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This note discusses the basic economics of central clearing for derivatives and the need for a proper regulation, supervision and resolution of central counterparty clearing houses (CCPs). New regulation in the U.S. and in Europe renders the involvement of a central counterparty mandatory for standardized OTC derivatives’ trading and sets higher capital and collateral requirements for non-centrally cleared derivatives.
From a macrofinance perspective, CCPs provide a trade-off between reduced contagion risk in the financial industry and the creation of a significant systemic risk. However, so far, regulation and supervision of CCPs is very fragmented, limited and ignores two important aspects: the risk of consolidation of CCPs on the one side and the competition among CCPs on the other side. i) As the economies of scale of CCP operations in risk and cost reduction can be large, they provide an argument in favor of consolidation, leading at the extreme to a monopoly CCP that poses the ultimate default risk – a systemic risk for the entire financial sector. As a systemic risk event requires a government bailout, there is a public policy issue here. ii) As long as no monopoly CCP exists, there is competition for market share among existing CCPs. Such competition may undermine the stability of the entire financial system because it induces “predatory margining”: a reduction of margin requirements to increase market share.
The policy lesson from our consideration emphasizes the importance of a single authority supervising all competing CCPs as well as of a specific regulation and resolution framework for CCPs. Our general recommendations can be applied to the current situation in Europe, and the proposed merger between Deutsche Börse and London Stock Exchange.
We focus on the role of social media as a high-frequency, unfiltered mass information transmission channel and how its use for government communication affects the aggregate stock markets. To measure this effect, we concentrate on one of the most prominent Twitter users, the 45th President of the United States, Donald J. Trump. We analyze around 1,400 of his tweets related to the US economy and classify them by topic and textual sentiment using machine learning algorithms. We investigate whether the tweets contain relevant information for financial markets, i.e. whether they affect market returns, volatility, and trading volumes. Using high-frequency data, we find that Trump’s tweets are most often a reaction to pre-existing market trends and therefore do not provide material new information that would influence prices or trading. We show that past market information can help predict Trump’s decision to tweet about the economy.
In this paper, we investigate the relation between buildings' energy efficiency and the probability of mortgage default. To this end, we construct a novel panel dataset by combining Dutch loan-level mortgage information with provisional building energy ratings that are calculated by the Netherlands Enterprise Agency. By employing the Logistic regression and the extended Cox model, we find that buildings' energy efficiency is associated with lower likelihood of mortgage default. The results hold for a battery of robustness checks. Additional findings indicate that credit risk varies with the degree of energy efficiency.
We delve into the EU's regulatory changes aimed at boosting transparency in sustainable investments. By examining disparities among ESG rating agencies, we assess how these differences challenge standardization and consensus. Our analysis underscores the critical need for clearer ESG assessments to guide the sustainable investment landscape.
We show that bond purchases undertaken in the context of quantitative easing efforts by the European Central Bank created a large mispricing between the market for German and Italian government bonds and their respective futures contracts. On top of the direct effect the buying pressure exerted on bond prices, we show three indirect effects through which the scarcity of bonds, resulting from the asset purchases, drove a wedge between the futures contracts and the underlying bonds: the deterioration of bond market liquidity, the increased bond specialness on the repurchase agreement market, and the greater uncertainty about bond availability as collateral.
We study how the Eurosystem Collateral Framework for corporate bonds helps the European Central Bank (ECB) fulfill its policy mandate. Using the ECBs eligibility list, we identify the first inclusion date of both bonds and issuers. We find that due to the increased supply and demand for pledgeable collateral following eligibility, (i) securities lending market trading activity increases, (ii) eligible bonds have lower yields, and (iii) the liquidity of newly-issued bonds declines, whereas the liquidity of older bonds is una↵ected/improves. Corporate bond lending relaxes the constraint of limited collateral supply, thereby making the market more cohesive and complete. Following eligibility, bond-issuing firms reduce bank debt and expand corporate bond issuance, thus increasing overall debt size and extending maturity.
We study how the Eurosystem Collateral Framework for corporate bonds helps the European Central Bank (ECB) fulfill its policy mandate. Using the ECBs eligibility list, we identify the first inclusion date of both bonds and issuers. We find that due to the increased supply and demand for pledgeable collateral following eligibility, (i) securities lending market trading activity increases, (ii) eligible bonds have lower yields, and (iii) the liquidity of newly-issued bonds declines, whereas the liquidity of older bonds is unaffected/improves. Corporate bond lending relaxes the constraint of limited collateral supply, thereby making the market more cohesive and complete. Following eligibility, bond-issuing firms reduce bank debt and expand corporate bond issuance, thus increasing overall debt size and extending maturity.