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In finance and economics, aggregate risk (sometimes called market risk, systematic risk, or undiversifiable risk) is risk to which all market actors are vulnerable.

Properties of Aggregate Risk

Aggregate or systematic risk arises from market structure or dynamics which produce shocks or uncertainty faced by all agents in the market. In contrast, idiosyncratic risk (sometimes called specific risk, unsystematic risk, residual risk, or diversifiable risk) is risk to which only specific agents or industries are vulnerable (and is uncorrelated with broad market returns). Due to the idiosyncratic nature of unsystematic risk, it can be insured against (or diversified); but since all market actors are vulnerable to aggregate risk, it cannot be insured against or diversified. As a result, assets whose expected returns are negatively correlated with broader market returns are more valuable than assets not possessing this property.

Aggregate or systematic risk should not be confused with systemic risk, the risk of loss from some catastrophic event with potential to collapse an entire financial system.

Aggregate Risk in Finance

Aggregate risk is a key driver of Beta in finance. Since Beta indicates the degree to which an asset's expected return is correlated with broader market outcomes, it is simply an indicator of an asset's vulnerability to aggregate risk. Hence, the capital asset pricing model (CAPM) directly ties an asset's equilibrium price to its exposure to systematic risk.

A Simple Example

Consider an investor who purchases $10,000 of stock in each of ten biotechnology companies. If unforeseen events cause a catastrophic setback and one or two companies' stock prices drop, the investor incurs a loss. On the other hand, an investor who purchases $100,000 in a single biotechnology company would incur ten times the loss from such an event. The second investor's portfolio has more unsystematic risk than the diversified portfolio. Finally, if the setback were to affect the entire industry instead, the investors would incur similar losses due to systematic risk.

Aggregate Risk in Economics

In economic modeling, model outcomes depend heavily on the nature of risk. Modelers often incorporate aggregate risk through shocks to endowments, productivity, monetary policy, or external factors like terms of trade. Idiosyncratic risks can be introduced through mechanisms like individual labor productivity shocks; if agents possess the ability to trade assets and lack borrowing constraints, the welfare effects of idiosyncratic risks are minor. The welfare costs of aggregate risk, though, can be significant.

Aggregate risk has potentially large implications for economic growth. For example, Elosegui (2003) shows that, in the presence of credit rationing, aggregate risk can cause bank failures and hinder capital accumulation. Banks may respond to increases in profitability-threatening aggregate risk by raising standards for quality and quantity credit rationing to reduce monitoring costs; but the practice of lending to small numbers of borrowers reduces the diversification of bank portfolios (concentration risk) while also denying credit to some potentially productive firms or industries. As a result, capital accumulation and the overall productivity level of the economy can decline.

Aggregate risk can be generated by a variety of sources. Fiscal, monetary, and regulatory policy can all be sources of aggregate risk. In some cases, shocks from phenomena like weather and natural disaster can post aggregate risks. Small economies can also be subject to aggregate risks generated by international conditions such as terms of trade shocks.

Under some conditions, aggregate risk can arise from the aggregation of micro shocks to individual agents. Jovanovic (1987) demonstrates that this can be the case in models with many agents and strategic complementarities and lists economic situations with such characteristics: innovation, search and trading, production in the presence of input complementarities, and information sharing. Such situations can generate aggregate data which are empirically indistinguishable from a data-generating process with aggregate shocks.

Example: Arrow-Debreu Equilibrium

The following example is from Mas-Colell, Whinston, and Green (1995). Consider a simple exchange economy with two identical agents, one (divisible) good, and two potential states of the world (which occur with some probability). Each agent has a utility function of the form $\pi _{1}*u_{i}(x_{1i})+\pi _{2}*u_{i}(x_{2i})$ where $\pi _{1}$ and $\pi _{2}$ are the probabilities of states 1 and 2 occurring, respectively. In state 1, agent 1 is endowed with one unit of the good while agent 2 is endowed with nothing. In state 2, agent 2 is endowed with one unit of the good while agent 1 is endowed with nothing. That is, $\omega _{1}=(1,0)$, $\omega _{2}=(0,1)$. Then the aggregate endowment of this economy is one good regardless of which state is realized; that is, the economy has no aggregate risk. It can be shown that, if agents are allowed to make trades, the ratio of the price of a claim on the good in state 1 to the price of a claim on the good in state 2 is equal to the ratios of their respective probabilities of occurance (and, hence, the marginal rates of substitution of each agent are also equal to this ratio). That is, $p_{1}/p_{2}=\pi _{1}/\pi _{2}$. If allowed to do so, agents make trades such that their consumption is equal in either state of the world.

Now consider an example with aggregate risk. The economy is the same as that described above except for endowments: in state 1, agent 1 is endowed two units of the good while agent 2 still receives zero units; and in state 2, agent 2 still receives one unit of the good while agent 1 receives nothing. That is, $\omega _{1}=(2,0)$, $\omega _{2}=(0,1)$. Now, if state 1 is realized, the aggregate endowment is 2 units; but if state 2 is realized, the aggregate endowment is only 1 unit; this economy is subject to aggregate risk. Agents cannot fully insure and guarantee the same consumption in either state. It can be shown that, in this case, the price ratio will be less than the ratio of probabilities of the two states: $p_{1}/p_{2}<\pi _{1}/\pi _{2}$, so $p_{1}/\pi _{1}<p_{2}/\pi _{2}$. So, for example, if the two states occur with equal probability, then $p_{1}<p_{2}$. This is the well-known finance result that the contingent claim that delivers more resources in the state of low market returns has a higher price.

Aggregate Risk in Heterogeneous Agent Models

While the inclusion of aggregate risk is common in macroeconomic models, considerable challenges arise when researchers attempt to incorporate aggregate uncertainty into models with heterogeneous agents. In this case, the entire distribution of allocational outcomes is a state variable which must be carried across periods. This gives rise to the well-known curse of dimensionality. One approach to the dilemma is to let agents ignore attributes of the aggregate distribution, justifying this assumption by referring to bounded rationality. Den Haan (2010) evaluates several algorithms which have been applied to solving the Krusell and Smith (1998) model, showing that solution accuracy can depend heavily on solution method. Researchers should carefully consider the results of accuracy tests while choosing solution methods and pay particular attention to grid selection.

Global Hedging and Aggregate Risk

In some cases, aggregate risk exists due to institutional or other constraints on market completeness. For countries or regions lacking access to broad hedging markets, events like earthquakes and adverse weather shocks can also act as costly aggregate risks. Shiller (1995) found that, despite the globalization progress of recent decades, country-level aggregate income risks are still significant and could potentially be reduced through the creation of better global hedging markets (thereby potentially becoming idiosyncratic, rather than aggregate, risks). Specifically, Shiller advocated for the creation of macro futures markets. The benefits of such a mechanism would depend on the degree to which macro conditions are correlated across countries.