Optimal Order Scheduling for Deterministic Liquidity Patterns

We consider a broker who has to place a large order which consumes a sizable part of average daily trading volume. The broker's aim is thus to minimize execution costs he incurs from the adverse impact of his trades on market prices. By contrast to the previous literature, see, e.g., Obizhaeva and Wang (2005), Predoiu, Shaikhet, and Shreve (2011), we allow the liquidity parameters of market depth and resilience to vary deterministically over the course of the trading period. The resulting singular optimal control problem is shown to be tractable by methods from convex analysis and, under minimal assumptions, we construct an explicit solution to the scheduling problem in terms of some concave envelope of the resilience adjusted market depth

Optimal execution strategies in limit order books with general shape functions

We consider optimal execution strategies for block market orders placed in a limit order book (LOB). We build on the resilience model proposed by Obizhaeva and Wang (2005) but allow for a general shape of the LOB defined via a given density function. Thus, we can allow for empirically observed LOB shapes and obtain a nonlinear price impact of market orders. We distinguish two possibilities for modeling the resilience of the LOB after a large market order: the exponential recovery of the number of limit orders, i.e., of the volume of the LOB, or the exponential recovery of the bid-ask spread. We consider both of these resilience modes and, in each case, derive explicit optimal execution strategies in discrete time. Applying our results to a block-shaped LOB, we obtain a new closed-form representation for the optimal strategy, which explicitly solves the recursive scheme given in Obizhaeva and Wang (2005). We also provide some evidence for the robustness of optimal strategies with respect to the choice of the shape function and the resilience-type

COVID-19-Pandemie führte zu starkem Rückgang von darmpathogenen Erregern

Im Zuge der im März 2020 zur Bewältigung der COVID-19-Pandemie ergriffenen Infektionsschutzmaßnahmen wurde nicht nur ein abrupter Rückgang von Atemwegserkrankungen beobachtet, sondern im Verlauf des Jahres auch ein in diesem Maße nicht erwarteter Rückgang von bakteriellen Enteritiden. Abgebildet wurde dieser Trend durch die erfassten Fallzahlen im Meldesystem gemäß Infektionsschutzgesetz. Trotz einer geringeren Anzahl von Erkrankungsfällen bzw. Einsendungen konnte das Nationale Referenzzentrum für Salmonellen und andere bakterielle Enteritiserreger die integrierte molekulare Surveillance von ausgewählten lebensmittelbedingten darmpathogenen Infektionserregern (S. enterica, EHEC, L. monocytogenes, Shigella und Campylobacter) erfolgreich fortführen und ausbauen.Peer Reviewe

Genome‑wide insights into population structure and host specifcity of Campylobacter jejuni

The zoonotic pathogen Campylobacter jejuni is among the leading causes of foodborne diseases worldwide. While C. jejuni colonises many wild animals and livestock, persistence mechanisms enabling the bacterium to adapt to host species' guts are not fully understood. In order to identify putative determinants influencing host preferences of distinct lineages, bootstrapping based on stratified random sampling combined with a k-mer-based genome-wide association was conducted on 490 genomes from diverse origins in Germany and Canada. We show a strong association of both the core and the accessory genome characteristics with distinct host animal species, indicating multiple adaptive trajectories defining the evolution of C. jejuni lifestyle preferences in different ecosystems. Here, we demonstrate that adaptation towards a specific host niche ecology is most likely a long evolutionary and multifactorial process, expressed by gene absence or presence and allele variations of core genes. Several host-specific allelic variants from different phylogenetic backgrounds, including dnaE, rpoB, ftsX or pycB play important roles for genome maintenance and metabolic pathways. Thus, variants of genes important for C. jejuni to cope with specific ecological niches or hosts may be useful markers for both surveillance and future pathogen intervention strategies.Peer Reviewe

Outbreaks of virulent diarrheagenic Escherichia coli - are we in control?

