Research articles for the 2021-07-30
A Tale of Two Premiums Revisited
SSRN
This paper investigates the effect of the “financialization†of commodity markets in terms of pricing. I explore whether the emergence of commodity index traders affects weekly returns and turnover during the roll periods. I split the sample (1994â€"2017) into the pre-financialization (1994â€"2003) and the post-financialization (2004â€"2017). I directly test whether the market share of index traders contributes to commodity returns and whether risk adjustments (based on momentum, basis, basis-momentum, open interest, crowding, and average factors) alter liquidity and insurance premiums documented in Kang, Rouwenhorst, and Tang (2020). I also examine how the financialization affects liquidity and insurance premiums. Finally, since previous results are obtained with Fama-MacBeth regressions, I use an alternative method totest how liquidity and insurance premiums determine commodity returns.
SSRN
This paper investigates the effect of the “financialization†of commodity markets in terms of pricing. I explore whether the emergence of commodity index traders affects weekly returns and turnover during the roll periods. I split the sample (1994â€"2017) into the pre-financialization (1994â€"2003) and the post-financialization (2004â€"2017). I directly test whether the market share of index traders contributes to commodity returns and whether risk adjustments (based on momentum, basis, basis-momentum, open interest, crowding, and average factors) alter liquidity and insurance premiums documented in Kang, Rouwenhorst, and Tang (2020). I also examine how the financialization affects liquidity and insurance premiums. Finally, since previous results are obtained with Fama-MacBeth regressions, I use an alternative method totest how liquidity and insurance premiums determine commodity returns.
Application of Classification Algorithms for the Assessment of Confirmation to Quality Remarks
SSRN
In the context of the data quality management of supervisory banking data, the Bank of Italy receives a significant number of data reports at various intervals from Italian banks. If any anomalies are found, a quality remark is sent back, questioning the data submitted. This process can lead to the bank in question confirming or revising the data it previously transmitted. We propose an innovative methodology, based on text mining and machine learning techniques, for the automatic processing of the data confirmations received from banks. A classification model is employed to predict whether these confirmations should be accepted or rejected based on the reasons provided by the reporting banks, the characteristics of the validation quality checks, and reporting behaviour across the banking system. The model was trained on past cases already labelled by data managers and its performance was assessed against a set of cross-checked cases that were used as gold standard. The empirical findings show that the methodology predicts the correct decisions on recurrent data confirmations and that the performance of the proposed model is comparable to that of data managers currently engaged in data analysis.
SSRN
In the context of the data quality management of supervisory banking data, the Bank of Italy receives a significant number of data reports at various intervals from Italian banks. If any anomalies are found, a quality remark is sent back, questioning the data submitted. This process can lead to the bank in question confirming or revising the data it previously transmitted. We propose an innovative methodology, based on text mining and machine learning techniques, for the automatic processing of the data confirmations received from banks. A classification model is employed to predict whether these confirmations should be accepted or rejected based on the reasons provided by the reporting banks, the characteristics of the validation quality checks, and reporting behaviour across the banking system. The model was trained on past cases already labelled by data managers and its performance was assessed against a set of cross-checked cases that were used as gold standard. The empirical findings show that the methodology predicts the correct decisions on recurrent data confirmations and that the performance of the proposed model is comparable to that of data managers currently engaged in data analysis.
Climate Change Uncertainty Spillover in the Macroeconomy
SSRN
The design and conduct of climate change policy necessarily confronts uncertainty along multiple fronts. We explore the consequences of ambiguity over various sources and configurations of models that impact how economic opportunities could be damaged in the future. We appeal to decision theory under risk, model ambiguity and misspecification concerns to provide an economically motivated approach to uncertainty quantification. We show how this approach reduces the many facets of uncertainty into a low dimensional characterization that depends on the uncertainty aversion of a decision-maker or fictitious social planner. In our computations, we take inventory of three alternative channels of uncertainty and provide a novel way to assess them. These include i) carbon dynamics that capture how carbon emissions impact atmospheric carbon in future time periods; ii) temperature dynamics that depict how atmospheric carbon alters temperature in future time periods; iii) damage functions that quantify how temperature changes diminish economic opportunities. We appeal to geoscientific modeling to quantify the first two channels. We show how these uncertainty sources interact for a social planner looking to design a prudent approach to the social pricing of carbon emissions.
