Long-Run Cash-Flow and Discount-Rate Risks in the Cross-Section of US Returns

This paper decomposes the overall market beta of common stocks into four parts reflecting uncertainty related to the long-run dynamics of stock- specific and market-wide cash flows and discount rates. We employ a discrete time version of Merton’s Intertemporal CAPM to test whether these four sources of risk command different risk prices. The model performs well in pricing average returns on single- and double-sorted portfolios according to size, book-to-market, dividend-price ratios and past risk. It generates high estimates for the explained cross-sectional variation in average returns, lower average pricing errors than the Fama-French three factor model and economically and statistically acceptable estimates for the coefficient of relative risk aversion.CAPM, cash-flow risk, discount-rate risk, asset pricing

Realized Volatility and Asymmetries in the A.S.E. Returns

Using a newly developed dataset of daily, value-weighted market returns we construct and analyze the monthly realized volatility of the Athens Stock Exchange (A.S.E.) from 1985 to 2003. Our analysis focuses on the distributional and time series properties of the realized volatility series and on assessing the connection between realized volatility and returns. In particular, we find strong evidence on the existence of a volatility feedback effect and the leverage effect, and on the existence of asymmetries between lagged returns and volatility. Furthermore, we examine the cross-sectional distribution of unconditional loadings on the realized risk factor(s) for different sets of characteristics-sorted common stock portfolios. We find that realized risk is a significantly priced factor in A.S.E. and its high explanatory power for the cross- section of portfolio average returns is independent of any return variation related to the market (CAPM) or size and book-to-market (Fama- French) factors. We discuss our findings in the context of the recent literature on realized volatility and feedback effects, as well as the literature on the pricing power of realized risk.realized volatility, leverage effect, volatility feedback effect, asset pricing, A.S.E.

JGraphT -- A Java library for graph data structures and algorithms

Mathematical software and graph-theoretical algorithmic packages to efficiently model, analyze and query graphs are crucial in an era where large-scale spatial, societal and economic network data are abundantly available. One such package is JGraphT, a programming library which contains very efficient and generic graph data-structures along with a large collection of state-of-the-art algorithms. The library is written in Java with stability, interoperability and performance in mind. A distinctive feature of this library is the ability to model vertices and edges as arbitrary objects, thereby permitting natural representations of many common networks including transportation, social and biological networks. Besides classic graph algorithms such as shortest-paths and spanning-tree algorithms, the library contains numerous advanced algorithms: graph and subgraph isomorphism; matching and flow problems; approximation algorithms for NP-hard problems such as independent set and TSP; and several more exotic algorithms such as Berge graph detection. Due to its versatility and generic design, JGraphT is currently used in large-scale commercial, non-commercial and academic research projects. In this work we describe in detail the design and underlying structure of the library, and discuss its most important features and algorithms. A computational study is conducted to evaluate the performance of JGraphT versus a number of similar libraries. Experiments on a large number of graphs over a variety of popular algorithms show that JGraphT is highly competitive with other established libraries such as NetworkX or the BGL.Comment: Major Revisio

ENORM: A Framework For Edge NOde Resource Management

Current computing techniques using the cloud as a centralised server will become untenable as billions of devices get connected to the Internet. This raises the need for fog computing, which leverages computing at the edge of the network on nodes, such as routers, base stations and switches, along with the cloud. However, to realise fog computing the challenge of managing edge nodes will need to be addressed. This paper is motivated to address the resource management challenge. We develop the first framework to manage edge nodes, namely the Edge NOde Resource Management (ENORM) framework. Mechanisms for provisioning and auto-scaling edge node resources are proposed. The feasibility of the framework is demonstrated on a PokeMon Go-like online game use-case. The benefits of using ENORM are observed by reduced application latency between 20% - 80% and reduced data transfer and communication frequency between the edge node and the cloud by up to 95\%. These results highlight the potential of fog computing for improving the quality of service and experience.Comment: 14 pages; accepted to IEEE Transactions on Services Computing on 12 September 201

DYVERSE: DYnamic VERtical Scaling in Multi-tenant Edge Environments

Multi-tenancy in resource-constrained environments is a key challenge in Edge computing. In this paper, we develop 'DYVERSE: DYnamic VERtical Scaling in Edge' environments, which is the first light-weight and dynamic vertical scaling mechanism for managing resources allocated to applications for facilitating multi-tenancy in Edge environments. To enable dynamic vertical scaling, one static and three dynamic priority management approaches that are workload-aware, community-aware and system-aware, respectively are proposed. This research advocates that dynamic vertical scaling and priority management approaches reduce Service Level Objective (SLO) violation rates. An online-game and a face detection workload in a Cloud-Edge test-bed are used to validate the research. The merits of DYVERSE is that there is only a sub-second overhead per Edge server when 32 Edge servers are deployed on a single Edge node. When compared to executing applications on the Edge servers without dynamic vertical scaling, static priorities and dynamic priorities reduce SLO violation rates of requests by up to 4% and 12% for the online game, respectively, and in both cases 6% for the face detection workload. Moreover, for both workloads, the system-aware dynamic vertical scaling method effectively reduces the latency of non-violated requests, when compared to other methods