Shiga toxin-producing Escherichia coli (STEC) are the most virulent diarrheagenic E. coli known to date. They can be spread with alarming ease via food as exemplified by a large sprout-borne outbreak of STEC O104:H4 in 2011 that was centered in northern Germany and affected several countries. Effective control of such outbreaks is an important public health task and necessitates early outbreak detection, fast identification of the outbreak vehicle and immediate removal of the suspected food from the market, flanked by consumer advice and measures to prevent secondary spread

Optimale Handelsausführung mit stochastischer Liquidität

In klassischen Finanzmarktmodellen wird davon ausgegangen, dass Preise nicht davon abhängen, wie viel gehandelt wird. In Wirklichkeit sind Märkte jedoch illiquide, so dass die eigene Handelsstrategie den Preis nachteilig beeinflusst. In der vorliegenden Arbeit wird dieser Preiseinfluss durch ein Modell eines Orderbuchs einer elektronischen Börsenplattform beschrieben. Unter Verwendung dieses Modells betrachten wir das Problem eines institutionellen Investors, der eine große Aktienposition in vorgegebener Zeit kaufen möchte. Gesucht ist die optimale Zerlegung der Order, so dass die gesamten erwarteten Preiseinflusskosten minimiert werden. Wir formulieren diese Fragestellung des Investors als singuläres Kontrollproblem mit drei Zustandsvariablen. Verglichen zu vorhandener Literatur liegt unser Hauptaugenmerk auf der sich zeitlich ändernden Liquidität im Orderbuch. Dies erlaubt uns zu beschreiben, wie der Investor sich in Zeiten relativ hoher bzw. niedriger Liquidität verhalten sollte. Zunächst behandeln wir den deterministischen Fall, wo wir das Liquiditätsprofil am Anfang des Zeithorizonts fixieren. Wie erwartet lässt sich der Zustandsraum in eine Kauf- und Warteregion zerlegen. In diskreter Zeit können wir per Induktion nachweisen, dass die Struktur dieser Regionen besonders intuitiv ist. In stetiger Zeit lässt sich die Existenz optimaler Strategien zeigen und somit unser Resultat aus diskreter zu stetiger Zeit überführen. In einigen Situationen können wir schließlich explizite Lösungen unseres Optimierungsproblems angeben. Im Anschluss betrachten wir den Fall stochastischer Liquidität, so dass optimale Strategien sich der Liquiditätsentwicklung anpassen. Es stellt sich als schwierig heraus, dass unsere Kostenfunktion nicht in allen Fällen konvex in der Strategie des Investors ist. Sobald wir diese Konvexität erzwingen, folgt die Eindeutigkeit optimaler Strategien unmittelbar. Gleichzeitig können wir aber auch die Existenz optimaler Strategien zeigen und wiederum das gewünschte Strukturresultat für die Kauf- und Warteregion sicherstellen. Darüber hinaus lassen sich nicht konvexe Fälle stochastischer Liquidität angeben, die das Strukturresultat verletzen. Zu guter Letzt leiten wir durch Näherung der Zustandsvariablen durch kontrollierte Markovketten ein numerisches Schema her und beweisen dessen Konvergenz. Auf diese Weise können wir die Wertfunktion und die zugehörigen optimalen Strategien näherungsweise berechnen.Classical models in mathematical finance assume that an arbitrary amount of assets can be traded at the current market price. But in reality, markets are illiquid such that trading does have an adverse price impact. In this thesis, this price dependence on trading strategies is described by a model of a limit order book which is relevant in exchange electronic trading systems. Using this model, we consider a large investor who wants to purchase a given amount of shares over a fixed interval of time. We look for the optimal trading schedule such that the total expected costs due to the adverse price impact are minimized. We phrase this optimal execution task of the large investor as a singular control problem with three state dimensions. Compared to the existing literature, our focus is on time-varying liquidity in the limit order book. This allows us to derive how the large investor should trade in periods of comparatively high or low liquidity. We first treat the deterministic case, where we fix the liquidity profile at the initial time. As one would expect, the state space separates into a no-trading and a trading region. In discrete time, the structure of these regions is found to be particularly intuitive. Together with the fact that we can prove the existence of optimal strategies in continuous time, we can transfer our results from discrete to continuous time. We derive closed-form solution under appropriate conditions. We go ahead by considering the stochastic liquidity case, where optimal trading strategies react to the liquidity available in the market. A major difficulty is that our cost function may not be convex in the strategies. Enforcing this convexity, uniqueness follows immediately, but we are additionally able to conclude the existence of optimal strategies and again derive convenient structural results concerning the no-trading and trading region. We also construct non-convex stochastic liquidity cases where these structural results fail. Finally, we establish a convergent numerical scheme which allows us to compute the value function and optimal strategies by approximating the state space variables by a controlled Markov chain

