Realized Volatility and Asymmetries in the A.S.E. Returns

Using a newly developed dataset of daily, value-weighted market returns we construct and analyze the monthly realized volatility of the Athens Stock Exchange (A.S.E.) from 1985 to 2003. Our analysis focuses on the distributional and time series properties of the realized volatility series and on assessing the connection between realized volatility and returns. In particular, we find strong evidence on the existence of a volatility feedback effect and the leverage effect, and on the existence of asymmetries between lagged returns and volatility. Furthermore, we examine the cross-sectional distribution of unconditional loadings on the realized risk factor(s) for different sets of characteristics-sorted common stock portfolios. We find that realized risk is a significantly priced factor in A.S.E. and its high explanatory power for the cross- section of portfolio average returns is independent of any return variation related to the market (CAPM) or size and book-to-market (Fama- French) factors. We discuss our findings in the context of the recent literature on realized volatility and feedback effects, as well as the literature on the pricing power of realized risk.realized volatility, leverage effect, volatility feedback effect, asset pricing, A.S.E.

Consumer Confidence and Elections

We investigate the behavior of consumer confidence around national elections in the EU-15 countries during 1985:1-2007:3. Consumer confidence increases before the date of elections and falls subsequently by almost the same amount. It is able to predict the strength of the performance of the incumbent party and its probability of re-election both alone and in the presence of macroeconomic and fiscal variables. The post-election drop is negatively related to the previous run up and is a function of the political - but not the economic - environment. A similar rise and fall characterizes consumer confidence in the United States.consumer confidence, national elections, incumbent party, macro-economy, fiscal conditions, political business cycle, EU-15, USA.

Improving forecasting performance by window and model averaging

This study presents extensive results on the benefits of rolling window and model averaging. Building on the recent work on rolling window averaging by Pesaran et al (2010, 2009) and on exchange rate forecasting by Molodtsova and Papell (2009), we explore whether rolling window averaging can be considered beneficial on a priori grounds. We investigate whether rolling window averaging can improve the performance of model averaging, especially when ‘simpler’ models are used. The analysis provides strong support for rolling window averaging, outperforming the best window forecasts more than 50% of the time across all rolling windows. Furthermore, rolling window averaging smoothes out the forecast path, improves robustness, and minimizes the pitfalls associated with potential structural breaks.Exchange rate forecasting, inflation forecasting, output growth forecasting, rolling window, model averaging, short horizon, robustness.

NoVaS Transformations: Flexible Inference for Volatility Forecasting

In this paper we contribute several new results on the NoVaS transformation approach for volatility forecasting introduced by Politis (2003a,b, 2007). In particular: (a) we introduce an alternative target distribution (uniform); (b) we present a new method for volatility forecasting using NoVaS ; (c) we show that the NoVaS methodology is applicable in situations where (global) stationarity fails such as the cases of local stationarity and/or structural breaks; (d) we show how to apply the NoVaS ideas in the case of returns with asymmetric distribution; and finally (e) we discuss the application of NoVaS to the problem of estimating value at risk (VaR). The NoVaS methodology allows for a flexible approach to inference and has immediate applications in the context of short time series and series that exhibit local behavior (e.g. breaks, regime switching etc.) We conduct an extensive simulation study on the predictive ability of the NoVaS approach and find that NoVaS forecasts lead to a much ÔtighterÕ distribution of the forecasting performance measure for all data generating processes. This is especially relevant in the context of volatility predictions for risk management. We further illustrate the use of NoVaS for a number of real datasets and compare the forecasting performance of NoVaS -based volatility forecasts with realized and range-based volatility measures.ARCH, GARCH, local stationarity, structural breaks, VaR, volatility.

Forecasting Industry-Level CPI and PPI Inflation: Does Exchange Rate Pass-Through Matter?

