bulls bears and market sheep abstract a deterministic excess demand model of stock market behavior is presented that generates stochastically fluctuating prices and randomly switching bear and bull markets

garch inadequacy for modelling exchange rates empirical evidence from latin america this article checks for the adequacy of using garch models in exchange rate series using the hinich portmanteau bicorrelation test we find that a garch formulation or any of its variants fails to capture the data generating process of the main latin american exchange rates our results highlight the potential of having misleading public policy when estimates are based in garch types of models this article also complements recent similar findings encountered in european and asian economies

chaos in oil prices evidence from futures markets abstract we test for the presence of low dimensional chaotic structure in crude oil heating oil and unleaded gasoline futures prices from the early 1980s evidence on chaos will have important implications for regulators and short term trading strategies while we find strong evidence of non linear dependencies the evidence is not consistent with chaos our test results indicate that arch type processes with controls for seasonal variation in prices generally explain the non linearities in the data we also demonstrate that employing seasonally adjusted price series contributes to obtaining robust results via the existing tests for chaotic structure maximum likelihood methodologies that are robust to the non linear dynamics lend support for samuelson s hypothesis on contract maturity effects in futures price changes however the tests for chaos are not found to be sensitive to the maturity effects in the futures contracts the results are robust to controls for the oil shocks of 1986 and 1991

uncovering nonlinear structure in real time stock market indexes the s p 500 the dax the nikkei 225 and the ftse 100 this article tests for nonlinear dependence and chaos in real time returns on the world s four most important stock market indexes both the brock dechert scheinkman and the lee white and granger neural network based tests indicate persistent nonlinear structure in the series estimates of the lyapunov exponents using the nychka ellner gallant and mccaffrey neural net method and the zeng pielke and eyckholt nearest neighbor algorithm confirm the presence of nonlinear dependence in the returns on all indexes but provide no evidence of low dimensional chaotic processes given the sensitivity of the results to the estimation parameters we conclude that the data are dominated by a stochastic component

alfred marshall lecture social capital as good culture to explain the extremely long term persistence more than 500 years of positive historical experiences of cooperation putnam 1993 we model the intergenerational transmission of priors about the trustworthiness of others we show that this transmission tends to be biased toward excessively conservative priors as a result societies can be trapped in a low trust equilibrium in this context a temporary shock to the return to trusting can have a permanent effect on the level of trust we validate the model by testing its predictions on the world values survey data and the german socio economic panel we also present some anecdotal evidence that these priors are reflected in novels that originate in different parts of the country jel 04 016 043 p16

episodic nonlinearity and nonstationarity in alberta s power and natural gas markets abstract this paper uses a new method of testing for linear and nonlinear lead lag relationships between time series introduced by brooks and hinich brooks c and hinich m j cross correlations and cross bicorrelations in sterling exchange rates journal of empirical finance 20 1999 385 404 on alberta s natural gas and power markets the test based on the concepts of cross correlation and cross bicorrelation is used after pre whitening of the data to test for the existence of residual nonlinearity as well as the episodic nature of the nonlinearity our evidence points to a relatively rare episodic nonlinearity within and across the two series having important implications for forecasting these series

the impact of obesity on wages abstract previous studies of the relationship between body weight and wages have found mixed results this paper uses a larger data set and several regres sion strategies in an attempt to generate more consistent estimates of the effect of weight on wages differences across gender race and ethnicity are explored this paperjnds that weight lowers wages for white females ols esti mates indicate that a difference in weight of two standard deviations roughly 65 pounds is associated with a difference in wages of 9 percent in absolute value this is equivalent to the wage effect of roughly one and a half years of education or three years of work experience negative cor relations between weight and wages observed for other gender ethnic groups appear to be due to unobserved heterogeneity i introduction several previous studies have found among females a negative cor relation between body weight and wages there exist three broad categories of ex planations for this finding the first explanation is that obesity lowers wages for example by lowering productivity or because of workplace discrimination the sec ond is that low wages cause obesity this would be true if poorer people consume

