• Distributional characteristics of interday stock returns and their asymmetric conditional volatility: firm-level evidence

      Balaban, Ercan; Ozgen, Tolga; Girgin, Mehmet Sencer; University of Bedfordshire; Craig Associates, Edinburgh; TJK, Istanbul (Elsevier B.V., 2018-05-16)
      This paper is a pioneering effort to jointly analyze the characteristics of interday distributions of stock returns and their asymmetric time varying volatility using firm-level data in local currency from an emerging stock market, namely, the Bourse Istanbul, for the period January 1996 to December 2015. Using a modified Threshold Generalized Autoregressive Conditional Heteroscedasticity-in-Mean [TGARCH(1,1)-M] model; these distributional characteristics statistically assess in a unique framework (i) the weak-form informational efficiency based on the stylized facts of day of the week effects on stock returns and their conditional volatility; (ii) volatility persistence and asymmetry in conditional volatility; and (iii) the conditional total risk–return relationship, and the impact of systematic risk as an asset pricing factor. It is found that at firm level there are statistically significant positive or negative day of the week effects on either stock returns or their conditional volatility, or both. However, for a sample of 120 firms, a full and cross-sectional analysis of the interday distributions does not lead to a systematic pattern of return differences across days of the week. The average volatility is found to be highest on Mondays and the lowest on Wednesdays. It is reported that – as a proxy of total risk in a mean–variance framework – the estimated conditional standard deviation does not have a significant impact on stock returns for the great majority of the sample firms. With reference to the total risk–return relationship and the asymmetry in volatility, there are no significant differences between the industrial and financial sector companies. It is reported that the systematic risk is always priced; and the results are highly significant with a high explanatory power. Volatility is decidedly persistent for all firms investigated; while, a significant asymmetry in the conditional volatility cannot be reported for most of the firms. Contributing to the existing literature as a first time analysis of firm-level distributional characteristics of interday stock returns and their asymmetric conditional volatility with an additional proper risk-impact investigation, the empirical results are of importance primarily for asset pricing and risk management research and practice.
    • Modelling and analysis of intermodal food grain transportation under hub disruption towards sustainability

      Maiyar, Lohithaksha M.; Thakkar, Jitesh J.; Indian Institute of Technology Kharagpur (Elsevier B.V., 2018-07-27)
      Escalating global food security concerns across several nations has shifted the focus of policy makers towards risk adaptive sustainable food grain operations. This paper builds a sustainable food grain transportation model for intermodal transportation operations between two Indian states, in the presence of hub disruption. A hub and spoke system is used to connect origin and destination warehouses through intermodal hubs in a multi-layered network. The problem is formulated as a multi-period mixed integer nonlinear single objective optimization problem considering minimization of transportation, hub location, rerouting, environmental and social costs with near optimal shipment quantities and hub allocations as the prime decisions. The proposed MINLP is solved using Particle Swarm Optimization with Differential Evolution (PSODE), a superior metaheuristic to deal with NP-hard problems. Convergence graphs and global optimal costs are reported for small, medium and large size instances consisting of 1824, 9768 and 28848 variables respectively, inspired from food grain industry in the southern part of India. Pareto plots are generated to capture the complementarity between economical and socio-environmental cost categories for all instances. The effect of hub location, hub disruption, cost consolidation and vehicle resource availability factors on individual and total costs is studied through sensitivity analysis. Results indicate that food grain demand is fulfilled with 14% increase in the mean total cost for single hub disruption case and with 40% increase for multiple hub disruption. Finally, managerial implications provide specific factor level recommendations for different strategic objectives.