beyond stochastic volatility and jumps in returns and volatility while a great deal of attention has been focused on stochastic volatility in stock returns there is strong evidence suggesting that return distributions have time varying skewness and kurtosis as well under the risk neutral measure for example this can be observed from variation across time in the shape of black scholes implied volatility smiles this article investigates model characteristics that are consistent with variation in the shape of return distributions using a stochastic volatility model with a regime switching feature to allow for random changes in the parameters governing volatility of volatility leverage effect and jump intensity the analysis consists of two steps first the models are estimated using only information from observed returns and option implied volatility standard model assessment tools indicate a strong preference in favor of the proposed models since the information from option implied skewness and kurtosis is not used in fitting the models it is available for dia

business cycle analysis with a markov switching model this article explores the hamilton markov switching model through an analysis of the business cycles of eight developed market economies forecasting and specification tests suggest only marginal improvements over linear autoregressive models yet filtered and smoothed conditional probabilities indicate turning points in business cycles that closely correlate with turning points from traditional methods tests regarding the asymmetry of business cycles reject the null of symmetry for most countries

mcmc based estimation of markov switching arma garch models regime switching models especially markov switching ms models are regarded as a promising way to capture nonlinearities in time series combining the elements of ms models with full autoregressive moving average generalized autoregressive conditional heteroskedasticity arma garch models poses severe difficulties for the computation of parameter estimators existing methods can become completely unfeasible due to the full path dependence of such models in this article we demonstrate how to overcome this problem we formulate a full ms arma garch model and its bayes estimator this facilitates the use of markov chain monte carlo methods and allows us to develop an algorithm to compute the bayes estimator of the regimes and parameters of our model the approach is illustrated on simulated data and with returns from the new york stock exchange nyse our model is then compared to other approaches and clearly proves to be advantageous

idiosyncratic variation of treasury bill yields i document a dramatic increase in the importance of two types of variation in treasury bill yields beginning in the early 1980s the first is idiosyncratic variation in individual short maturity less than three months bill yields the second is a common component in treasury bill yields that is not shared by yields on other instruments such as short maturity privately issued instruments or longer maturity treasury notes and bonds some evidence suggests the first type reflects increased market segmentation these results have important implications for the calibration and testing of no arbitrage term structure models and interpreting tests of the expectations hypothesis united states treasury bill yields play a central role in economists efforts to understand the behavior of financial markets the focus on treasury bills is driven by the belief that bill yields can be viewed as benchmarks from which yields on other debt instruments are derived for example in no arbitrage models of the default free term structure the stochastic properties of the hypothetical instantaneous interest rate determine bond prices researchers often construct and evaluate these models using short maturity bill yields as proxies for instantaneous interest rates similarly bill yields are frequently used to test the expectations hypothesis of the term structure 2 economists standard pricing models for default risky securities also view treasury yields as building blocks in such models yields on default risky securities depend at least in part on the yields of default free securities and the underlying stochastic default process therefore yields on treasury bills have been used in studies of the effects of monetary policy on the business cycle not because bills are intrinsically critical to the economy but because

estimation of an asymmetric stochastic volatility model for asset returns a stochastic volatility model may be estimated by a quasi maximum likelihood procedure by transforming to a linear state space form the method is extended to handle correlation between the two disturbances in the model and applied to data on stock returns

macroeconomic linkages taxes and subsidies in the u s agricultural sector lj ar division of agricultural sciences unlversily of califorj ha ma croecono nc linkages t xes and subsidies in tiie u s agr cuttural secl or by gordon c rausser james a chalfant h alan love and kostas g stamoulis tt r i f r in i jq lifor ia agricultura experiment station clmoation of j gricultural economics january 1986

