352 research outputs found
The value of the early unwind option in futures contracts with an endogenous basis
In this paper the implicit early unwind option of a risk neutral arbitrageur is valued. The problem is analyzed in a market microstructure framework where four different groups of market participants interact. Within this model the equilibrium price relationship between stock and futures markets is determined. Since the underlying of the option is influenced by arbitrage trading the underlying of the option depends contrary to standard option pricing theory on the unwind option itself. The non-Markovian stochastic process of the basis is characterized and the results of an extensive comparative static analysis of the option value are presented. --
DAX Index Futures: Mispricing and Arbitrage in German Markets
The paper reports the results of an empirical study of the price relation between the German Performance Stock Index, DAX, and DAX futures. An ex-ante arbitrage strategy based on arbitrage signals is analyzed. The data set contains intraday bid- and ask futures quotes and index values on a minute by minute basis. It is found that the number and persistence of arbitrage opportunities differs considerably for futures nearest to deliver as compared to futures which are not nearest to deliver. The findings suggest that arbitrageurs trade mainly in futures nearest to deliver. The risk associated with arbitrage trading is found to be very small so that arbitrage profits are nearly risk free. --
High Temperature Series Expansions for Spin- and Spin-Phonon-Systems
In this thesis the thermodynamical properties of spin- and spin-phonon-systems are investigated. In the first part of the thesis pure spin-1/2 models are addressed: the dimerized, frustrated chain, the ladder with cyclic exchange, and the two-dimensional Shastry-Sutherland model. The second part presents results for a spin-1/2 system coupled to lattice vibrations, i.e. phonons. By means of high temperature series expansions quantities like the magnetic susceptibility and the specific heat are calculated. These quantities are in most cases easily accessible experimentally. The obtained truncated series have the full dependence of the model parameters. Thus, fitting procedures become a fast and easy task. The coefficients of the truncated series are given as fractions of integers such that no accuracy is lost. The results are exact up to the given order. To improve the representations of the results extrapolation techniques are applied, namely Padé and Dlog-Padé extrapolations. The extrapolations are stabilized in the low temperature region using well-known information on the T=0 and on the low temperature behavior. The extrapolated series expansion results are gauged carefully by investigating their convergence and by comparing them to numerical data obtained from other methods like exact complete diagonalization, quantum Monte-Carlo, and transfer matrix-renormalization group. For the dimerized, frustrated spin system the difficulty is discussed to extract more than two coupling constants from the temperature dependence of the magnetic susceptibility. The ladder system is extended by the inclusion of a four-spin (cyclic) exchange. The impact of this new type of interaction is investigated. Comparison to experimental data of the ladder system SrCu2O3 shows, that the ladder model with a significant but small amount of cyclic exchange can serve as a description of the experimental data just as well as a pure ladder model. The inclusion of cyclic exchange leads to more realistic values for the coupling constants than the values obtained from fitting the ladder model without this type of exchange. The two-dimensional Shastry-Sutherland model has a realization in the compound SrCu2(BO3)2 allowing a detailed comparison between theory and experiment. The three-dimensionality of the substance is explicitly taken into account in the calculations using a mean-field like ansatz for the inter-layer coupling. The extrapolations of the high temperature series data can reproduce the experimental susceptibility data down to very low temperatures. The explicit calculations for the spin-1/2 system coupled to dispersionless phonons are performed using the cluster expansion technique. No cut-off in the phonon subspace is necessary such that the full phonon dynamics are taken into account. The influence of the additional coupling to the phononic degrees of freedom is addressed concerning the magnetic susceptibility and the specific heat
Effective Spin Models for Spin-Phonon Chains by Flow Equations
We investigate the anti-adiabatic limit of an anti-ferromagnetic S=1/2
Heisenberg chain coupled to Einstein phonons. The flow equation method is used
to decouple the spin and the phonon part of the Hamiltonian. In the effective
spin model long range spin-spin interactions are generated. We determine the
phase transition from a gapless state to a gapped (dimerised) phase, which
occurs at a non-zero value of the spin-phonon coupling. In the effective phonon
sector a phonon hardening is observed.Comment: RevTeX, 6 pages, 4 eps figures; final version containing some
clarification
Optimale Arbitragestrategien in Terminmärkten
Der folgende Beitrag analysiert das optimale Verhalten eines Investors, der Arbitrage zwischen Kassa- und Futuresmarkt betreibt. Gegenüber dem Standardmodell der cash & carry-Arbitrage wird der zulässige Strategieraum des Arbitrageurs erweitert, indem berücksichtigt wird, daß der Arbitrageur in der Vergangenheit eingegangene Arbitragepositionen jederzeit vor Fälligkeit glattstellen kann. ; The following article analyses the optimal arbitrage strategy of an investor in the spot and in the futures market. In contrast to the cost of carry model, the arbitrageur is not obliged to hold positions until maturity, but he may unwind arbitrage positions before maturity whenever it is favourable to hirn. --
Der DAX-Future: Kursverhalten und Arbitragemöglichkeiten
Der folgende Beitrag analysiert das Verhalten des DAX-Futures im ersten Jahr seines Bestehens und untersucht insbesondere die Arbitrage-Effizienz dieses neuen Marktes relativ zum Kassamarkt unter Verwendung sämtlicher Transaktionskurse. Dabei zeigt sich, daß die Anzahl. der Arbitragemöglichkeit im Zeitablauf deutlich abnimmt. ; The following article analyses the price behaviour of stock index futures in Germany during the fIrst year of trading. It especially addresses the question of arbitrage efficiency in this new financial rnarket using a cornplete set of transaction data. It can be shown that the number of free lunches in the stock index futures rnarket dramatically decreased. --
Disulfiram, an Option for the Treatment of Pathological Gambling?
