Studies related to primitive chemistry. A proton and nitrogen-14 nuclear magnetic resonance amino acid and nucleic acid constituents and a and their possible relation to prebiotic

Preliminary proton nuclear magnetic resonance (NMR) studies were made to determine the applicability of this technique for the study of interactions between monomeric and polymeric amino acids with monomeric nucleic acid bases and nucleotides. Proton NMR results for aqueous solutions (D2O) demonstrated interactions between the bases cytosine and adenine and acidic and aromatic amino acids. Solutions of 5'-AMP admixed with amino acids exhibited more complex behavior but stacking between aromatic rings and destacking at high amino acids concentration was evident. The multisite nature of 5'-AMP was pointed out. Chemical shift changes for adenine and 5'-AMP with three water soluble polypeptides demonstrated that significant interactions exist. It was found that the linewidth-pH profile of each amino acid is unique. It is concluded that NMR techniques can give significant and quantitative data on the association of amino acid and nucleic acid constituents

НАРРАТИВНАЯ ЭКОНОМИКА И НЕЙРОЭКОНОМИКА

This article is a reworked lecture I have given at theFinancialUniversityunder the Government of theRussian FederationinMoscow. This lecture has considered the epidemiology of narratives relevant to economic fluctuations (outcomes), allowing them to “go viral” and spread far away, even worldwide, and thereby influencing economic outcomes. However, I had to accommodate my talk to the Russian audience adding some illustrative examples for better understanding. My basic goal in this paper is to describe what we know about narratives and the penchant of the human mind to be engaged by them, to consider reasons to expect that narratives might well be thought of as important, largely exogenous shocks to the aggregate economy. Thus, the main focus was on narratives going viral, affecting the economy in an age of neuroimaging, big data. This is because the human brain has always been highly tuned towards narratives, whether factual or not, to justify ongoing actions — even in such basic actions as spending and investing. Though these narratives are deeply human phenomena that are difficult to study in a scientific manner, quantitative analysis may help us gain a better understanding of these epidemics in the future. Many examples are seen as revealing the importance of the linkage of human brains and now computers through narratives associated with popular models of the economy and offering new research opportunities for both economics and neuroscience.Эта статья является переработанной лекцией, которую я прочитал в Финансовом университете при Правительстве Российской Федерации в Москве. В этой лекции была рассмотрена эпидемиология нарративов, имеющих отношение к экономическим колебаниям (результатам), что позволило им «стать вирусными», распространиться далеко, даже по всему миру, и тем самым повлиять на экономические результаты. Тем не менее я должен был адаптировать мое выступление для российской аудитории, добавив некоторые иллюстративные примеры для лучшего понимания. Моя основная цель в этой статье состоит в том, чтобы описать то, что мы знаем о нарративах и склонности человеческого разума к их восприятию, а затем обосновать причины нашего ожидания, что нарративы вполне могут рассматриваться как важные, в основном экзогенные потрясения для экономики в целом. Таким образом, основное внимание было уделено нарративам, которые становятся вирусными, влияющими на экономику в эпоху нейровизуализации больших данных. Это потому, что человеческий мозг всегда был настроен на рассказы, будь то фактические или нет, чтобы оправдать текущие действия — даже в таких основных действиях, как расходы и инвестиции. Поскольку эти рассказы являются глубоко человеческими явлениями, которые трудно изучить на научной основе, количественный анализ может помочь нам в будущем лучше понять эти эпидемии. Многие примеры рассматриваются как важные доказательства связи человеческого мозга и теперь компьютеров через рассказы, связанные с популярными моделями экономики, что и представляет новые возможности для исследований в области как экономики, так и нейронауки.

Theory of Fano-Kondo effect of transport properties through quantum dots

The Fano-Kondo effect in zero-bias conductance is investigated based on a theoretical model for the T-shaped quantum dot. The conductance as a function of the gate voltage is generally characterized by a Fano asymmetric parameter q. With varying temperature the conductance shows a crossover between the high and low temperature regions compared with the Kondo temperature T_K: two Fano asymmetric peaks at high temperatures and the Fano-Kondo plateau inside a Fano peak at low temperatures. Temperature dependence of conductance is calculated numerically by the Finite temperature density matrix renormalization group method (FT-DMRG).Comment: 8 pages, 7 figure

The long-run performance of IPOs: the case of the Stock Exchange of Mauritius

This study examines the long-run performance of initial public offerings on the Stock Exchange of Mauritius (SEM). The results show that the 3-year equally weighted cumulative adjusted returns average −16.5%. The magnitude of this underperformance is consistent with most reported studies in different developed and emerging markets. Based on multivariate regression models, firms with small issues and higher ex ante financial strength seem on average to experience greater long-run underperformance, supporting the divergence of opinion and overreaction hypotheses. On the other hand, Mauritian firms do not on average time their offerings to lower cost of capital and as such, there seems to be limited support for the windows of opportunity hypothesis

Have Financial Markets Become More Informative?

