This is one of a series of columns that were produced for Moneyweb Investor in which Stuart Theobald explores the intersection of philosophy of science and finance. This followed an earlier series for Business Day Investors Monthly on the same theme. This column was first published in January 2016.
We are used to separating out investment products in terms of their riskiness – equities at one end, bank-guaranteed products at the other. But the real problem that hit investors during the financial crisis was complexity. Investors simply didn’t understand how their products worked.
Some academics are now suggesting that complexity should be an additional dimension to how we think about financial products, alongside the traditional considerations of returns and risk. Risk in finance has, rightly or wrongly, come to be seen simply as volatility of returns, measured by standard deviation. So a risky product is one whose price jumps around more than others. Returns are, of course, difficult to forecast at the best of times, but that is the art of financial analysis. Complexity, though, refers to something different: the ability to link an event to the value of the financial instrument. The more complex a financial instrument, the more difficult it is to understand how changes in the world affect the value of that instrument.
In part, complexity is an inevitable feature of financial market development. Think of the JSE, which not too long ago consisted only of cash equities. Now you can get all manner of derivatives from futures to swaptions. Those can then be factored into investment portfolios alongside other instruments with different features and return sources like scrip lending. With such complexity a simple question like, “how will that interest rate change affect the value of my investment” becomes bewilderingly complex to answer. The same trend is clear in exchange-traded funds, which started as simple trackers of established, well understood indices, and now include “smart beta” products that are much more complex.
One practical observation is that herding effects tend to be more pronounced for complex products. Because it takes longer to work through the implications of new information, investment decision makers are more prone to follow the signals emerging from others’ behaviour. One apparent example is the financial crisis, when investors chose “sell” rather than wait to figure out the implications of events for their holdings. In this case, complexity feeds into riskiness because volatility will be amplified by herding, suggesting that complexity is effectively just a component of risk.
One response, at least in the case of retail investors, is to simply declare complex products to be unsuitable for them. Globally, regulators have been concerned about suitability – placing retail investors into products with the wrong risk and return profile for them. In South Africa that demon frequently rears its head in the corridors of the Financial Services Board, as clients complain about products sold by advisors chasing high commissions rather than their interests. But the problem of miss-selling doesn’t map neatly on to the problem of complexity. In fact, a complex product can be made very simple for retail clients. Consider a market-linked capital guaranteed investment product. These can be created by taking an interest free deposit, using the foregone interest to purchase an out-of-the-money call option on a market index. The investors’ capital is guaranteed, but if the market performs well they will get a market-linked return. A fairly simple product to understand, though a complex product in structure.
The problem is best understood as a one of decision making. The normal story is that investors try to estimate returns and understand the riskiness of an investment in the context of their portfolios, and aim to maximise returns and minimise risk. Complexity is really an information constraint – it factors into the cognitive load that is needed to make decisions. Seen that way, it is clear that some products which are complex in structure are not complex in the sense relevant to decisions – being able to understand the risk/return profile, such as market-linked capital guaranteed products. The type of complexity that matters is that which lies beyond our mental capabilities, and there are no ways to frame it so that the decisions are simple. Seen that way complexity is apparent in cases like hedge funds, where the actual investment strategy is a proprietary secret. In such cases, investors simply don’t know how events will affect performance.
One solution is to rate complexity by five factors: layers that affect payoffs; expansiveness of derivatives used; amenability to valuation by standard valuation techniques; number of scenarios that affect return outcomes; amount and simplicity of language in disclosures required to assess the profile of a financial product. These can be mapped onto a scorecard that allows for a metric to complement risk and return estimates. So a highly complex product would have several layers of derivatives which are highly responsive to price changes of underlying assets, depend on complex non-traditional valuation factors (like weather swaps), and have many pages of verbose disclosures. Such complexity makes decision making very difficult.
For the average investor, then, it is helpful when looking at a product to ask just how complex it is. Applying a “complexity threshold” may well be a wise move if you’re going to keep a tight control over your investment portfolio and not end up following the herd when things change.
 Suggested by Benedict S.K. Koh, Francis Koh, David Lee Kuo Chuen, Lim Kian Guan, David Ng, Phoon Kok Fai. A Risk- and Complexity-Rating Framework for Investment Products, Financial Analysts Journal
November/December 2015 | Vol. 71 | No. 6