Building a real-time market distress index

A new Fed paper explains how to construct a real-time distress index, using the case of the corporate bond market. The index is based on metrics that describe the functioning of primary and secondary markets and, unlike other distress measures, does not rely on prices and volatility alone. Thus, it includes issuance volumes and issuer characteristics on the primary side and trading volumes and liquidity on the secondary market side. Making use of a broad range of data on market functioning reduces the risk of mistaking a decline in asset values for actual market distress. Distress in a market that is critical for funding the economy and the financial system has predictive power for future economic dynamics and can be a valuable trading signal in its own right. It can be used for more advanced trend following and for detecting price distortions.


How market liquidity causes price distortions

Liquidity is a critical force behind market price distortions (and related trading opportunities). First, the cost of trading in and out of a contract gives rise to a liquidity premium. Second, the risk that transaction costs will rise when market conditions necessitate trading commands a separate liquidity risk premium. Third, actual changes in liquidity can precipitate large price changes without any fundamental value consideration. Finally, low liquidity is conducive to ‘run equilibria`, where bids or offers of some institutional investors turn into pricing signals for others, giving rise to self-reinforcing dynamics with feedback loops and margin calls. Examples for liquidity-driven price distortions in the past include breakdowns of covered interest parity across currencies, bond market ‘tantrums’, and ‘fire sales’ in emerging local-currency markets.


The price effects of order flow

Order flow means buyer- or seller-initiated transactions at electronic exchanges. Order flow consumes liquidity provided by market makers and drives a wedge between transacted market price and equilibrium price, even if the flow is based on information advantage. Flow distorts market prices for two reasons. First, the need for imminent transaction carries a convenience charge. Second, the prevalence of informed flow justifies a charge for market risk on the part of the market maker. Standard models suggest that the price impact is increasing in the square root of the order flow, i.e. increases with the order size, but not linearly so. New theoretical work suggests that the price impact function may be “S-shaped”, i.e. increases more than proportionately in the smaller size range and less than proportionately for large sizes. The price effects of order flow are relevant for the design of algorithmic trading strategies, both as signal and execution parameter.


Endogenous market risk: updated primer

Endogenous risk arises from the interaction of financial market participants, as opposed to traded assets’ fundamental value. It often manifests as feedback loops after some exogenous shock. An important type of endogenous market risk is setback risk, which refers to the asymmetry of the upside and downside potential of a trade that arises from market positioning. Setback risk is a proclivity to incur outsized mark-to-market losses even if the fundamental value proposition of the trade remains perfectly valid. This makes it the natural counterweight to popular positioning. A useful two-factor model for detecting setback risk can be based on market positioning and exit risk. There are quantitative metrics for both. The highest setback risk is characterized by crowded positions that face an incoming type of shock that most investment managers had not considered.

The below is an updated summary.

What is endogenous market risk?

Endogenous market risk is the risk generated and reinforced within the financial system by the interaction of its participants. This is opposed to exogenous risk which refers to shocks that come from outside the financial system, such as changes in fundamental asset values or political risk. The term endogenous risk was coined by researchers at the London School of Economics (LSE) and this risk is the focus of the LSE’s Systemic Risk Centre.

A key propagation mechanism of endogenous market risk is feedback loops: one trader’s losses and liquidation often trigger another trader’s risk reduction and so forth. Risk management, balance sheet constraints and publicity all can act as amplification mechanisms. Importantly, the actively trading part of the market is not a zero-sum book but often jointly bets on a growing financial wealth of the world or takes positions that are implicitly subsidized by non-financial institutions. The habitual focus of most professional traders on flows and positions testifies to the critical importance of endogenous market risk for short-term price action.

What is setback risk?

Setback risk is a particularly important form of endogenous market risk. Technically speaking, setback risk is the difference between downside and upside risk to the mark-to-market of a contract due to investor positioning. Like all endogenous risk, it is in itself unrelated to the fundamental value of the underlying assets. If an investor believes that a security is fundamentally overvalued and may reprice in the future this is not endogenous market risk, but merely a disagreement with the prevailing market valuation.

Setback risk indicates the market’s latent tendency to revert to a state where positions are “cleaner”, meaning less crowded or reliant on leverage. Importantly, such risk arises merely through the “crowdedness” of trades and their risk management, irrespective of whether the fundamental value proposition is good or not. In fact, it is often the trades that offer the highest and most plausible long-term expected value that are subject to the greatest setback risk. This is consistent with a negative skew in the returns of popular risk premium strategies. For example, FX carry trade returns have historically displayed a proclivity to much larger negative than positive outliers (view post here), even when they remained profitable in the long run.

