Bibliographic record
Abstract
The goal of this diploma thesis is to take an insight into the world of investment during unstable economic times based on the example of the selected country, Germany. The thesis seeks to analyze the performance of five different investment options, real estate, REIT, Stock market, Gold and Bitcoin, and compare them, while identifying the most important macroeconomic factors influencing the value of the investment options. The methodology of the diploma thesis is represented by a time series analysis based on the time period between the first quarter of 2000 and the first quarter of 2023. Additionally, the technique of econometric estimation is applied, where, in total, six models are created. In the end, it is concluded that gold is the most superior investment choice, while the least attractive one is the REIT Index, representing indirect real estate investment due to its relatively unstable nature and unpredictability. JEL Classification J11, R30, D81, G11, E27 Keywords Real Estate, COVID-19, Investment, REIT, Stock Index, Gold, Bitcoin, Economic Recessions, Germany, Portfolio, Risk Title Comparison of Different Investment Opportunities during Unstable Times
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".