haika Andrew Mbwambo, Laban Gaspe Letema
Pág. 204 - 211
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Szabolcs Deák, Paul Levine, Joseph Pearlman and Bo Yang
We construct a New Keynesian (NK) behavioural macroeconomic model with bounded-rationality (BR) and heterogeneous agents. We solve and simulate the model using a third-order approximation for a given policy and evaluate its properties using this solution...
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Dean Fantazzini
In this paper, we analyzed a dataset of over 2000 crypto-assets to assess their credit risk by computing their probability of death using the daily range. Unlike conventional low-frequency volatility models that only utilize close-to-close prices, the da...
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Sumathi Kumaraswamy, Yomna Abdulla and Shrikant Krupasindhu Panigrahi
Recurrent stock market fall and rise sequel by COVID-19, rising global inflation, increase in Fed interest rates, the unprecedented meltdown of technology stocks, fear of trade wars, tightening of governments? fiscal policies call for a new trend in inte...
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Daniel Manfre Jaimes, Manuel Zamudio López, Hamidreza Zareipour and Mike Quashie
This paper proposes a new hybrid model to forecast electricity market prices up to four days ahead. The components of the proposed model are combined in two dimensions. First, on the ?vertical? dimension, long short-term memory (LSTM) neural networks and...
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Zdenek Zme?kal, Dana Dluho?ová, Karolina Lisztwanová, Antonín Poncík and Iveta Ratmanová
The paper is focused on predicting the financial performance of a small open economy with an automotive industry with an above-standard share. The paper aims to predict the probability distribution of the decomposed relative economic value-added measure ...
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Yulong Liu, Shuxian Liu and Juepu Chen
Accurate precipitation forecasting is of great significance to social life and economic activities. Due to the influence of various factors such as topography, climate, and altitude, the precipitation in semi-arid and arid areas shows the characteristics...
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Dongsheng Li, Jinfeng Ma, Kaifeng Rao, Xiaoyan Wang, Ruonan Li, Yanzheng Yang and Hua Zheng
Accurate rainfall prediction remains a challenging problem because of the high volatility and complicated essence of atmospheric data. This study proposed a hybrid model (DSP) that combines the advantages of discrete wavelet transform (DWT), support vect...
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Kate Murray, Andrea Rossi, Diego Carraro and Andrea Visentin
Traders and investors are interested in accurately predicting cryptocurrency prices to increase returns and minimize risk. However, due to their uncertainty, volatility, and dynamism, forecasting crypto prices is a challenging time series analysis task. ...
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