Robustness of the CUSUM and CUSUM-of-Squares Tests to Serial Correlation, Endogeneity and Lack of Structural Invariance. Some Monte Carlo Evidence

This paper investigates by means of Monte Carlo techniques the robustness of the CUSUM and CUSUM-of-squares tests (Brown et al., 1975) to serial correlation, endogeneity and lack of structural invariance. Our findings suggest that these tests perform better in the context of a dynamic model of the ADL type, which is not affected by serial correlation or nonpredetermined regressors even if over-specified. In this case, the empirical sizes of both tests are close to the nominal ones, whether a stationary or a cointegration environment is considered. The CUSUM-of-squares test is to be preferred, as it is very powerful to detect changes in the conditional model parameters, whether or not the variance of the regression error is included in the set of parameters shifting, especially towards the end of the sample.CUSUM and CUSUM-of-squares tests, Parameter instability, Structural invariance, Marginal and conditional processes, ADL model

Looking far in the past: Revisiting the growth-returns nexus with non-parametric tests

In this paper we reexamine the linkages between output growth and real stock price changes for the G7 countries using a battery of non-parametric procedures to account for the impact of long-lagged observations. We find that correlation between growth and returns is detected at larger horizons than those typically employed in parametric studies. The major feedbacks emerge from stock price changes to growth within the first 6 to 12 months, but we show that significant feedbacks may last for up to two or three years. Our evidence also suggests that the correlation patterns differ substantially between the countries at hand when the sectoral share indices are considered.real stock price changes, output growth, long-run covariance matrix

Parameter Instability and Forecasting Performance. A Monte Carlo Study

This paper uses Monte Carlo techniques to assess the loss in terms of forecast accuracy which is incurred when the true DGP exhibits parameter instability which is either overlooked or incorrectly modelled. We find that the loss is considerable when a FCM is estimated instead of the true TVCM, this loss being an increasing function of the degree of persistence and of the variance of the process driving the slope coefficient. A loss is also incurred when a TVCM different from the correct one is specified, the resulting forecasts being even less accurate than those of a FCM. However, the loss can be minimised by selecting a TVCM which, although incorrect, nests the true one, more specifically an AR(1) model with a constant. Finally, there is hardly any loss resulting from using a TVCM when the underlying DGP is characterised by fixed coefficients.Fixed coefficient model, Time varying parameter models, Forecasting

On The Equivalence Of The Mean Variance Criterion And Stochastic Dominance Criteria

We study the necessary and sufficient conditions under which the Mean-Variance Criterion (MVC) is equivalent to the Maximum Expected Utility Criterion (MEUC), for two lotteries. Based on Chamberlain (1983), we conclude that the MVC is equivalent to the Second-order Stochastic Dominance Rule (SSDR) under any symmetric Elliptical distribution. We then discuss the work of Schuhmacher et al. (2021). Although their theoretical findings deduce that the Mean-Variance Analysis remains valid under Skew-Elliptical distributions, we argue that this does not entail that the MVC coincides with the SSDR. In fact, generating multiple MV-pairs that follow a Skew-Normal distribution it becomes evident that the MVC fails to coincide with the SSDR for some types of risk-averse investors. In the second part of this work, we examine the premise of Levy and Markowitz (1979) that "the MVC deduces the maximization of the expected utility of an investor, under any approximately quadratic utility function, without making any further assumption on the distribution of the lotteries". Using Monte Carlo Simulations, we find out that the set of approximately quadratic utility functions is too narrow. Specifically, our simulations indicate that $\log{(a+Z)}$ and $(1+Z)^a$ are almost quadratic, while $-e^{-a(1+Z)}$ and $-(1+Z)^{-a}$ fail to approximate a quadratic utility function under either an Extreme Value or a Stable Pareto distribution

Dynamic Estimates Of The Arrow-Pratt Absolute And Relative Risk Aversion Coefficients

We derive a closed-form expression capturing the degree of Relative Risk Aversion (RRA) of investors for non-"fair" lotteries. We argue that our formula is superior to earlier methods that have been proposed, as it is a function of only three variables. Namely, the Treasury yields, the returns and the market capitalization of a specific market index. Our formula, is tested on CAC 40, EURO, S&P 500 and STOXX 600, with respect to the market capitalization of each index, for different time periods. We deduce that the investors in these markets exhibit Decreasing Absolute Risk Aversion (DARA) through all the different time periods that we consider, while the degree of RRA has altered between being constant, decreasing or increasing. Furthermore, we propose a simple and intuitive way to measure the degree to which a wrong assumption with respect to the utility function of an investor will affect the structure of his portfolio. Our method is built on a two asset portfolio framework. Namely, a portfolio consisting of one risky and one risk-free asset. Applying our method, the empirical findings indicate that the weight invested in the risky asset varies substantially even among utility functions with similar characteristics

The Contribution of Growth and Interest Rate Differentials to the Persistence of Real Exchange Rates

This paper employs a new methodology for measuring the contribution of growth and interest rate differentials to the half-life of deviations from Purchasing Power Parity (PPP). Our method is based on directly comparing the impulse response function of a VAR model, where the real exchange rate is Granger caused by these variables with the impulse response function of a univatiate ARMA model for the real exchange rate. We show that the impulse response function of the VAR model is not, in general, the same with the impulse response function obtained from the equivalent ARMA representation, if the real exchange rate is Granger caused by other variables in the system. The difference between the two functions captures the effects of the Granger-causing variables on the half-life of deviations from PPP. Our empirical results for a set of four currencies suggest that real and nominal long term interest rate differentials and real GDP growth differentials account for 22% to 50% of the half-life of deviations from PPP.real exchange rate; persistence measures; VAR; impulse response function; PPP.

The Contribution of Growth and Interest Rate Differentials to the Persistence of Real Exchange Rates.

This paper employs a new methodology for measuring the contribution of growth and interest rate differentials to the half-life of deviations from Purchasing Power Parity (PPP). Our method is based on directly comparing the impulse response function of a VAR model, where the real exchange rate is Granger caused by these variables with the impulse response function of a univatiate ARMA model for the real exchange rate. We show that the impulse response function of the VAR model is not, in general, the same with the impulse response function obtained from the equivalent ARMA representation, if the real exchange rate is Granger caused by other variables in the system. The difference between the two functions captures the effects of the Granger-causing variables on the half-life of deviations from PPP. Our empirical results for a set of four currencies suggest that real and nominal long term interest rate differentials and real GDP growth differentials account for 22% to 50% of the half-life of deviations from PPP.real exchange rate; persistence measures; VAR; impulse response function; PPP

Selectivity, Market Timing and the Morningstar Star-Rating System

This paper evaluates the Morningstar mutual fund ranking system. We find that indeed higher Morningstar ratings are associated with higher returns on the portfolios including respectively five-, four-, three-, two- and one-star funds only (STAR5 to STAR1). We then perform an unconditional and conditional portfolio performance evaluation. In both cases the evidence suggests that the better performance of the STAR3, STAR4 and STAR5 categories reflects superior stock selection rather than market timing abilities. Overall, the implication for the Morningstar ranking system is that this is most effective in identifying the worst-performing funds (STAR1 or STAR2) rather than the best-performing ones.mutual fund, Morningstar Star-Rating System, CAPM, conditional and unconditional portfolio performance evaluation

Statistical modeling of stock returns: explanatory ordescriptive? A historical survey with some methodologicalreflections

The purpose of this paper is twofold: first, to survey the statistical models of stock returns that have been suggested in the finance literature since the middle of the twentieth century; second, to examine under the prism of the contemporary philosophy of science, which of the aforementioned models can be classified as explanatory and which as descriptive. Special emphasis is paid on tracing the interactions between the motivation for the birth of statistical models of stock returns in any given historical period and the concurrent changes of the theoretical paradigm in financial economics, as well as those of probability theory

Looking far in the Past: Revisiting the growth-returns nexus with non-parametric tests

In this paper we reexamine the linkages between output growth and real stock price changes for the G7 countries using a batttery of non-parametrric procedures to account for the impact of long-lagged observations. Wer find that correlation between growth and returns is detected at larger horizons than those typically employed in parametric studies. The major feedback emerge from stock price changes to growth within the first 6 to 12 months, but we show that significant feedbacks may last for up to two or three years. Our evidence also suggests htat the correlation patterns differ substantially between the countries at hand when the sectoral share indices are considered