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Amid increasing regulation, structural changes of the market and Quantitative Easing as well as extremely low yields, concerns about the market liquidity of the Eurozone sovereign debt markets have been raised. We aim to quantify illiquidity risks, especially such related to liquidity dry-ups, and illiquidity spillover across maturities by examining the reaction to illiquidity shocks at high frequencies in two ways:
a) the regular response to shocks using a variance decomposition and,
b) the response to shocks in the extremes by detecting illiquidity shocks and modeling those as ultivariate Hawkes processes.
We find that:
a) market liquidity is more fragile and less predictable when an asset is very illiquid and,
b) the response to shocks in the extremes is structurally different from the regular response.
In 2015 long-term bonds are less liquid and the medium-term bonds are liquid, although we observe that in the extremes the medium-term bonds are increasingly driven by illiquidity spillover from the long-term titles.
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.
To ensure the credibility of market discipline induced by bail-in, neither retail investors nor peer banks should appear prominently among the investor base of banks’ loss absorbing capital. Empirical evidence on bank-level data provided by the German Federal Financial Supervisory Authority raises a few red flags. Our list of policy recommendations encompasses disclosure policy, data sharing among supervisors, information transparency on holdings of bail-inable debt for all stakeholders, threshold values, and a well-defined upper limit for any bail-in activity. This document was provided by the Economic Governance Support Unit at the request of the ECON Committee.
The paper discusses the policy implications of the Wirecard scandal. The study finds that all lines of defense against corporate fraud, including internal control systems, external audits, the oversight bodies for financial reporting and auditing and the market supervisor, contributed to the scandal and are in need of reform. To ensure market integrity and investor protection in the future, the authors make eight suggestions for the market and institutional oversight architecture in Germany and in Europe.
This paper analyzes sovereign risk shift-contagion, i.e. positive and significant changes in the propagation mechanisms, using bond yield spreads for the major eurozone countries. By emphasizing the use of two econometric approaches based on quantile regressions (standard quantile regression and Bayesian quantile regression with heteroskedasticity) we find that the propagation of shocks in euro's bond yield spreads shows almost no presence of shift-contagion. All the increases in correlation we have witnessed over the last years come from larger shocks propagated with higher intensity across Europe.
In this paper we argue that the own findings of the SSM THEMATIC REVIEW ON PROFITABILITY AND BUSINESS MODEL and the academic literature on bank profitability do not provide support for the business model approach of supervisory guidance. We discuss in the paper several reasons why the regulator should stay away from intervening in management practices. We conclude that by taking the role of a coach instead of a referee, the supervisor generates a hazard for financial stability.
We develop a simple theoretical model to motivate testable hypotheses about how peer-to-peer (P2P) platforms compete with banks for loans. The model predicts that (i) P2P lending grows when some banks are faced with exogenously higher regulatory costs; (ii) P2P loans are riskier than bank loans; and (iii) the risk-adjusted interest rates on P2P loans are lower than those on bank loans. We confront these predictions with data on P2P lending and the consumer bank credit market in Germany and find empirical support. Overall, our analysis indicates the P2P lenders are bottom fishing when regulatory shocks create a competitive disadvantage for some banks.
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.
This paper investigates the effect of the conventional and unconventional (e.g. Quantitative Easing - QE) monetary policy intervention on the insurance industry. We first analyze the impact on the stock performances of 166 (re)insurers from the last QE programme launched by the European Central Bank (ECB) by constructing an event study around the announcement date. Then we enlarge the scope by looking at the monetary policy surprise effects on the same sample of (re)insurers over a timeframe of 12 years, also extending the analysis to the Credit Default Swaps (CDS) market. In the second part of the paper by building a set of balance sheet-based indices, we identify the characteristics of (re)insurers that determine sensitivity to monetary policy actions. Our evidences suggest that a single intervention extrapolated from the comprehensive strategy cannot be utilized to estimate the effect of monetary policy intervention on the market. With respect to the impact of monetary policies, we show how the effect of interventions changes over time. Expansionary monetary policy interventions, when generating an instantaneous reduction of interest rates, generated movement in stock prices in the same direction till September 2010. This effect turned positive during the European sovereign debt crisis. However, the effect faded away in 2014-2015. The pattern is confirmed by the impact on the CDS market. With regard to the determinants of these effects, our analysis suggests that sensitivity is mainly driven by asset allocation and in particular by exposure to fixed income assets.
