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

testing for nonlinear dependence in daily foreign exchange rates the purpose of this article is to investigate whether daily changes in five major foreign exchange rates contain any nonlinearities although the data contain no linear correlation evidence indicates the presence of substantial nonlinearity in a multiplicative rather than additive form further examination reveals that a generalized autoregressive conditional heteroskedasticity model can explain a large part of the nonlinearities for all five exchange rates copyright 1989 by the university of chicago

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

nonlinearities in economic dynamics two reasons that led to the dominance of the linear stochastic difference equations approach the first one was the fact that the nonlinear systems seemed incapable of reproducing the statistical aspects of actual economic time series at best such models were able to produce periodic motion1 and an examination of the spectra of economic time series showed the absence of the spikes that characterise periodic data the emphasis on the equilibrium approach to aggregate economic behaviour cf lucas i 986 would make things even more difficult the plethora of stability results for models of infinitely lived agents with perfect foresight turnpike theorems suggested that even the regular fluctuations that had been derived in the literature on endogenous business cycles were incompatible with a theory that had solid microeconomic foundations further this indicated that while nonlinearities could be present the explanations of the fluctuations had to rest solely on the presence of exogenous shocks that working through the equilibrating mechanism would create the observed randomness if such shocks were absent the system would tend to a stationary state the second reason was the empirical success of the models based on linear stochastic difference equations low order autoregressive processes captured some of the features of aggregate time series in turn these processes can in principle result from an economy with complete markets where production is subject to exogenous shocks though the task of confronting these equilibrium models with actual data has not yielded uncontroversial results see the discussion and references in section i there was no obvious gain in the

nonlinear monetary dynamics this article uses the correlation dimension technique along with the residual and shuffle tests to look for evidence of nonlinear dynamic structure in various weekly monetary aggregates their components the monetary base and the money multipliers the results support the barnett and chen 1988 and chen 1988 findings of nonlinearity in divisia m2 divisia m3 and simple sum m2 evidence of nonlinear structure is also found for simple sum m1 currency demand deposits all checkable deposits m3 minus m2 the monetary base and the multipliers of m1 m2 and m3

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

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

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

nonparametric modeling of carbon prices this paper constitutes the first exercise of nonparametric modeling applied to carbon markets the framework of analysis is carefully detailed and the empirical application unfolds in the case of bluenext spot and ecx futures prices the data is gathered in daily frequency from april 2005 to april 2010 first we document the presence of strong nonlinearities in the conditional mean functions second the conditional volatility functions reveal an asymmetric and heteroskedastic behavior which is dramatically different between carbon spot and futures logreturns the results for spot prices are also robust to subsamples decomposition third we show in an out of sample forecasting exercise that nonparametric modeling allows reducing the prediction error by almost 15 compared to linear ar models this latter result is confirmed by the diebold mariano pairwise test statistic

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 dow theory william peter hamilton s track record reconsidered alfred cowles test of the dow theory apparently provides strong evidence against the ability of wall street s most famous chartist to forecast the stock market cowles 1934 analyzes editorials published by the chief exponent of the dow theory william peter hamilton we review cowles evidence and find that it supports the contrary conclusion hamilton s timing strategies actually yield high sharpe ratios and positive alphas for the period 1902 to 1929 neural net modeling to replicate hamilton s market calls provides interesting insight into the dow theory and allows us to examine the properties of the theory itself out of sample alfred cowles test of the dow theory apparently provides strong evidence against the ability of wall street s most famious chartist william peter hamilton to forecast the stock market cowles 1934 analysis is a landmark in the development of empirical evidence about the informational efficiency of the market he claims that market timing based on the dow theory results in returns that lag the market in this paper we review cowles evidence and find that it supports the contrary conclusion the dow theory as applied by hamilton over the period 1902 to 1929 yields positive risk adjusted returns the difference in the results is apparently due to t he lack of adjustment for risk cowles compares the returns obtained from hamilton s market timing strategy to a benchmark of a fully invested stock portfolio in fact the hamilton portfolio as cowles interprets it is frequently out of the market adjustment for systematic risk appears to vindicate hamilton as a market timer to estimate the risk adjusted returns that may have been obtained by following the dow theory over the hamilton period we classify the miarket forecasts he made in the 255 editorials published in the wall street journal during his tenure as editor using the risk less rate as a benchmark we find that hamilton s ratio of correct to incorrect calls is higher than would be expected by chance using total return data for the cowles index of stock market returns and the s p index over the 27 year period we find that the

