Markets are not efficient in respect to macroeconomic information, because both research and strategy development are expensive. As a result, there is ample scope for value generation based on researching fundamental valuation gaps, detecting implicit subsidies, and tracking the setback risk to popular strategies. Increased macro information efficiency benefits both investors and economies at large.
The below is an update of the summary page “macro information efficiency” of this blog.
It is based on a number of posts, with the links given below.
Further research and thoughts on this subject would be highly appreciated (email@example.com)
Why macro information is relevant
Financial market prices are part of the global macroeconomic equilibrium. Interest rates affect agents’ savings, consumption, and investment decisions. Credit spreads determine the conditions of lending and borrowing of firms and sovereigns. Exchange rates affect the competitiveness and net asset positions of countries’ residents. Equity prices determine the attractiveness of taking economic risk. And commodity prices shape the terms-of-trade of economies and companies. The main social value of macroeconomic information efficiency is the adjustment of prices to changing economic conditions in a way that fosters the efficient allocation of resources. At the same time, portfolio managers that invest in macro research can create investor value by detecting fundamental economic and price trends early.
Why markets are not (macro) information efficient
The quantity of economic and financial data that is available to financial market participants has expanded rapidly. Also, transmission speed, scope, and detail of non-quantitative information has surged. Analytic tools, infrastructure, and support programs for dealing with large quantities of information have multiplied as well. Notwithstanding these advancements there is reason and evidence to suggest that markets have not come even close to exhausting their potential for information efficiency.
- The seminal article “On the Impossibility of Informationally Efficient Markets” by Grossman and Stiglitz explained that since price-relevant information is costly it will only be procured to the extent that inefficient markets allow translating it into sufficient returns. As the article points out: ” The only way informed traders can earn a return on their activity of information gathering, is if they can use their information to take positions in the market which are ‘better’ than the positions of uninformed traders…Hence the assumptions that all markets, including that for information, are always in equilibrium and always perfectly arbitraged are inconsistent when arbitrage is costly” (view journal article here).
- More recent theoretical work suggests that even (fundamental) value traders only invest in research and information if (i) information cost is not too high, (ii) overall markets are poorly informed, and (iii) market makers do not suspect that value traders are well informed (view post here). The latter is important, because a value trader with a reputation of being well informed is easily “front run” when giving orders to market makers. In summary, information efficiency is a complex trade-off, with no guarantee that markets as a whole set asset prices close to their fundamental value.
- In practice, macroeconomic research itself is tedious and expensive and often beyond the scope of portfolio management teams. This reflects thee basic difficulties. First, economic data are notoriously hard to interpret and require considerable adjustments. Even the most popular and highest-quality economic data, such as U.S. economic reports, need in-depth research to be understood (view post here). Second, the relation between economic information and asset prices requires an profound experience and theoretical understanding. Good mathematical modeling is in short supply. Institutional investors prefer simple relations, often condensed in the three main categories of risk premia strategies, i.e. carry, momentum, and relative value (view post here).
- Finally, the diffusion of information through markets depends on transactions. It is not enough to research and publish. Financial markets research translates into price information only if it is acted upon. In practice, the transformation of research and information into positions is often obstructed by institutional rules and regulations. This “obstruction to diffusion” means that relevant information and research often translate into gradual price trends rather than instantaneous price adjustments (view post here).
The above points go some way in explaining why in the past simple trend following has been a profitable trading strategy, even in the best researched and most liquid markets (view post here). Moreover, there is ample evidence of herding and sequential dissemination of information in markets with great macroeconomic importance, including currencies (view post here, and here). These phenomena testify to the sluggishness of market responses to broad shifts in fundamental conditions.
The consequence is that investment managers have scope to contribute to and benefit from information efficiency. From practical experience I would propose to structure indicators into three groups, in order to facilitate their subsequent combination and transformation into a single investment proposition .
- Valuation gaps are defined as differences between the market price of an asset and its research-based estimated value.
- Implicit subsidies are defined as premia paid to or discounts offered to financial investors by other market participants.
- Setback risks are factors that increase the vulnerability of a dominant positioning motive, typically implicit subsidies, and that are unrelated to fundamental value considerations.