We show that FED policy announcements lead to a significant increase in international comovements in the cross-section of equity and in particular sovereign CDS markets. The relaxation of unconventionary monetary policies is felt strongly by emerging markets, and by countries that are open to the trading of goods and flows, even in the presence of floating exchange rates. It also impacts closed economies whose currencies are pegged to the dollar. This evidence is consistent with recent theories of a global financial cycle and the pricing of a FED’s put. In contrast, ECB announcements hardly affect comovements, even in the Eurozone.
We investigate the default probability, recovery rates and loss distribution of a portfolio of securitised loans granted to Italian small and medium enterprises (SMEs). To this end, we use loan level data information provided by the European DataWarehouse platform and employ a logistic regression to estimate the company default probability. We include loan-level default probabilities and recovery rates to estimate the loss distribution of the underlying assets. We find that bank securitised loans are less risky, compared to the average bank lending to small and medium enterprises.
The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the ”Natural Language Toolkit” that uses machine learning models to extract the news’ sentiment. We consider the period from January till June 2020 and analyze 203,886 online articles that deal with the pandemic and that were published on three platforms: MarketWatch.com, Reuters.com and NYtimes.com. Our findings show that there is a significant and positive relationship between sentiment score and market returns. This result indicates that an increase (decrease) in the sentiment score implies a rise in positive (negative) news and corresponds to positive (negative) market returns. We also find that the variance of the sentiments and the volume of the news sources for Reuters and MarketWatch, respectively, are negatively associated to market returns indicating that an increase of the uncertainty of the sentiment and an increase in the arrival of news have an adverse impact on the stock market.
We propose a spatiotemporal approach for modeling risk spillovers using time-varying proximity matrices based on observable financial networks and introduce a new bilateral specification. We study covariance stationarity and identification of the model, and analyze consistency and asymptotic normality of the quasi-maximum-likelihood estimator. We show how to isolate risk channels and we discuss how to compute target exposure able to reduce system variance. An empirical analysis on Euro-area cross-country holdings shows that Italy and Ireland are key players in spreading risk, France and Portugal are the major risk receivers, and we uncover Spain's non-trivial role as risk middleman.
We investigate the default probability, recovery rates and loss distribution of a portfolio of securitised loans granted to Italian small and medium enterprises (SMEs). To this end, we use loan level data information provided by the European DataWarehouse platform and employ a logistic regression to estimate the company default probability. We include loan-level default probabilities and recovery rates to estimate the loss distribution of the underlying assets. We find that bank securitised loans are less risky, compared to the average bank lending to small and medium enterprises.
Banks can deal with their liquidity risk by holding liquid assets (self-insurance), by participating in interbank markets (coinsurance), or by using flexible financing instruments, such as bank capital (risk-sharing). We use a simple model to show that undiversifiable liquidity risk, i.e. the liquidity risk that banks are unable to coinsure on interbank markets, represents an important risk factor affecting their capital structures. Banks facing higher undiversifiable liquidity risk hold more capital. We posit that empirically banks that are more exposed to undiversifiable liquidity risk are less active on interbank markets. Therefore, we test for the existence of a negative relationship between bank capital and interbank market activity and find support in a large sample of U.S. commercial banks.
Market fragmentation and technological advances increasing the speed of trading altered the functioning and stability of global equity limit order markets. Taking market resiliency as an indicator of market quality, we investigate how resilient are trading venues in a high-frequency environment with cross-venue fragmented order flow. Employing a Hawkes process methodology on high-frequency data for FTSE 100 stocks on LSE, a traditional exchange, and on Chi-X, an alternative venue, we find that when liquidity becomes scarce Chi-X is a less resilient venue than LSE with variations existing across stocks and time. In comparison with LSE, Chi-X has more, longer, and severer liquidity shocks. Whereas the vast majority of liquidity droughts on both venues disappear within less than one minute, the recovery is not lasting, as liquidity shocks spiral over the time dimension. Over half of the shocks on both venues are caused by spiralling. Liquidity shocks tend to spiral more on Chi-X than on LSE for large stocks suggesting that the liquidity supply on Chi-X is thinner than on LSE. Finally, a significant amount of liquidity shocks spill over cross-venue providing supporting evidence for the competition for order flow between LSE and Chi-X.
The European Commission is trying to reboot the CMU project: The High-Level Forum on Capital Markets Union – a group of 28 selected experts from industry, academia and civil society – is expected to submit policy recommendations by the end of May 2020 which will feed into the Commission’s new CMU agenda. This contribution is largely based on a letter to the High-Level Forum that gives feedback on the Interim Report published in February. There, we introduce a comprehensive approach to distinguish, from a functional finance perspective, between the ‘game changers’ and what is nice to have. We highlight the importance of common and consistent supervisory practices across Member States and recommend building up a European Securities and Exchange Commission (E-SEC) according to the American model.