SSRN
The design and conduct of climate change policy necessarily confronts uncertainty along multiple fronts. We explore the consequences of ambiguity over various sources and configurations of models that impact how economic opportunities could be damaged in the future. We appeal to decision theory under risk, model ambiguity and misspecification concerns to provide an economically motivated approach to uncertainty quantification. We show how this approach reduces the many facets of uncertainty into a low dimensional characterization that depends on the uncertainty aversion of a decision-maker or fictitious social planner. In our computations, we take inventory of three alternative channels of uncertainty and provide a novel way to assess them. These include i) carbon dynamics that capture how carbon emissions impact atmospheric carbon in future time periods; ii) temperature dynamics that depict how atmospheric carbon alters temperature in future time periods; iii) damage functions that quantify how temperature changes diminish economic opportunities. We appeal to geoscientific modeling to quantify the first two channels. We show how these uncertainty sources interact for a social planner looking to design a prudent approach to the social pricing of carbon emissions.
Corporate Tax Avoidance of Malaysian Public Listed Companies: A Multi-Measure Analysis
RePEC
" Objective - Even with corporate tax avoidance being extensively studied, it is still lacking a single universal measurement. There is also a dearth of studies focusing on developing economies such as Malaysia. This study, therefore, analyses the correlations between effective tax rates (ETRs) and book-tax differences (BTDs), which are the most commonly used measures of corporate tax avoidance on Malaysian listed companies for ten years. Methodology/Technique - This study performs distribution, frequency, and correlation analyses on the ETRs and BTDs of the Top 300 companies listed in the Main Market of Bursa Malaysia based on market capitalization. The data used spans a ten-year period from 2010 to 2019. Findings - The results of the distribution, frequency, and correlation analyses show that both these measures are closely related gauges of corporate tax avoidance. Novelty - The results of this study provide further statistical proof that ETR and BTD measures of corporate tax avoidance are closely related. Its utilization of data from listed companies in Malaysia expands the current body of literature by addressing corporate tax avoidance practice in a developing economy. By concentrating on both ETR and BTD measures, this study's analysis is consistent with the broad continuum of corporate tax avoidance spectrum and significantly reduces the risk of warping its determination of tax avoidance level. Type of Paper - Empirical."
RePEC
" Objective - Even with corporate tax avoidance being extensively studied, it is still lacking a single universal measurement. There is also a dearth of studies focusing on developing economies such as Malaysia. This study, therefore, analyses the correlations between effective tax rates (ETRs) and book-tax differences (BTDs), which are the most commonly used measures of corporate tax avoidance on Malaysian listed companies for ten years. Methodology/Technique - This study performs distribution, frequency, and correlation analyses on the ETRs and BTDs of the Top 300 companies listed in the Main Market of Bursa Malaysia based on market capitalization. The data used spans a ten-year period from 2010 to 2019. Findings - The results of the distribution, frequency, and correlation analyses show that both these measures are closely related gauges of corporate tax avoidance. Novelty - The results of this study provide further statistical proof that ETR and BTD measures of corporate tax avoidance are closely related. Its utilization of data from listed companies in Malaysia expands the current body of literature by addressing corporate tax avoidance practice in a developing economy. By concentrating on both ETR and BTD measures, this study's analysis is consistent with the broad continuum of corporate tax avoidance spectrum and significantly reduces the risk of warping its determination of tax avoidance level. Type of Paper - Empirical."
Dynamic Clustering of Multivariate Panel Data
SSRN
We propose a dynamic clustering model for uncovering latent time-varying group structures in multivariate panel data. The model is dynamic in three ways. First, the cluster location and scale matrices are time-varying to track gradual changes in cluster characteristics over time. Second, all units can transition between clusters based on a Hidden Markov model (HMM). Finally, the HMM’s transition matrix can depend on lagged time-varying cluster distances as well as economic covariates. Monte Carlo experiments suggest that the units can be classified reliably in a variety of challenging settings. Incorporating dynamics in the cluster composition proves empirically important in an a study of 299 European banks between 2008Q1 and 2018Q2. We find that approximately 3% of banks transition per quarter on average. Transition probabilities are in part explained by differences in bank profitability, suggesting that low interest rates can lead to long-lasting changes in financial industry structure.
SSRN
We propose a dynamic clustering model for uncovering latent time-varying group structures in multivariate panel data. The model is dynamic in three ways. First, the cluster location and scale matrices are time-varying to track gradual changes in cluster characteristics over time. Second, all units can transition between clusters based on a Hidden Markov model (HMM). Finally, the HMM’s transition matrix can depend on lagged time-varying cluster distances as well as economic covariates. Monte Carlo experiments suggest that the units can be classified reliably in a variety of challenging settings. Incorporating dynamics in the cluster composition proves empirically important in an a study of 299 European banks between 2008Q1 and 2018Q2. We find that approximately 3% of banks transition per quarter on average. Transition probabilities are in part explained by differences in bank profitability, suggesting that low interest rates can lead to long-lasting changes in financial industry structure.