investment allocation decisions home bias and the mandatory ifrs adoption abstract we examine the familiarity hypothesis of home bias by studying how foreign ownership of swedish firms is affected by the mandatory adoption of ifrs we decompose foreign investors into institutional and non institutional investors foreign investors are further decomposed into eu ifrs adopting countries and non eu residents non ifrs adopting countries we analyse the equity investments of these foreign investor groups in sweden during the period of 2001 2007 we find that after the mandatory adoption of ifrs foreign ownership owners from countries that adopted ifrs and particularly those from the eu increased these effects are particularly strong in small firms foreign institutional investors increased their ownership stake after the mandatory ifrs adoption whereas foreign non institutional investments were not affected significantly by the ifrs adoption in contrast to ownership from non adopting countries ownership from the eu increased in firms with both more and less tangible assets similarly foreign ownership from the eu increased in firms with both concentrated ownership and dispersed ownership after the adoption because sweden has already had strict legal enforcement and a low level of earnings management prior to the adoption our results suggest that increased foreign ownership is due to better abilities to compare firms rather than an improved quality

the stochastic volatility of short term interest rates some international evidence this paper estimates a stochastic volatility model of short term riskless interest rate dynamics estimated interest rate dynamics are broadly similar across a number of countries and reliable evidence of stochastic volatility is found throughout in contrast to stock returns interest rate volatility exhibits faster meanreverting behavior and innovations in interest rate volatility are negligibly correlated with innovations in interest rates the less persistent behavior of interest rate volatility reflects the fact that interest rate dynamics are impacted by transient economic shocks such as central bank announcements and other macroeconomic news the past decade has witnessed unprecedented growth in the market for fixedincome derivatives domestically as well as internationally in light of this growth recent research has attempted to empirically characterize the dynamics of short term riskless interest rates necessary for the valuation of many of these securities with few exceptions much of this evidence has been concerned with the behavior of u s interest rates the purpose of this paper is to investigate the dynamics of short term interest rates across a number of countries a particularly noteworthy feature at least of the u s evidence is that the volatility of short term interest rates is itself volatile the stochastic nature of volatility is an important property of interest rate dynamics which we wish to focus on in our comparison to do so practically this paper implements a computationally efficient and statistically reliable method for estimating stochastic volatility models in finance we apply this method to chan et al s 1992 specification of short term riskless interest rate dynamics augmented with stochastic volatility for a clean international comparison we use proxies for short term riskless interest rates drawn from the same market the london interbank market over the same sample period unlike nowman 1997 we find that the

differing degree of price flexibilities and the policy ineffectiveness proposition price regulations impart stickiness to prices the degree of response is analysed for three cpi subindex inflations freely determined regulated and mixed prices and of aggregate cpi inflation to anticipated and unanticipated monetary policies freely determined prices and aggregate cpi show similar responses but faster and larger adjustments than regulated prices to anticipated monetary policies the results imply that the extent to which monetary policies can influence prices depends on the degree of price inertia in various sectors for monetary authorities to control inflation effectively they need to focus on price movements in various sectors

effects of fiscal policies on us agriculture according to the macro rational expectation mre hypothesis only unanticipated macroeconomic policy has impacts on real economic variables and anticipated policy changes have no real impacts this study analysis the effects of the anticipated and unanticipated components of fiscal policy on the us farm real gnp by testing the neutrality and rationality propositions of the mre hypothesis the test results show that both the rationality and neutrality propositions are rejected the empirical findings indicate that the anticipated fiscal policy does have significant effects on farm output examination of a specific sector sheds light on the nature of the market and helps ascertain the resons for the non neutrality

oil prices and the impact of the financial crisis of 2007 2009 abstract oil prices increased dramatically during 2004 2006 industry experts initially attributed these price increases to fundamental factors such as the rise in global demand but also because of disruptions in the supply of oil the price increases however were so substantial that additional factors are needed to explain such dramatic changes we propose that the decline in the value of the u s dollar measured both by the appreciation of the euro and of gold prices played an important role as oil suppliers demanded compensation for the declining value of the dollar using a markov switching regime methodology we find evidence that this hypothesis is true prior to the financial crisis but its validity does not hold after the crisis when oil prices crashed and the dollar rallied

equity home bias and corporate disclosure abstract i show that more comprehensive corporate disclosure reduces investors uncertainty about domestic companies payoffs at no cost thereby decreasing investors equity home bias toward a country since investors should base their investment decisions on valid and easily interpretable company information only more comprehensive disclosure will reduce the home bias only if domestic securities law is sufficiently stratified and domestic companies use international accounting standards using panel data for 38 countries from 2003 to 2008 i find that more comprehensive disclosure reduces investors home bias though significantly only for countries that sufficiently enforce their securities law and implement international accounting standards