This paper studies the impact of financial sector size and leverage on business cycles and risk-free rates dynamics. We model a general equilibrium productive economy where financial intermediaries provide costly risk mitigation to households by pooling the idiosyncratic risks of their investment activities. We find that leverage amplifies variations of intermediaries’ relative size, but may also mitigate the business cycle. Moreover, it makes risk-free rates pro-cyclical. Households benefit the most when the financial sector is neither too small, thus avoiding high consumption fluctuations and costly mitigation, nor too big, so that fewer resources are lost after intermediation costs.
Using a novel regulatory dataset of fully identified derivatives transactions, this paper provides the first comprehensive analysis of the structure of the euro area interest rate swap (IRS) market after the start of the mandatory clearing obligation. Our dataset contains 1.7 million bilateral IRS transactions of banks and non-banks. Our key results are as follows:
1) The euro area IRS market is highly standardised and concentrated around the group of the G16 Dealers but also around a significant group of core “intermediaries"(and major CCPs).
2) Banks are active in all segments of the IRS euro market, whereas non-banks are often specialised.
3) When using relative net exposures as a proxy for the “flow of risk" in the IRS market, we find that risk absorption takes place in the core as well as the periphery of the network but in absolute terms the risk absorption is largely at the core.
4) Among the Basel III capital and liquidity ratios, the leverage ratio plays a key role in determining a bank's IRS trading activity.
Recent advances in natural language processing have contributed to the development of market sentiment measures through text content analysis in news providers and social media. The effectiveness of these sentiment variables depends on the imple- mented techniques and the type of source on which they are based. In this paper, we investigate the impact of the release of public financial news on the S&P 500. Using automatic labeling techniques based on either stock index returns or dictionaries, we apply a classification problem based on long short-term memory neural networks to extract alternative proxies of investor sentiment. Our findings provide evidence that there exists an impact of those sentiments in the market on a 20-minute time frame. We find that dictionary-based sentiment provides meaningful results with respect to those based on stock index returns, which partly fails in the mapping process between news and financial returns.
This paper discusses policy implications of a potential surge in NPLs due to COVID-19. The study provides an empirical assessment of potential scenarios and draws lessons from previous crises for effective NPL treatment. The paper highlights the importance of early and realistic assessment of loan losses to avoid adverse incentives for banks. Secondary loan markets would help in this process and further facilitate bank resolution as laid down in the BRRD, which should be uphold even in extreme scenarios.
Even if the importance of micro data transparency is a well-established fact, European institutions are still lacking behind the US when it comes to the provision of financial market data to academics. In this Policy Letter we discuss five different types of micro data that are crucial for monitoring (systemic) risk in the financial system, identifying and understanding inter-linkages in financial markets and thus have important implications for policymakers and regulatory authorities. We come to the conclusion that for all five areas of micro data, outlined in this Policy Letter (bank balance sheet data, asset portfolio data, market transaction data, market high frequency data and central bank data), the benefits of increased transparency greatly offset potential downsides. Hence, European policymakers would do well to follow the US example and close the sizeable gap in micro data transparency. For most cases, relevant data is already collected (at least on national level), but just not made available to academics for partly incomprehensible reasons. Overcoming these obstacles could foster financial stability in Europe and assure level playing fields with US regulators and policymakers.
This policy note summarizes our assessment of financial sanctions against Russia. We see an increase in sanctions severity starting from (1) the widely discussed SWIFT exclusions, followed by (2) blocking of correspondent banking relationships with Russian banks, including the Central Bank, alongside secondary sanctions, and (3) a full blacklisting of the ‘real’ export-import flows underlying the financial transactions. We assess option (1) as being less impactful than often believed yet sending a strong signal of EU unity; option (2) as an effective way to isolate the Russian banking system, particularly if secondary sanctions are in place, to avoid workarounds. Option (3) represents possibly the most effective way to apply economic and financial pressure, interrupting trade relationships.
We empirically examine the Capital Purchase Program (CPP) used by the US gov- ernment to bail out distressed banks with equity infusions during the Great Recession. We find strong evidence that a feature of the CPP – the government’s ability to ap- point independent directors on the board of an assisted bank that missed six dividend payments to the Treasury – helped attenuate bailout-related moral hazard. Banks were averse to these appointments – the empirical distribution of missed payments exhibits a sharp discontinuity at five. Director appointments by the Treasury led to improved bank performance, lower CEO pay, and higher stock market valuations.
