Your team has to submit a report of3 to 5 pages documenting the project and an excel spreadsheet containing key results and formulas, following the guidelines below.

This project has to do with creating and back-testing a long-only multi-asset portfolio with tilts. Your investment universe should comprise a diversified set of assets including US and international equity indexes, US and international bond indexes, etc. You can use the returns and market values of global assets, posted on Courseworks, or download your own. At the minimum, you have to establish 2 tilts. Your backtest should  be at least 10 years long.

Your goals are as follows:

1.    Each year, produce the expected returns for assets in your investment universe. Apply the Black-    Litterman method to blend the market (or a benchmark) with views. At the minimum, you have to introduce at least two view portfolios, which can be as simple as a positive weight for at least one asset, such as US Small Cap Value equities, and a negative weight for another asset, such as US Small Cap Growth equities, or a positive weight for commodities and negative weights for the rest of the    assets (market value-weighted), for example. Use the lecture notes and the He-Litterman paper for    guidance as to the choice of any parameters and make the level of confidence in your views sufficiently weak. The deviations from the market of your final weights should be with the -5%     and +5% range.

2.   In your spreadsheet, for the final portfolio only, provide:

a.   The market capitalization weights and the view portfolio weights [tab name:“Weights”]

b.   Your chosen risk aversion and the measures of your confidence in the market-implied expected returns and your views [tab name:“Parameters”]

c.   The market-implied expected returns, and the Black-Litterman blended expected returns [tab name:“Expected Returns”]

3.   Estimate your covariance matrix and re-estimate it every year by using at least 36 months of prior    returns. In your excel spreadsheet, provide the annualized covariance matrix for the last year of your backtest in a tab labeled“Covariances”. In addition, provide volatility of each asset and provide  the correlation matrix of the assets, extracting them from the covariance matrix that you used for the last year of your backtest.

4.   Produce optimized long-only portfolio for each year in your backtest. Use mean-variance optimization with the same risk aversion that you used to derive the expected returns, the covariance matrices computed in item 3 and the Black-Litterman expected returns computed in item 1. Impose the following constraints in the optimization, if needed:

a.   The portfolio is long only (no negative weights)

b.   Portfolio weights add to 1

5.   In your spreadsheet, in a tab named“Backtest weights”, present a chart of the market capitalization weights and the optimal portfolio weights, for every year of your backtest.

6.   Backtest your portfolio and produce the following set of analytics. Formulas must be given in your spreadsheet for at least the last month:

a.   Cumulative payoffs (growth of $1) of your portfolio and the market (to calculate monthly  returns on the market, you can multiply the weights calculated form the provided monthly market capitalization values by the respective monthly index returns and sum them up for all assets every month), also presented as a chart [tab name:“Payoffs”].