1 the purpose of this assignment is to use python to

Question

1. The purpose of this assignment is to use Python to construct portfolio returns, and to demonstrate the bias in rebalanced returns identified by Blume and Stambaugh (1983).

Use two data samples (1), the TSX 60 data sample that we gave you initially; (2) the portfolio of "small" stocks whose data you downloaded for the second part of assignment 2. For each of these two samples, compute the following four sets of portfolio returns (so eight return series total):

i. Daily returns of a portfolio that is initially equal-weighted, but then never rebalanced.

ii. Daily returns of a portfolio that is rebalanced to equal weights each day.

iii. Monthly returns of a portfolio that is initially equal-weighted, but then never rebalanced.

iv. Monthly returns of a portfolio that is rebalanced to equal weights each month.

For each return series report the mean, standard deviation, percentiles, and the min/max. Explain any interesting aspects of your results. Please use a sample period of January 1, 2014 to December 31, 2014 for your analysis.

If you wish, you may carry out an additional analysis over a longer time period (e.g., 10 years), which might make some of the empirical effects appear more strongly. Interpret your results.

Answer 1

To complete this assignment, you have to make use of Python to construct the portfolio returns, and to illustrate the bias in rebalanced returns recognized by Blume and Stambaugh (1983). For each of such two samples, calculate the given four sets of portfolio returns: 1) Daily returns of portfolio which is primarily equal-weighted, however then never rebalanced. 2) Daily returns of a portfolio which is rebalanced to equivalent weights every day. 3) Monthly returns of portfolio which is initially equal-weighted, however then never rebalanced. 4) Monthly returns of portfolio which is rebalanced to equivalent weights every month.