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 study the role of various trader types in providing liquidity in spot and futures markets based on complete order-book and transactions data as well as cross-market trader identifiers from the National Stock Exchange of India for a single large stock. During normal times, short-term traders who carry little inventory overnight are the primary intermediaries in both spot and futures markets, and changes in futures prices Granger-cause changes in spot prices. However, during two days of fast crashes, Granger-causality ran both ways. Both crashes were due to large-scale selling by foreign institutional investors in the spot market. Buying by short-term traders and cross-market traders was insufficient to stop the crashes. Mutual funds, patient traders with better trade-execution quality who were initially slow to move in, eventually bought sufficient quantities leading to price recovery in both markets. Our findings suggest that market stability requires the presence of well-capitalized standby liquidity providers.
The centrality of the United States in the global financial system is taken for granted, but its response to recent political and epidemiological events has suggested that China now holds a comparable position. Using minute-by-minute data from 2012 to 2020 on the financial performance of twelve country-specific exchange-traded funds, we construct daily snapshots of the global financial network and analyze them for the centrality and connectedness of each country in our sample. We find evidence that the U.S. was central to the global financial system into 2018, but that the U.S.-China trade war of 2018–2019 diminished its centrality, and the Covid-19 outbreak of 2019–2020 increased the centrality of China. These indicators may be the first signals that the global financial system is moving from a unipolar to a bipolar world.
We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also affect sustainable investments leading to the identification of different investment universes and consequently to the creation of different benchmarks. This implies that in the asset management industry it is extremely difficult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the effect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also a↵ect sustainable investments leading to the identification of di↵erent investment universes and consequently to the creation of di↵erent benchmarks. This implies that in the asset management industry it is extremely dicult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the e↵ect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
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.
Coming early to the party
(2017)
We examine the strategic behavior of High Frequency Traders (HFTs) during the pre-opening phase and the opening auction of the NYSE-Euronext Paris exchange. HFTs actively participate, and profitably extract information from the order flow. They also post "flash crash" orders, to gain time priority. They make profits on their last-second orders; however, so do others, suggesting that there is no speed advantage. HFTs lead price discovery, and neither harm nor improve liquidity. They "come early to the party", and enjoy it (make profits); however, they also help others enjoy the party (improve market quality) and do not have privileges (their speed advantage is not crucial).
Do competition and incentives offered to designated market makers (DMMs) improve market liquidity? Using data from NYSE Euronext Paris, we show that an exogenous increase in competition among DMMs leads to a significant decrease in quoted and effective spreads, mainly through a reduction in adverse selection costs. In contrast, changes in incentives, through small changes in rebates and requirements for DMMs, do not have any tangible effect on market liquidity. Our results are of relevance for designing optimal contracts between exchanges and DMMs and for regulatory market oversight.
This paper analyses whether the post-crisis regulatory reforms developed by global-standard-setting bodies have created appropriate incentives for different types of market participants to centrally clear Over-The-Counter (OTC) derivative contracts. Beyond documenting the observed facts, we analyze four main drivers for the decision to clear: 1) the liquidity and riskiness of the reference entity; 2) the credit risk of the counterparty; 3) the clearing member’s portfolio net exposure with the Central Counterparty Clearing House (CCP) and 4) post trade transparency. We use confidential European trade repository data on single-name Sovereign Credit Derivative Swap (CDS) transactions, and show that for all the transactions reported in 2016 on Italian, German and French Sovereign CDS 48% were centrally cleared, 42% were not cleared despite being eligible for central clearing, while 9% of the contracts were not clearable because they did not satisfy certain CCP clearing criteria. However, there is a large difference between CCP clearing members that clear about 53% of their transactions and non-clearing members, even those that are subject to counterparty risk capital requirements, that almost never clear their trades. Moreover, we find that diverse factors explain clearing members’ decision to clear different CDS contracts: for Italian CDS, counterparty credit risk exposures matter most for the decision to clear, while for French and German CDS, margin costs are the most important factor for the decision. Clearing members use clearing to reduce their exposures to the CCP and largely clear contracts when at least one of the traders has a high counterparty credit risk.
This work uses financial markets connected by arbitrage relations to investigate the dynamics of price and liquidity discovery, which refer to the cross-instrument forecasting power for prices and liquidity, respectively. Specifically, we seek to understand the linkage between the cheapest to deliver bond and closest futures pairs by using high-frequency data on European governments obligations and derivatives. We split the 2019-2021 sample into three subperiods to appreciate changes in the liquidity discovery induced by the COVID-19 pandemic. Within a cointegration model, we find that price discovery occurs on the futures market, and document strong empirical support for liquidity spillovers both from the futures to the cash market as well as from the cash to the futures market.
