How Fractional Shares Empower Portfolio Customization
It took 40 years, but it finally happened: in Q4 2018, assets invested in large-cap equity funds surpassed assets invested in equivalent actively managed funds.
John Bogle, the founder of Vanguard, was the the first to offer an index fund to individual investors in 1975. But the philosophy– built on the belief that most investment managers do not outperform the broader market, and that investors were therefore better off buying portfolios designed to capture the growth of the market (or an index designed to mirror the market, such as the S&P 500 or the Russell 1000)– took decades to catch on.
But buying and maintaining the right proportion of every company in an index is impractical for all but the most sophisticated investors. Most advisors implement diversification for their clients by buying diversified funds instead of individual stocks, paying a fund manager to select and weight individual companies’ stocks to resemble the portion of the benchmark.
The downside to funds
There is a real and under-examined disadvantage of using funds and ETFs: they are one-size-fits-all. If your client is employed by Johnson & Johnson and receives Restricted Stock Units (or some other form of equity compensation), he can’t buy an S&P 500 ETF without JNJ. He just has to accept that he is overexposed to JNJ in his investment portfolio if it’s composed solely of funds, as many are. This is bad news for diversification: if the company’s stock suffers and the client in question is laid off, his investment portfolio—not to mention his income—are more highly correlated than they should optimally be.
What’s an advisor to do? You want to provide your clients with personalized service, but you can’t exactly get BlackRock to remove just JNJ from their ETF for this one client. However, improvements in technology now make broad market exposure and direct stock ownership compatible.
Algorithms execute rules-based investment strategies more accurately and precisely than humans could ever hope to, changing the tools available to advisors. With fractional shares, these rules-based systems can do it at practically any scale– at OpenInvest, investors can open an account for as little as $100 and expect good, dynamic diversification, and customization to the causes they cherish most. Algorithmic investing also executes trades at a fraction of the cost of the old guard’s relatively manual, human error-prone ways – which explains how Dynamic Custom Indices (DCIs) and their ETF ancestors display comparable prices, and why both typically charge half of what an actively managed fund charges.
Both customization and diversification
Additionally, fractional shares give advisors the ability to control two aspects that are often diametric: diversification and customization. An investor concerned about climate change and the influence of corporate money in politics can rely on OpenInvest’s cause-based portfolios to benefit from full diversification to match the market’s performance. She can also rest easy knowing that her assets aren’t invested in companies whose values are contrary to hers, and that her investment manager has flexibility in harvesting tax losses in her portfolio, since she owns the stocks underlying the index.
Finally, she knows that as more data emerges about companies, and as they acquire and divest business units, develop new products, and their CEOs turn over, her portfolio will keep up with the changes as well as the performance of the benchmark.
Client as PM
With good passive investing, an advisor can be confident that the fundamentals of portfolio construction and management are taken care of: risk management through diversification; low costs and clean execution through rules-based investing. Fractional shares unlock these tools for small accounts, and improve execution for large accounts. By creating the instruments to customize your client’s portfolios to match their values without compromising their returns, OpenInvest helps you transform their financial assets into an expression of their whole selves.