The finance industry has grown. Financial markets have become more liquid. Information technology has improved. But have prices become more informative? Using stock and bond prices to forecast earnings, we find that the information content of market prices has not increased since 1960. The magnitude of earnings surprises, however, has increased. A baseline model predicts that as the efficiency of information production increases, prices become more disperse and covary more strongly with future earnings. The forecastable component of earnings improves capital allocation and serves as a direct measure of welfare. We find that this measure has remained stable. A model with endogenous information acquisition predicts that an increase in fundamental uncertainty also increases informativeness as the incentive to produce information grows. We find that uncertainty has indeed increased outside of the S&P 500, but price informativeness has not

Stock market volatility and business cycle: Evidence from linear and nonlinear causality tests

This paper investigates the relationship between stock market volatility and the business cycle in four major economies, namely the US, Canada, Japan and the UK. We employ both linear and nonlinear bivariate causality tests and we further conduct a multivariate analysis to explore possible spillover effects across countries. Our results suggest that there is a bidirectional causal relationship between stock market volatility and the business cycle within each country and additionally reveal that the recent financial crisis plays an important role in this context. Finally, we identify a significant impact of the US on the remaining markets

Value at Risk models with long memory features and their economic performance

We study alternative dynamics for Value at Risk (VaR) that incorporate a slow moving component and information on recent aggregate returns in established quantile (auto) regression models. These models are compared on their economic performance, and also on metrics of first-order importance such as violation ratios. By better economic performance, we mean that changes in the VaR forecasts should have a lower variance to reduce transaction costs and should lead to lower exceedance sizes without raising the average level of the VaR. We find that, in combination with a targeted estimation strategy, our proposed models lead to improved performance in both statistical and economic terms

Predicting the Spread of Financial Innovations: An Epidemiological Approach

I construct an estimable statistic that predicts whether a financial innovation will spread. The approach embeds the multi-host SIR model from epidemiology within a financial model of correlated securities trade; and takes advantage of the related predictive tools from mathematical epidemiology, including the basic reproductive ratio (R0) and herd immunity. In the model, banks and their creditors are assumed to have imperfect information about a newly-created security, and must search over the portfolios of other investors and intermediaries to infer the security's properties. In the absence of historical returns data, a large mass of firms holding the new security and not experiencing insolvency provides a positive signal about the distribution of its returns within the current period, and perpetuates further holding of the security. The model yields a set of structural equations that are used to construct the statistic. I provide two estimation strategies for the statistic; and identify 12 theoretical parameter restrictions that enable inference when only a subset of the model's parameters are identifiable. I use the approach to predict the spread of exchange traded funds (ETFs) and asset-backed securities (ABS). Additionally, I show how regulators can use the method to monitor the joint solvency of depository institutions within a given geographic region

UK imports, third country effect and the global financial crisis: Evidence from the asymmetric ARDL method

This paper examines the role of exchange rate volatility in determining real imports. As a robustness check, it further explores the impact of the recent global financial crisis which is a period characterized by heightened exchange rate volatility. More specifically, we investigate the impact of exchange rate volatility on UK real imports from Germany, Japan and the US during the period January 1991–March 2013. In contrast to most studies which focus on bilateral trade, we additionally explore the third country exchange rate volatility effect on UK imports. To capture the nonlinear features which often characterize macroeconomic data, we employ the asymmetric autoregressive distributed lag (ARDL) approach to cointegration. Our results suggest that exchange rate volatility plays an important role and reveal that there is a significant effect of the recent financial crisis on UK imports. This finding is consistent when we test for the third country volatility effect. Finally, we find that there is a significant causal relationship between exchange rate volatility and UK imports both in bilateral tests and in tests which account for the third country exchange rate volatility

Volatility in the Housing Market: Evidence on Risk and Return in the London Sub-market

The impact of volatility in housing market analysis is reconsidered via examination of the risk-return relationship in the London housing market is examined. In addition to providing the first empirical results for the relationship between risk (as measured by volatility) and returns for this submarket, the analysis offers a more general message to empiricists via a detailed and explicit evaluation of the impact of empirical design decisions upon inferences. In particular, the negative risk-return relationship discussed frequently in the housing market literature is examined and shown to depend upon typically overlooked decisions concerning components of the empirical framework from which statistical inferences are drawn