| dc.description.abstract | The main scope of this thesis is to examine how alternative asset classes affect performance
of traditional stock and bond portfolios. We will employ financial engineering and
quantitative analytics to construct the most optimal portfolio of asset classes from 1928 –
2020 and investigate the diversification effect of alternative asset classes. The methodology
to find an optimal portfolio follows the prominent mean-variance framework of Harry
Markowitz, which determines portfolio weights to maximize the return-to-risk ratio. The
analyzed asset classes are U.S. equity, government bonds, corporate bonds, gold, real estate,
commodities, options strategies and factor exposure towards Fama-French’ SMB, HML
and UMD portfolios.
The purpose of utilizing 93 years of data is to construct a portfolio which performs in every
stage of the business cycle. It should handle inflation and deflation, rising and falling interest
rates, as well as market booms and crashes. Quadratic optimization suggests an allocation
of government bonds, corporate bonds, real estate, UMD factor exposure and a covered call
option strategy. This combination leads to a significant improvement of risk management,
where the risk exposure is halved compared to a traditional stock and bond portfolio
without influencing returns. The optimal portfolio achieves an annual alpha of 3.40%
compared to our benchmark, and Sharpe ratio increases from 0.397 to 0.835. As the riskadjusted
return is significantly improved, will our research suggest that including
alternative asset classes enhances portfolio quality. | en_US |