regime switching stochastic volatility evidence from the crude oil market this paper incorporates regime switching into the stochastic volatility sv framework in an attempt to explain the behavior of crude oil prices in order to forecast their volatility more specifically it models the volatility of oil return as a stochastic volatility process whose mean is subject to shifts in regime the shift is governed by a two state first order markov process the bayesian markov chain monte carlo method is used to estimate the models the main findings are first there is clear evidence of regime switching in the oil market ignoring it will lead to a false impression that the volatility is highly persistent and therefore highly predictable second incorporating regime switching into the sv framework significantly enhances the forecasting power of the sv model third the regime switching stochastic volatility model does a good job in capturing major events affecting the oil market

a maximum likelihood approach for non gaussian stochastic volatility models a maximum likelihood approach for the analysis of stochastic volatility models is developed the method uses a recursive numerical integration procedure that directly calculates the marginal likelihood only conventional integration techniques are used making this approach both flexible and simple experimentation shows that the method matches the performance of the best estimation tools currently in use new stochastic volatility models are introduced and estimated the model that best fits recent stock index data is characterized by a highly non gaussian stochastic volatility innovation distribution this model dominates a model that includes an autoregressive conditional heteroscedastic effect in the stochastic volatility process and a model that includes a stochastic volatility effect in the conditional mean

a markov model of heteroskedasticity risk and learning in the stock market abstract we examine a variety of models in which the variance of a portfolio s excess return depends on a state variable generated by a first order markov process a model in which the state is known to economic agents is estimated it suggests that the mean excess return moves inversely with the level of risk we then estimate a model in which agents are uncertain of the state the estimates indicate that agents are consistently surprised by high variance periods so there is a negative correlation between movements in volatility and in excess returns

a stochastic volatility model with markov switching this article presents a new way of modeling time varying volatility we generalize the usual stochastic volatility models to encompass regime switching properties the unobserved state variables are governed by a first order markov process bayesian estimators are constructed by gibbs sampling high medium and low volatility states are identified for the standard and poor s 500 weekly return data persistence in volatility is explained by the persistence in the low and the medium volatility states the high volatility regime is able to capture the 1987 crash and overlap considerably with four u s economic recession periods

relative prices and money a vector autoregression on brazilian data recent data on brazilian agricultural prices industrial prices and money supply are analyzed in a vector autoregression the empirical findings show strong one way granger type causality from money supply to agricultural prices while feedback is observed between industrial prices and money supply under the usual monetarist ordering of contemporaneous innovation covariance agricultural prices do not adjust faster than industrial prices to a shock in the money supply

does anticipated monetary policy matter an econometric investigation a heated debate has arisen over the policy ineffectiveness proposition associate with the work of lucas sargent and wallace it postulates that anticipated aggregate demand policy will have no effect on business cycle fluctuations so that one deterministic feedback policy rule is as good as any other from the point of view of stabilizing the economy this paper develops a methodology for empirically analyzing rational expectations models displaying this neutrality result and then applies it to the important question of whether anticipated monetary policy matters to the business cycle

markov switching and stochastic volatility diffusion models of short term interest rates this article empirically compares the markov switching and stochastic volatility diffusion models of the short rate the evidence supports the markov switching diffusion model estimates of the elasticity of volatility parameter for single regime models unanimously indicate an explosive volatility process whereas the markov switching models estimates are reasonable itis found that either markov switching or stochastic volatility but not both is needed to adequately fit the data a robust conclusion is that volatility depends on the level of the short rate finally the markov switching model is the best for forecasting a technical contribution of this article is a presentation of quasi maximum likelihood estimation techniques for the markov switching stochastic volatility model

macroeconomics and agriculture in tunisia this article aims to analyse the impact of changes in the monetary policy and the exchange rate on agricultural supply prices and exports the methodology used is based on the multivariate cointegration approach ten variables are considered interest and exchange rates money supply inflation agricultural output and input prices agricultural supply and exports income and the rate of commercial openness the sample period covers annual data from 1967 to 2002 due to the short sample period two subsystems are considered first long run relationships are identified in each subsystem second both subsystems are merged in order to calculate the short run dynamics the results indicate that changes in macroeconomic variables have an effect on the agricultural sector but the reverse effect does not hold

