Winners-minus-adjusted-losers: optimizing momentum payoffs

While being considered one of the most pervasive and return-promising anomalies across various asset classes Momentum has strained investors with extreme crashes in the past. A proposed ex-ante implementable strategy based on key-findings in the available literature about the characteristics, patterns and predictability of Momentum crashes more than doubles the Sharpe ratio of conventional Momentum. More importantly it significantly reduces the crash risk by adjusting the exposure to those stocks being mostly responsible for these crashes. The strategy yields positive results during a period from 1964 to 2018 and has been tested in various subsamples

Explaining heatwaves with machine learning

Heatwaves are known to arise from the interplay between large-scale climate variability, synoptic weather patterns and regional to local scale surface processes. While recent research has made important progress for each individual contributing factor, ways to properly incorporate multiple or all of them in a unified analysis are still lacking. In this study, we consider a wide range of possible predictor variables from the ERA5 reanalysis, and ask, how much information on heatwave occurrence in Europe can be learned from each of them. To simplify the problem, we first adapt the recently developed logistic principal component analysis to the task of compressing large binary heatwave fields to a small number of interpretable principal components. The relationships between heatwaves and various climate variables can then be learned by a neural network. Starting from the simple notion that the importance of a variable is given by its impact on the performance of our statistical model, we arrive naturally at the definition of Shapley values. Classic results of game theory show that this is the only fair way of distributing the overall success of a model among its inputs. With this approach, we find a non-linear model that explains 70% of reduced heatwave variability, 27% of which are due to upper level geopotential while top level soil moisture contributes 15% of the overall score. In addition, Shapley interaction values enable us to quantify overlapping information and positive synergies between all pairs of predictors

PHYSICAL MODEL OF SI-ENGINE PROCESS AND GAS EXCHANGE FOR REAL-TIME IMPLEMENTATION IN ENGINE MANAGEMENT SYSTEM

This paper presents a physical, crank angle resolved model of spark ignited (SI) engine process and gas exchange developed by Continental AG for real‐time engine management system. Transient 1D flow in pipe systems is the most time‐consuming part of the numerical solution. A so‐called detailed model, including intake and exhaust pipe components, is defined and reduced to its fast‐running version where pipes are neglected. Experimental validation confirms that the detailed model captures transient effects and fulfills accuracy targets over the entire engine operation range, while the fast‐running model requires additional empirical parameterization. Both models, however, provide more detailed information on dynamic gas exchange process and the in‐cylinder state for each individual engine cycle than today’s data driven models do (e.g., transient gas states and internal engine exhaust gas recirculation). Finally, simplifications according to classical acoustic theory are proposed for pipe components to solve the conflict between accuracy and real‐time capability.Tento článek prezentuje fyzikální model čtyřdobého procesu a výplachu zážehového spalovacího motoru. Model byl vyvinut u Continental AG pro účely sériových řídících jednotek. Nestacionární 1D proudění v potrubních systémech je časově nejnáročnější součástí numerického řešení. Proto je nejprve definován podrobný model, zahrnující řešení sacích a výfukových potrubí, který je dále zjednodušen na rychle fungující verzi se zanedbáním zákona zachování impulsu v potrubních systémech. Experimentální ověření potvrzuje, že podrobný model zachycuje přechodové jevy a splňuje cíle přesnosti v celém rozsahu provozu motoru, zatímco zjednodušený model vyžaduje další empirickou parametrizaci. Oba modely však poskytují podrobnější informace o výplachu a termodynamickém stavu ve válcích než to činí běžné datově orientované modely (např. přechodné stavy plynu, nebo vnitřní recirkulace výfukových plynů motoru). Nakonec jsou navržena zjednodušení řešení proudění v potrubích podle klasické akustické teorie s cílem vyřešení rozporu mezi přesností a schopností dosáhnout řešení v reálném čase na daném hardwaru (ECU 240 MHz)

Ubiquitination and Ubiquitin-Like Modifications in Multiple Myeloma: Biology and Therapy

Multiple myeloma is a genetically heterogeneous plasma cell malignancy characterized by organ damage and a massive production of (in-)complete monoclonal antibodies. Coping with protein homeostasis and post-translational regulation is therefore essential for multiple myeloma cells to survive. Furthermore, post-translational modifications such as ubiquitination and SUMOylation play key roles in essential pathways in multiple myeloma, including NFκB signaling, epigenetic regulation, as well as DNA damage repair. Drugs modulating the ubiquitin-proteasome system, such as proteasome inhibitors and thalidomide analogs, are approved and highly effective drugs in multiple myeloma. In this review, we focus on ubiquitin and ubiquitin-like modifications in the biology and current developments of new treatments for multiple myeloma