Fredj Jawadi

Modelling Money Demand: Further Evidence from an International Comparison

This article aims at estimating money demand for the euro area, the United States and the United Kingdom using a Dynamic Ordinary Least Squares (DOLS) estimator. Our findings show that (1) wealth effects on money demand are important in the euro area and the United Kingdom; (2) the impact of changes in the interest rate on real money holdings is negative and small; (3) goods are a reasonable alternative to money and (4) international currency substitution has a major influence on the behaviour of real money demand in the United Kingdom.

NONLINEARITY, CYCLICITY, AND PERSISTENCE IN CONSUMPTION AND INCOME RELATIONSHIPS: RESEARCH IN HONOR OF MELVIN J. HINICH

This paper is dedicated to the memory of the great statistician Melvin J. Hinich, with whom we were in contact about this research prior to his untimely death from a tragic fall. We develop a neoclassical growth model with habit formation to exhibit an equilibrium nonlinear relationship between aggregate consumption growth and income growth. We first provide empirical evidence consistent with this relationship both for the United States and France, and we reject the hypothesis of a random walk for consumption. We then estimate this nonlinear relationship. We find for both countries robust evidence of persistence, nonlinearity, and cyclicity in the relationship between consumption and income.

Nonlinear mean reversion in oil and stock markets

Purpose - While price studies such as Jawadi Design/methodology/approach - Using nonlinear econometric modeling, this paper investigates the oil market adjustment dynamics for four developed and emerging countries: France, the USA, Mexico and the Philippines. Our findings show strong evidence of significant linkages between oil and stock markets for all the countries under consideration. Findings - As in Jawadi Research limitations/implications - This paper develops a new nonlinear framework that should improve the investigation of oil-stock market linkages. Future research could check the forecasting properties of this model to forecast the future dynamics of oil prices. Originality/value - This paper adds to the literature by suggesting that it is not only oil shocks that affect stock markets, but that the latter also have a strong nonlinear impact on oil markets, reducing the diversification benefits of oil-stock portfolios.

Chapter 6 Oil Prices and Exchange Rates: Some New Evidence Using Linear and Nonlinear Models

Purpose – The purpose of this chapter is to investigate the linear and nonlinear short- and long-run relationships between the real price of oil and the US real effective exchange rate. n nMethodology/approach – We use recent linear and nonlinear econometric techniques over the period 1973–2009. n nFindings – Our main findings are that (i) there is significant evidence that both variables contain a unit root; (ii) the oil price and the US exchange rate are strongly linked in the short run; and finally (iii) there are some signs of nonlinearity in the oil–exchange rate relationship. n nOriginality – Using recent econometric techniques, we show that exchange rates are not a fundamental determinant of oil prices but exchange rate changes help to better forecast oil prices in the short run.

Threshold Cointegration Relationships between Oil and Stock Markets

The aim of this paper is to study the oil price adjustment dynamics and to implicitly test the efficiency hypothesis for the oil market. Thus, we propose to study the oil price evolution in a nonlinear framework while testing the interdependence hypothesis between oil and stock markets. Four countries, the USA, France, Mexico and the Philippines are concerned by our findings which show several important results. Firstly, we show some evidence of linear linkage between stock markets and oil industry and we prove the existence of significant long-run relationships between oil and stock markets, indicating that the oil market is not efficient. Secondly, using nonlinear cointegration techniques, we propose a new nonlinear modeling to reproduce the oil price adjustment dynamics. It takes into account both stock and oil market variations. More importantly, the oil price is nonlinear, mean-reverting toward the equilibrium and with an adjustment speed that increases according to oil price deviations toward the stock market equilibrium.

Do the US trends drive the UK–French market linkages?: empirical evidence from a threshold intraday analysis

This article investigates the impact of US stock market openings on linkages between the UK and French markets. Using intraday data over the period December 2004 to March 2009, we find significant time-varying dependence between the UK and French stock returns, which alter according to the state of the US market. Indeed, not only does the opening of the US market itself significantly affect the UK stock dependency, but such linkages also seem to be closely dependent on bearish or bullish US market trends. Interestingly, the estimation of a two-regime Threshold Autoregressive (TAR) model indicates that the bearish US trends are a source of minor linkage (lower regime), whereas the bullish US trends involve higher interdependency (upper regime). This finding is particularly interesting as following the US trend expectations enables us to better forecast future European stock prices and to calculate the level of their potential contagion effects.

Measuring time-varying equity risk premium in the context of financial crisis: do developed and emerging markets differ?