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 time series analysis of stock volatilities summary the absolute value of the mean corrected excess return is used in this paper to measure the volatility of stock returns we apply various nonlinearity tests available in the literature to show that such volatility series are strongly nonlinear we then explore the use of threshold autoregressive tar models in describing monthly volatility series the models built suggest that the volatility series exhibit significant lower order serial correlations when the volatility is large indicating certain volatility clustering in stock returns out of sample forecasts are used to compare the tar models with linear arma models and nonlinear garch and egarch models based on mean squared error and average absolute deviation the comparisons show that a the tar models consistently outperform the linear arma models in multi step ahead forecasts for large stocks b the tar models provide better forecasts than the garch and egarch models also for the volatilities of large stock returns and c the egarch model gives the best long horizon volatility forecasts for small stock returns

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

martingales nonlinearity and chaos abstract in this article we provide a review of the literature with respect to the efficient markets hypothesis and chaos in doing so we contrast the martingale behavior of asset prices to nonlinear chaotic dynamics discuss some recent techniques used in distinguishing between probabilistic and deterministic behavior in asset prices and report some evidence moreover we look at the controversies that have arisen about the available tests and results and raise the issue of whether dynamical systems theory is practical in finance

nonlinear dynamics in cee stock markets indices abstract we investigate the existence of nonlinearities in the dynamics of the returns of stock markets indices from cee economies we use several types of nonlinear tests we discuss the implications of the results with respect to the efficient market hypothesis

is the business cycle characterized by deterministic chaos abstract tests are conducted on u s macroeconomic data for the presence of low dimensional deterministic chaos where deterministic chaos is defined as in grandmont s 1985 walras bowley lecture or in brock 1986 the idea is to test for evidence of endogenous instability causing the business cycle low order autoregressions are hard to reject with our methods evidence of chaos is weak but our tests may be too weak to detect it evidence of nonlinearity is present in employment 1950 i to 1983 iv unemployment 1949 i to 1982 iv monthly post war industrial production and pig iron production 1877 1937

chaos significance mechanism and economic applications imagine a bargaining model say involving diplomats negotiating tariff levels or a disarmament treaty in which each party has been instructed by higher headquarters to respond to each new offer by her opposite number with a counteroffer that is to be calculated from a simple reaction function provided in advance both negotiating parties are prohibited from revealing their own reaction functions to the other if the perfectly deterministic sequence of offers and counteroffers that must emerge from these simple rules were to begin to oscillate wildly and apparently at random the negotiations could easily break down as each party not understanding the source of the problem came to suspect the other side of duplicity and sabotage yet all that may be involved as we will see is the phenomenon referred to as chaos a case that is emphatically not pathological but in which a dynamic mechanism that is very simple and deterministic yields a time path so complicated that it will pass most standard tests of randomness chaos has become a subject of great interest to specialists and nonspecialists alike besides economics it has entered the literature of geometry physics ecology and meteorology it has been written about at length in the new york times magazine and scientific american as well as technical publications this article seeks to describe what it is how it works and what it means for economics

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

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

asymmetry in the ems new evidence based on non linear forecasts abstract in this paper we provide new evidence on the hypothesis of german leadership and asymmetric performance in the ems in the framework of causality tests using daily data given the evidence about non linearity in financial series we propose applying non linear forecasting methods based on the literature on complex dynamic systems our analysis covers nine countries and the sample period runs until 30 april 1998 so including the more recent events in the ems history a comparison of our results with those obtained from standard linear econometric techniques leads us to conclude that inference on causality based on our non linear predictors would be preferable to that based on the standard linear approach

