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Code for solving dynamic programming optimization problems (i.e. Bellman equations) through value & policy function iteration. This code was developed as part of my paper, "Maturity Mismatch and Fractional-Reserve Banking" (see http://rncarpio.com for more on my economics research). Some projects that the code relies upon are: - Python, Scipy, Numpy : http://python.org, http://scipy.org - PythonXY, a convenient all-in-one distribution for Python : http://pythonxy.com - Intel's Thread Building Blocks library for parallel computing : http://threadingbuildingblocks.org - Boost.Python, for mixing C++ with Python : http://www.boost.org/doc/libs/release/libs/python/ - PyUBlas, a glue layer between numpy and C++ matrices : http://mathema.tician.de/software/pyublas I compiled and ran on Windows 7, Visual Studio 10. Other platforms should work, but I haven't tested them.