Emmanouil Sofianos

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• Doctor of Philosophy
• PostDoc Position at University of Strasbourg

This paper aims to forecast deviations of the US output measured by the industrial production index (IPI), from its long-run potential output, known as output gaps. These gaps are important for policymakers when designing relevant economic policies, especially when a negative output gap may show economic slack or underperformance, often associated...

This study aims to forecast New York and Los Angeles gasoline spot prices on a daily frequency. The dataset includes gasoline prices and a big set of 128 other relevant variables spanning the period from 17 February 2004 to 26 March 2022. These variables were fed to three tree-based machine learning algorithms: decision trees, random forest, and XG...

Short Course in Artificial Intelligence and Machine Learning in Greek

In this paper, we use machine learning models to directionally forecast the Bitcoin and implicitly test the Efficient Market Hypothesis. We use technical, asset based and sentiment-based data that are fed to 4 machine learning algorithms. Sentiment analysis is introduced by using data from Google Trends. The frequency of the data used is weekly, sp...

In this study we investigate possible long-range trends in the cryptocurrency market. We employed the Hurst exponent in a sample covering the period from 1 January 2016 to 26 March 2021. We calculated the Hurst exponent in three non-overlapping consecutive windows and in the whole sample. Using these windows, we assessed the dynamic evolution in th...

The Covid-19 crisis, started as an endemic health crisis but it was rapidly transformed to a globalpandemic. As expected, it did not leave the global economy unaffected. The prolonged interruption of the productionactivity and the relevant general lockdowns, led to a significant drop in production, consumption and employment.This rapid deterioratio...

This study aims to forecast spikes in the inflation rate for the US. The data set includes inflation and 35 other relevant variables spanning the period from 2000:1 to 2022:12 in monthly frequency. These variables are fed to three different machine learning methodologies, Support Vector Machines (SVM), Decision Trees (DT) and Random Forests (RF) wi...

In this study we investigate possible long-range trends in the cryptocurrency markets. Our sample includes 37 of the most important cryptocurrencies that reflect more than 80% of the relevant market. For the analysis in the empirical part, we employed the Hurst exponent, a statistical tool used to identify long range autocorrelations and memory in...

Unemployment has a direct impact on public finances and yields serious sociopolitical implications. This study aims to directionally forecast the euro-area unemployment rate. To the best of our knowledge, no other studies forecast the euro-area unemployment rate as a whole. The data set includes the unemployment rate and 36 explanatory variables, a...

The ability to accurately forecast the spot price of natural gas benefits stakeholders and is a valuable tool for all market participants in the competitive gas market. In this paper, we attempt to forecast the natural gas spot price 1, 3, 5, and 10 days ahead using machine learning methods: support vector machines (SVM), regression trees, linear r...

In this paper, we use the Eurozone yield curve in an effort to forecast the deviations of the euro-area output (IPI) from its long-run trend. We use various short- and long-term interest rates spanning the period from 2004:9 to 2020:6 in monthly frequency. The interest rates are fed to three machine learning methodologies: Decision Trees, Random Fo...

In this paper, we use the Eurozone yield curve in an effort to forecast the deviations of the euro-area output (IPI) from its long-run trend. We use various short-and long-term interest rates spanning the period from 2004:9 to 2020:6 in monthly frequency. The interest rates are fed to three machine learning methodologies: Decision Trees, Random For...

The issue of whether or not money affects real economic activity (money neutrality) has attracted significant empirical attention over the last five decades. If money is neutral even in the short-run, then monetary policy is ineffective and its role limited. If money matters, it will be able to forecast real economic activity. In this study, we tes...