distinguishing between stochastic and deterministic behavior in foreign exchange rate returns further evidence abstract the nature of non linear dependence in hourly exchange rate returns is scrutinized while the brock dechert and scheinkman bds test results reject i i d behavior various correlation dimension estimates reveal little evidence in favor of a low dimensional attractor in the time series

predicting dax trends from dow jones data by methods of the mathematical theory of democracy abstract the mathematical theory of democracy operates on the indices of popularity and universality which are used to find socially optimal representatives and representative bodies regarded mathematically neither the society nor its representatives are necessarily human so that some objects can represent the behavior of other objects this idea is applied to predicting the dax trends german stock index from the actual dow jones data the current fluctuations of stock prices in new york are regarded as representative indicators of future stock price fluctuations in frankfurt in particular it is found that american express anticipates on the average the price fluctuations of 2 3 of the dax stocks the statistical significance of the null hypothesis that such a bias from the uncertainty 50 can occur by chance is only 3 5

complexity and the character of stock returns empirical evidence and a model of asset prices based on complex investor learning empirical evidence on the distributional characteristics of common stock returns indicates 1 a power law tail index close to three describes the behavior of the positive tail of the survivor function of returns pr r x x a reflection of fat tails 2 general linear and nonlinear dependencies exist in the time series of returns 3 the time series return process is characterized by short run dependence short memory in both returns as well as their volatility the latter usually characterized in the form of autoregressive conditional heteroskedasticity and 4 the time series return process probably does not exhibit long memory but the squared returns process does exhibit long memory we propose a model of complex self referential learning and reasoning amongst economic agents that jointly produces security returns consistent with these general observed facts and which are supported here by empirical results presented for a benchmark sample of 50 stocks traded on the new york stock exchange the market we postulate is populated by traders who reason inductively while compressing information into a few fuzzy notions that they can in turn process and analyze with fuzzy logic we analyze the implications of such behavior for the returns on risky securities within the context of an artificial stock market model dynamic simulation experiments of the market are conducted from which market clearing prices emerge allowing us to then compute realized returns we test the effects of varying values of the parameters of the model on the character of the simulated returns the results indicate that the model proposed in this paper can jointly account for the presence of a power law characterization of the positive tail of the survivor function of returns with exponent on the order of three for autoregressive conditional heteroskedasticity for long memory in volatility and for general nonlinear dependencies in returns

tick size the compass rose and market nanostructure abstract economists have begun using methods borrowed from the physical sciences to search for non linearities in economic and financial data the so called phase portrait from chaos theory in which the values of a time series are plotted against their delayed values is one of the techniques employed for this purpose it has recently been shown however that when returns on traded assets are plotted in this manner in two or three dimensional space surprising patterns arise which seriously distort the conclusions that can be drawn about the underlying data these patterns which resemble a compass rose reflect the microstructure of the market or more specifically the finite size of the ticks by which prices can change in a market the present paper clarifies the reason for this phenomenon it is shown that within the microstructure there exists nanostructure that becomes visible only when the computations are performed without approximation high frequency data from a foreign exchange market are used to illustrate this phenomenon

testing for non linear structure in an artificial financial market abstract we present a stochastic simulation model of a prototype financial market our market is populated by both noise traders and fundamentalist speculators the dynamics covers switches in the prevailing mood among noise traders optimistic or pessimistic as well as switches of agents between the noise trader and fundamentalist group in response to observed differences in profits the particular behavioral variant adopted by an agent also determines his decision to enter on the long or short side of the market short run imbalances between demand and supply lead to price adjustments by a market maker or auctioneer in the usual walrasian manner our interest in this paper is in exploring the behavior of the model when testing for the presence of chaos or non linearity in the simulated data as it turns out attempts to determine the fractal dimension of the underlying process give unsatisfactory results in that we experience a lack of convergence of the estimate explicit tests for non linearity and dependence the bds and kaplan tests also give very unstable results in that both acceptance and strong rejection of iidness can be found in different realizations of our model all in all this behavior is very similar to experience collected with empirical data and our results may point towards an explanation of why robustness of inference in this area is low however when testing for dependence in second moments and estimating garch models the results appear much more robust and the chosen garch specification closely resembles the typical outcome of empirical studies

