An increase in expected default ratios naturally reduces prices for corporate bonds. However, it also triggers feedback loops. First, it reduces funds’ wealth and demand for corporate credit in terms of notional, resulting in selling for rebalancing purposes. Second, negative performance of funds typically triggers investor outflows, resulting in selling for redemption purposes. Flow-sensitive market-making and momentum trading can aggravate these price dynamics. A larger market share of passive funds can increase tail risks.

Braun-Munzinger, Karen, Zijun Liu and Arthur Turrell (2016), “An agent-based model of dynamics in corporate bond trading”, Bank of England, Staff Working Paper No. 592.

The post ties in with the subject of price distortions through risk reduction and investor redemptions as summarized here.

The below are excerpts from the paper. Headings and cursive text have been added.

Modelling a corporate bond market

“We construct a…model of the corporate bond market capturing the interaction of market maker behaviour, fund trading strategies, and cash allocation by investors in funds to study feedback effects and the impact of market changes.”

“There are two types of active trading. Value traders assume that yields will revert to some fixed value over time, and thus buy more of the risky asset when they believe it is undervalued and less when overvalued. Momentum traders believe short-term trends in yield will persist and so sell if yields are above a long-term average and buy if yields are below it… These funds are subject to cash in- and outflows from a stylised investor pool.…A third set of funds, passive investment funds, only trade in response to in- and outflows from investors rather than taking a view on price.”

“Prices are adjusted by the (stylised) market maker…The market maker changes prices in response to demand. This allows us to proxy increased risk aversion as a consequence of volatility.”


“The model parameters are calibrated against empirical data on US corporate bond trading…We use empirical properties of the post-crisis sample (since end–2010) only. This comprises 1503 trading days.

  • The duration of corporate bonds is set to 6.917 years…
  • The annual loss rate is set to 0.04%, which was the annual credit loss rate of investment-grade corporate bonds in 2010 according to Moody’s…
  • There are around 1000 open-ended mutual funds that invest in US corporate bonds…
  • The total amount of US corporate bonds held by open-ended mutual funds (i.e. mutual funds that allow daily investment and redemptions, as in the case in our model) is around $740 billion as at 2015Q2….There are around $6.7 trillion of US corporate bonds outstanding as at 2015Q2, of which $5.3 trillion were investment grade…
  • Around 20% of open-ended mutual funds that invest in US corporate bonds were index funds…
  • Fund flows in our model depend on both market-wide factors, such as the return on the market index, and fund-specific factors…We find that a 1% return on the index is associated with a 0.25% increase in aggregate net flow…A fund will have an inflow of 0.621% for 1% excess returns (above the industry average), and an outflow of 1.128% for a -1% excess return.”

Shock impact

“When running the calibrated model, we typically find repeating cycles of yield swings and corrections.”

“A schematic of what occurs in a shock to the expected loss rate value is shown in…[the figure below]. The change in the annual loss rate feeds into the proportion of risky assets that funds are willing to hold, thus changing excess demand. This changes price and yield via the market maker, who responds to excess demand…One consequence of this is that funds’ wealth is reduced. Furthermore, the fall in price means that the returns to investors are lower, triggering investor outflows. This then causes a further reduction in fund wealth. Reductions in fund wealth must be met by both selling the risky asset, and through the risk-less asset. Asset sales by funds prompt further price cuts, and the feedback loop continues.”

“We find broadly similar feedback effects in response to a shock to funds’ wealth, which could be triggered, for example, by a reassessment by investors of the liquidity risk inherent in holding fund assets or news on fund management.”


What factors aggravate price volatility?

“We find that the sensitivity of the market maker to demand and the degree to which momentum traders are active strongly influence the over and undershooting of yields in response to a shock. This suggests that correlation in funds’ trading strategies can exacerbate extreme price movements and contribute to the pro-cyclicality of financial markets.”

“The median impact of an increased presence of passive funds is dependent on the shock in question. Their presence can reduce overshooting due to new information as, in contrast to momentum traders and value traders, they do not trade based on news. But in exogenous shocks such as reduced demand due to investor withdrawals, median yield dislocations can increase. This reflects increased tail risk of large yield swings in the absence of active investors.”