13,612 research outputs found

    The Efficient Market Hypothesis: Is It Applicable to the Foreign Exchange Market?

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    The study analyses the applicability of the efficient market hypothesis to the foreign exchange market by testing the profitability of the filter rule on the spot market. The significance of the returns was validated by comparing them to the returns from randomly generated shuffled series via bootstrap methods. The results were surprising. For the total period (1984-2003) small filter rules could deliver significant returns indicating an inefficient foreign exchange market. However, once the data was separated into four sub-periods of five years to test the stability of the returns, the results indicate that only the first sub period delivered significant returns. In the last two sub periods or ten years, the returns from employing filter rules were negative. This supports the conclusion that the efficient market hypothesis is valid in the foreign exchange market.Efficient market hypothesis, foreign exchange market, filter rules

    Time-Shared Execution of Realtime Computer Vision Pipelines by Dynamic Partial Reconfiguration

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    This paper presents an FPGA runtime framework that demonstrates the feasibility of using dynamic partial reconfiguration (DPR) for time-sharing an FPGA by multiple realtime computer vision pipelines. The presented time-sharing runtime framework manages an FPGA fabric that can be round-robin time-shared by different pipelines at the time scale of individual frames. In this new use-case, the challenge is to achieve useful performance despite high reconfiguration time. The paper describes the basic runtime support as well as four optimizations necessary to achieve realtime performance given the limitations of DPR on today's FPGAs. The paper provides a characterization of a working runtime framework prototype on a Xilinx ZC706 development board. The paper also reports the performance of realtime computer vision pipelines when time-shared

    Controlling composition factors of a finite group by its character degree ratio

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    For a finite nonabelian group GG let \rat(G) be the largest ratio of degrees of two nonlinear irreducible characters of GG. We show that nonabelian composition factors of GG are controlled by \rat(G) in some sense. Specifically, if SS different from the simple linear groups \PSL_2(q) is a nonabelian composition factor of GG, then the order of SS and the number of composition factors of GG isomorphic to SS are both bounded in terms of \rat(G). Furthermore, when the groups \PSL_2(q) are not composition factors of GG, we prove that |G:\Oinfty(G)|\leq \rat(G)^{21} where \Oinfty(G) denotes the solvable radical of GG.Comment: 16 pages, 1 tabl

    Transactions Costs and Point-Nonpoint Source Water Pollution Trading

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    The implications of transactions costs for the performance of water pollution trading involving point and nonpoint sources are examined. The analysis focuses on the impacts of transaction costs on different classes of trading partners and its consequence on the trading equilibrium. The model of point-nonpoint water pollution trading in the context of the total maximum daily loads explicitly incorporates transactions costs for both buying and selling exchanges of nonpoint source and point source permits. Transactions costs unarguably reduce the optimal level of trades in both types of permits compared to the costless trade case.Environmental Economics and Policy,

    Asian Americans on the Streets: Strategies for Prevention and Intervention

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    Notably lacking in the literature on Vietnamese and Cambodian youth gangs in the United States and particularly Southern California have been solutions that address the underlying causative factors of gang involvement. Relying on life histories collected over a span of fifteen years, the authors propose a multi-faceted prevention and intervention strategy that includes the community and schools to heighten cultural awareness for children and parents. It is also recommended that policies take into account nuanced differences between Asian communities and bring together multiple stakeholders including officials and hard-core gang members to improve communicative problems that have resulted in gang-policy failures

    A Framework to Adjust Dependency Measure Estimates for Chance

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    Estimating the strength of dependency between two variables is fundamental for exploratory analysis and many other applications in data mining. For example: non-linear dependencies between two continuous variables can be explored with the Maximal Information Coefficient (MIC); and categorical variables that are dependent to the target class are selected using Gini gain in random forests. Nonetheless, because dependency measures are estimated on finite samples, the interpretability of their quantification and the accuracy when ranking dependencies become challenging. Dependency estimates are not equal to 0 when variables are independent, cannot be compared if computed on different sample size, and they are inflated by chance on variables with more categories. In this paper, we propose a framework to adjust dependency measure estimates on finite samples. Our adjustments, which are simple and applicable to any dependency measure, are helpful in improving interpretability when quantifying dependency and in improving accuracy on the task of ranking dependencies. In particular, we demonstrate that our approach enhances the interpretability of MIC when used as a proxy for the amount of noise between variables, and to gain accuracy when ranking variables during the splitting procedure in random forests.Comment: In Proceedings of the 2016 SIAM International Conference on Data Minin
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