a search for long memory in international stock market returns abstract a major issue in financial economics is the behavior of stock returns over long as opposed to short horizons this study provides empirical evidence from the perspective of long memory analysis international evidence on long memory is explored using the morgan stanley capital international stock index data for eighteen countries two tests that are robust to short term dependence and conditional heteroskedasticity are employed a modified rescaled range test and a fractional differencing test the empirical results in general provide little support for long memory in international stock returns the findings are not sensitive to inflation adjustments in stock returns data sources and statistical methods used

statistical inference based upon non linear science abstract this paper discusses testing for the presence of deterministic chaos and presents probems surrounding such research statistical inference methods arising from the study of non linear dynamics are presented along with research utilizing these methods the general goal of these inference methods is to test for evidence of hidden structures in economic time series data which may lead to a greater understanding of how the economy functions while evidence of significant non linear structure has been demonstrated in many economic and financial time series precisely how important these structures are to economic science is a relevant issue

large shocks small shocks and economic fluctuations outliers in macroeconomic time series summary we analyse fifteen post world war i1 us macroeconomic time series using a modified outlier identification procedure based on tsay 1988a large shocks appear to be present in all the series we examined furthermore there are three basic outlier patterns i outliers seem to be associated with business cycles 2 outliers are clustered together both over time and across series 3 there appears to be a dichotomy between outlier behaviour of real versus nominal series also after controlling for outliers much of the evidence of non linearity in many of the time series is eliminated

the impact of consumer credit access on unemployment unemployed households access to unsecured revolving credit more than tripled over the last three decades this article analyses how both cyclical fluctuations and trend increases in credit access impact the business cycle the main quantitative result is that credit expansions and contractions have contributed to moderately deeper and more protracted recessions over the last 40 years as more individuals obtained credit from 1977 to 2010 cyclical credit fluctuations affected a larger share of the population and became more important determinants of employment dynamics even though business cycles are more volatile newborns strictly prefer to live in the economy with growing but fluctuating access to credit markets

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

testing for linear and nonlinear granger causality in the stock price volume relation linear and nonlinear granger causality tests are used to examine the dynamic relation between daily dow jones stock returns and percentage changes in new york stock exchange trading volume we find evidence of significant bidirectional nonlinear causality between returns and volume we also examine whether the nonlinear causality from volume to returns can be explained by volume serving as a proxy for information flow in the stochastic process generating stock return variance as suggested by clark s 1973 latent common factor model after controlling for volatility persistence in returns we continue to find evidence of nonlinear causality from volume to returns

are commodity prices chaotic we conduct tests for the presence of low dimensional chaotic structure in the futures prices of four important agricultural commodities though there is strong evidence of non linear dependence the evidence suggests that there is no long lasting chaotic structure the dimension estimates for the commodity futures series are generally much higher than would be for low dimension chaotic series our test results indicate that autoregressive conditional heteroskedasticity arch type processes with controls for seasonality and contract maturity effects explain much of the non linearity in the data we make a case that employing seasonally adjusted price series is important in obtaining robust results via some of the existing tests for chaotic structure finally maximum likelihood methodologies that are robust to the non linear dynamics lend strong support to the samuelson hypothesis of maturity effects in futures price changes 2002 elsevier science b v all rights reserved

cost allocation and opportunity costs one explanation for the widespread use of allocated fixed costs is that they can serve as a proxy for difficult to calculate opportunity costs this explanation is pursued by modeling a service department as an m m s s queueing system two main results are that the expected value of opportunity costs equals both the incremental productivity of capacity and the optimal transfer price when the cost of capacity is of the form cs as and is close to one we show that allocated fixed costs are a good proxy for average opportunity costs however if there are great economies of scale is close to zero then a method which charges users only for the variable costs of the service department is recommended finally the economic efficiency of transfer prices based on either variable cost or full cost is compared with optimal transfer pricing policies

