The Effects of feedback on judgmental interval predictions

Cataloged from PDF version of article.The majority of studies of probability judgment have found that judgments tend to be overconfident and that the degree of overconfidence is greater the more difficult the task. Further, these effects have been resistant to attempts to ‘debias’ via feedback. We propose that under favourable conditions, provision of appropriate feedback should lead to significant improvements in calibration, and the current study aims to demonstrate this effect. To this end, participants first specified ranges within which the true values of time series would fall with a given probability. After receiving feedback, forecasters constructed intervals for new series, changing their probability values if desired. The series varied systematically in terms of their characteristics including amount of noise, presentation scale, and existence of trend. Results show that forecasts were initially overconfident but improved significantly after feedback. Further, this improvement was not simply due to ‘hedging’, i.e. shifting to very high probability estimates and extremely wide intervals; rather, it seems that calibration improvement was chiefly obtained by forecasters learning to evaluate the extent of the noise in the series. D 2003 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved

Currency forecasting: an investigation of extrapolative judgement

Cataloged from PDF version of article.This paper aims to explore the potential effects of trend type, noise and forecast horizon on experts' and novices' probabilistic forecasts. The subjects made forecasts over six time horizons from simulated monthly currency series based on a random walk, with zero, constant and stochastic drift, at two noise levels. The difference between the Mean Absolute Probability Score of each participant and an AR(1) model was used to evaluate performance. The results showed that the experts performed better than the novices, although worse than the model except in the case of zero drift series. No clear expertise effects occurred over horizons, albeit subjects' performance relative to the model improved as the horizon increased. Possible explanations are offered and some suggestions for future research are outlined

On the Delay Margin for Consensus in Directed Networks of Anticipatory Agents

We consider a linear consensus problem involving a time delay that arises from predicting the future states of agents based on their past history. In case the agents are coupled in a connected and undirected network, the exact condition for consensus is that the delay be less than a constant threshold that is independent of the network topology or size. In directed networks, however, the situation is quite different. We show that the allowable maximum delay for consensus depends on the network topology in a nontrivial way. We study this delay margin in several network constellations, including various circulant networks with directed links. We show that the delay margin depends not only on the number of neighbors, but also on the directionality of connections with those neighbors. Furthermore, the delay margin improves as the circulant networks are rewired en route to a small-world configuration. © 201

A delayed consensus algorithm in networks of anticipatory agents

We introduce and analyze a delayed consensus algorithm as a model for interacting agents using anticipation of their neighbors' states to improve convergence to consensus. We derive a necessary and sufficient condition for the system to reach consensus. Furthermore, we explicitly calculate the dominant characteristic root of the consensus problem as a measure of the speed of convergence. The results show that the anticipatory algorithm can improve the speed of consensus, especially in networks with poor connectivity. Hence, anticipation can improve performance in networks if the delay parameter is chosen judiciously, otherwise the system might diverge as agents try to anticipate too aggressively into the future. © 2016 EUCA

Evaluating predictive performance of judgemental extrapolations from simulated currency series

Cataloged from PDF version of article.Judgemental forecasting of exchange rates is critical for ®nancial decision-making. Detailed investigations of the potential e ects of time-series characteristics on judgemental currency forecasts demand the use of simulated series where the form of the signal and probability distribution of noise are known. The accuracy measures Mean Absolute Error (MAE) and Mean Squared Error (MSE) are frequently applied quantities in assessing judgemental predictive performance on actual exchange rate data. This paper illustrates that, in applying these measures to simulated series with Normally distributed noise, it may be desirable to use their expected values after standardising the noise variance. A method of calculating the expected values for the MAE and MSE is set out, and an application to ®nancial experts' judgemental currency forecasts is presented. Ó 1999 Elsevier Science B.V. All rights reserved

The cultural impact of hidden curriculum on language learners: A review and some implications for curriculum design

With reference to theory and research, this chapter discusses the hidden curriculum of language textbooks and other teaching materials where culture, gender, race, or other topics associated with equality, diversity, and representativeness were presented in biased ways. Hidden curriculum may describe, present, or elicit stereotypes and reproduce cultural, gender, and racial bias in subtle ways; sometimes even teachers may not notice what the curriculum refers to or they may perceive stereotyping as harmless. This makes sociolinguistic problems with regard to use of a purist and monolithic cultural content more salient than ever. Yet, the new sociolinguistic landscape of language teaching where changing needs of language learners might not be accurately represented in teaching materials require the revision of current curricula and pedagogical practices. Therefore, this chapter draws conclusions from empirical studies on the topic and provides some implications for teaching and materials design

Concave Plasmonic Particles: Broad-Band Geometrical Tunability in the Near Infra-Red

Optical resonances spanning the Near and Short Infra-Red spectral regime were exhibited experimentally by arrays of plasmonic nano-particles with concave cross-section. The concavity of the particle was shown to be the key ingredient for enabling the broad band tunability of the resonance frequency, even for particles with dimensional aspect ratios of order unity. The atypical flexibility of setting the resonance wavelength is shown to stem from a unique interplay of local geometry with surface charge distributions

Mean field approximation of two coupled populations of excitable units

The analysis on stability and bifurcations in the macroscopic dynamics exhibited by the system of two coupled large populations comprised of $N$ stochastic excitable units each is performed by studying an approximate system, obtained by replacing each population with the corresponding mean-field model. In the exact system, one has the units within an ensemble communicating via the time-delayed linear couplings, whereas the inter-ensemble terms involve the nonlinear time-delayed interaction mediated by the appropriate global variables. The aim is to demonstrate that the bifurcations affecting the stability of the stationary state of the original system, governed by a set of 4N stochastic delay-differential equations for the microscopic dynamics, can accurately be reproduced by a flow containing just four deterministic delay-differential equations which describe the evolution of the mean-field based variables. In particular, the considered issues include determining the parameter domains where the stationary state is stable, the scenarios for the onset and the time-delay induced suppression of the collective mode, as well as the parameter domains admitting bistability between the equilibrium and the oscillatory state. We show how analytically tractable bifurcations occurring in the approximate model can be used to identify the characteristic mechanisms by which the stationary state is destabilized under different system configurations, like those with symmetrical or asymmetrical inter-population couplings.Comment: 5 figure