Joseph Noss

Estimating Probability Distributions of Future Asset Prices: Empirical Transformations from Option-Implied Risk-Neutral to Real-World Density Functions

The prices of derivatives contracts can be used to estimate ‘risk-neutral’ probability density functions that give an indication of the weight investors place on different future prices of their underlying assets, were they risk-neutral. In the likely case that investors are risk-averse, this leads to differences between the risk-neutral probability density and the actual distribution of prices. But if this difference displays a systematic pattern over time, it may be exploited to transform the risk-neutral density into a ‘real-world’ density that better reflect agents’ actual expectations. This work offers a methodology for performing this transformation. The resulting real-world densities may better represent market participants’ views of future prices, and so offer an enhanced means of quantifying the uncertainty around financial variables. Comparison with their risk-neutral equivalents may also reveal new and useful information as to how attitudes towards risk are affecting pricing.

Estimating the Impact of Changes in Aggregate Bank Capital Requirements During an Upswing

This paper estimates the effect of changes in capital requirements applied to all UK-resident banks on lending by studying the joint dynamics of the aggregate capital ratio of the UK banking system and a set of macro-financial variables. This is achieved by means of sign restrictions that attempt to identify shocks in past data that match a set of assumed directional responses of other variables to future changes in capital requirements aimed at increasing the resilience of the banking system to losses during an upswing. This may provide policymakers with a plausible ‘upper bound’ on the short-term effects of future increases in macroprudential capital requirements in certain states of the economic cycle. An increase in the aggregate bank capital requirement during an economic upswing is associated with a reduction of lending, with the effect larger for lending to corporates than for that to households. The impact on GDP growth is statistically insignificant.

The role of collateral in supporting liquidity

Collateral plays an important role in supporting a vast range of transactions that help ensure the efficient functioning of the financial system. But collateral markets also have the potential to exacerbate risks to financial stability, not least given that during periods of market stress demand for high-quality collateral may increase, whilst collateral availability may fall. This paper offers a means to estimate how this potential imbalance between collateral supply and demand is likely to vary as a function of market stress. In doing so, it offers an estimate of the increase in market volatility sufficient to cause a dislocation in the market for collateral and a subsequent deterioration in market functioning. It suggests that — from the perspective of financial stability — the implications of an imbalance between the supply and demand of collateral are likely to be comparatively benign, but that the implications of a reduction in the willingness and/or ability of market participants to act as intermediaries in collateral markets are likely to have more serious consequences for market functioning. This work also provides a framework through which policymakers might be able to investigate how regulations might affect the proximity of these risks.

Extracting Information from Structured Credit Markets

Structured credit instruments offer an insight into markets’ perceptions of the extent of future credit defaults. Claims of different seniorities incur losses only if defaults reach different magnitudes, so their relative value offers an insight into the likelihood of losses being of different severities. This paper matches the traded values of structured credit products by modelling the defaults of the underlying credits and their interdependence. It offers an improvement on the industry-standard ‘Gaussian copula’ model in its ability to capture the ‘tail event’ of multiple firms defaulting together. This allows policymakers to draw better inference as to the likely scale of defaults implied by structured credit prices. It offers an indication of the extent to which defaults are driven by systemic shocks to firms’ balance sheets. It may also be of use to those who trade structured credit products and may offer an improvement in risk management.

The October 2016 sterling flash episode: when liquidity disappeared from one of the world’s most liquid markets

This paper provides an in-depth analysis of the evolution of liquidity during the flash episode in sterling during the early hours of 7 October 2016. It examines a number of estimates both of the cost of trading, and the price impact of executed transactions. These include a variant of the ‘volatility over volume’ measure of liquidity based on transaction data, which provides a better proxy of illiquidity — as given by measures based on high-frequency limit order book data — than other summary measures of price impact. The paper also shows that the fall in the value of sterling during the initial part of the flash episode was consistent with the estimated impact on prices of a large number of individually small — but in aggregate large — volume of orders to sell sterling during a normally quiet period of the trading day. However, the subsequent change in price was larger than that consistent with the estimated impact on prices of observed orders to sell sterling. This might support the suggestion, which was included in the report on the episode provided by the Bank for International Settlements, that the move in sterling may have been amplified by the pause in trading on the CME futures exchange.

The Impact of Solvency II Regulations on Life Insurers' Investment Behaviour

This paper provides a means of estimating how ‘Solvency II’ regulations — introduced in the European Union in January 2016 — might affect UK life insurers’ incentives to hold different types of financial assets, and how these asset holdings are likely to vary in the face of hypothetical changes to market prices. To do so, it sets out a structural model of firms’ equity to assess their investment behaviour under different regulatory regimes. It finds that, while Solvency II may partly protect insurers’ solvency positions from falls in risky asset prices, the new regulations might encourage certain types of UK life insurers to de-risk — that is, move to holding safe assets in place of risky — following falls in risk-free interest rates. This behaviour is driven by changes in the so-called ‘risk margin’, which, under its current design within the Solvency II framework, reduces insurers’ solvency positions following falls in risk-free interest rates, thereby encouraging them to sell risky assets to reduce their probability of regulatory insolvency. The model also suggests that, once Solvency II is fully implemented by 2032, UK life insurers may have markedly reduced their holdings of long-term, risky assets. In the model, this behaviour is also driven by the risk margin, which, by increasing the volatility of insurers’ solvency, encourages them to de-risk to reduce the variance of their asset portfolios.

A Heterogeneous Agent Model for Assessing the Effects of Capital Regulation on the Interbank Money Market Under a Corridor System

Money markets play an important role in the implementation of monetary policy. Their structure and dynamics have, however, changed significantly in recent years. In particular, a number of new banking regulations will affect the behaviour of money market participants, and so have the potential to affect money market interest rates. This paper offers a model to examine how prudential regulation might affect interbank overnight interest rates where the central bank implements monetary policy using a corridor system. Combined with a set of assumptions as to the cost banks might incur in meeting regulatory capital requirements, it offers a framework with which to explore how such prudential regulation might affect the dynamics of overnight interest rates. The results — which are illustrative — estimate the interest rates at which banks might borrow and lend reserves overnight in the presence of prudential regulation. They suggest that risk-weighted capital requirements might increase the average level of overnight interbank interest rates, while the regulatory minimum leverage ratio might decrease it. If applied to real-world data on central bank reserves balances and regulatory metrics, this model also offers an insight into how central bank policymakers could — if they so choose — amend their operational frameworks to account for the effects of regulation.