TY - GEN A1 - Mondal, Suvendu Sekhar A1 - Bhunia, Asamanjoy A1 - Demeshko, Serhiy A1 - Kelling, Alexandra A1 - Schilde, Uwe A1 - Janiak, Christoph A1 - Holdt, Hans-Jürgen T1 - Synthesis of a Co(II)–imidazolate framework from an anionic linker precursor BT - gas-sorption and magnetic properties N2 - A Co(II)–imidazolate-4-amide-5-imidate based MOF, IFP-5, is synthesized by using an imidazolate anion-based novel ionic liquid as a linker precursor under solvothermal conditions. IFP-5 shows significant amounts of gas (N2, CO2, CH4 and H2) uptake capacities. IFP-5 exhibits an independent high spin Co(II) centre and antiferromagnetic coupling. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 235 KW - building-blocks KW - carbon-dioxide capture KW - exchange KW - ionic liquids KW - ionothermal synthesis KW - ligand KW - metal-organic frameworks KW - solvent KW - surface KW - zeolitic imidazolate frameworks Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-94424 SP - 39 EP - 42 ER - TY - GEN A1 - Lara, Mark J. A1 - Nitze, Ingmar A1 - Grosse, Guido A1 - Martin, Philip A1 - McGuire, A. David T1 - Reduced arctic tundra productivity linked with landform and climate change interactions T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Arctic tundra ecosystems have experienced unprecedented change associated with climate warming over recent decades. Across the Pan-Arctic, vegetation productivity and surface greenness have trended positively over the period of satellite observation. However, since 2011 these trends have slowed considerably, showing signs of browning in many regions. It is unclear what factors are driving this change and which regions/landforms will be most sensitive to future browning. Here we provide evidence linking decadal patterns in arctic greening and browning with regional climate change and local permafrost-driven landscape heterogeneity. We analyzed the spatial variability of decadal-scale trends in surface greenness across the Arctic Coastal Plain of northern Alaska (similar to 60,000 km(2)) using the Landsat archive (1999-2014), in combination with novel 30 m classifications of polygonal tundra and regional watersheds, finding landscape heterogeneity and regional climate change to be the most important factors controlling historical greenness trends. Browning was linked to increased temperature and precipitation, with the exception of young landforms (developed following lake drainage), which will likely continue to green. Spatiotemporal model forecasting suggests carbon uptake potential to be reduced in response to warmer and/or wetter climatic conditions, potentially increasing the net loss of carbon to the atmosphere, at a greater degree than previously expected. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 550 KW - winter warming events KW - permafrost KW - Alaska KW - trends KW - ice KW - CO2 KW - degradation KW - landscapes KW - ecosystem KW - exchange Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-423132 SN - 1866-8372 IS - 550 ER - TY - THES A1 - Gomolka, Johannes T1 - Algorithmic Trading T1 - Algorithmic Trading BT - Analyse von computergesteuerten Prozessen im Wertpapierhandel unter Verwendung der Multifaktorenregression BT - analysis of computer driven processes in securities trading using a multifactor regression model N2 - Die Elektronisierung der Finanzmärkte ist in den letzten Jahren weit vorangeschritten. Praktisch jede Börse verfügt über ein elektronisches Handelssystem. In diesem Kontext beschreibt der Begriff Algorithmic Trading ein Phänomen, bei dem Computerprogramme den Menschen im Wertpapierhandel ersetzen. Sie helfen dabei Investmententscheidungen zu treffen oder Transaktionen durchzuführen. Algorithmic Trading selbst ist dabei nur eine unter vielen Innovationen, welche die Entwicklung des Börsenhandels geprägt haben. Hier sind z.B. die Erfindung der Telegraphie, des Telefons, des FAX oder der elektronische Wertpapierabwicklung zu nennen. Die Frage ist heute nicht mehr, ob Computerprogramme im Börsenhandel eingesetzt werden. Sondern die Frage ist, wo die Grenze zwischen vollautomatischem Börsenhandel (durch Computer) und manuellem Börsenhandel (von Menschen) verläuft. Bei der Erforschung von Algorithmic Trading wird die Wissenschaft mit dem Problem konfrontiert, dass keinerlei Informationen über diese Computerprogramme zugänglich sind. Die Idee dieser Dissertation bestand darin, dieses Problem zu umgehen und Informationen über Algorithmic Trading indirekt aus der Analyse von (Fonds-)Renditen zu extrahieren. Johannes Gomolka untersucht daher die Forschungsfrage, ob sich Aussagen über computergesteuerten Wertpapierhandel (kurz: Algorithmic Trading) aus der Analyse von (Fonds-)Renditen ziehen lassen. Zur Beantwortung dieser Forschungsfrage formuliert der Autor eine neue Definition von Algorithmic Trading und unterscheidet mit Buy-Side und Sell-Side Algorithmic Trading zwei grundlegende Funktionen der Computerprogramme (die Entscheidungs- und die Transaktionsunterstützung). Für seine empirische Untersuchung greift Gomolka auf das Multifaktorenmodell zur Style-Analyse