The important feature of the above distinction is that the three types of indicators are complementary, not competing. Typically a negative price-value gap arises as consequence of implicit subsidies, suggesting that the two need to be weighed against each other. Also, setback risks arise alongside subsidies, making it advisable to adjust the latter for the influence of the former.
This post leaves out investment value generation based on the research of price distortions (view summary page here). That is because the exploitation of price distortions is not primarily an issue of macro information efficiency. Rather it depends on being able to understand and operate free from the constraints and conventions that trap many institutional investors.
There are two basic methods of estimating valuation gaps. The first is to estimate an asset’s fundamental value directly and compare it with the price. The second method works indirectly, estimating key relevant economic trends and comparing these with market perceptions.
Method 1: Fundamental value estimates
The fundamental value of a security or derivative contract is the expected risk-adjusted present value of all associated entitlements or obligations. Such estimation is very challenging. Among the great difficulties are [i] a full understanding of contract or security properties, [ii] an appropriate modeling of the uncertain environment, and [iii] the application of stochastic calculus to both. In practice, most investors shun all three of the above, and much prefer rules of thumb, such as earnings yields or price-to-book ratios.
An improvement of fundamental value estimates over such rules of thumb can already be achieved by carefully considering the exact properties of a contract. Common areas of negligence are conditions of credit default swaps, sector specifics of country equity indices, and counterparty risk involved in many standard over-the-counter derivative contracts. Even standard exchange traded contracts may not deliver the underlying at the time and place it would be needed. For example, buyers of commodity futures in the base metal space have been facing long delays in the load-out from designated warehouses. This has led market rationing and high premiums for physical metals over exchange traded spot prices (view post here).
The more common means of outperforming conventional valuation metrics is by improving them through a more advanced consideration the relevant environment. For example, in the equity space fundamental value gaps can often be detected by adjusting conventional valuation ratios to the specifics of the economy or the corporate sector. J.P. Morgan Cazenove illustrated how the information value of equity dividend yield can be enhanced, by measuring a “shareholder yield” that integrates dividends with other forms of cash returns such as. share buybacks and debt redemption (view post here). Each iteration that makes valuation ratios more meaningful, while keeping the cost of data and maintenance acceptable improves decisions and value generation.
Another example from the FX space are “smart” concepts of real trade-weighted exchange rates. The more closely they are related to a country’s competitiveness, the greater their predictive power for a currency’s future trajectory and its equity market’s relative performance (view post here).
Method 2: Macroeconomic trend indicators
This method does not focus on the valuation gap holistically, but on plausible sources of misalignment. A primary suspect is economic change, which often is not incorporated in asset prices in a timely and efficient manner. Apprehending economic trends more quickly and reliably than the majority of the market is a very practical method for detecting valuation gaps.
Importantly, the longer the time horizon of a market price change the greater the influence of macroeconomic trends, because they are more persistent than non-fundamental factors. For example, it has been estimated that more than a third of bond price fluctuations in the U.S. can be explained by the country’s major published economic data (view post here). Beyond obvious directional relations (i.e. low inflation supporting low interest rates) there are also links in volatility. For example, there is evidence that uncertainty about the economic and financial state of an economy is conducive to higher volatility in market prices (view post here on evidence for commodity markets).
While there are countless economic time series, few of them provide on their own reliable and relevant information for broad macroeconomic and market trends. In practice, market participants must build their own indicators, based on available statistics, quantitative methods, and a good deal of judgment. A macroeconomic trend indicator can be defined as a time series representing a meaningful macroeconomic trend that can be mapped to the performance of tradable assets.
Major challenges for macroeconomic trend indicators are [i] the consideration of the full global picture (rather than just local data) and [ii] the use of qualitative information alongside quantitative metrics. This is nicely illustrated by the concept of “capital flow deflection”, which stipulates that one country’s capital inflow restrictions are likely to increase the inflows into other similar countries (view post here). In order to measure this effect one needs to build a time series of capital controls in all major economies in order to distill the specific impact on a single currency.
