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SummaryBangladesh has emerged as a leading ship breaking nation. We conducted a material flow analysis of steel in Bangladesh with an emphasis on the ship breaking industry (SBI). The total aggregate domestic steel consumption in fiscal year (FY) 2010 was 2,930,000 tonnes (t) in Bangladesh; SBI met approximately 51% of the demand for raw materials and 37% of the demand for finished steel products. Rolling industries output in FY2010 was 1,451,000 t; 23% of the input for this production was from ship breaking sources. Dismantled ships also generate high-quality reusable steel scraps. SBI was found to be the sole source of scraps for small rerolling industries in Bangladesh, and their output in 2008 more than doubled as compared to 2005. Larger rolling industries fulfilled their input needs for steel scraps by using both SBI and imported materials. We found a sharp increase in input imports during the global ship breaking recession in [2003][2004][2005][2006][2007] and when Bangladesh's SBI faced a temporary ban in 2010. Induction furnaces in Bangladesh in FY2010 produced a total of 787,000 t of billets; more than 40% was from ship-sourced scraps. In 2008, the country's steel consumption was 3,220,000 t, that is, 22 kilograms per person, and the intensity of steel use was 40 grams per U.S. dollar, which was much higher than that of other developing countries with a similar per capita gross domestic product (GDP). The country exhibited a high level of steel consumption relative to its GDP, which is indicative of the contribution of SBI.

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Although there is a growing interest of applying regime switching models to portfolio optimization, it has never been quite easy as yet to obtain analytical solutions under practical conditions such as self-financing constraints and short sales constraints. In this paper, we extend the linear rebalancing rule proposed in Moallemi and Saglam [17] to regime switching models and provide a multi-period dynamic investment strategy that is comprised of a linear combination of factors with regime dependent coefficients. Under plausible mathematical assumptions, the problem to determine optimal coefficients maximizing a mean-variance utility penalized for transaction costs subject to self-financing and short sales constraints can be formulated as a quadratic programming which is easily solved numerically. To suppress an exponential increase of a number of optimization variables caused by regime switches, we propose a sample space reduction method. From numerical experiments under a practical setting, we confirm that our approach achieves sufficiently reasonable performances, even when sample space reduction is applied for longer investment horizon. The results also show superior performance of our approach to that of the optimal strategy without concerning transaction costs.