The macro information inefficiency of financial markets

Understanding macro information (in-) efficiency

What is macro information efficiency?

Macro information here refers to public information on the economy and its key sectors that is relevant for the pricing of assets and derivatives. This type of information includes economic data (on growth, inflation, confidence, and so forth), government and corporate balance sheets, financial market data (including turnover and open interest), social and political developments, and even environmental and weather trends.

The information efficiency of an asset market is defined as the extent to which the price of the asset reflects available information. Importantly, the efficiency of a market does not mean efficient use of information across all market participants. Different individuals or institutions have different capacities to buy, collect and use data. This is one key reason why there is trading and rational herding behavior (view post here). Herding is rational for uninformed but flexible traders when important releases are forthcoming and some market participants are likely to have private advance information. An information-efficient market produces, researches, and applies macro information to the extent that investment returns and social benefits exceed information costs.

Academic literature often neglects information and research costs, which is not without irony. For the case of negligible information costs, Burton Malkiel (1992) offers a stricter efficiency condition: “A capital market is…efficient if it fully and correctly reflects all relevant information in determining security prices. Formally, the market is said to be efficient with respect to some information set…if the security price would be unaffected by revealing that information to all participants.”

Why are markets not (macro) information efficient?

The principal obstacles to information efficiency are costs, trading restrictions, and external effects. In their seminal article “On the Impossibility of Informationally Efficient Markets” Grossman and Stiglitz explained that since price-relevant information comes at a cost it will only be procured to the extent that inefficient markets allow translating it into sufficient returns: ” 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). This theory shows what practitioners already know: investment in information involves a trade-off between cost and return, with no guarantee that markets set asset prices close to their fundamental value.

Acknowledging the cost-return trade-off, the theory of rational inattention provides a model of how market participants manage their scarcity of attention (view post here). In general, people cannot continuously process and act upon all information, but they can set priorities and choose the mistakes they are willing to make. Rational inattention explains why agents pay disproportionate attention to popular variables, simplify the world into a small set of indicators, pay more attention in times of uncertainty, and limit their range of actions.

Theory and practice show that investment managers only collect information and engage in research if costs are contained, if the overall market is not already well informed, and if the information advantage can remain confidential:

• First, information cost must not exceed related expected returns. Genuine value-generating macroeconomic and financial research requires experience, quantitative skills and systems, and a lot of legwork. This means that information costs easily add up to large numbers in practice. Many essential areas of this research, such as real-time economic data or advanced modeling, are beyond the scope of most portfolio management teams, even at large institutions. Thus, standard economic data are notoriously hard to interpret and require considerable adjustments. Economists often disagree on their interpretation of data and do not normally update their predictions continuously. Even the most popular and highest-quality economic data, such as U.S. labor market reports, need in-depth research to extract information (view post here). Also, forecasts are also not easily comparable across countries due to different conventions and biases. All this gives rise to rational information inattentiveness of markets (view post here). This means that market participants update their information set sporadically, rather than continuously. Rational inattentiveness reflects costs of acquiring information or costs of re-optimizing investment decisions. There is empirical evidence that inattentiveness causes sticky expectations and goes some way in explaining price momentum after important relevant news, such as corporate earnings releases (view post here). Moreover, understanding the relationship between economic information and asset prices requires experience and econometric skills. Data science has come a long way in providing powerful tools for analysis and model construction. However, in the data-constrained macro space, the success of statistical models hinges on good judgment and real in-depth understanding of methods, models, and data, all of which remain in short supply. Therefore, most, 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).
• Second, investor research only pays off when the overall market is not already well informed. Put simply, research must result in a significant information advantage. This can be a serious obstacle because the information content of prices with respect to known fundamentals tends to grow faster than the information content of private research. This discourages fundamental research and can lead to over-reliance on price information (view post here). Experimental research has confirmed that traders do not invest in information if they believe that others have already done so and that market prices already reflect this research (view post here). For a profitable investment management business, it is crucial to invest in relevant information where or when others do not.
• Third, the information advantage must remain confidential. In particular, market makers must not suspect that their counterpart is in possession of superior information (view post here). A value trader with a reputation of being well informed is easily ‘front run’ when giving orders to market makers. As pointed out by Bouchaud, Farmer and Lillo (2009): “If I know that you are rational, and I know that you have different information than I have, when I see you trade and the price rises I can infer the importance of your information and thus I should change my own valuation.”

Moreover, research alone does not produce efficient markets. Financial markets research translates into price information only if it is acted upon. Alas, the link between research and actual investment flows is often tenuous, for various reasons.

• Taking positions in accordance with research is frequently obstructed by institutional rules and regulations. For example, many funds face limitations to leverage and short selling or are prohibited from investing in specific asset classes, currencies, and sectors.
• For some institutions market access is limited and trading costs can be prohibitively high. For example, in OTC (over-the-counter) markets bid-offer spreads vary across counterparties(view post here), favoring clients with high volumes and sophistication. Since institutional investment strategies in forwards, swaps, and options that are sensitive to transaction cost implementation depends on the institution’s standing with market makers.
• Often enough investment managers simply do not fully trust their researchers, possibly due to conflicts of interest. Portfolio managers sometimes denigrate research to elevate their own role in profit generation. Researchers sometimes gear their research towards company politics and reputation rather than investment value.
• Finally, there is evidence that financial decision-making under uncertainty is far from rational and subject to a range of behavioral biases, such as the illusion of control, anchoring bias, sunk-cost bias, and gambler’s fallacy (view post here). This implies irrational neglect of optimal strategies.

