The benefits of combining seasonal anomalies and technical trading rules

Although many seasonal anomalies and technical trading rules have been shown to have predictive ability, investigations have focused only on them operating individually. We study the benefits of trading based on combinations of three of the best known effects: the moving average rule, the turn of the month effect, and the Halloween effect. We show that the rules can be combined effectively, giving significant levels of returns predictability with low risk and offering the possibility of profitable trading. This new investment approach is especially beneficial for a typical individual investor, who faces high transaction costs and is poorly diversified

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Credit market imperfections, financial intermediation and the transmission of monetary policy

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THE DECLINE IN THE VOLATILITY OF THE BUSINESS CYCLES IN THE UK

We analyse the sources of the decline of business cycle volatility in the UK using a dynamic factor model that allows for the presence of a structural break in the conditional mean and variance of output, sales, income and unemployment. We augment the factor model with an economic component to investigate the role of structural changes and improved monetary policy in the volatility decline of the series. Our results suggest that the dominant cause for the observed volatility decline is the reduced variability of shocks. Copyright � 2008 The Authors. Journal compilation � 2008 Blackwell Publishing Ltd and The University of Manchester.

Technical trading rules and calendar anomalies -- Are they the same phenomena?

The predictive ability of technical trading rules and the presence of calendar anomalies are well known, but theoretically anomalous, features of equity markets. We show that while some rules exploit calendar effects they are primarily being driven by other factors.Stocks Technical trading Calendar anomalies