Δεν διατίθεται στα ελληνικά.
Sebastiano Michele Zema
- 16 November 2022
- FINANCIAL STABILITY REVIEW - BOXCross-asset correlations in a more inflationary environment and challenges for diversification strategiesFinancial Stability Review Issue 2, 2022Details
- In many previous editions of the FSR, we have warned about the risk of a “disorderly correction in asset markets”. In the most recent publication, we argued that higher than expected inflation can increase this risk and provide some arguments to substantiate this claim. However, with the inflation remaining a key topic, our “warning” needs to be better substantiated and more specific. The analytics in the box do exactly this. In both 2021 2022, the 12-month correlation between daily US bond and stock returns has crossed into positive territory. The assumption of having a low correlation between stock and bond returns has historically been one of the bedrocks of strategic asset allocation (e.g. the “standard” 60-40 split). The resulting diversification benefits, however, are contingent on the low correlation between asset classes. Higher or unstable cross-asset correlations complicate portfolio optimisation and risk management, and could also destabilise bond markets, where volatility is already elevated. We discuss the challenges that this poses for portfolio management and the implications for financial stability. Then we go on to investigate the direct and indirect drivers of the stock-bond correlation. We find empirical evidence that the current higher correlation, with its associated financial stability risks, may be driven by the present high inflation environment and related monetary policy expectations.
- JEL Code
- C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
F65 : International Economics→Economic Impacts of Globalization→Finance
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
- 15 September 2022
- WORKING PAPER SERIES - No. 2721Uncovering the network structure of non-centrally cleared derivative markets: evidences from regulatory dataDetails
- The network structure of non-centrally cleared derivative markets, uncovered via the European Market Infrastructure Regulation (EMIR), is investigated with a focus on the Covid-19 market turmoil period. Initial and variation margin networks are reconstructed to analyze channels of potential losses and liquidity dynamics. Despite the absence of central clearing, the derivative network is found to be ultrasmall and a filtering tool is proposed to identify channels in the network characterized by the highest exposures. I find these exposures to be mainly toward institutions outside the euro-area (EA), emphasizing the need for cooperation across different jurisdictions. Anomalous behavior in terms of diverging first and second moments on the degree and strength distributions are detected, signaling the presence of large exposures generating extreme liquidity outflows. A reference table of parameters’ estimates based on real data is provided for different network sizes, with no break of confidentiality, making possible to simulate in a realistic way the liquidity dynamic in global derivative markets even when the access to supervisory data is not granted.
- JEL Code
- G01 : Financial Economics→General→Financial Crises
G15 : Financial Economics→General Financial Markets→International Financial Markets
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
- 25 May 2022
- FINANCIAL STABILITY REVIEW - BOXFinancial Stability Review Issue 1, 2022Details
- Synthetic leverage has become an important feature of the financial system. In our analysis, we propose two complementary measures that explore the link between synthetic leverage and margining in equity derivative portfolios of non-banks. We show that leverage risk can materialise through margin calls and uncovered counterparty exposure during periods of high market volatility.
- JEL Code
- G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill
- 17 November 2021
- FINANCIAL STABILITY REVIEW - BOXFinancial Stability Review Issue 2, 2021Details
- This box establishes stylised facts about the significant increase in initial margin (IM) in the euro area derivatives market during the March 2020 market turmoil. First, it shows that the increase was concentrated almost entirely in centrally cleared derivatives and driven mainly by equity, credit and interest rate portfolios. Second, by comparing static portfolios with those where portfolio repositioning took place, the IM increase is decomposed into (i) changes attributable to the CCP model sensitivity to market volatility, and (ii) changes attributable to portfolio repositioning by investors. For centrally cleared interest rate and credit derivatives (where this method is applicable), CCP model sensitivity to market volatility is found to be a key driver of the IM increase. Overall, the results suggest that it is important to develop a clearer understanding of “excessive procyclicality” for IM and possibly, on the basis of this common understanding, to review the models which CCPs use to calibrate IMs. The supervisory and regulatory framework governing the liquidity management of market participants, and in particular that of some non-bank financial intermediaries, should also be strengthened.
- JEL Code
- C60 : Mathematical and Quantitative Methods→Mathematical Methods, Programming Models, Mathematical and Simulation Modeling→General
G10 : Financial Economics→General Financial Markets→General
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing