Testing the CAPM revisited

This paper re-examines the tests of the Sharpe–Lintner Capital Asset Pricing Model (CAPM). The null that the CAPM intercepts are zero is tested for ten size-based stock portfolios and for twenty five book-to-market sorted portfolios using five-year, ten-year and longer sub-periods during 1965–2004. The paper shows that the evidence for rejecting the CAPM on statistical grounds is weaker than the consensus view suggests, and highlights the pitfalls of testing multiple hypotheses with the conventional heteroskedasticity and autocorrelation robust (HAR) test with asymptotic P-values. The conventional test rejects the null for almost all sub-periods, which is consistent with the evidence in the literature. By contrast, the null is not rejected for most of the sub-periods by the new HAR tests developed by Kiefer et al. (2000), Kiefer and Vogelsang (2005), and Sun et al. (2008).     

Are exchange rates interdependent? Evidence using wavelet analysis

We examine the co-movement in daily returns of USD–INR, EUR–INR, GBP–INR, and JPY–INR currency pair futures contracts traded on the National Stock Exchange of India (NSE) using the wavelet cohesion approach. This study contributes to the literature by examining the scantly studied area of co-movement in exchange rates and using the wavelet approach, which allows us to analyse time–frequency-wise co-movement of the time series. The empirical results indicate that the currency futures markets are nearly perfectly integrated in the long run (monthly, quarterly and biannual scales) offering little potential gains from international portfolio diversification. The discrepancies between currency futures markets are small and almost fade away within 3–6 months. Moreover, international currency diversification might offer relatively higher potential gains at intraweek, weekly, and fortnightly time horizons owing to lower correlations among the currencies under consideration. Finally, our multiple-wavelet correlation and cross-correlation analysis shows that GBP acts as a potential leader/follower across scales. The results of our analysis indicate the dynamic pattern of co-movement among the major currency futures contracts, which provides several implications for portfolio managers and international investors participating in the Indian market.     

Do global financial crises validate assertions of fractal market hypothesis?

The frequent occurrence of crises in recent decades has triggered a debate between the proponents of Efficient market hypothesis and Fractal market hypothesis. While, the proponents of Efficient market hypothesis view crises as non-existent and highly improbable, the advocates of Fractal market hypothesis view crises as the dominance of certain investment horizons. We test whether the assertion of Fractal Market hypothesis regarding the dominance of certain frequencies during financial crises hold for the global stock markets. Following Kristoufek (Sci Rep 3:2857, 2013) the wavelet power spectra based on continuous wavelet framework are used to test the said hypothesis. It is shown that stock markets around the globe indicate the dominance of higher frequencies during the crises periods, hence, validate the assertions of Fractal market hypothesis. The results drawn are robust to the use of different countries as well as different crises.     

Renewable and nonrenewable energy production and economic growth in sub-Saharan Africa: a hidden cointegration analysis

The objective of this article is to investigate the hypothesis of asymmetric effects between economic growth and renewable and nonrenewable energy production. To this end, both the linear cointegration and the hidden cointegration methodology are employed, with the latter allowing a straightforward delimitation of the data in an economically sensible way. We test for the presence of hidden cointegration across 12 sub-Saharan African countries spanning the period 1971–2011. The empirical results confirm the growth hypothesis for a subset of countries, suggesting that their growth could be adversely affected by conservation policies, while for a second subgroup of countries they confirm the conservation hypothesis, indicating that conservation policies could enhance the growth process in these countries. The differentiation of the results could be captured entirely by the linear approach, indicating that the lack of cointegration between renewable energy production and economic growth found in previous studies may be due to failures to properly delimit the nonlinearity property in the data.     

Analysing the spillover of inflation in selected Euro-area countries

Journal of Quantitative Economics - We examined the spillover of inflation in selected Euro-area countries using monthly consumer price index (CPI) based inflation data covering the period 1955M1...     

Modes of Commuting in Mumbai: A Discrete Choice Analysis

Using a nested multinomial logit model (NMNL), this paper estimates the choice probabilities and demand elasticities of various modal alternatives for Mumbai using 1990 trip origination and destination data. The results indicate that with an increase in the cost of private transit system, market share is reduced. The result of this experiment is highly elastic private commuting mode demand. In addition, reduction in the market share of own vehicles is larger than that of hired vehicles. The increase in the cost of mass transit system reduces its share but is inelastic. Decrease in the market share of one mode is accompanied by increase in the market share of others. Income has a positive effect on the market share of private transit modes, particularly on the own vehicles' share. Other explanatory variables such as distance have a negative effect on mass transit system and duration has a negative elasticity for all modes of transportation.     

Algorithm portfolios for logistics optimization considering stochastic demands and mobility allowance

The vehicle routing problem with stochastic demand (VRPSD) is a well known NP-hard problem. The uncharacteristic behaviour associated with the problem enhances the computational efforts required to obtain a feasible and near-optimal solution. This paper proposes an algorithm portfolio methodology based on evolutionary algorithms, which takes into account the stochastic nature of customer demand to solve this computationally complex problem. These problems are well known to have computationally complex objective functions, which make their solutions hard to find, particularly when problem instances of large dimensions are considered. Of particular importance in such situations is the timeliness of the solution. For example, Apple was forced to delay their shipments of iPads internationally due to unprecedented demand and issues with their delivery systems in Samsung Electronics and Seiko Epson. Such examples illustrate the importance of stochastic customer demands and the timing of delivery. Moreover, most of the evolutionary algorithms, known for providing computationally efficient solutions, are unable to always provide optimal or near optimal solutions to all the VRPSD instances within allocated time interval. This is due to the characteristic variations in the computational time taken by evolutionary algorithms for same or varying size of the VRPSD instances. Therefore, this paper presents portfolios of different evolutionary algorithms to reduce the computational time taken to resolve the VRPSD. Moreover, an innovative concept of the mobility allowance (MA) in landmoves based on the levy’s distribution function has been introduced to cope with real situations existing in vehicle routing problems. The proposed portfolio approach has been evaluated for the varying instances of the VRPSD. Four of the existing metaheuristics including Genetic Algorithm (GA), Simulated Annealing (SA), Artificial Immune System (AIS), TABU Search (TS) along with new neighbourhood search, are incorporated in the portfolios. Experiments have been performed on varying dimensions of the VRPSD instances to validate the different properties of the algorithm portfolio. An illustrative example is presented to show that the set of metaheuristics allocated to certain number of processors (i.e. algorithm portfolio) performed better than their individual metaheuristics.     

A wavelet analysis for exploring the relationship between economic policy uncertainty and tourist footfalls in the USA

We attempt to establish the relationship between Economic Policy Uncertainty (EPU) and international tourist footfalls in the USA. In the first stage, we investigate the influence of country-specific EPU and global EPU on tourist footfalls. Since, these two are overlapping in nature, in the second stage, we study the isolated influence of country-specific EPU on footfalls by eliminating the influence of global EPU and vice versa. We consider a study period spanning over January 1997 to April 2017. To capture the variations in the relationship at different time dimensions, we apply wavelet-based techniques. We observe the following: (a) the impact of policy uncertainty shock has a little immediate impact on tourist footfalls, (b) medium to long-run shocks persist due to occurrence of major undesirable economic events, and (c) the influence of domestic (country-specific) EPU is dominant in comparison to global EPU for the USA.     

A global food–energy–water nexus with heterogeneity,non-stationarity and cross-sectional dependence

We estimate the Food–Energy–Water (FEW) nexus for 21 countries worldwide, with data available from year 1990–2000 in order to investigate the relationship between food production and two scarce resources: energy and water. Food production is proxied by four alternative variables: The index of agricultural production, the index of crops production, the index of livestock production and the value added from agriculture. Water and energy as independent variables are controlled by methane and nitrogen emissions, capital, labor and five versions of fertilizer proxy: pesticides, insecticides, fungicides, herbicide and other. For robust estimation, we have perused a number of standard and novel panel estimators such as the common correlated effects mean group estimator and the augmented mean group estimator (AMG). These estimators can account both for non-stationarity and the cross-dependence problems. Based on standard estimators such as the generalized least squares estimator or the Arellano-Bond generalized method of moments GMM, they reveal the existence of a significant FEW nexus while the mean group estimator, the group mean DOLS estimator, the common correlated effects and the augmented mean group estimator (AMG) do not yield significant coefficients for water and energy. In the latter models only labor and pesticides are significant at 5%. Also, the unobserved total factor productivity appears significant at 5% under the AMG estimation. When significant, energy and water elasticities ranged from ? 0.001 to ? 0.256 and from ? 0.014 to ? 0.084 respectively.