von Fung und Hsieh (1997) zurück. Mit Hilfe dieses Modells ist es möglich, die Zeitreihen von Fondsrenditen in interpretierbare Grundbestandteile zu zerlegen und den einzelnen Regressionsfaktoren eine inhaltliche Bedeutung zuzuordnen. Die Ergebnisse dieser Dissertation zeigen, dass man mit Hilfe der Style-Analyse Aussagen über Algorithmic Trading aus der Analyse von (Fonds-)Renditen machen kann. Die Aussagen sind jedoch keiner technischen Natur, sondern auf die Analyse von Handelsstrategien (Investment-Styles) begrenzt. N2 - During the last decade the electronic trading on the stock exchanges advanced rapidly. Today almost every exchange is running an electronic trading system. In this context the term algorithmic trading describes a phenomenon, where computer programs are replacing the human trader, when making investment decisions or facilitating transactions. Algorithmic trading itself stands in a row of many other innovations that helped to develop the financial markets technologically (see for example telegraphy, the telephone, FAX or electronic settlement). Today the question is not, whether computer programs are used or not. The question arising is rather, where the border between automatic, computer driven and human trading can be drawn. Conducting research on algorithmic trading confronts scientists always with the problem of limited availability of information. The idea of this dissertation is to circumnavigate this problem and to extract information indirectly from an analysis of a time series of (fund)-returns data. The research question here is: Is it possible to draw conclusions about algorithmic trading from an analysis of (funds-)return data? To answer this question, the author develops a complete definition of algorithmic trading. He differentiates between Buy-Side and Sell-Side algorithmic trading, depending on the functions of the computer programs (supporting investment-decisions or transaction management). Further, the author applies the multifactor model of the style analysis, formely introduced by Fung and Hsieh (1997). The multifactor model allows to separate fund returns into regression factors that can be attributed to different reasons. The results of this dissertation do show that it is possible to draw conclusions about algorithmic trading out of the analysis of funds returns. Yet these conclusions cannot be of technical nature. They rather have to be attributed to investment strategies (investment styles). KW - Algorithmic Trading KW - Software KW - Börse KW - Computer KW - Wertpapierhandel KW - Black Box KW - Neuronale Netze KW - Handelssystem KW - Hedge Fonds KW - algorithmic trading KW - software KW - exchange KW - computer driven trading KW - black box KW - hedge funds KW - electronic KW - low latency Y1 - 2011 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-51009 SN - 978-3-86956-125-7 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - GEN A1 - Hoffmann, Mathias A1 - Schulz-Hanke, Maximilian A1 - Alba, Juana Garcia A1 - Jurisch, Nicole A1 - Hagemann, Ulrike A1 - Sachs, Torsten A1 - Sommer, Michael A1 - Augustin, Jürgen T1 - A simple calculation algorithm to separate high-resolution CH4 flux measurements into ebullition- and diffusion-derived components T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Processes driving the production, transformation and transport of methane (CH4) in wetland ecosystems are highly complex. We present a simple calculation algorithm to separate open-water CH4 fluxes measured with automatic chambers into diffusion- and ebullition-derived components. This helps to reveal underlying dynamics, to identify potential environmental drivers and, thus, to calculate reliable CH4 emission estimates. The flux separation is based on identification of ebullition-related sudden concentration changes during single measurements. Therefore, a variable ebullition filter is applied, using the lower and upper quartile and the interquartile range (IQR). Automation of data processing is achieved by using an established R script, adjusted for the purpose of CH4 flux calculation. The algorithm was validated by performing a laboratory experiment and tested using flux measurement data (July to September 2013) from a former fen grassland site, which converted into a shallow lake as a result of rewetting. Ebullition and diffusion contributed equally (46 and 55 %) to total CH4 emissions, which is comparable to ratios given in the literature. Moreover, the separation algorithm revealed a concealed shift in the diurnal trend of diffusive fluxes throughout the measurement period. The water temperature gradient was identified as one of the major drivers of diffusive CH4 emissions, whereas no significant driver was found in the case of erratic CH4 ebullition events. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 604 KW - water methane emissions KW - chamber system KW - CO2 KW - lake KW - fen KW - exchange KW - mechanism KW - turbulence KW - transport KW - reservior Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-416659 SN - 1866-8372 IS - 604 SP - 109 EP - 118 ER -