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

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

linear versus nonlinear macroeconomies a statistical test a statistical test based on the estimated bispectrum is presented which can distinguish between the linear stochastic dynamics widely used in macroeconomic models and alternative nonlinear dynamic mechanisms including both nonlinear stochastic models and nonlinear deterministic chaotic models the test is applied to an aggregate stock market index and to an aggregate industrial production index in both cases the test easily rejects the null hypothesis of a linear stochastic generating mechanism this result strongly suggests that nonlinear dynamics deterministic or stochastic should be an important feature of any empirically plausible macroeconomic model copyright 1989 by economics department of the university of pennsylvania and the osaka university institute of social and economic research association

the operation of the hospital sector towards a diagnosis it is not surprising to find that most of the existing medical economics research has focused attention on the hospital sector since over 50 percent of all health care expenditures in most western countries cover hospital expenses what is surprising is the lack of a unified economic model for the operation of the hospital sector that goes beyond a piecemeal explanation for some specific institutional regularity it is the intent of this paper to use a traditional economic model of maximizing behavior to develop a general analysis of the hospital sector behavioral models of hospitals are surveyed by jacobs 28 many of the approaches are variants of the classic baumol model of output maximization 2 newhouse 36 and feldstein 17 consider utility maximization subject to a budget constraint with utility a function of both the quality and quantity of medical services in contrast pauly and redisch 38 examine a model in which physicians take an active role in determining the behavior of the not for profit hospital physicians with fixed hours of work maximize net per capita income recently harris 26 has offered a description of the internal operation of hospitals in which both physicians and administrators take an active role in management although the models mentioned provide specific predictions they do not provide a general analysis of the hospital sector furthermore questions concerning market segmentation alternative reimbursement procedures cost management waiting times bed management and occupancy rates are not addressed these issues are addressed in the model formulated in this paper the formal analysis of the present paper is developed within the environment of third party insurance in which all medical services offered by hospitals are financed out of general insurance revenues while consumers face no user charges 2 the technique of equalizing differences formalized by rosen 41 is used to analyze hospitals under competi

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

efficiency and the role of default when security markets are incomplete this paper argues that default plays an important positive role in the economy if markets are incomplete and traders are only able to enter into contracts that they will be able to execute regardless of future events contingent contracting may be severely restricted moreover opening new markets may not relieve these restrictions default promotes efficiency in a way that opening new markets does not by making it possible for traders to enter into contracts that they will be able to execute with high probability but not with certainty copyright 1993 by american economic association

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

implications of nonlinear dynamics for financial risk management this paper demonstrates that when log price changes are not iid their conditional density may be more accurate than their unconditional density for describing short term behavior using the bds test of independence and identical distribution daily log price changes in four currency futures contracts are found to be not iid while there appear to be no predictable conditional mean changes conditional variances are predictable and can be described by an autoregressive volatility model that seems to capture all the departures from independence and identical distribution based on this model daily log price changes are decomposed into a predictable part which is described parametrically by the autoregressive volatility model and an unpredictable part which can be modeled by an empirical density either parametrically or nonparametrically this two step seminonparametric method yields a conditional density for daily log price changes which has a number of uses in financial risk management

is the us business cycle asymmetric some further evidence evidence of nonlinearity in growth rates of monthly industrial production unit labour costs consumer prices and unemployment is reported and alternative representations of that nonlinearity exami

should the holding period matter for the intertemporal consumption based capm abstract empirical studies of the restrictions implied by the intertemporal capital asset pricing model across different asset markets have found conflicting evidence this paper asks whether an auxiliary assumption implicit in these tests could be responsible for the pattern of rejections this auxiliary assumption requires that covariances of returns with consumption move in constant proportion over time the paper tests this condition empirically using data on foreign exchange bonds and equity returns interestingly the evidence suggests that the tendency to reject the intertemporal consumption based asset pricing relationship depends upon the inadequacy of the auxiliary assumption not necessarily the relationship itself

trading asymmetric trend and volatility by leverage trend garch in taiwan stock index this article develops a leverage trend generalized autoregressive conditional heteroscedasticity garch model by incorporating asymmetric trend of returns of the exponential autoregressive and asymmetric volatility of garch models to study the asymmetric effects using in sample daily data of taiex over the period 4 january 1980 to 25 august 1997 and postsample daily data over the period 26 august 1997 to 10 september 2007 the evidence reveals that a curvaceous risk return relationship and both asymmetric volatility and asymmetric trend of returns are significant in taiex the episode of asymmetric trend of returns is that the positive information creates a higher return trend than the negative information of the same amount while similarly to most studies the evidence of asymmetric volatility appears that the negative information makes a higher volatility than the positive information of the same size most remarkably we evidence that the volatility asymmetry effect is a conservative trading factor