Setback risk in trading practice

Setback risk is the natural counterweight to popular positioning motives, such as implicit subsidies, fundamental trends or statistical trend-following. Its presence means that the popularity and crowdedness of trades should be justified by a sufficient risk premium. Therefore, systematic strategies that rely on popular factors can often be improved by complementary setback risk measures.

Setback risk also ties the prospects of popular presumed market-neutral strategies to the state of overall market risk prices. When risk-off shocks hit the dominant directional exposure of financial market participants their capacity for maintaining other positions also decreases. Hence all crowded and popular positions are exposed, even if they have no significant historical market beta. For example, there is empirical evidence that momentum strategies that buy winners and sell losers in terms of recent price trends have greater sensitivity to downside than to upside market risk across asset classes (view post here).

Generally, the presence of endogenous market risk has profound consequences on trading returns across many valid trading styles and systematic strategies. This risk is hard to avoid and skews the probability of future price moves against valid positioning motives, as long as these motives are common to a significant part of the market. Mechanical risk reduction rules and market liquidity constraints also suggest that the distribution of returns will have “fat tails”. Put simply, large adverse outliers relative to standard deviations should be expected in most value-generating trading strategies.


Information on endogenous market risk comes from a broad variety of sources, including positioning data, short-term correlation of PnL’s with hedge fund benchmarks, asymmetries of upside and downside market correlation, or simply past performance and the popularity of trades in broker research recommendation. Endogenous market risk of relative value and arbitrage trades often arises from outflows in the hedge fund industry. Hedge funds’ capital structure is vulnerable to market shocks because most of them offer high liquidity to loss-sensitive investors (view post here).  Moreover, the build-up of endogenous market risk can be inferred from theory. For example, compressed interest rate term premia at the zero lower bound for policy rates are naturally quite vulnerable to any risk of future rates increases (view post here).

A two-factor model for detecting setback risk

It is useful to decompose setback risk into two factors: positioning and exit riskPositioning refers to the “crowdedness” of a trade. Exit risk refers to the probability of liquidation, i.e. that the crowd will run for the exit. Setback risk is high when a trade is “crowded” and near-term position reductions are probable. While the positioning component always relates to a specific contract, exit risk can be a global factor, such as tightening dollar funding conditions.


Positioning relative to market liquidity principally indicates the potential size of the PnL setback. For some contracts exchanges or custodian banks provide outright positioning data. However, these are not always easy to interpret. In practice, macro traders pay much heed to informal warning signs, such as anecdotal evidence of positioning provided by their brokers, surveys among investment managers, return correlation with market benchmarks (view post here) and lack of position performance in spite of positive news. Also, medium-term historic performance of popular risk premium strategies is often good indirect indicators of their popularity and, hence, positioning.

Conceptually, the crowdedness of trades in a portfolio can be measured by “centrality”, a concept of network analysis that measures how similar one institution’s portfolio is to its peers (view post here). Empirical evidence suggests that the centrality of portfolios is negatively related to future returns.

Exit risk

Exit risk principally indicates the probability of a near-term setback, be it small or large. The most prominent triggers of large-scale unwinding of macro trades are volatility or Value-at-Risk jumps (view post here) and liquidity and funding pressure (view post here and here). The term trigger here refers to an endogenous market shock that is likely to lead to subsequent self-reinforcing price dynamics. Catching such triggers requires estimation of [1] the complacency of the market with respect to an adverse shock and [2] the gravity of specific adverse shocks.

Complacency here means lack of resilience to adverse shocks. This lack of resilience arises from an optimistic mode of expectations, typically fuelled by marketing pitches for assets and trades, or from implausibly low-risk perceptions that are likely to be revised upward during the lifetime of the trade even if the risk itself does not manifest. Risk perceptions can be measured in a wide range of news-based, survey-based and asset price-based indicators (view post here). Direct measures of complacency include variance risk premia (view post here) and the term structure of option-implied equity volatility (view post here). Another plausible indication for complacency is the homogeneity of economist forecasts. Empirical analyses point to an important principle: when economists are clustered tightly around a consensus, actual data surprises tend to have stronger market impact (view post here). Generalizing this point, it seems plausible that a strong analyst consensus that supports a macro position makes this position more vulnerable to data surprises.

Gravity of shock refers to the probability that a shock is rated as significant and consequential by market participants. This depends upon type and strength of shock. Note that the shock itself can be exogenous (come from outside the market) but is evaluated due to its potential for unleashing self-reinforcing endogenous market dynamics.