a class of nonlinear arch models a class of nonlinear arch models is suggested the proposed class encompasses several functional forms for arch which have been put forth in the literature a lagrange multiplier test is developed to test engle s arch specification against the wider class of models this test provides an easily computed diagnostic check of the adequacy of an arch model after it has been estimated the theory is applied to a number of weekly exchange rate series and we find strong evidence of nonlinear arch

the slave trade and the origins of mistrust in africa in a recent study nunn 2008 examines the long term impacts of africa s slave trade he finds that the slave trade which occurred over a period of more than 400 years had a significant negative effect on long term economic development although the article arguably identifies a negative causal relationship between the slave trade and income today the analysis is unable to establish the exact causal mechanisms underlying this reduced form relationship in this article we examine one of the channels through which the slave trade may affect economic development today combining contemporary individual level survey data with historical data on slave shipments by ethnic group we ask whether the slave trade caused a culture of mistrust to develop within africa initially slaves were captured primarily through state organized raids and warfare but as the trade progressed the environment of ubiquitous insecurity caused individuals to turn on others including friends and family members and to kidnap trick and sell each other into slavery sigismund wilhelm koelle 1854 p e h hair 1965 charles piot 1996 we hypothesize that in this environment a culture of mistrust may have evolved which may persist to this day we show that current differences in trust levels within africa can be traced back to the transatlantic and indian ocean slave trades combining contemporary individual level survey data with historical data on slave shipments by ethnic group we find that individuals whose ancestors were heavily raided during the slave trade are less trusting today evidence from a variety of identification strategies suggests that the relationship is causal examining causal mechanisms we show that most of the impact of the slave trade is through factors that are internal to the individual such as cultural norms beliefs and values jel j15 n57 z13

chaos and the compass rose abstract we show that the recently discovered compass pattern in stock returns that results from discrete jumps of stocks seriously distorts the null distribution of the brock dechert scheinkmann bds chaos test under the null hypothesis of i i d returns the true rejection probability exceeds the nominal size by wide margins which suggests that much of the evidence for chaos that has so far been found in stock returns might well be due to the fact that prices change only in discrete ticks

nonlinear dependence in finnish stock returns abstract past research into the evolution of finnish stock returns focuses on modeling linear and nonlinear dependence using various arima and garch formulations respectively this paper extends the extant work by using grassberger procaccia correlations dimensions to explore the nature of the nonlinear dynamics in daily finnish stock returns during the 1970s and 1980s nonlinear behavior in both periods is evident a simple garch model removes the nonlinearity in the first decade and dramatically reduces the nonlinearity in the second period this supports the notion that finnish stock returns exhibit nonlinear dependence but that the form of dependence is not chaotic

nonlinear dynamics and stock returns simple deterministic systems are capable of generating chaotic output that mimics the output of stochastic systems for this reason algorithms have been developed to distinguish between these two alternatives these algorithms and related statistical tests are also useful in detecting the presence of nonlinear dependence in time series in this article the authors apply these procedures to stock returns and find evidence that indicates the presence of nonlinear dependence on weekly returns from the center for research in security prices value weighted index copyright 1989 by the university of chicago

pairs trading and outranking the multi step ahead forecasting case abstract pairs trading is a popular speculation strategy several implementation methods are proposed in the literature they can be based on a distance criterion or on co integration this article extends previous research in another direction the combination of forecasting techniques neural networks and multi criteria decision making methods electre iii the key contribution of this paper is the introduction of multi step ahead forecasts it leads to major changes in the trading system and raises new empirical and methodological questions the results of an application based on s p 100 index stocks are promising this methodology could be a powerful tool for pairs selection in a highly non linear environment

