Portfolio calculation: This is some code written for David Kendricks Computational Economics course which calculates the optimal portfolio (for a given objective). Currently the code calculates the maximum portfolio optimization given risk concerns and the minimum variance portfolios.
Metrics II P1: This was a small portion of PS2, Problem 1, Metrics II Fall 2010 taught by Dr. Jason Abrevaya. Here I played around with Python's maximization toolbox. While the coding is fine, the answers were not as expected. To correct this, a while loop could be added to check for changes in iterating upon the minimization function.
Random_Cipher.py: This is a small code I wrote for my friend and I to challenge each other. He is way into decryption. So far he has not broken my short messages.
Patents as Options (Pakes 1986): This is code I transcribed from my Matlab code to solve for Pakes 1986 "Patent as Options" routine (the producer's problem). Mainly done to help me remember python (it has been awhile since I have programmed in it). This has some very simple errors to correct (namely the integral). The corrected Matlab code was used for the assignment, so do not stress. Email me if you would like the correct Matlab code.
Genetic Algorithm: This is Python code I tweaked from the original Matlab that ran a genetic algorithm on the Prisoner's dilemma. Now it can handle any symmetric game (even those with no odd-numbered pure-strategy Nash Equilibria).
Automated PDF download: This is a little script I wrote for Dr. Kendrick's Computational Economics course module on Big Data. While this does no data access nor data analysis, it does use the standard Python 2.X library and show automation for PDF collection. Please don't change the time.sleep command, as this will result in that poor old server getting overly hammered.