  • One of the most toxic types of shock is a “black swan”, an event had been rated as highly unlikely, has an extreme impact and is incorrectly rationalized even after it occurred. Put simply, the less probable a negative shock, the harder its impact. The worst market crises are the ones that investment managers have never prepared for (view post here).
  • Another particularly dangerous type of shock is a decline of liquidity or capital ratios of financial intermediaries. This type of shock diminishes the capacity of dealers to warehouse the net risk position of other market participants (view post here). The result can be forced liquidations that put particular pressure on risk positions that offer high expected long-term value or that are popular for other reasons.
  • A more frequent shock with self-reinforcing potential is a surge in people’s fear of disaster. Theoretical research shows that a re-assessment of beliefs towards higher disaster risk triggers all sorts of uncertainty shocks, for example with respect to macro variable, company-specific performances and other people’s beliefs (view post here). This can derail both directional and relative value trades.

From a statistical angle, shock detection often focuses on ”volatility surprises” (market price changes outside the range of expected variation) that make investors revise drastically the probabilities for various risks. Volatility shocks typically draw attention to previously underestimated risks and transmit easily across markets and asset classes (view post here). Moreover, volatility shocks are critical in a statistical sense because financial returns plausibly have “fat tails”. This means that [1] financial returns have a proclivity to extreme events and [2] the occurrence of extreme events changes our expectations for uncertainty and risk in the future significantly (view post here). Such a reassessment may take days or weeks to complete and give rise to negative trends.
It is important to discriminate between the medium-term volatility trends and short-term volatility spikes. Longer-term changes of volatility mostly reflect risk premiums and hence establish a positive relation to returns. Short-term swings in volatility often indicate news effects and shocks to leverage, causing a negative volatility-return relation. (view post here).

A theory of hedge fund runs

Hedge funds’ capital structure is vulnerable to market shocks because most of them offer high liquidity to loss-sensitive investors. Moreover, hedge fund managers form expectations about each other based on market prices and investor flows. When industry-wide position liquidations become a distinct risk they will want to exit early, in order to mitigate losses. Under these conditions, market runs arise from fear of runs, not necessarily because of fundamental risk shocks. This is a major source of “endogenous market risk” to popular investment strategies and subsequent price distortions in financial markets, leading to both setbacks and opportunities in arbitrage and relative value trading.


Covered interest parity: breakdowns and opportunities

Since the great financial crisis conventional measures of the covered interest parity across currencies have regularly broken down. Two developments seem to explain this. First, money markets have become more segmented, with top tier banks having access to cheaper and easier funding, particularly in times distress. Second, FX swap markets have experienced recurrent imbalances and market makers have been unable or unwilling to buffer one-sided order flows. Profit opportunities arise for some global banks in form of arbitrage and for other investors in form of trading signals for funding liquidity risk premia.


Volcker Rule and liquidity risk

The Volcker Rule has banned proprietary trading of banks with access to official backstops. Also, market making has become more onerous as restrictions and ambiguities of the rule make it harder for dealers to manage inventory and to absorb large volumes of client orders in times of distress. This increases liquidity risk, particularly in market segments with longer turnover periods, such as corporate bonds. A new empirical paper confirms that the Volcker Rule has indeed reduced corporate bond liquidity and aggravated the price impact of distress events, such as significant rating downgrades.


The illiquidity risk premium

The illiquidity risk premium is an excess return paid to investors for tying up capital. The premium compensates the investor for forfeiting the options to contain mark-to-market losses and to adapt positions to a changing environment. A brief paper by Willis Towers Watson presents an approach to measure the illiquidity risk premium across assets. The premium appears to be time-variant and highest during and pursuant to financial crises.


Why the covered interest parity is breaking down

Deviations in the covered interest parity have become a regular phenomenon even in developed markets. Persistent gaps between on-shore and FX-implied interest rate differentials (“cross-currency basis”) can be explained by the combination of increased cost of financial intermediation in the wake of regulatory reform and global imbalances in investment demand and funding supply. They can offer information value and arbitrage opportunities for investors.


How poor liquidity creates rational price distortions

When OTC markets become illiquid and dealers fail to buffer flows, institutional investors effectively face each other directly in the market. They can observe each other’s actions and position changes. For example, if large investors make offers to sell under illiquidity, the market expects to become “over-positioned” and will avoid bids at a fair price or even put in offers. In equilibrium investors transact at prices below true value and exacerbate initial negative shocks.