Bibliographic record
Abstract
In the IW Financial Expert Survey for the second quarter of 2018 the surveyed experts predict, on average, a steeper yield curve, i.e. a larger increase in the long-term than in the short-term interest rate. Moreover, the average forecasts indicate higher stock market indices, a depreciation of the Euro vis-à-vis the US Dollar, and lower oil prices by the end of the third quarter of 2018. However, despite the expectation of higher interest rates, the short-term interest rate is predicted to remain in negative territory. The 3-month Euribor is, on average, expected to reach -0.31 percent at the end of the third quarter of 2018, while the yield on German government bonds with 10-year maturity is expected to reach 0.81 percent by then. However, the experts do not expect the European Central Bank (ECB) to change the forward guidance of its monetary policy significantly. Stock markets are, on average, expected to increase by 9.2 percent (Stoxx 50) and 8.4 percent (DAX 30) until the end of the third quarter of 2018. During that same period, the experts predict the Euro to depreciate by 2.5 percent vis-à-vis the US Dollar, while oil prices are expected to fall by 7.8 percent. The expectation of an increase in the long rate and a slight increase in the short rate, together with the expected delayed monetary tightening of the ECB, hints at a financial market outlook characterised by a cautious approach to monetary policy normalisation. In this cautious approach, the ECB lets the market determine the first increases in long-term interest rates before it stops intervening at the long end of the yield curve, while keeping the short end of the yield curve lower. This cautious approach to monetary policy normalization is reflected in the projections of the yield curve. Moreover, the experts expect that the development of the Euro and the development of oil prices as well as the development of the stock market will support the ECB's cautious approach to monetary normalization instead of forcing a faster exit from low interest rates. The experts do not expect the ECB to change its forwards guidance in the forthcoming Governing Council meeting. The evaluation of the forecasting performance of the latest forecasts yields the result that Commerzbank and DZ Bank performed best in predicting trends within the long-term ranking, which covers all forecasts from March 2015 to March 2018. DekaBank and Deutsche Bank performed best in the short-term ranking, which covers the surveys for the third and the fourth quarter of 2017 for the 3-months ahead prediction and the survey for the third quarter of 2017 for the 6-month forecasts. When it comes to point prediction, in the long-term evaluation of the period running from March 2015 to March 2018, the experts of National-Bank performed best in predicting all indicators, while the Postbank experts produced the most precise point forecasts for all indicators for the short-term evaluation period.
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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 | 0.003 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.086 | 0.079 |
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".