While still in its infant stages, the rise of automated investments services incorporates advancements in technology with financial services. Underlying these platforms are complex algorithms following ubiquitously used theories in the investment industry. Created with the support of financial experts and engineers, most major automated investment services have based their portfolios on a form of Modern Portfolio Theory (MPT). Fundamentally the theory prioritizes asset allocation, diversification and periodic rebalancing in order to maintain an optimal portfolio.
Modern Portfolio Theory
Developed by Nobel Laureate Harry Markowitz in the 1950s and later refined by other economists, Modern Portfolio Theory remains fundamental to the financial industry. By definition, Modern Portfolio Theory explains how to optimize portfolio returns for any given level of market risk. Within its framework, an optimal portfolio is constructed on the basis of asset allocation, diversification and periodic rebalancing. For each level of risk, an optimal asset allocation is designed to produce the greatest tradeoff between risk and return. One core principle of the theory emphasizes that greater potential returns are associated with higher risk and conversely, the lower the risk, the lower the return. Over a period of time the theory suggests there is no portfolio greater than the market portfolio. As a result, the optimal portfolio will provide neither the greatest returns nor the lowest risk, but a balance residing on the Efficient Frontier.
With respect to Modern Portfolio Theory, optimal diversification encompasses holding multiple uncorrelated instruments amongst the various asset classes. It is important your investment is diversified over several asset classes because each asset class performs differently over time. Traditionally, stocks have a higher rate of return due to higher risk. Bonds, on the other hand, are lower risk investments and as a result produce more modest returns. While international assets are also high risk investments, emerging economies are one of the fastest growing in the world with many of them trading at relatively low valuations.
As most of the major digital asset managers adhere to Modern Portfolio Theory, it is the asset allocations and fine tunings of the theory which differentiate them. Even with similar asset classes, varying estimates of expected returns and volatility produce significantly different portfolios. That being said, each platform assesses your risk tolerance, investment horizon and financial goals in order to create a portfolio best suited to you; typically consisting of ETFs in stocks, emerging markets and corporate bonds.
Assuming your portfolio adheres to facets of Modern Portfolio Theory, then you are seeking to maximize potential returns while also minimizing your risk. The optimal balance of risk to reward is determined by the portfolio which lies tangent to the efficient frontier. Portfolios along the efficient frontier will have higher returns than portfolios of similar risk. With the shape of an exponential curve, the efficient frontier reaches a point by which adding additional volatility does not provide any significant benefits to asset returns.
Assets Classes over Time
Depending on your investment horizon, investable assets and risk tolerance, different strategies are considered more appropriate at different points in your life. For a young millennial, portfolio theory suggests a larger distribution of stocks over bonds. Even for ETF portfolios, robo advisors channel young investors to a majority of stock ETFs with a small share of emerging market and bond ETFs. Conversely, baby boomers, with a much shorter investment horizon, are directed to more fixed income assets over higher risk equities. Since the algorithms of each service are different, the number of assets your investment are allocated to will vary with your choice of platform.
Fundamental to MPT is the constant oversight and efforts to rebalance portfolios. By definition, rebalancing is the process of realigning one’s portfolio to its target asset allocation. When assets accrue dividends or simply fluctuate in value, rebalancing back to its target allocation intends to optimize returns for the initial level of risk. In the past, rebalancing drew criticism due to accumulating transaction costs. However, due to low overhead costs, automated advisors can offer transactions free of charge and automatically rebalance portfolios. As research suggests, rebalancing can significantly lower the risk of a portfolio.
Unfortunately, many of us cannot afford the services of traditional financial advisors. However, with the advancement in technology and sound academic research, automated services are democratizing investing to the masses. Since many automated platform base their algorithms on Modern Portfolio Theory, financial concepts of diversification, rebalancing, and asset allocation have a major impact on your portfolio.