the euro dollar exchange rate chaotic or non chaotic a continuous time model with heterogeneous beliefs abstract the aim of this paper is to develop a continuous time exchange rate model that allows for heterogeneity of the agents beliefs in order to explore non linearities and possible chaotic behaviour the theoretical model contains an intrinsic non linearity that gives rise to a jerk differential equation which is in principle capable of generating chaos the model is econometrically estimated in continuous time with euro dollar data and examined for the possible presence of chaotic motion our results indicate that the possibility of chaotic dynamics in our model is rejected

statistical arbitrage pairs trading strategies review and outlook this survey reviews the growing literature on pairs trading frameworks i e relative value arbitrage strategies involving two or more securities research is categorized into five groups the distance approach uses nonparametric distance metrics to identify pairs trading opportunities the cointegration approach relies on formal cointegration testing to unveil stationary spread time series the time series approach focuses on finding optimal trading rules for mean reverting spreads the stochastic control approach aims at identifying optimal portfolio holdings in the legs of a pairs trade relative to other available securities the category other approaches contains further relevant pairs trading frameworks with only a limited set of supporting literature finally pairs trading profitability is reviewed in the light of market frictions drawing from a large set of research consisting of over 100 references an in depth assessment of each approach is performed ultimately revealing strengths and weaknesses relevant for further research and for implementation

multicriteria decision aid in financial management abstract the financial decisions of an organization are usually included in the context of optimization concerning a long term period there are decisions related to the optimal allocation of funds and decisions related to the optimal financial structure in the short term case the decisions are related to the optimization of stocks cash accounts receivable current liabilities etc the financial theory analyzes these decisions mainly from an optimal point of view the optimal character of such decisions has led researchers to propose operations research techniques to solve the problems that are inherent in such decisions this paper examines the contribution of multicriteria analysis in solving financial decision problems in a realistic context the paper also includes an extensive bibliography on the subject

an economic approach to social capital a standard optimal investment model can be used to analyse an individual s decision to accumulate social capital we analyse six facts that support the predictions of this individual based approach 1 social capital first rises and then falls with age 2 social capital declines with expected mobility 3 social capital rises in occupations with greater returns to social skills 4 social capital is higher among homeowners 5 social connections fall sharply with physical distance 6 people who invest in human capital also invest in social capital we fail to find robust evidence that social capital investments fall with the value of time or that geographic religious groups generate social capital complementarities

on nonlinear dynamics the case of the pork cycle new methods for analyzing nonlinear dynamic processes are used to evaluate the hogcorn price ratio the results present evidence of nonlinear dynamics in the pork cycle moreover while garch processes account for some of the nonlinearities the pork cycle is apparently characterized by more complex dynamic forms the empirical analysis provides some evidence of the presence of chaos in the pork cycle the results also indicate that the dynamic process generating the pork cycle is nonlinear and cannot be adequately characterized by a small number of state variables

initial labor market conditions and long term outcomes for economists each year graduate students entering the academic job market worry that they will suffer due to uncontrollable macroeconomic risk given the importance of general human capital and the relative ease of publicly observing productivity in academia one might expect that long term labor market outcomes for students graduating in unfavorable climates will resemble long term outcomes for those graduating in favorable climates in this paper i analyze the relationship between macroeconomic conditions at graduation initial job placement and long term outcomes for ph d economists from seven programs using macroeconomic conditions as an instrument for initial placement i show that a quality and type of initial job have a causal effect on long term job characteristics i also show that better initial placement increases research productivity which helps to limit the set of economic models that can explain the effect of initial placement on long term jobs

multiple criteria decision making combined with finance a categorized bibliographic study abstract this paper provides a categorized bibliography on the application of the techniques of multiple criteria decision making mcdm to problems and issues in finance a total of 265 references have been compiled and classified according to the methodological approaches of goal programming multiple objective programming the analytic hierarchy process etc and to the application areas of capital budgeting working capital management portfolio analysis etc the bibliography provides an overview of the literature on mcdm combined with finance shows how contributions to the area have come from all over the world facilitates access to the entirety of this heretofore fragmented literature and underscores the often multiple criterion nature of many problems in finance

