Should Monetary Policy Respond to Asset Price Misalignments?

This paper analyses the relationship between monetary policy and asset prices using a structural rational expectations model that allows for the effect of asset prices on aggregate demand. We assume that asset prices follow a partial adjustment mechanism whereas they are positively affected by past changes, thus allowing for ‘momentum trading’, while at the same time we allow for reversion towards fundamentals. We then conduct stochastic simulations using two alternative monetary policy rules, inflation-forecast targeting and the standard Taylor rule. The results indicate that, under both rules, interest rate setting that takes into account asset price misalignments leads to lower overall macroeconomic volatility, as measured by the postulated loss function of the central bank

Liquidity effects due to information costs from changes

In this paper we examine effect on the returns of firms that have been included to and deleted from the FTSE 100 over the time period of 1984-2001. Like the S&P 500 listing studies, we find that the price and trading volume of newly listed (deleted) firms increases (decreases). The evidence is consistent with the information cost/liquidity explanation. This is because investors hold stocks with more (less) available information, consequently implying that they have lower (higher) trading costs. This explains the increase (decrease) in the stock price and trading volume of newly listed (deleted) stocks to (from) the FTSE 100 List

GMM and present value test of the C-CAPM under transactions costs: Evidence from the UK stock market

In this paper we test for the inclusion of the bid-ask spread in the consumption CAPM, in the UK stock market over the time period of 1980-2000. Two econometric models are used; first, Fisher’s (1994) asset pricing model is estimated by GMM, and secondly, the VAR approach proposed by Campbell and Shiller is extended to include the bid-ask spread. Overall the statistical tests are unable to reject the bid-ask spread as an independent explanatory variable in the C-CAPM. This leads to the conclusion that transactions costs should be included in asset pricing models

Most UK scientists who publish extremely highly-cited papers do not secure funding from major public and charity funders: A descriptive analysis

The UK is one of the largest funders of health research in the world, but little is known about how health funding is spent. Our study explores whether major UK public and charitable health research funders support the research of UK-based scientists producing the most highly-cited research. To address this question, we searched for UK-based authors of peer-reviewed papers that were published between January 2006 and February 2018 and received over 1000 citations in Scopus. We explored whether these authors have held a grant from the National Institute for Health Research (NIHR), the Medical Research Council (MRC) and the Wellcome Trust and compared the results with UK-based researchers who serve currently on the boards of these bodies. From the 1,370 papers relevant to medical, biomedical, life and health sciences with more than 1000 citations in the period examined, we identified 223 individuals from a UK institution at the time of publication who were either first/last or single authors. Of those, 164 are still in UK academic institutions, while 59 are not currently in UK academia (have left the country, are retired, or work in other sectors). Of the 164 individuals, only 59 (36%; 95% CI: 29-43%) currently hold an active grant from one of the three funders. Only 79 (48%; 95% CI: 41-56%) have held an active grant from any of the three funders between 2006-2017. Conversely, 457 of the 664 board members of MRC, Wellcome Trust, and NIHR (69%; 95% CI: 65-72%) have held an active grant in the same period by any of these funders. Only 7 out of 655 board members (1.1%) were first, last or single authors of an extremely highly-cited paper. There are many reasons why the majority of the most influential UK authors do not hold a grant from the country’s major public and charitable funding bodies. Nevertheless, the results are worrisome and subscribe to similar patterns shown in the US. We discuss possible implications and suggest ways forward

Replication in Genome-Wide Association Studies

Replication helps ensure that a genotype-phenotype association observed in a genome-wide association (GWA) study represents a credible association and is not a chance finding or an artifact due to uncontrolled biases. We discuss prerequisites for exact replication, issues of heterogeneity, advantages and disadvantages of different methods of data synthesis across multiple studies, frequentist vs. Bayesian inferences for replication, and challenges that arise from multi-team collaborations. While consistent replication can greatly improve the credibility of a genotype-phenotype association, it may not eliminate spurious associations due to biases shared by many studies. Conversely, lack of replication in well-powered follow-up studies usually invalidates the initially proposed association, although occasionally it may point to differences in linkage disequilibrium or effect modifiers across studies.Comment: Published in at http://dx.doi.org/10.1214/09-STS290 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

xPF: Packet Filtering for Low-Cost Network Monitoring

The ever-increasing complexity in network infrastructures is making critical the demand for network monitoring tools. While the majority of network operators rely on low-cost open-source tools based on commodity hardware and operating systems, the increasing link speeds and complexity of network monitoring applications have revealed inefficiencies in the existing software organization, which may prohibit the use of such tools in high-speed networks. Although several new architectures have been proposed to address these problems, they require significant effort in re-engineering the existing body of applications. We present an alternative approach that addresses the primary sources of inefficiency without significantly altering the software structure. Specifically, we enhance the computational model of the Berkeley packet filter (BPF) to move much of the processing associated with monitoring into the kernel, thereby removing the overhead associated with context switching between kernel and applications. The resulting packet filter, called xPF, allows new tools to be more efficiently implemented and existing tools to be easily optimized for high-speed networks. We present the design and implementation of xPF as well as several example applications that demonstrate the efficiency of our approach

Why Most Published Research Findings Are False

There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research