Energy efficiency represents one of the key planned actions aiming at reducing greenhouse emissions and the consumption of fossil fuel to mitigate the impact of climate change. In this paper, we investigate the relationship between energy efficiency and the borrower’s solvency risk in the Italian market. Specifically, we analyze a residential mortgage portfolio of four financial institutions which includes about 70,000 loans matched with the energy performance certificate of the associated buildings. Our findings show that there is a negative relationship between a building’s energy efficiency and the owner’s probability of default. Findings survive after we account for dwelling, household, mortgage, market control variables, and regional and year fixed effect. Additionally, a ROC analysis shows that there is an improvement in the estimation of the mortgage default probability when the energy efficiency characteristic is included as a risk predictor in the model.
The SVB case is a wake-up call for Europe’s regulators as it demonstrates the destructive power of a bank-run: it undermines the role of loss absorbing capital, elbowing governments to bailout affected banks. Many types of bank management weaknesses, like excessive duration risk, may raise concerns of bank losses – but to serve as a run-trigger, there needs to be a large enough group of bank depositors that fails to be fully covered by a deposit insurance scheme. Latent run-risk is the root cause of inefficient liquidations, and we argue that a run on SVB assets could have been avoided altogether by a more thoughtful deposit insurance scheme, sharply distinguishing between loss absorbing capital (equity plus bail-in debt) and other liabilities which are deemed not to be bail-inable, namely demand deposits. These evidence-based insights have direct implications for Europe’s banking regulation, suggesting a minimum and a maximum for a banks’ loss absorption capacity.
The present paper proposes an overview of the existing literature covering several aspects related to environmental, social, and governance (ESG) factors. Specifically, we consider studies describing and evaluating ESG methodologies and those studying the impact of ESG on credit risk, debt and equity costs, or sovereign bonds. We further expand the topic of ESG research by including the strand of the literature focusing on the impact of climate change on financial stability, thus allowing us to also consider the most recent research on the impact of climate change on portfolio management.
Through the lens of market participants' objective to minimize counterparty risk, we provide an explanation for the reluctance to clear derivative trades in the absence of a central clearing obligation. We develop a comprehensive understanding of the benefits and potential pitfalls with respect to a single market participant's counterparty risk exposure when moving from a bilateral to a clearing architecture for derivative markets. Previous studies suggest that central clearing is beneficial for single market participants in the presence of a sufficiently large number of clearing members. We show that three elements can render central clearing harmful for a market participant's counterparty risk exposure regardless of the number of its counterparties: 1) correlation across and within derivative classes (i.e., systematic risk), 2) collateralization of derivative claims, and 3) loss sharing among clearing members. Our results have substantial implications for the design of derivatives markets, and highlight that recent central clearing reforms might not incentivize market participants to clear derivatives.
We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to market quality, defined by price discovery and liquidity provision, in the opening auction. We use a unique dataset from the Tokyo Stock Exchange (TSE) based on server-IDs and find that HFTs dynamically alter their presence in different stocks and on different days. In spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and contribute significantly to market quality in the pre-opening period, the opening auction that ensues and the continuous trading period. Their contribution is largely different from that of the other HFTs during the continuous period.
We show that High Frequency Traders (HFTs) are not beneficial to the stock market during flash crashes. They actually consume liquidity when it is most needed, even when they are rewarded by the exchange to provide immediacy. The behavior of HFTs exacerbate the transient price impact, unrelated to fundamentals, typically observed during a flash crash. Slow traders provide liquidity instead of HFTs, taking advantage of the discounted price. We thus uncover a trade-o↵ between the greater liquidity and efficiency provided by HFTs in normal times, and the disruptive consequences of their trading activity during distressed times.
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.
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.
The impact of network connectivity on factor exposures, asset pricing and portfolio diversification
(2017)
This paper extends the classic factor-based asset pricing model by including network linkages in linear factor models. We assume that the network linkages are exogenously provided. This extension of the model allows a better understanding of the causes of systematic risk and shows that (i) network exposures act as an inflating factor for systematic exposure to common factors and (ii) the power of diversification is reduced by the presence of network connections. Moreover, we show that in the presence of network links a misspecified traditional linear factor model presents residuals that are correlated and heteroskedastic. We support our claims with an extensive simulation experiment.