An implicit subsidy is defined as a premium paid to financial investors by a significant group of market participants for reasons that are unrelated to conventional financial return motives. The premium can be positive or negative (discount accepted). Classic examples are interventions of governments and central banks for the purpose of economic policy. Another example are insurance premia paid by suppliers or industrial users in various commodity future markets for the purpose of hedging price risk.
Receiving an implicit subsidy creates value for financial investors because it is payment for the service of bearing risk that is disliked elsewhere. This type of value generation does require information efficiency insofar as the financial investor must detect and quantify the subsidy. However, unlike valuation gaps, it does not require to be better informed than the market. The drawback of subsidies is that they attract crowds and, like all crowded trades, incur the risk of sudden outsized drawdowns when conditions change. This “setback risk” is dealt with in the final section of this summary.
One of the most popular implicit subsidies is the FX carry trade. Historically, positions in floating and convertible currencies have benefited from two premia paid.
- First, central banks often impose high local short-term interest rates or even intervene persistently for the sake of exchange rate and price stability. This is an implicit subsidy to lenders in local currency. Empirical research shows that official currency interventions can cause persistent external imbalances and over- or under-valuation of a currency (view post here).
- Second, institutions and households that have experienced or fear financial turmoil are often willing to forgo expected return by holding “hard currencies” rather than currencies. This is an implicit insurance premium. Indeed, carry trades work particularly well when high risk premia give rise to both high interest rates and subsequent revaluation of “carry currencies” (view post here).
FX carry trades also illustrate the inherent vulnerability of subsidy-based investment strategies. Positive carry often encourages capital inflows into small markets that reduce inflation and but cause a domestic asset market boom. Because of the former, the central bank does not fight the latter. Thereby, FX carry strategies can produce self-validating flows. Conversely, a reversal of such flows is self-destructing (view post here).
Another popular example are “convenience yields” implied in commodity futures curves. Commodity convenience yields represent the implied interest paid for borrowing physical commodity. Holding physical inventories carries benefits of flexibility for industrial consumers. The value of such inventories increases when scarcities arise. As a consequence, convenience yields help predicting future demand and price changes (view post here).
The price information of volatility markets can be helpful in distinguishing subsidies from price expectations. For example, insurance costs for currency exposure, which is highly relevant for financial and real economic investors, can be inferred from the relation between expected realized and options-implied volatility (volatility risk premium, view post here). More generally, volatility markets are indicative of the price charged by financial markets for both known and unknown risks (view post here). These “insurance costs” can help assessing fear and uncertainty in financial markets and the economy at large.
A setback risk is defined as the risk of a significant asset “sell-off” (or “squeeze”) unrelated to fundamental value considerations. Setback risk is the natural counterweight to a dominant positioning motivation, typically an implied subsidy. It usually implies that the distribution of probability for future prices is skewed and has “fat tails”. A setback risk has two components: positioning and exit risks. Put simply, setback risk is high when a trade is “crowded” and conditions for its survival are demanding, for example due to high expectations, high leverage, or tight risk management. Information efficiency in respect to setback risk creates social value by reducing the risk of dislocation and crisis. It creates investor value by reducing the occurrence of large outsized drawdowns and forced expensive position liquidations.
Positioning relative to market liquidity indicates the potential size of a setback. For some contracts there are outright position data being produced by exchanges or custodian banks. However, neither of these are easy to interpret. In practice, macro traders pay much heed to anecdotal evidence of positioning provided by their brokers. More objectively, the existence of apparent implicit subsidies and past performance of related strategies is often a good indirect indicator of positioning.
Exit risks gives the probability of popular value-generating trades being unwound. The most prominent of these relate to global events such as volatility or Value-at-Risk shocks (view post here) or liquidity and funding pressure (view post here and here). Forward looking indicators can include estimation of “complacency” or shock effects.
- Complacency here means lack of resilience. This could be indicated by ratio of the level of implied volatility to estimated macro risk.
- Shock effect indicators require an assessments whether recent changes to market prices might indicate or trigger escalatory dynamics. There is research suggesting that”volatility surprises” (market price changes outside the range of expected variation) provide information on the probable evolution of prices for various risks. These shocks typically draw attention to previously underestimated risks and transmit easily across markets and asset classes (view post here).