multi group discrimination using multi criteria analysis illustrations from the field of finance abstract the primary objective in the discrimination problem is to assign a set of alternatives into predefined classes during the last two decades several new approaches such as mathematical programming neural networks machine learning rough sets multi criteria decision aid mcda etc have been proposed to overcome the shortcomings of traditional statistical and econometric techniques that have dominated this field since the 1930s this paper focuses on the mcda approach a new method to achieve multi group discrimination based on an iterative binary segmentation procedure is proposed five real world applications from the field of finance credit cards assessment country risk evaluation credit risk assessment corporate acquisitions business failure prediction are used to illustrate the efficiency of the proposed method as opposed to discriminant analysis

does social capital reduce crime abstract we investigate the effects of civic norms and associational networks on crime rates civic norms may attach guilt and shame to criminal behavior thus increasing its opportunity cost associational networks may increase returns to noncriminal activities and raise detection probabilities but they may also work as communication channels for criminals and may offer official cover to criminal activities the empirical assessment of these effects poses serious problems of endogeneity omitted variables measurement error and spatial correlation italy s great variance in social and economic characteristics its homogeneity in policies and institutions and the availability of historical data on social capital in its regions allow us to minimize the first two problems to tackle the last two problems we use report rate adjusted crime rates and estimate a spatial lag model we find that both civic norms and associational networks have a negative and significant effect on property crimes across italia

pairs trading performance of a relative value arbitrage rule we test a wall street investment strategy pairs trading with daily data over 1962 2002 stocks are matched into pairs with minimum distance between normalized historical prices a simple trading rule yields average annualized excess returns of up to 11 for self financing portfolios of pairs the profits typically exceed conservative transaction cost estimates bootstrap results suggest that the pairs effect differs from previously documented reversal profits robustness of the excess returns indicates that pairs trading profits from temporary mispricing of close substitutes we link the profitability to the presence of a common factor in the returns different from conventional risk measures wall street has long been interested in quantitative methods of speculation one popular short term speculation strategy is known as pairs trading the strategy has at least a 20 year history on wall street and is among the proprietary statistical arbitrage tools currently used by hedge funds as well as investment banks the concept of pairs trading is disarmingly simple find two stocks whose prices have moved together historically when the spread between them widens short the winner and buy the loser if history repeats itself prices will converge and the arbi

the role of social capital in financial development to identify the effect of social capital on financial development we exploit social capital differences within italy in high social capital areas households are more likely to use checks invest less in cash and more in stock have higher access to institutional credit and make less use of informal credit the effect of social capital is stronger where legal enforcement is weaker and among less educated people these results are not driven by omitted environmental variables since we show that the behavior of movers is still affected by the level of social capital of the province where they were born

non linear dependence modelling with bivariate copulas statistical arbitrage pairs trading on the s p 100 abstractwe develop a copula based pairs trading framework and apply it to the sp the top 5 momentum pairs yield 7 22 per year standard deviations are low leading to annualized sharpe ratios of 1 52 top 5 mean reversion and 1 33 top 5 momentum respectively

pairs selection and outranking an application to the s p 100 index pairs trading is a popular quantitative speculation strategy this article proposes a general and flexible framework for pairs selection the method uses multiple return forecasts based on bivariate information sets and multi criteria decision techniques our approach can be seen as a sort of forecast combination but the output of the method is a ranking it helps to detect potentially under and overvalued stocks a first application with s p 100 index stocks provides promising results in terms of excess return and directional forecasting

trust in large organizations several authors suggest that trust is an important determinant of cooperation between strangers in a society and therefore of performance of social institutions we argue that trust should be particularly important for the performance of large organizations in a cross section of countries evidence on government performance participation in civic and professional societies importance of large firms and the performance of social institutions more generally supports this hypothesis moreover trust is lower in countries with dominant hierarchical religions which may have deterred networks of cooperation trust hold up remarkably well on a cross section of countries this abstract was borrowed from another version of this item

