Amélie Charles

Market Efficiency in the European Carbon Markets

In this paper, we study the relationship between futures and spot prices in the European carbon markets from the cost-of-carry hypothesis. The aim is to investigate the extent of efficiency market. The three main European markets (BlueNext, EEX and ECX) are analyzed during Phase II, covering the period from March 13, 2009 to January, 17, 2012. Futures contracts are found to be cointegrated with spot prices and interest rates for several maturities in the three CO2 markets. Results are similar when structural breaks are taken into account. According to individual and joint tests, the cost-of-carry model is rejected for all maturities and CO2 markets, implying that neither contract is priced according to the cost-of-carry model. The absence of the cost-of-carry relationship can be interpreted as an indicator of market inefficiency and may bring arbitrage opportunities in the CO2 market.

Does the day-of-the-week effect on volatility improve the volatility forecasts?

This study tests the presence of the day-of-the-week effect on stock market volatility of six European stock markets. Using a GARCH or GARCH-GJR specifications for the variance equation, we find that the day of week effect is present in volatility equation. Finally, we test whether the statistically significant in-sample findings regarding seasonality in volatility lead to better out-of-sample forecasts of volatility.

A Note on Unit Root Tests and GARCH Errors: A Simulation Experiment

This article re-examines the Monte Carlo experiments in Seo (1999) for unit root tests with GARCH errors. We report a Monte Carlo study with data generated from various GARCH(1, 1) processes where 0.8 ≤ α + β < 1 and β > α. In this case, the Dickey–Fuller test works better than the Seo test.

Stock Exchange Mergers and Market Efficiency

Abstract The aim of this article is to examine the impact of stock exchange mergers on the degree of informational efficiency. For this purpose, we apply the generalized spectral shape test for the martingale difference hypothesis to the stock returns before and after the 31 domestic and cross-border mergers completed from 1997 to 2011. The test is conducted with moving subsample windows, allowing us to detect the periods of (in)efficiency, and thus to conduct a comparative analysis for pre-merger and post-merger periods. We find that higher levels of efficiency are less frequent than lower levels of efficiency after a stock exchange merger. We also find that the impact on the level of efficiency depends on a range of merger characteristics such as the level of development, size, geographical diversification and industrial diversification of stock exchange.

Uncertainty and the Macroeconomy: Evidence from an Uncertainty Composite Indicator

ABSTRACT This article proposes a uncertainty composite indicator (UCI) based on three distinct sources of uncertainty (namely financial, political, and macroeconomic) for the US economy on the period 1985–2015. For that, we use a dynamic factor model, summarizing efficiently six individual uncertainty proxies, namely two macroeconomic and financial uncertainty factors based on the unpredictability, a measure of (micro)economic uncertainty, the implied volatility index, the corporate bond spreads, and an index of economic policy uncertainty. We then compare the effects of uncertainty on economic activity when the UCI is used instead of individual uncertainty proxies in structural VAR models. The interest of our UCI is to synthesize theses effects within one measure of uncertainty. Overall, the UCI was able to account for the most important dynamics of uncertainty which play an important role in business cycles.

International Stock Return Predictability: Evidence from New Statistical Tests

We investigate whether stock returns of international markets are predictable from a range of fundamentals including key financial ratios (dividend-price ratio, dividend-yield, earnings-price ratio, dividend-payout ratio), technical indicators (price pressure, change in volume), and short-term interest rates. We adopt two new alternative testing and estimation methods: the improved augmented regression method and wild bootstrapping of predictive model based on a restricted VAR form. Both methods take explicit account of endogeneity of predictors, providing bias-reduced estimation and improved statistical inference in small samples. From monthly data of 16 Asia-Pacific (including U.S.) and 21 European stock markets from 2000 to 2014, we find that the financial ratios show weak predictive ability with small effect sizes and poor out-of-sample forecasting performances. In contrast, the price pressure and interest rate are found to be strong predictors for stock return with large effect sizes and satisfactory out-of-sample forecasting performance.

Are Unit Root Tests Useful in the Debate over the (Non) Stationarity of Hours Worked

The performance of unit root tests on simulated series is compared, using the business-cycle model of Chang et al. (2007) to generate data. Overall, Monte Carlo simulations show that the e¢ cient unit root tests of Ng and Perron (2001) are more powerful than the standard unit root tests. These e¢ cient tests are frequnetly able (i) to reject the unit-root hypothesis on simulated series, using the best speci…-cation of the business-cycle model found by Chang et al. (2007), in which hours worked are stationary with adjustment costs, and (ii) to reduce the gap between the theoretical impulse response functions and those estimated with a Structural VAR model. The results of Monte Carlo simulations show that the hump-shaped behaviour of data can explain the divergence between unit root tests.

Adaptive Markets Hypothesis for Islamic Stock Portfolios: Evidence from Dow Jones Size and Sector-Indices

This paper analyzes the degree of return predictability (or weak-form informational efficiency) of Dow Jones Islamic and conventional size and sectorindices using the data from 1996 to 2013. Employing the automatic portmanteau and variance ratio tests for the martingale difference hypothesis of asset returns, we find that all Islamic and conventional portfolio returns have been predictable in a number of periods, consistent with the implications of the adaptive markets hypothesis. Overall, Islamic portfolios exhibit a higher degree of informational efficiency than the conventional ones, especially in the Consumer Goods, Consumer Services, Financials and Technology sectors. We also find that Islamic portfolios tend to be more efficient than the conventional ones during crisis periods

Stock Return Predictability: Evaluation Based on Prediction Intervals

This paper evaluates the predictability of monthly stock return using out-of-sample (multi-step ahead and dynamic) prediction intervals. Past studies have exclusively used point forecasts, which are of limited value since they carry no information about the intrinsic predictive uncertainty associated. We compare empirical performances of alternative prediction intervals for stock return generated from a naive model, univariate autoregressive model, and multivariate model (predictive regression and VAR), using the U.S. data from 1926. For evaluation free from data snooping bias, we adopt moving sub-sample windows of different lengths. It is found that the naive model often provides the most informative prediction intervals, outperforming those generated from the univariate model and multivariate models incorporating a range of economic and financial predictors. This strongly suggests that the U.S. stock market has been informationally efficient in the weak-form as well as in the semi-strong form, subject to the information set considered in this study.