Even if some market participants have superior information and do rationally trade on it, there is no guarantee that their trading will make the overall market more information efficient. As Markus Brunnermeier (2005) illustrated: “While information leakage makes the price process more informative in the short-run, it reduces its informativeness in the long-run…A trader who receives a noisy signal about a forthcoming public announcement can exploit it twice. First, when he receives it, and second, after the public announcement since he knows best the extent to which his information is already reflected in the pre-announcement price. Given his information he expects the price to overshoot and intends to partially revert his trade.” In summary, “obstructions to information diffusion” are common. This means that relevant information and research translate into gradual price trends rather than instantaneous price adjustments (view post here). Gradual diffusion directly conflicts with Eugene Fama’s requirement that an “efficient market is a market which adjusts rapidly to new information.”. Indeed, sluggish price adjustment seems to go a long way in explaining unexpected deviations of financial markets from a rational expectations equilibrium, including the many so-called ‘puzzles’ in the foreign exchange market (view post here).

What is the evidence for macro inefficiency?

Macro information inefficiency is consistent with the evidence of numerous behavioral biases of both retail and professional investors.

• Indicators of growth and inflation cycles have been successful predictors of outright and relative asset class returns with relationships being consistent with standard macroeconomic theory (view post here). Macroeconomic trends such as economic growth, inflation, and credit growth have been powerful predictors of fixed-income returns in the past (view post here) even when they were in plain sight of attentive economic analysts. Similarly, changes in market-implied breakeven inflation and data-based estimations of inflation expectations have been predictors of interest rate swap returns (view post here). Also, inflation trends in particular have been powerful predictors of international equity returns (view post here).
• Survey evidence suggests that retail investors adjust positions sluggishly to changing beliefs and that their beliefs themselves defy classic rationality (view post here). Sluggishness manifests in two ways. First, the sensitivity of portfolio choices to beliefs is small. Second, the timing of trades does not depend much on belief changes. Contrary to standard rationality, investors cling stubbornly to diverse beliefs with little convergence over time.
• There is also empirical evidence that overall financial markets pay less attention to macroeconomic news when market sentiment is positive (view post here). Behavioral research supports the idea that investors prefer heuristic decision-making and neglect fundamental information in bullish markets.
• Macro information inefficiency also explains the dominance of simple investment rules with little fundamental research. In practice, asset allocation often just follows past performance (view post here), simplistic highly stylized factors (view post here), risk parity and valuation ratios (view post here), or simply market capitalization and benchmark index conventions (view post here). Even active portfolio managers often find it more practical to produce “fake alpha” through receiving risk premia on exposure to non-directional conventional factors and strategies rather than to generate true investor value (view post here).
• Furthermore, information inefficiency explains why momentum trading has been a profitable trading strategy, even in the best researched and most liquid markets (view post here), and is widely used as a trading style to protect against adverse macro trends (view post here). There is ample evidence of herding and sequential dissemination of information in markets with great macroeconomic importance, including currencies (view post here, and here). And there is evidence simple fundamentals trend following has yielded significant returns in equity markets in past decades (view post here). All these phenomena testify to the sluggishness of market responses to broad shifts in fundamental conditions.
• Finally, experimental research has added evidence for mispricing of assets relative to their fundamental values. Academic studies support a wide range of causes for such mispricing, including asset supply, peer performance pressure, overconfidence in private information (view post here), speculative overpricing, risk aversion, confusion about macroeconomic signals and – more generally – inexperience and cognitive limitations of market participants (view post here). In particular, as pointed out by Bouattour and Martinez (2019), “laboratory experiments…find that market efficiency is reduced when the fundamental value of stocks is volatile…The more volatile the fundamental value, the more the informational efficiency is reduced…Also, participants under-react to information announcements. This under-reaction, which is more pronounced in markets with information asymmetry between subjects…is not corrected during trading periods.”

What is the value of striving for macro efficiency?

Trading towards information efficiency produces social and business value:

• The main social value of macro information efficiency is the alignment of prices with economic conditions. Put simply, macro traders help to guide the efficient allocation of resources across the world economy. Financial market prices guide the decisions of virtually all economic agents. Interest rates guide savings, consumption, and investment decisions. Credit spreads influence the conditions of lending to and borrowing of households, firms, and sovereigns. Exchange rates affect the competitiveness and net asset positions of residents across currency areas. Equity prices determine the attractiveness of entrepreneurial risk. And commodity prices set the terms-of-trade of economies and companies.
• The main individual business value of macro efficient trading are returns that arise from detecting misalignments and trends early before the more sluggish part of the market has caught up with the flow of macro information underlying various markets. Trading based on information efficiency is often enough “trend leading” or trend-setting” as opposed to “trend following”.