why beauty matters we decompose the beauty premium in an experimental labor market where employers determine wages of workers who perform a maze solving task this task requires a true skill which we show to be unaffected by physical attractiveness we find a sizable beauty premium and can identify three transmission channels a physically attractive workers are more confident and higher confidence increases wages b for a given level of confidence physically attractive workers are wrongly considered more able by employers c controlling for worker confidence physically attractive workers have oral skills such as communication and social skills that raise their wages when they interact with employers our methodology can be adopted to study the sources of discriminatory pay differentials in other settings

exchange rate dynamics central bank interventions and chaos control methods abstract we use a simple chartist fundamentalist model developed by day and huang to explore recent chaos control algorithms as potential candidates for central bank intervention rules we find that methods such as delayed feedback control ogy and constant feedback have in principle the potential to reduce exchange rate variability and deviations from fundamentals even in the presence of large dynamic noise

chaotic dynamics in a cash in advance economy abstract this paper introduces sufficient conditions for the existence of deterministic cycles and chaos in cash in advance models building on the earlier work of woodford 1994 chaotic equilibria are shown to be particularly likely in the cash in advance model because of a unique characteristic of such models a discontinuous derivative in the difference equation map at the satiation level of real balances the existence of a kink means that chaotic equilibria may exist without implausibly large curvatures in the utility function since a chaotic time series that makes use of the kink would sometimes exhibit zero nominal interest rates the paper also gives an example of chaos in which nominal interest rates remain strictly positive

deep learning with long short term memory networks for financial market predictions abstract long short term memory lstm networks are a state of the art technique for sequence learning they are less commonly applied to financial time series predictions yet inherently suitable for this domain we deploy lstm networks for predicting out of sample directional movements for the constituent stocks of the s p 500 from 1992 until 2015 with daily returns of 0 46 percent and a sharpe ratio of 5 8 prior to transaction costs we find lstm networks to outperform memory free classification methods i e a random forest raf a deep neural net dnn and a logistic regression classifier log the outperformance relative to the general market is very clear from 1992 to 2009 but as of 2010 excess returns seem to have been arbitraged away with lstm profitability fluctuating around zero after transaction costs we further unveil sources of profitability thereby shedding light into the black box of artificial neural networks specifically we find one common pattern among the stocks selected for trading they exhibit high volatility and a short term reversal return profile leveraging these findings we are able to formalize a rules based short term reversal strategy that yields 0 23 percent prior to transaction costs further regression analysis unveils low exposure of the lstm returns to common sources of systematic risk also compared to the three benchmark models

credit risk assessment using a multicriteria hierarchical discrimination approach a comparative analysis corporate credit risk assessment decisions involve two major issues the determination of the probability of default and the estimation of potential future benefits and losses for credit granting the former issue is addressed by classifying the firms seeking credit into homogeneous groups representing different levels of credit risk classification discrimination procedures commonly employed for such purposes include statistical and econometric techniques this paper explores the performance of the m h dis method multi group hierarchical discrimination an alternative approach that originates from multicriteria decision aid mcda the method is used to develop a credit risk assessment model using a large sample of firms derived from the loan portfolio of a leading greek commercial bank a total of 1411 firms are considered in both training and holdout samples using financial information through the period 1994 1997 a comparison with discriminant analysis da logit analysis la and probit analysis pa is also conducted to investigate the relative performance of the m h dis method as opposed to traditional tools used for credit risk assessment 2002 elsevier science b v all rights reserved

