It has been our view for some time that the biggest issue confronting financial markets has been the markets themselves. The change in mood in equity markets has been both sudden and impactful. This Letter unpicks some of the terminology used in shorthand to identify causal factors in the correction.
The study of and commentary on market conditions is sometimes called internals or dynamics. We field a number of technical terms and explain each as we go.
When financial markets break-down the finger tends to be first pointed at fast money. Fast money was once loosely approximated to hedge funds where the dominant investment style is assumed to be short term and twitchy. In truth, fast money is a much broader amalgam of investment styles. It also includes quantitative investment. These strategies use powerful computer driven analysis to jockey on trends, mainly price trends. Quantitative strategies hop onto positively performing price trends whilst simultaneously shorting negatively performing price trends and when the variables change, the model buys and sells accordingly. There is a general suspicion, not fully proven, that the growth in quantitative styles amplifies market moves at points of stress. Curators of quantitative funds will counter-argue “Ah, but we’ve built an algorithm for that too” whilst keeping it secret how the magic mix works on commercial grounds.
The biggest constituency in the fast money camp is now Index Trackers or ETFs (Exchange Traded Funds). At their most basic expression, these funds replicate an index, for example the S&P500, by owning all the constituents of the index in the exact proportion that they appear in the index. Structures such as these are called physically backed. When the relative weights between index members changes, the manager of the ETF must then adjust the weights in the fund to avoid tracking error. Tracking error is a measurement of the risk that the ETF does not precisely replicate the actual index over time. Tracking errors are always positive and always more than zero. An investor in an ETF decides, upon purchase, that the possible tracking error is acceptable.
A further subset of the ETF world uses what is termed a synthetic approach. This sub-species replicated the index by typically owning some index heavyweight stocks and then replicating the others or indeed replicating the whole index by financial derivative contracts with affiliated or other financial institutions. These contracts are called swaps. Swaps are an agreement to pay the difference either on a transaction between two or more assets or a price change of a single asset.
There is considerable and unanswerable anxiety toward the total reliability of synthetic based strategies on account of the fact that there are now so many ETF providers and so many ETF strategies extant. Our own approach to this is to use (when we have need of) a very small list of ETF providers, for a vanilla list of indexes, and always in a physically backed form where the underlying assets are liquid.
Finally on ETFs, they trade through the market and also at their day’s end net asset value (NAV). When an investor sells at NAV, the fund shrinks in size so the manager of the ETF has to sell stock in the market to account for this shrinkage. ETFs are often spoken of as passive strategies as they follow adopted rules on constituents.
The terms de-grossing and window-dressing have been used quite a bit in the past few weeks. Any investment structure that is able to deploy leverage, either through lending or financial contracts that work akin to a contract-for-difference will raise the gross in the fund. If the gross is measured at 120%, then £100 invested would have £120 of financial assets working for it. This can have the effect of amplifying returns when the fund is hitched to themes that are working or vice versa. When a manager de-grosses, they are reducing the aggregate amount of risk being taken. After 10 years of generally upward trending markets backed by cheap rates of debt, one might expect gross levels to have trended higher over that time. This has not necessarily been the case in the visible hedge fund universe as markets have been rising but many themes have been fickle outside the US Technology sector.
Window dressing is an old fashioned but still current term for adjusting portfolio positions close to reporting periods to provide a better optical view to investors. Window dressing in falling markets would tend to entail part or full selling of positions that have not gone well in the short term. If a sufficient number of investors are active in this manner in the same securities, a demand supply imbalance is created, exacerbating short term falls. Window dressing is not to be encouraged and detailed transactional information should always reveal it.
In fact, leverage is much more widely deployed than most people assume. High value accounts held at brokerages and banks can be borrowed against to fund other activities: sometimes unrelated to the portfolio but sometimes channeled back in to the same securities. This type of round-tripping becomes uncomfortable when the underlying securities fall in price. Private investors, family offices and other unregulated entities may then be motivated to de-risk, by selling some of these positions.
In the US equity market, the largest buyer of securities currently are the listed companies themselves. We wrote about this in a Letter in September, found here. 2018 looks as if it will be a crescendo for buy-backs totaling close to or above US$1tn. The last crescendo year was ominously 2007, just before the Global Financial Crisis.
Why do companies buy back their own shares? It is generally regarded as a tax efficient, legitimate use of surplus cash. Bought back shares reduces the share count, thereby increasing earnings per share. However, an increasing numbers of companies are, in effect, borrowing to buy back shares. This also creates the desired effect as long as the cost of borrowing is not higher than the EPS enhancement effect. These calculations change as interest rates rise. As companies approach “optimal” gearing meaning they cannot comfortably borrow more, the cash and earnings flowing through the business has a larger determining effect on their ability to maintain buy-back levels. If earnings were to fall, for any reason, then US companies would have less cash on hand to buy-back shares, reducing the most important source of buying activity in the US stock-market.
Moving on, close watchers of markets speak often of leadership and rotation: these are somewhat opposite phenomena. Leadership is when a group of stocks or a sector is accountable for the bulk of the rise in a market, normally an equity market. Leadership is good for investors who follow momentum (as market capitalisation ETF’s tacitly do). Rotation takes place when sectors or groups of stocks pass the baton in terms of index contribution. Rotation secures market breadth but leadership can result in markets becoming narrow. Narrowness ultimately fails, as it has just done, when a smaller number of constituents account for substantially all the gains, then capital gravitates towards them and momentum takes over often resulting in overvaluation. We have seen this take place in the US in and around the FAANG (Facebook, Amazon, Apple, Netflix Google) group of companies. A recent note pointed the assumptions required to justify Amazon’s lofty valuation around its year’s high of US$2050 on the 4th of September.
In the human body, our internals move towards purgative events, an analogy that can be drawn into markets.
Nothing stands still for long in investment. The variables move and effect each other in different ways: what George Soros calls reflexivity. Here, at the last, comes the positive point. As leverage is drawn out of the markets, room for rallies is created. If weakening economic fundamentals combine with moves to slow the tightening in financial conditions, the US dollar may lose ground. That creates room for differential performance that favours Emerging over Developed markets and plausibly sets off a long wave in which the US begins to underperform the rest of the world. A few months of turmoil beget ten years of opportunities for a global portfolio.