Leading indicators for US house prices: New evidence and implications for EU financial risk managers

This study draws on machine learning as a means to causal inference for econometric investigation. We utilize the concept of transfer entropy to examine the relationship between the US National Association of Home Builders Index and the S&P CoreLogic Case-Shiller 20 City Composite Home Price Index (SPCS20). The empirical evidence implies that the survey data can help to predict US house prices. This finding extends the results of Granger causality tests performed by Rodriguez Gonzalez et al. in 2018 using a new machine learning approach that methodologically differs from traditional methods in empirical financial research. © 2021 The Authors. European Financial Management published by John Wiley & Sons Ltd

LuFo V-3 CORINNE - Schlussbericht Comfort Of Ride Improved eNgiNEering -Komfortverbesserung im niederfrequenten Bereich für Hubschrauber

Hubschrauberpiloten sind auch in aktuellen Hubschraubermustern einem hohen Vibrationsniveau ausgesetzt. Diese Vibrationen können negative Auswirkungen auf die Gesundheit und die Leistungsfähigkeit der Hubschrauberbesatzung und der Passagiere haben. Insbesondere Schwingungen im niederfrequenten Bereich standen dabei im Fokus des Verbundprojekts CORINNE. Diese Vibrationen werden u.a. durch Turbulenz angeregt und wirken verstärkt durch Flugregelungssysteme und Autopiloten auf die flugmechanischen Moden des Hubschraubers. Im DLR-Beitrag von CORINNE wurde hauptsächlich an drei Teilaspekten zur Reduzierung der niederfrequenten Vibrationen geforscht. Erstens wurde ein Turbulenzmodell für den Forschungshubschrauber ACT/FHS auf Basis von Flugversuchsdaten erstellt und validiert. Dieses sog. CETI-Modell wurde auch auf andere Hubschraubermuster skaliert. Zusätzlich ist es im ACT/FHS und AVES Simulator verfügbar, um Turbulenz zu simulieren. Zweitens wurde das Simulationsverfahren UPM in das Hubschraubersimulationsmodell von Airbus Helicopters integriert und validiert. Mit diesem Simulationsverfahren können flugmechanische Stabilitätseigenschaften wie die der Phygoide und des Dutch Rolls genauer vorhersagt und die Simulationsgüte im Manöverflug gesteigert werden. Drittens wurde ein Beobachter für die longitudinalen und lateralen Rotormastmomente des ACT/FHS auf Basis von Flugversuchsdaten entwickelt. Der Beobachter benötigt dabei lediglich Messgrößen aus dem stehenden Hubschraubersystem, welche auch auf Serienhubschraubern verfügbar sind. Durch die Integration des Beobachters in die Flugregelung soll der Komfort in turbulenter Luft gesteigert werden

Performance of Survey Forecasts by Professional Analysts: Did the European Debt Crisis Make it Harder or Perhaps Even Easier?

As the future movements of financial time series like the European Central Bank’s benchmark rate are exposed to uncertainty, financial market participants regularly have to rely on professional analysts’ forecasts. Not surprisingly—and for decades already—the quality of survey forecasts has been evaluated, with heterogeneous results. In addition, forecasters’ performance can change through the course of time. This may happen not only due to wrong or inadequate underlying models. Especially in times of financial turmoil or monetary crisis—like the European debt crisis—the interest rate moves made by central bankers may become even harder to predict (at least the direct reaction to the crisis). Because of this, we evaluate the performance of survey forecasts for the three months rate in the Euro zone performed by financial professionals and test for structural breaks to evidence for crisis related changes and the corresponding forecast errors

Leading indicators for US house prices: New Evidence and Implications for EU Financial Risk Managers

This study draws on machine learning as a means to causal inference for econometric investigation. We utilize the concept of transfer entropy to examine the relationship between the US National Association of Home Builders Index and the S&P CoreLogic Case-Shiller 20 City Composite Home Price Index (SPCS20). The empirical evidence implies that the survey data can help to predict US house prices. This finding extends the results of Granger causality tests performed by Rodriguez Gonzalez et al. in 2018 using a new machine learning approach that methodologically differs from traditional methods in empirical financial research. © 2021 The Authors. European Financial Management published by John Wiley & Sons Ltd

Validation of the silicon nanoparticle production on the pilot plant scale via long-term gas-phase synthesis using a microwave plasma reactor

The formation of crystalline silicon nanoparticles by homogeneous gas-phase reactions as a direct way to produce high-purity raw material is applied. For this purpose, a microwave-assisted plasma reactor is used. Goal of this paper is to show the scalability of our process technology from laboratory scale to pilot plant scale while maintaining the particle characteristics. This is demonstrated by producing and analyzing silicon nanoparticles during long-term synthesis in a pilot-scale microwave plasma reactor over a period of six hours. The focus is on a high production rate in conjunction with consistent particle characteristics. A continuous production of the mostly spherical crystalline silicon particles with a count median diameter (CMD) of 23.4 nm and a geometric standard deviation of 1.5 is shown using TEM analysis. The stability of the synthesis process is monitored by means of regular sampling and analyzing batch samples extracted from the process every 30 min. Here it is shown that the CMD varies statistically between 21 and 26 nm. Moreover, the decomposition rate of the precursor was determined to be 99%, while the energy supply remained constant. A constant production rate of about 200 g∙h−1 is shown