stabilization policy can lead to chaos stabilization policy can lead to chaos nonlinearities in economies as elsewhere can generate chaotic equilibria the presence of pareto inferior chaotic equilibria might seem reason enough to use stabilization policy to select preferable equilibria however i show that a stabilization policy with feedback can itself lead to chaotic dynamics thus the existence of nonlinearities in the economy does not by itself justify monetary or fiscal policies aimed at reducing economic instability current evidence cannot distinguish whether monetary policy stabilizes a nonlinear economy creates nonlinear dynamics in the economy or both i introduction in recent years the claim has been made that nonlinearities and self fulfilling expectations in the private economy generate economic instability that can and should be offset by government policies this instability shows up as a positive variance in the steady state of an economy that otherwise would have a steady state with zero variance and higher utility for households on the basis of such models grandmont and malgrange 1986 9 conclude that we should expect a free market economy to perform rather badly under laissez faire in addition there is a possible role for deterministic stabilization policies that would if understood and believed eliminate forecasting mistakes and the corresponding efficiency losses and would guarantee the ultimate disappearance of endogenous fluctuations the purpose of this note is to provide a simple example of stabilization policy leading to chaotic time series behavior this example is an elaboration of friedman s 1953 classic argument that with uncertain knowledge about the economy stabilization policy can increase the variance of the goal variable nonlinearities can make as much a case against stabilization policy as for it the example is ad hoc in some respects but it is based on common ingredients of many models ii a simple example interesting aspects of an economy can be summarized by the quantity equation 1 mv y assume that real income y is constant which implies that changes in nominal income are proportional to changes in the price level in one respect using the quantity equation means that the example below does not have the same force as a tight general equilibrium model of the economy without the underlying detail equation 1 is ad hoc in another respect the example below has more force an equation such as 1 commonly characterizes the general equilibrium models in which money has a significant effect on the economy hence one interpretation is that the example has some generality assume that the monetary authority targets nominal income and knows 1 that the quantity theory characterizes the long run equilibrium of the economy and 2 the level of velocity that is consistent with zero inflation v in these circumstances there is one obvious equilibrium consistent with the goal the money stock is constant and the public expects a constant money supply and zero inflation in this equilibrium nominal income can be stabilized at the target level of nominal income y the monetary authority just need set the money supply to m v 1y if the monetary authority is uncertain about the public s response to its actions one strategy is to adopt a cautious stabilization policy to support the economy s approach to the long run deterministic equilibrium one commonly proposed set of feedback rules is the proportional policies introduced by phillips 1954 in the levels such a rule for the money supply is 2 m m alpha y y sub 1 where y sub 1 is last period s nominal income and alpha is the adjustment parameter assume that private agents believe that the monetary authority eventually will accomplish its goal of setting y equal to y

a weighty issue revisited the dynamic effect of body weight on earnings and satisfaction in germany we estimate the relationship between changes in the body mass index bmi and wages or satisfaction respectively in a panel of german employees in contrast to previous findings our dynamic models indicate an inverse u shaped association between bmi and wages as the implied maximum occurs in the overweight category the positive trend in weight may not yet constitute a major limitation to productivity further investigation points out a stronger association among young workers and workers with jobs that are less protected work satisfaction of young workers is associated with bmi beyond the effect of earnings

cointegration and detectable linear and nonlinear causality analysis using the london metal exchange lead contract this study applies linear and nonlinear granger causality tests to examine the dynamic relation between london metal exchange lme cash prices and three possible predictors the analysis uses matched quarterly inventory uk treasury bill interest rates futures prices and cash prices for the commodity lead traded on the lme the effects of cointegration on both linear and nonlinear granger causality tests is also examined when cointegration is not modelled evidence is found of both linear and nonlinear causality between cash prices and analysed predictor variables however after controlling for cointegration evidence of significant nonlinear causality is no longer found these results contribute to the empirical literature on commodity price forecasting by highlighting the relationship between cointegration and detectable linear and nonlinear causality the importance of interest rate and inventory as well as futures price in forecasting cash prices is also illustrated failure to detect significant

non linear granger causality in the currency futures returns abstract this paper examines the relationship between currency futures returns by employing a test for non linear causality the results indicate evidence of unidirectional non linear causality relationship in four cases however after filtering the returns using a garch 1 1 model we find insignificant and statistically weaker non linear causality relationships

