6,538 research outputs found
Parrondo Strategies for Artificial Traders
On markets with receding prices, artificial noise traders may consider
alternatives to buy-and-hold. By simulating variations of the Parrondo
strategy, using real data from the Swedish stock market, we produce first
indications of a buy-low-sell-random Parrondo variation outperforming
buy-and-hold. Subject to our assumptions, buy-low-sell-random also outperforms
the traditional value and trend investor strategies. We measure the success of
the Parrondo variations not only through their performance compared to other
kinds of strategies, but also relative to varying levels of perfect
information, received through messages within a multi-agent system of
artificial traders.Comment: 10 pages, 4 figure
The Use of Videotaped Segments of The Apprentice in a Food and Agricultural Sales Class: The Case of ApEc 3451
This paper described the incorporation of selected segments of the Apprentice Series into an Ag and Food Sales course. A description of the use of these segments and student evaluation of the experience are also included.Teaching/Communication/Extension/Profession,
Estimating individual treatment effect: generalization bounds and algorithms
There is intense interest in applying machine learning to problems of causal
inference in fields such as healthcare, economics and education. In particular,
individual-level causal inference has important applications such as precision
medicine. We give a new theoretical analysis and family of algorithms for
predicting individual treatment effect (ITE) from observational data, under the
assumption known as strong ignorability. The algorithms learn a "balanced"
representation such that the induced treated and control distributions look
similar. We give a novel, simple and intuitive generalization-error bound
showing that the expected ITE estimation error of a representation is bounded
by a sum of the standard generalization-error of that representation and the
distance between the treated and control distributions induced by the
representation. We use Integral Probability Metrics to measure distances
between distributions, deriving explicit bounds for the Wasserstein and Maximum
Mean Discrepancy (MMD) distances. Experiments on real and simulated data show
the new algorithms match or outperform the state-of-the-art.Comment: Added name "TARNet" to refer to version with alpha = 0. Removed sup
Obscenity and the Mail: A Study of Administrative Restraint
This paper shows how 3-dimensional interactive visualization can be used as a tool in system identification. Non-linear or time-dependent dynamics often leave a significant residual with linear, time-invariant models. The structure of this residual is decisive for the subsequent modelling, and by using advanced visualization techniques, the modeller may gain a deeper insight into this structure than can be obtained by standard correlation analysis
Maximal Unitarity for the Four-Mass Double Box
We extend the maximal-unitarity formalism at two loops to double-box
integrals with four massive external legs. These are relevant for higher-point
processes, as well as for heavy vector rescattering, VV -> VV. In this
formalism, the two-loop amplitude is expanded over a basis of integrals. We
obtain formulas for the coefficients of the double-box integrals, expressing
them as products of tree-level amplitudes integrated over specific complex
multidimensional contours. The contours are subject to the consistency
condition that integrals over them annihilate any integrand whose integral over
real Minkowski space vanishes. These include integrals over parity-odd
integrands and total derivatives arising from integration-by-parts (IBP)
identities. We find that, unlike the zero- through three-mass cases, the IBP
identities impose no constraints on the contours in the four-mass case. We also
discuss the algebraic varieties connected with various double-box integrals,
and show how discrete symmetries of these varieties largely determine the
constraints.Comment: 25 pages, 3 figures; final journal versio
Two-Loop Maximal Unitarity with External Masses
We extend the maximal unitarity method at two loops to double-box basis
integrals with up to three external massive legs. We use consistency equations
based on the requirement that integrals of total derivatives vanish. We obtain
unique formulae for the coefficients of the master double-box integrals. These
formulae can be used either analytically or numerically.Comment: 41 pages, 7 figures; small corrections, final journal versio
An Overview of Maximal Unitarity at Two Loops
We discuss the extension of the maximal-unitarity method to two loops,
focusing on the example of the planar double box. Maximal cuts are
reinterpreted as contour integrals, with the choice of contour fixed by the
requirement that integrals of total derivatives vanish on it. The resulting
formulae, like their one-loop counterparts, can be applied either analytically
or numerically.Comment: 7 pages, presented at Loops & Legs 2012, Wernigerode, German
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