Assessing the Rental Value of Residential Properties: An Abductive Learning Networks Approach

This paper attempts to estimate rental value of residential properties using Abductive Learning Networks (ALN), and artificial intelligence technique. The results indicate that the ALN model provides an accurate estimation of rents with only seven input variables, while other multivariate statistical techniques do not. The ALN model automatically selects the best network structure, node types and coefficients, and therefore it simplifies the maintenance of the model. Once the final model is synthesized, the ALN model becomes very compact, rapidly executable and cost-effective.

Provocative, honest, fierce: a review of Ai Weiwei’s London exhibition

Ai Weiwei’s art situates itself within the cold reality of human rights in China. The very material used within his work is suggestive of the authorities’ hold upon the political and economic freedom of its citizens. In his recent exhibition at the Royal Academy – the largest showing of his work in the UK – important issues have been raised relating to governance, human rights, and freedom of expression within his country

The doctrine of humanitarian intervention: lessons from the Chilcot Report

In the midst of what can only be described as the tumultuous climate that defines Britain’s current political scene, the release of The Chilcot Report should not be forgotten as one of the most significant moments in the country’s recent history. While many agonize over an uncertain future, Chilcot reminds us of a not so distant past which some people – most of all, former Prime Minister Tony Blair – would rather forget

Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence

Recent research based on variance ratios and multiperiod-return autocorrelations concludes that the stock market exhibits mean reversion in the sense that a return in excess of the average tends to be followed by partially offsetting returns in the opposite direction. Dividing history into pre-1926, 1926-46, and post-1946 subperiods, we find that the mean-reversion phenomenon is a feature of the 1926-46 period, but not of the post-1946 period which instead exhibits persistence of returns. Evidence for pre-1926 data is mixed. The statistical significance of test statistics is assessed by estimating their distribution using stratified randomization. Autocorrelations of multiperiod returns imply a forecast of future returns, which is presented for post-war three-year returns using 1926-46, full sample, and sequentially updated coefficient estimates. The correlation between actual and forecasted returns is negative in each case. We conclude that evidence of mean reversion in U.S. stock returns is substantially weaker than reported in the recent literature. If mean-reversion continues to be a feature of the stock market, then the experience of the past forty years has been an aberration.

The less volatile U.S. economy: a Bayesian investigation of timing, breadth, and potential explanations

Using a Bayesian model comparison strategy, we search for a volatility reduction within the post-war sample for the growth rates of U.S. aggregate and disaggregate real GDP. We find that the growth rate of aggregate real GDP has been less volatile since the early 1980s, and that this volatility reduction is concentrated in the cyclical component of real GDP. The growth rates of many of the broad production sectors of real GDP display similar reductions in volatility, suggesting the aggregate volatility reduction does not have a narrow source. We also find a large volatility reduction in measures of final sales in the goods sector. We contrast this evidence to an existing literature documenting an aggregate volatility reduction that is shared by only one narrow sub-component, the production of durable goods, and is not present in final sales. We also document structural breaks in the persistence and conditional volatility of inflation that occurred over a similar time frame as the volatility reduction in real GDP.Econometric models ; Business cycles

Magnetic field dependence of charge stripe order in La2-xBaxCuO4 (x~1/8)

We have carried out a detailed investigation of the magnetic field dependence of charge ordering in La2-xBaxCuO4 (x~1/8) utilizing high-resolution x-ray scattering. We find that the charge order correlation length increases as the magnetic field greater than ~5T is applied in the superconducting phase (T=2K). The observed unusual field dependence of the charge order correlation length suggests that the static charge stripe order competes with the superconducting ground state in this sample.Comment: 4 pages, 4 figure