In our previous blog, we covered behavioural drivers of the factor premium. Alongside behavioural and risk-based explanations, market frictions constitute an important driver behind various factor premia.
Various market structures can impact factors in their own way as they constitute another powerful force which shapes investors’ preferences or actions. These obstructions are not always addressed in academic research on factors that often overlook taxes, transaction costs, manager ranking, stop-losses, and regulatory constraints. Market structures don’t necessary need to have a monetary value at all times and can be linked to behaviour – people tend to stand in long queues to buy cheap products as much as fund managers monitor and deeply care about their peer ranking.
In the context of traditional asset pricing (e.g. the capital asset pricing model also known as CAPM), market structures (often referred to as market frictions) are absent. In reality, financial market structures cause market participants to act and respond in a certain way which makes them exposed to more or less risk than originally intended. For example, higher trading costs, stamp duty or a margin call on a leveraged trade may interfere with the management of the underlying strategy.
How does market friction come into play with factors?
Corporate executives might be incentivised to inflate earnings through accruals and markets might overvalue these accrued earnings. Revenues and expenses are recognised on the balance sheet as soon as they are incurred instead of when the cashflow actually takes place. 'Accrual' refers to any individual entry recording revenue or expense in the absence of a cash transaction. Research has shown that companies with net positive accruals tend to earn lower risk-adjusted returns. Conversely, companies with high net cashflow as a part of total profit tend to outperform as this may reflect a 'true' measure of economic success while the accrual component is subject to adjustments and does not necessarily reflect the actual performance of a firm. Based on empirical evidence and academic literature, if market participants overvalue accrued earnings, that drives down the prospective returns on low quality companies over time.
Market frictions associated with more pro-cyclical factors – value and momentum – can be analysed from the perspective of investors’ behaviour. Investors tend to react to news if they see a price movement which can be linked, rightly or wrongly, to that information. This adds upward or downward pressure on the price and makes omnipresent performance rankings an associated market structure. Peer group assessment and league tables of fund managers could lead investors to set up stop-loss levels or buy back stocks just to avoid fourth quartile rankings. On the back of negative headline news, fund managers may have a low appetite for bottom performers, essentially driving the momentum premium.
Traditional finance theory (e.g. CAPM) assumes that investors can borrow and invest at the risk free rate, but in reality the cost of borrowing is much higher. Hence, some investors are willing to pay a small premium for 'risky' stocks (high beta or high volatility) to mimic a leveraged position. That demand drives the expected return of high volatility stock lower and the expected return of low volatility stocks higher. Moreover, the leverage aversion hypothesis holds that many investors who demand high returns are leverage constrained and choose to increase their expected returns by over-allocating to high beta stocks, even if the latter have demonstrably lower return per unit of risks. As a result, investing in low beta stocks may be associated with what is often referred to as a low volatility premium.
Finally, the delegated-agency model provides an explanation for why the low volatility premium could persist even when professional money managers have been aware of the anomaly. The theory contends that most portfolio managers are benchmarked against a common core equity index; they are simply unwilling to buy low volatility stocks, which would significantly increase their tracking error against the benchmark. We will discuss that relative risk of low volatility stocks in more detail in our next and final piece on factor premia drivers.