Genome-based Salmonella serotyping as the new gold standard

Salmonella enterica is the second most reported bacterial cause of food-borne infections in Europe. Therefore molecular surveillance activities based on pathogen subtyping are an important measure of controlling Salmonellosis by public health agencies. In Germany, at the federal level, this work is carried out by the National Reference Center for Salmonella and other Bacterial Enteric Pathogens (NRC). With rise of next generation sequencing techniques, the NRC has introduced whole-genome-based typing methods for S. enterica in 2016. In this study we report on the feasibility of genome-based in silico serotyping in the German setting using raw sequence reads. We found that SeqSero and seven gene MLST showed 98% and 95% concordance, respectively, with classical serotyping for the here evaluated serotypes, including the most common German serotypes S. Enteritidis and S. Typhimurium as well as less frequently found serotypes. The level of concordance increased to >99% when the results of both in silico methods were combined. However, both tools exhibited misidentification of monophasic variants, in particular monophasic S. Typhimurium and therefore need to be fine-tuned for reliable detection of this epidemiologically important variant. We conclude that with adjustments Salmonella genome-based serotyping might become the new gold standard

Whole genome-based public health surveillance of less common STEC serovars and untypable strains identifies four novel O genotypes

Shiga toxin-producing E. coli (STEC) and the subgroup of enterohemorrhagic E. coli cause intestinal infections with symptoms ranging from watery diarrhea to hemolytic uremic syndrome (HUS). A key tool for epidemiological differentiation of STEC is serotyping. The serotype in combination with the main virulence determinants gives an important insight into the virulence potential of a strain. However, a larger fraction of STEC found in human disease, including strains causing HUS, belongs to less frequently detected STEC serovars or their O/H antigens are unknown or even untypable. Recent implementation of whole genome sequence (WGS) analysis in principal allows the deduction of serovar and virulence gene information. Therefore we here compared classical serovar and PCR-based virulence marker detection with WGS-based methods for 232 STEC strains focusing on less frequently detected STEC serovars and non-typable strains. We found that WGS-based extraction showed a very high degree of overlap with the more classical methods. Specifically, concordance was 97% for O antigens (OAGs) and 99% for H antigens (HAGs) of typable strains and > 99% concerning stx1/2 or eaeA for all strains. 98% of non-typable OAGs and 100% of non-typable HAGs were defined by WGS analysis. In addition, the novel methods enabled a more complete analysis of strains causing severe clinical symptoms and the description of four novel STEC OAG loci. In conclusion, WGS is a promising tool for gaining serovar and virulence gene information especially from a public health perspective.Peer Reviewe

Intensivierte genombasierte Surveillance von Campylobacter-Isolaten humaner Erkrankungsfälle in Deutschland

Campylobacter ist ein wichtiger Infektionserreger des Menschen und die Campylobacteriose stellt die häufigste meldepflichtige bakterielle Zoonose in Europa dar. In Deutschland werden jährlich ca. 60.000 Erkrankungsfälle gemeldet. Als Infektionsquellen werden hauptsächlich kontaminierte tierische Lebensmittel ermittelt oder vermutet. Die Infektion ist typi¬scherweise selbstlimitierend und auf den Gastrointestinaltrakt beschränkt. Seit 2019 gibt es am Nationalen Referenzzentrum für Salmonellen und andere bakterielle Enteritiserreger am RKI eine intensivierte molekulare Surveil-lance von Campylobacter aus menschlichen Infektio¬nen in Deutschland, deren vorrangiges Ziel die erweiterte Akquise von Isolaten mit epidemiologischen Basisdaten ist. So sollen die Repräsentativität der Einsendungen bewertet und die Er¬reger möglichst bis hin zur Genomebene untersucht werden.Peer Reviewe