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

linear and nonlinear dependence in turkish equity returns and its consequences for financial risk management abstract this paper investigates the dynamic behaviour of daily aggregate returns of one of europe s largest and fastest growing emerging equity markets the istanbul stock exchange ise it is found that ise returns exhibit significant linear and nonlinear dependence we investigate the nature and source of the nonlinear dependence and find that it is due primarily to linear dependence in the conditional variance of returns rather than nonlinear dependence in the conditional mean we analyse the implications of our findings for financial risk management we show that by exploiting the nonlinear dependence in ise returns the average capital required to cover against unexpected portfolio losses can be considerably reduced in contrast exploiting the linear dependence in ise returns has only a negligible impact on capital requirements

the relationship between crude oil spot and futures prices cointegration linear and nonlinear causality the present study investigates the linear and nonlinear causal linkages between daily spot and futures prices for maturities of one two three and four months of west texas intermediate wti crude oil the data cover two periods october 1991 october 1999 and november 1999 october 2007 with the latter being significantly more turbulent apart from the conventional linear granger test we apply a new nonparametric test for nonlinear causality by diks and panchenko after controlling for cointegration in addition to the traditional pairwise analysis we test for causality while correcting for the effects of the other variables to check if any of the observed causality is strictly nonlinear in nature we also examine the nonlinear causal relationships of vecm filtered residuals finally we investigate the hypothesis of nonlinear non causality after controlling for conditional heteroskedasticity in the data using a garch bekk model whilst the linear causal relationships disappear after vecm cointegration filtering nonlinear causal linkages in some cases persist even after garch filtering in both periods this indicates that spot and futures returns may exhibit asymmetric garch effects and or statistically significant higher order conditional moments moreover the results imply that if nonlinear effects are accounted for neither market leads or lags the other consistently videlicet the pattern of leads and lags changes over time

nonlinear dynamics in real time equity market indices evidence from the united kingdom this paper tests for the presence of nonlinear dependence and chaos in real time returns on the u k ftse 100 index using a six month sample of about 60 000 observations since there is clear evidence of nonlinearity the authors follow other researchers in this field by applying the same tests to the residuals from a garch process fitted to the data in order to find out whether or not the nonlinearity can be explained by this type of model in the event their results suggest that garch can explain some but not all of the observed nonlinear dependence copyright 1995 by royal economic society

nonlinear behaviour of emerging market bonds spreads the latin american case in this article we check for nonlinear behaviour of the 10 most important latin american emerging market bonds spreads applying the hinich portmanteau bicorrelation test the bds test and the engle lm test we observe systematic nonlinear structure in the spreads series our results suggest that the nonlinear serial dependencies are episodic in nature all the stock returns series with the exception of mexico are characterized by few brief periods of highly significant nonlinearity followed by long time periods in which the returns follow a pure noise process our findings support the idea that even in this well informed and sophisticated market the weak form of the efficient market hypothesis cannot be supported

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

nonlinear business cycle modelling abstract literature which employs nonlinearities to explain economic fluctuations commonly called business cycles is surveyed relaxation of the linearity assumption significantly increases the range of possible dynamic solution paths and introduces the possibility that business cycles are endogenously determined the dominant post war modelling strategy has been the frisch 1933 and slutsky 1937 inspired one of developing essentially log linear economic models which produce damped cycles or monotonic damping to propagate the energy provided by repeated random or autocorrelated shocks the cycle is exogenously driven since it would die out in the absence of shocks deterministic nonstochastic nonlinear models can produce a wide range of endogenous fluctuations including stable limit cycles growth cycles and chaotic output which have the appearance of random fluctuations further the same model can produce qualitatively different outputs according to starting and parameter values if the possibility of shocks to parameters is admitted then behaviour can change abruptly following shocks evidence on the existence of nonlinearities and chaos in macroeconomic time series is assessed and alternative approaches to modelling dynamic economic development related to the work of keynes marx schumpeter and shackle are discussed their ideas have not proved readily amenable to mathematical modelling but attempts to encapsulate some of them are reviewed