a markov model of switching regime arch in this article i present a new approach to model more realistically the variability of financial time series i develop a markov arch model that incorporates the features of both hamilton s switching regime model and engle s autoregressive conditional heteroscedasticity arch model to examine the issue of volatility persistence in the monthly excess returns of the three month treasury bill the issue can be resolved by taking into account occasional shifts in the asymptotic variance of the markov arch process that cause the spurious persistence of the volatility process i identify two periods during which there is a regime shift the 1974 2 1974 8 period associated with the oil shock and the 1979 9 1982 8 period associated with the federal reserve s policy change the variance approached asymptotically in these two episodes is more than 10 times as high as the asymptotic variance for the remainder of the sample i conclude that regime shifts have a greater impact on the properties of the data and i ca

relative prices and money further results for the united states empirical results support the hypothesis that agricultural prices respond faster than manufactured product prices to a change in money supply in the united states sims vector autoregression var technique was applied in examining this hypothesis the monte carlo integration method was used to test the significance of the impulse responses generated by the var technique

an error correcting model of farmland prices granger has demonstrated that if two variables are integrated of order one and are conitegrated they can be modelled as having been generated by an error correction mechanism cointegration and error correction systems allow long run components of variables to obey equilibrium constraints while short run components are allowed to have flexible dynamic specification using data from five corn belt states in the us we show that farmland prices and cash rents are each integrated of order one and are model is estimated the error correction term is found to be significant in both equations indicating granger causality running in both directions historical simulation of the model is performed the price equation peroformed better although both equations simulate reasonably well

yield factor volatility models the term structure of interest rates is often summarized using a handful of yield factors that capture shifts in the shape of the yield curve in this paper we develop a comprehensive model for volatility dynamics in the level slope and curvature of the yield curve that simultaneously includes level and garch effects along with regime shifts we show that the level of the short rate is useful in modeling the volatility of the three yield factors and that there are significant garch effects present even after including a level effect further we find that allowing for regime shifts in the factor volatilities dramatically improves the model s fit and strengthens the level effect we also show that a regime switching model with level and garch effects provides the best out of sample forecasting performance of yield volatility we argue that the auxiliary models often used to estimate term structure models with simulation based estimation techniques should be consistent with the main features of the yield curve that are identified by our model

aggregation and stabilization policy in a multi contract economy abstract this paper presents a model of a multi sector economy in which each sector is characterized by a different type of wage or price stickness the various sectors experience the same exogenous shocks and have the same money supply the analysis shows that demand shocks pose no serious problems for stabilization policy in contrast supply shocks may force the policymaker to choose between stability in one sector and stability in another the analysis also shows that the economist as to the economy s underlying structure and obscures the tradeoffs the policymaker must confront in particular a feedback rule chosen on the basis of an aggregate model could be either better or worse than a passive policy

price inertia and policy ineffectiveness in the united states 1890 1980 this paper introduces a new approach to the empirical testing of the lucas sargent wallace lsw policy ineffectiveness proposition which compares the lsw hypothesis with an alternative that states that prices respond fully in the long run but only gradually in the short run to nominal aggregate demand disturbances the empirical equations estimated for a new set of quarterly data extending back to 1890 exhibit uniformly high responses of real output and low responses of price changes to anticipated changes in nominal gnp the paper compares and tests three alternative methods of introducing persistence effects into the lsw framework

the volatility of short term interest rates an empirical comparison of alternative models of the term structure of interest rates we estimate and compare a variety of continuous time models of the short term riskless rate using the generalised method of moments we find that the most successful models in capturing the dynamics of the short term interest rate are those that allow the volatility of interest rate changes to be highly sensitive to the level of the riskless rate a number of well known models perform poorly in the comparisons because of their implicit restrictions on term structure volatility we show that these results have important implications for the use of different term structure models in valuing interest rate contingent claims and in hedging interest rate risk