Aim: Pathological gambling and comorbid alcohol dependence often occur in combination. Disulfiram is one of the proven drugs for alcohol dependence. In addition to its inhibiting acetaldehyde dehydrogenase, disulfiram inhibits dopamine β-hydroxylase and may thereby increase dopamine and decrease norepinephrine cerebral concentrations. Because there may be common neurochemical substrates and neuronal circuits for pathological gambling and addiction, we wished to explore the effect of disulfiram in gambling. Method: We describe the outcome of a patient with alcohol dependence and pathological gambling treated with disulfiram D. Results: During treatment with disulfiram, the patient reported that his desire to gamble disappeared entirely. Follow-up indicated that he has not gambled for >12 months. Conclusions: Although uncontrolled case observations should be interpreted with caution, disulfiram deserves further investigation in pathological gamblin
Dicer and Hsp104 Function in a Negative Feedback Loop to Confer Robustness to Environmental Stress
SummaryEpigenetic mechanisms can be influenced by environmental cues and thus evoke phenotypic variation. This plasticity can be advantageous for adaptation but also detrimental if not tightly controlled. Although having attracted considerable interest, it remains largely unknown if and how environmental cues such as temperature trigger epigenetic alterations. Using fission yeast, we demonstrate that environmentally induced discontinuous phenotypic variation is buffered by a negative feedback loop that involves the RNase Dicer and the protein disaggregase Hsp104. In the absence of Hsp104, Dicer accumulates in cytoplasmic inclusions and heterochromatin becomes unstable at elevated temperatures, an epigenetic state inherited for many cell divisions after the heat stress. Loss of Dicer leads to toxic aggregation of an exogenous prionogenic protein. Our results highlight the importance of feedback regulation in building epigenetic memory and uncover Hsp104 and Dicer as homeostatic controllers that buffer environmentally induced stochastic epigenetic variation and toxic aggregation of prionogenic proteins
pForest: In-Network Inference with Random Forests
The concept of "self-driving networks" has recently emerged as a possible
solution to manage the ever-growing complexity of modern network
infrastructures. In a self-driving network, network devices adapt their
decisions in real-time by observing network traffic and by performing in-line
inference according to machine learning models. The recent advent of
programmable data planes gives us a unique opportunity to implement this
vision. One open question though is whether these devices are powerful enough
to run such complex tasks?
We answer positively by presenting pForest, a system for performing
in-network inference according to supervised machine learning models on top of
programmable data planes. The key challenge is to design classification models
that fit the constraints of programmable data planes (e.g., no floating points,
no loops, and limited memory) while providing high accuracy. pForest addresses
this challenge in three phases: (i) it optimizes the features selection
according to the capabilities of programmable network devices; (ii) it trains
random forest models tailored for different phases of a flow; and (iii) it
applies these models in real time, on a per-packet basis.
We fully implemented pForest in Python (training), and in P4_16 (inference).
Our evaluation shows that pForest can classify traffic at line rate for
hundreds of thousands of flows, with an accuracy that is on-par with
software-based solutions. We further show the practicality of pForest by
deploying it on existing hardware devices (Barefoot Tofino)
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