How to apply smart beta to investing

Beta measures how investing strategies are expected to perform relative to the market

Putting money to work well is not easy. Increasing one’s wealth at the highest-possible return but with the least chance of loss is not a trivial ask. Bank savings including fixed deposits and other such options provide a return. But this return, almost always, is not enough to cover the cost of inflation.

Unlike simple banks savings, professional fund management has two broad choices: active investing through specialised services such as mutual funds or through low-cost passive market portfolios. There is a third choice too – smart betas, a hybrid between the active and passive styles. All these choices converge on one central need: the expectation of money to grow at the least-possible risk. In any case, what are these choices and how well do they work?

Passive market portfolio

Many years ago (1964), Nobel laureate William Sharpe showed that it is possible to earn the highest-expected return at the lowest-possible expected risk by investing in the market portfolio. The logic Sharpe proposed is intuitively appealing. Over time, the market return equals the sum-total of the best and the worst of the possible investing strategies in the market place, adjusted for cost. So why not just invest in the “market portfolio”?

Given the significantly lesser cost, this passive, invest-in-‘the market’ approach has become quite popular. Beta, according to this model, is just a measure of how well investing strategies are expected to perform relative to the market.

Since the ‘market portfolio’ is a summation of all assets in the market place, this portfolio has a beta of 1. Betas for other portfolios represent how risky a strategy (or rather the portfolio) is compared with the overall market.

Smart beta connection

Smart betas dig deeper and take a different route to investing. Smart betas take active investing ideas and automate these ideas in a passive style, using computers. In many ways, it is a bare-bones approach to investing.

A practical analogy? When we eat fruits or drink soya milk, for example, at a very basic level, we satisfy our vitamin and protein needs. Smart betas classify investment risks and returns into their vitamin, protein, nutrient equivalents.

Eugene Fama (another Nobel laureate) and Kenneth French, in addition to the market beta discussed earlier, proposed two additional basic factors or betas (investment nutrients): value and size. Fama and French in their model showed that it is possible for relatively smaller and cheaper companies to outperform over time. Fundamental factors and smart beta have now become interchangeable names.

Rob Arnott (considered a pioneer in smart beta investing) along with his colleagues Jason Hsu and Philip Moore, have written in the Financial Analysts Journal on the use of fundamental factors for constructing indices.

Arnott et al used reported balance sheet numbers (book value, cash flow, revenue, dividends, and employment, among others) as weights to construct strategies for delivering better risk-return profiles than cap-weighted indices. About 400 factors have now evolved in the smart-beta space.

Like its passive cousin, smart beta is among the fastest-growing trends in investing. Globally, value and income have been amongst the most popular smart-beta factors.

Value smart betas use high book value to price stocks as a selection criterion. On the other hand, income strategies use high dividend pay and dividend coverage in their selection screens. The expectation in value strategies is that cheap stocks will outperform.

The expectation in income strategies is that high dividend-paying stocks will return more.

Reasons for popularity

Investing through mutual funds requires specialised investing skills. Mutual fund managers, often referred to as active managers, cost money.

Machines attempt to automate fund management and bring costs down. Sophisticated computer programs use simulations and back-testing to develop strategies that mimic active management. But it is not just the cost.

Many believe that smart betas with programmatic help can better exploit systematic biases that the marketplace has.

It can provide better control, too. All of this has helped attract a surge in investment flows to the smart-beta world.

The India context

India’s current total smart-beta asset size is relatively small ($148 million). But opportunities for smart-beta investing have been growing. Stock exchanges as well as mutual fund providers have come up with specialised indices.

From investing through an equal-weighted popular index (using same amount of money in each stock instead of market-cap weights) to investing in high-quality companies and fundamentally strong companies, there is a spectrum of options to choose from.

It is interesting that two of the topmost smart-beta strategies (as defined by assets) include investing in low-volatility stocks and stocks that track high-quality, fundamentally strong companies. Low-volatility and high-quality factors are good alternatives for limiting downside risk. It is easy to see that in market downturns, these factors are likely to suffer the least.

The smart-beta approach is cost-effective, too. But just like other investing strategies, too much of investing in one smart-beta factor can render the strategy expensive. A superior approach, experts recommend, is to not chase returns, but instead use smart betas for diversifying and limiting one’s risk.

The writer is Director, Continuing Education and Advocacy, India,

CFA Institute.

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