the effect of adolescent experience on labor market outcomes the case of height taller workers receive a wage premium net of differences in family background the disparity is similar in magnitude to the race and gender gaps we exploit variation in an individual s height over time to explore how height affects wages controlling for teen height essentially eliminates the effect of adult height on wages for white men the teen height premium is not explained by differences in resources or endowments the teen height premium is partially mediated through participation in high school sports and clubs we estimate the monetary benefits of a medical treatment for children that increases height

deep neural networks gradient boosted trees random forests statistical arbitrage on the s p 500 abstract in recent years machine learning research has gained momentum new developments in the field of deep learning allow for multiple levels of abstraction and are starting to supersede well known and powerful tree based techniques mainly operating on the original feature space all these methods can be applied to various fields including finance this paper implements and analyzes the effectiveness of deep neural networks dnn gradient boosted trees gbt random forests raf and several ensembles of these methods in the context of statistical arbitrage each model is trained on lagged returns of all stocks in the s p 500 after elimination of survivor bias from 1992 to 2015 daily one day ahead trading signals are generated based on the probability forecast of a stock to outperform the general market the highest k probabilities are converted into long and the lowest k probabilities into short positions thus censoring the less certain middle part of the ranking empirical findings are promising a simple equal weighted ensemble ens1 consisting of one deep neural network one gradient boosted tree and one random forest produces out of sample returns exceeding 0 45 percent per day for k 10 prior to transaction costs irrespective of the fact that profits are declining in recent years our findings pose a severe challenge to the semi strong form of market efficiency

some evidence concerning macroeconomic chaos abstract an empirical assessment of a linear stochastic perspective for canadian macroeconomic time series is presented the methods used are based on the mathematics of chaos present evidence suggests that low order deterministic chaos does not provide a satisfactory characterization of the data the absence of significant nonlinear structure for the investment and unemployment series is of particular note in light of past findings with american data the degree to which the use of a time trend can impose a pseudo structure on the data is illustrated

when does weight matter most past empirical work establishes a wage penalty from being overweight in this paper i exploit variation in an individual s weight over time to determine the age when weight has the largest impact on labor market outcomes for white men controlling for weight at younger ages does not eliminate the effect of older adult weight on wage being overweight as a young adult only adds an additional penalty to adult wages however for white women what they weigh in their early twenties solely determines the existence of an adult wage penalty the female early twenties weight penalty has a persistent effect on wages and differences in marital characteristics occupation status or education cannot explain it it also is not a proxy for intergenerational unobservables

long lasting differences in civic capital evidence from a unique immigration event in italy a range of evidence exists demonstrating that social capital is associated with a number of important economic outcomes such as economic growth trade and crime a recent literature goes further to illustrate how historical events and variation can lead to the development of differing and consequential social norms this paper examines the related questions of how persistent initial variations in social capital are and the extent to which immigrant groups do or do not converge to the cultural and social norms of their recipient country by examining a unique and geographically concentrated immigration event in 16th century italy we demonstrate that despite the substantial time since migration these communities still display different behavior consistent with higher civic capital than other comparable italian communities moreover we demonstrate that this difference does not appear to have changed over the last 70 years for instance differences in voter turnout apparent in the late 1940s remain in the 21st century this latter finding has implications for our view of the likelihood of assimilation of immigrant groups to local norms particularly in cases of large scale migration

some empirical evidence on the time series properties of four uk asset prices in this paper the authors examine the time series behavior of four u k asset prices and estimate two types of models for the differenced series much previous research has found the presence of time varying heteroskedasticity in the error process for asset prices a linear model with gqarch errors is compared to a joint bilinear model with gqarch errors the latter choice motivated by the ability of bilinear models to capture turbulent behavior the adequacy of these models is determined by examining simulations and also employing test statistics the forecasting performance of the two models is also compared copyright 1996 by the london school of economics and political science