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Engineering sciences. Technology --- Personnel management --- Career --- Technology sector --- CD --- Belgium

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Sociology of occupations --- Engineering sciences. Technology --- Sexual division of labour --- Technology sector --- Book --- France

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Teaching --- Engineering sciences. Technology --- History --- History --- Education --- Technology sector --- Book --- Netherlands

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This thesis investigates whether the real economy continues to provide predictive signals for
technology stock returns in U.S. companies during the digital era and economic crises. The study
updates and extends previous research by focusing on modern economic indicators and their
forecasting power amidst the evolving market landscape influenced by technological advancements
and recent economic disruptions.
The research explores the viability of historical economic indicators in forecasting stock returns,
particularly in the U.S. technology sector. It questions whether these indicators, which proved useful
in past decades, still hold predictive power in a radically transformed economic and technological
environment.
The thesis adopts a mixed-methods approach, combining quantitative analyses with econometric
modelling. The data spans several decades, focusing on periods marked by significant economic events,
such as the dot-com bubble, the 2008 financial crisis, and the COVID-19 pandemic, to assess the
robustness of forecasting models under different economic conditions.
The study replicates and extends previous methodologies using RStudio, allowing for a comparison
between past and current forecasting abilities of various economic indicators under different
economic conditions. Leveraging Google Colab and Python, the thesis incorporates machine learning
techniques to examine the predictive power of traditional and newly proposed economic indicators.
This analysis aims to uncover complex nonlinear relationships that might be missed by conventional
econometric models.
The findings suggest that the traditional indicators have diminished in predictive power. The discussion
delves into the implications of the findings for investors and policymakers, emphasising the need for
adaptive strategies that account for the rapid technological changes and their impact on the economic
landscape. The thesis concludes that the real economy continues to provide valuable insights into
technology stock returns, even if the predictive power has diminished. It calls for ongoing research to
refine these indicators and adapt forecasting models to the changing economic and technological
environment.
Suggestions for future research include exploring additional digital economy indicators and extending
the analysis to global technology markets to validate the findings and enhance the generalizability of
the forecasting models. This study contributes to the literature by updating forecasting models with
contemporary economic indicators and by demonstrating the evolving relationship between the real
economy and technology stock returns in the face of digital transformation and economic crises.

equity premium --- real economy --- technology sector --- Sciences économiques & de gestion > Finance

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Het beleid van de Nederlandse overheid is erop gericht om het aantal meisjes/vrouwen in technische opleidingen en technische beroepen te vergroten. In dit eindrapport wordt nagegaan welke knelpunten meisjes/vrouwen ondervinden tijdens het traject onderwijs-arbeidsmarkt. De bestaande projecten worden geanalyseerd ten einde de inzet en effectiviteit van de beleidsinstrumenten te beoordelen.

Sociology of occupations --- Social policy --- Teaching --- Technical, artistic and vocational education --- Education --- Government policy --- Technical education --- Technology sector --- Book --- Netherlands