Mechanistic studies on the molecular toxicology of the carcinogen PhIP: the role of microRNAs

The effect of environmental factors in cellular processes has been an area of interest for decades. Within this research field, emerging research niches appear concominantly with advances in molecular biology and genetics. One such field is the one of molecular toxicology, which investigates the molecular and cellular events that certain chemicals trigger. Chemicals that present genotoxic properties are of particular interest based on the potential contribution to the aetiology of cancer that the discoveries of their effects might provide. A group of chemicals that belong to this category are heterocyclic amines, organic compounds that are formed during the cooking of red meat from the pyrolysis of aminoacids. Research into heterocyclic amines has created a well established description for their ability to create DNA adducts that lead to mutations. Recent reports from our laboratory however, indicated that certain heterocyclic amines, and in particular 2-amino-1-methyl-6-phenylimidazo [4,5-b] pyridine (PhIP), present with molecular effects that are non genotoxic but nevertheless carcinogenic and are very similar to those induce by the natural hormone estradiol in breast cancer cells. Based on these findings this thesis set out to investigate whether these non-genotoxic effects of PhIP also extend to epigenetic mechanisms of gene expression control, and more specifically microRNA expression regulation. MicroRNAs are a class of small non-coding RNA molecules that posttrasncriptionally regulate gene expression and are involved in an array of process including carcinogenesis. Our results showed that PhIP, as well as estradiol, drive differential regulation of microRNAs and that these effects are very similar amongst the two compounds. This deregulation of microRNAs could be an attributing factor to the cancer promoting characteristics of both estradiol and PhIP and they extend the estrogenic character of this heterocyclic amine to the area of epigenetic regulation, and microRNAs in particular.Open Acces

NETCS: A New Simulator of Population Protocols and Network Constructors

Network Constructors are an extension of the standard population protocol model in which finite-state agents interact in pairs under the control of an adversary scheduler. In this work we present NETCS, a simulator designed to evaluate the performance of various network constructors and population protocols under different schedulers and network configurations. Our simulator provides researchers with an intuitive user interface and a quick experimentation environment to evaluate their work. It also harnesses the power of the cloud, as experiments are executed remotely and scheduled through the web interface provided. To prove the validity and quality of our simulator we provide an extensive evaluation of multiple protocols with more than 100000 experiments for different network sizes and configurations that validate the correctness of the theoretical analysis of existing protocols and estimate the real values of the hidden asymptotic coefficients. We also show experimentally (with more than 40000 experiments) that a probabilistic algorithm is capable of counting the actual size of the network in bounded time given a unique leader

Ahlfors regularity, extensions by Schatten ideals and a geometric fundamental class of Smale space C*-algebras using dynamical partitions of unity

In this thesis we study the Ahlfors regularity of Bowen's measure on Smale spaces and analyse Smale space C*-algebras in the framework of Connes' noncommutative geometry using smooth extensions by Schatten ideals and summable Fredholm modules. Bowen's construction of Markov partitions implies that Smale spaces are factors of topological Markov chains. The latter are equipped with Parry's measure which is Ahlfors regular. By extending Bowen's construction we create a tool for transferring, up to topological conjugacy, the Ahlfors regularity of the Parry measure down to the Bowen measure of the Smale space. An essential part of our method uses a refined notion of approximation graphs over compact metric spaces. Moreover, we obtain new estimates for the Hausdorff, box-counting and Assouad dimensions of a large class of Smale spaces. In the noncommutative setting, given a Smale space, our generalised Markov partitions yield dynamical partitions of unity which produce explicit θ-summable Fredholm modules that represent a fundamental K-homology class for the Spanier-Whitehead duality of the stable and unstable Ruelle algebras of the Smale space. Therefore, we obtain an exhaustive description of the K-homology classes of Ruelle algebras in terms of Fredholm modules constructed by Markov partitions. Our method involves the construction of dynamical metrics on Smale space groupoids that give rise to smooth (holomorphically stable and dense) *-subalgebras of Smale space C*-algebras. In particular, for every such smooth subalgebra of a Ruelle algebra, we show that every extension class in the BDF-theory group of the Ruelle algebra can be represented by an extension that on the smooth subalgebra reduces to an algebraic extension by a Schatten p-ideal. The value p is related to the dimension of the underlying Smale space. This provides a new approach to the noncommutative dimension theory of Smale spaces