Equity risk premium (RP) constitutes an interesting area of study in modern finance, as it is useful in assessing investor behaviour and risk aversion, estimating fundamental value and selecting optimal investment and portfolio options. Ex-ante RP is a key input factor in well-known financial models such as the Capital Asset Pricing Model (CAPM). It thus plays a crucial role in wealth allocation decisions about different financial assets and in evaluating the risk level. The specification of RP dynamics is therefore a major issue for financial economists, investors and traders. Interestingly, the highest stock market losses after the recent 2008/09 crisis involved considerable transaction trading declines, and might suggest significant changes to RP. Its measurement is therefore essential to improve investors’ decisions and to forecast future equity market dynamics during crisis periods. However, its estimation does not follow a unanimously agreed method as it depends on the sample period and the methodology used. Equity premium estimation has been the subject of several prior studies in the literature (Siegel and Thaler, 1997; Pastor and Stambaugh, 2001; Abou and Prat, 2010). In general, the authors highlight time-variation in RP dynamics, but such studies have not unanimously specified its determinants and factors. The divergence can be explained by the fact that the estimation of RP is not based entirely on observed values, but under conditions of uncertainty, expectation hypotheses and with respect to the risk-free rate. Accordingly, different methods have been implemented to estimate RP. Abou and Prat (2010) identified two important measurement methods for ex-ante RP: the Backward Approach and the Forward Approach. Whereas the former requires expectation assumptions and expresses the expected return according to the historic values of returns or other variables (dividends, earnings, interest rate, wealth, etc.), the Forward Approach relies on stock price forecast survey data and does not require any expectation hypotheses. Focusing uniquely on the few studies that showed the time-variation character in RP, we noted several explanations for time-variation in RP. First, ex-ante RP may vary as it requires forecasts made by market investors who can continuously revise them over time in line with business cycles. Indeed, microeconomic

Nonlinear Cointegration and Nonlinear Error-Correction Models: Theory and Empirical Applications for Oil and Stock Markets

Recently national markets around the world have become more interdependent due to the increasing process of economic globalization as well as to the rapid development of internet and telecommunication technologies. One of the major facts of the global finance is that asset price movements in one market can now spill over easily and quickly to another market. For this reason, one must consider the joint behavior of financial variables to better understand the dynamic nature of market interrelations. Traditionally, the relationship between any two variables can be investigated within the causality framework of Granger (1969) which bases itself upon on the predictability of time series. That is, if forecasts of a variable, say Y, using both past values of Y and those of another variable, say X, are better than forecasts obtained by using only past realizations of Y, then X is said to cause Y in the sense of Granger causality. Of course the direction of causality can be inversed. Notice also that the vector autoregressive (VAR) model popularized in econometric literature by Sims (1980), coupled with block exogeneity tests (or also referred to as Granger causality tests) is central to situations where the analysis requires a simultaneous equations framework rather than a single equation.

Essays in Nonlinear Financial Integration Modeling: The Philippine Stock Market Case

Emerging stock markets are one of the best areas for investment and have become more accessible to investors in recent years thanks to successive efforts to open up these markets. These markets not only offer investors generous returns and opportunities but also enable them to better diversify their portfolios. These efforts recently led to a significant increase in capital flows toward the region and a rise in emerging market capitalization that reached around 20 percent of world market capitalization in 2000. This also has a considerable impact on the emerging stock market industry. Indeed, in addition to the significant increase in the financial integration of emerging markets into the world market (Bekaert and Harvey 1995), the adjustment dynamics of their asset prices is almost simultaneously governed by internal, regional, and external economic, financial, and political factors (Adler and Qi 2003; Carrieri et al. 2007).

Chapter 2 Nonlinear Stock Market Links between Mexico and the World

Purpose – This chapter aims to investigate the stock market comovements between Mexico and the world capital market using nonlinear modeling tools. n nMethodology/approach – We apply recent nonlinear cointegration and nonlinear error correction models (NECMs) to investigate the comovements between stock prices over the recent period. n nFindings – While the previous literature only highlights some evidence of time-varying comovements, our chapter aims to specify the mechanism characterizing the comovement process through the comparison of two nonlinear error correction models (NECMs). It shows a nonlinear relationship between stock prices that are activated per regime. n nOriginality – Studying the integration hypothesis between stock markets over the recent financial crisis, our findings highlight strong evidence of significant comovements that explain the global collapse of stock markets in 2008–2009.