Nonlinear dynamics of interest rate and inflation
According to several empirical studies, US inflation and nominal interest rates, as well as the real interest rate, can be described as unit root processes. These results imply that nominal interest rates and expected inflation do not move one-for-one in the long run, which is not consistent with the theoretical models. In this paper we introduce a nonlinear bivariate mixture autoregressive model that seems to fit quarterly US data (1952 Q1 – 2000 Q2) reasonably well. It is found that the three-month treasury bill rate and inflation share a common nonlinear component that explains a large part of their persistence. The real interest rate is devoid of this component, indicating one-for-one m…
A Mixture Multiplicative Error Model for Realized Volatility
A multiplicative error model with time-varying parameters and an error term following a mixture of gamma distributions is introduced. The model is fitted to the daily realized volatility series of deutschemark/dollar and yen/dollar returns and is shown to capture the conditional distribution of these variables better than the commonly used autoregressive fractionally integrated moving average model. The forecasting performance of the new model is found to be, in general, superior to that of the set of volatility models recently considered by Andersen et al. (2003, Econometrica 71, 579--625) for the same data. Copyright 2006, Oxford University Press.
Nonlinear GARCH models for highly persistent volatility
In this paper we study new nonlinear GARCH models mainly designed for time series with highly persistent volatility. For such series, conventional GARCH models have often proved unsatisfactory because they tend to exaggerate volatility persistence and exhibit poor forecasting ability. Our main emphasis is on models that are similar to previously introduced smooth transition GARCH models except for the novel feature that a lagged value of conditional variance is used as the transition variable. This choice of the transition variable corresponds to the idea that high persistence in conditional variance is related to relatively infrequent changes in regime. U sing the theory of Markov chains w…
Robustness of the risk–return relationship in the U.S. stock market
Abstract Using GARCH-in-Mean models, we study the robustness of the risk–return relationship in monthly U.S. stock market returns (1928:1–2004:12) with respect to the specification of the conditional mean equation. The issue is important because in this commonly used framework, unnecessarily including an intercept is known to distort conclusions. The existence of the relationship is relatively robust, but its strength depends on the prior belief concerning the intercept. The latter applies in particular to the first half of the sample, where also the coefficient of the relative risk aversion is smaller and the equity premium greater than in the latter half.
Trends and Breaks in Per-Capita Carbon Dioxide Emissions, 1870-2028
We consider per-capita carbon dioxide emission trends in 16 early industrialized countries over the period 1870-2028. Using a multiple-break time series method we find more evidence for very early downturns in per-capita trends than for late downturns during the oil price shocks of the 1970s. Only for two countries do downturns in trends imply downward sloping stable trends. We also consider trends in emission composition and find little evidence for in-sample peaks for emissions from liquid and gaseous fuel uses. These results lead us to reject the oil price shocks as events causing permanent breaks in the structure and level of emissions, a conclusion often made in analyses using shorter …
Why Is It So Difficult to Uncover the Risk-Return Tradeoff in Stock Returns?
The low power of the standard Wald test in a GARCH-in-Mean model with an unnecessary intercept is shown to explain the apparent absence of a risk-return tradeoff in stocks. The importance of this finding is illustrated with monthly U.S. data. (c) 2006 Elsevier B.V. All rights reserved.
Modeling Conditional Skewness in Stock Returns
Abstract In this paper, we propose a new GARCH-in-Mean (GARCH-M) model allowing for conditional skewness. The model is based on the so-called z distribution capable of modeling skewness and kurtosis of the size typically encountered in stock return series. The need to allow for skewness can also be readily tested. The model is consistent with the volatility feedback effect in that conditional skewness is dependent on conditional variance. Compared to previously presented GARCH models allowing for conditional skewness, the model is analytically tractable, parsimonious and facilitates straightforward interpretation.Our empirical results indicate the presence of conditional skewness in the mon…
A Naïve Sticky Information Model of Households’ Inflation Expectations
This paper provides a simple epidemiology model where households, when forming their inflation expectations, rationally adopt the past release of inflation with certain probability rather than the forward-looking newspaper forecast as suggested in Carroll [2003, Macroeconomic Expectations of Households and Professional Forecasters, Quarterly Journal of Economics, 118, 269-298]. The posterior model probabilities based on the Michigan survey data strongly support the proposed model. We also extend the agent-based epidemiology model by deriving for it a simple adaptation, which is suitable for estimation. Our results show that this model is able to capture the heterogeneity in households’ expe…
Trading Nokia: The roles of the Helsinki vs the New York stock exchanges
We use the Autoregressive Conditional Duration (ACD) framework of Engle and Russell (1998) to study the effect of trading volume on price duration (ie the time lapse between consecutive price changes) of a stock listed both in the domestic and the foreign market. As a case study we use the example of Nokia's share, which is actively traded both in the Helsinki Stock Exchange and the New York Stock Exchange (NYSE). We find asymmetry in the volume-price duration relationship between the two markets. In the NYSE the negative relationship is much stronger and exists both during and outside common trading hours. Outside common trading hours no such relationship is significant in Helsinki. Based …
A Skewed GARCH-in-Mean Model: An Application to U.S. Stock Returns
In this paper we consider a GARCH-in-Mean (GARCH-M) model based on the so-called z distribution. This distribution is capable of modeling moderate skewness and kurtosis typically encountered in financial return series, and the need to allow for skewness can be readily tested. We apply the new GARCH-M model to study the relationship between risk and return in monthly postwar U.S. stock market data. Our results indicate the presence of conditional skewness in U.S. stock returns, and, in contrast to the previous literature, we show that a positive and significant relationship between return and risk can be uncovered, once an appropriate probability distribution is employed to allow for conditi…