In this paper, we examine whether industry-level forecasts of CPI and PPI inflation can be improved using the ``exchange rate pass-through" effect, that is, when one accounts for the variability of the exchange rate and import prices. An exchange rate depreciation leading to a higher level of pass-through to import prices implies greater expenditure switching, which should be manifested, possibly with a lag, in both producer and consumer prices. We build a forecasting model based on a two or three equation system involving CPI and PPI inflation where the effects of the exchange rate and import prices are taken into account. This setup also incorporates their dynamics, lagged correlations and appropriate restrictions suggested by the theory. We compare the performance of this model with a variety of unrestricted univariate and multivariate time series models, as well as with a model that, in addition, includes standard control variables for inflation, like interest rates and unemployment. Our results indicate that improvements on the forecast accuracy can be effected when one takes into account the possible pass-through effects of exchange rates and import prices on CPI and PPI inflation.Forecasting, Vector Autoregression, Non-linear Models, Inflation, Exchange Rates, Pass-Through Effect

The Implications of Retained and Distributed Earnings for Future Profitability and Market Mispricing

In this paper, we investigate the informational content of retained and distributed earnings for future profitability and market mispricing. We find that investors act as if the components of retained earnings (current operating accruals, non current operating accruals and retained cash flows) have similar implications for future profitability, leading to an overvaluation of their differential persistence. They also do not distinguish between the distinct properties of distributed earnings, correctly anticipate the persistence of net cash distributions to debt holders (net debt repayment) and underestimate the persistence of net cash distributions to equity holders (dividends minus net stock issues). Our evidence suggests that the accrual anomaly documented in the accounting literature and the anomaly on net stock issues documented in the finance literature could be a subset of a larger anomaly on retained earnings. Overall, our findings on the sources of this anomaly, indicate that it is primary attributable to investorÕs limited attention or limited cognitive power on understanding managerial empire building tendencies and managerial violation of accounting principles.retained earnings, distributed earnings, accruals, net stock issues, earnings management.

Median-Unbiased Optimal Smoothing and Trend Extraction

The problem of smoothing a time series for extracting its low frequency characteristics, collectively called its trend, is considered. A competitive approach is proposed and compared with existing methods in choosing the optimal degree of smoothing based on the distribution of the residuals from the smooth trend

Exchange Rate Pass-Through and Relative Prices: An Industry-Level Empirical Investigation

In this paper we explore the extent of exchange rate pass-through for the USA, UK and Japan using a post-Bretton Woods industry-level dataset. We investigate how different channels of exchange rate pass-through affect domestic and import prices. Our analysis is suggestive of two channels of transmission and we find considerable variation in the extent of pass-through across industries and countries.Exchange Rates, Pass-Through Effect, Expenditure-Switching

Inflation Dynamics and the Cross-Sectional Distribution of Prices in the E.U. Periphery

We explore the connection between inflation and its higher-order moments for three economies in the periphery of the European Union (E.U.), Greece, Portugal and Spain. Motivated by a micro-founded model of inflation determination, along the lines of the hybrid New Keynesian Phillips curve, we examine whether and how much does the cross-sectional skewness in producer prices affect the path of inflation. We develop our analysis with the perspective of economic integration/inflation harmonization (in the E.U.) and discuss the peculiarities of these three economies. We find evidence of a strong positive relation between aggregate inflation and the distribution of relative-price changes for all three countries. A potentially important implication of our results is that, if the cross-sectional skewness of prices is directly related to aggregate inflation, not only the direction but also the magnitude of a nominal shock would influence output and inflation dynamics. Moreover, the effect of such a shock could be received asymmetrically, even when countries share a common currency.Inflation; Cross-sectional distribution of prices; Greece, Portugal, Spain; European Union; Harmonization.

Optimal Linear Filtering, Smoothing and Trend Extraction for Processes with Unit Roots and Cointegration

In this paper I propose a novel optimal linear ølter for smoothing, trend and signal extraction for time series with a unit root. The filter is based on the Singular Spectrum Analysis (SSA) methodology, takes the form of a particular moving average and is di¨erent from other linear filters that have been used in the existing literature. To best of my knowledge this is the first time that moving average smoothing is given an optimality justification for use with unit root processes. The frequency response function of the filter is examined and a new method for selecting the degree of smoothing is suggested. I also show that the filter can be used for successfully extracting a unit root signal from stationary noise. The proposed methodology can be extended to also deal with two cointegrated series and I show how to estimate the cointegrating coe±cient using SSA and how to extract the common stochastic trend component. A simulation study explores some of the characteristics of the filter for signal extraction, trend prediction and cointegration estimation for univariate and bivariate series. The practical usefulness of the method is illustrated using data for the US real GDP and two financial time series. Classification-JEL:cointegration, forecasting, linear øltering, singular spectrum analysis, smoothing, trend extraction and prediction, unit root.