Firm-bank Linkages and Optimal Policies in a Lockdown
SSRN
We develop a novel framework featuring loss amplification through firm-bank linkages. We use it to study optimal intervention in a lockdown situation that creates cash shortfalls for firms, which must resort to bank lending. Firms’ increased debt reduces their output due to moral hazard. Banks need safe collateral to raise funds. Without intervention, aggregate risk constrains bank lending, amplifying output losses. Optimal government support provides sufficient aggregate risk insurance, and is implemented through transfers to firms and fairly-priced guarantees on banks’ debt. When aggregate risk is not too large, such guarantees can be financed through a procyclical taxation of firms’ profits.
SSRN
We develop a novel framework featuring loss amplification through firm-bank linkages. We use it to study optimal intervention in a lockdown situation that creates cash shortfalls for firms, which must resort to bank lending. Firms’ increased debt reduces their output due to moral hazard. Banks need safe collateral to raise funds. Without intervention, aggregate risk constrains bank lending, amplifying output losses. Optimal government support provides sufficient aggregate risk insurance, and is implemented through transfers to firms and fairly-priced guarantees on banks’ debt. When aggregate risk is not too large, such guarantees can be financed through a procyclical taxation of firms’ profits.
Interchange Fees and Card Payments: A Cross-country Analysis
SSRN
We study the relationship between interchange fees and card transactions in a large panel of countries and assess the impact of the Interchange Fee Regulation, introduced in 2015 in the European Union, on card usage. For our purposes, we take advantage of a newly assembled dataset covering almost 50 countries in the last decade and carry out two econometric exercises. Firstly, we estimate the relationship between card transactions per capita and average interchange fees by means of a panel estimator including both country and year fixed-effects, thus exploiting the broad heterogeneity across countries over time. Our results point toward a negative and significant relationship between the number and the growth rate of card-based transactions per capita and the level of interchange fees. Secondly, we adopt a difference-in-difference approach and compare the change in card payments in EU member countries (the treated group), before and after the implementation of the Interchange Fee Regulation in 2015, with that observed in a group of comparable countries (control group), which did not experience any change in interchange fee setting regulations. We find a strong and significant one-off impact of the Regulation immediately after its introduction and considerable propagation effects in the following years. Overall, we support the view that policy actions aiming at containing, but not eliminating, interchange fees can significantly contribute to the diffusion of electronic payments.
SSRN
We study the relationship between interchange fees and card transactions in a large panel of countries and assess the impact of the Interchange Fee Regulation, introduced in 2015 in the European Union, on card usage. For our purposes, we take advantage of a newly assembled dataset covering almost 50 countries in the last decade and carry out two econometric exercises. Firstly, we estimate the relationship between card transactions per capita and average interchange fees by means of a panel estimator including both country and year fixed-effects, thus exploiting the broad heterogeneity across countries over time. Our results point toward a negative and significant relationship between the number and the growth rate of card-based transactions per capita and the level of interchange fees. Secondly, we adopt a difference-in-difference approach and compare the change in card payments in EU member countries (the treated group), before and after the implementation of the Interchange Fee Regulation in 2015, with that observed in a group of comparable countries (control group), which did not experience any change in interchange fee setting regulations. We find a strong and significant one-off impact of the Regulation immediately after its introduction and considerable propagation effects in the following years. Overall, we support the view that policy actions aiming at containing, but not eliminating, interchange fees can significantly contribute to the diffusion of electronic payments.
Internet Access and its Implications for Productivity, Inequality, and Resilience
SSRN
About one-fifth of paid workdays will be supplied from home in the post-pandemic economy, and more than one-fourth on an earnings-weighted basis. In view of this projection, we consider some implications of home internet access quality, exploiting data from the new Survey of Working Arrangements and Attitudes. Moving to high-quality, fully reliable home internet service for all Americans (“universal accessâ€) would raise earnings-weighted labor productivity by an estimated 1.1% in the coming years. The implied output gains are $160 billion per year, or $4 trillion when capitalized at a 4% rate. Estimated flow output payoffs to universal access are nearly three times as large in economic disasters like the COVID-19 pandemic. Our survey data also say that subjective well-being was higher during the pandemic for people with better home internet service conditional on age, employment status, earnings, working arrangements, and other controls. In short, universal access would raise productivity, and it would promote greater economic and social resilience during future disasters that inhibit travel and in-person interactions.
SSRN
About one-fifth of paid workdays will be supplied from home in the post-pandemic economy, and more than one-fourth on an earnings-weighted basis. In view of this projection, we consider some implications of home internet access quality, exploiting data from the new Survey of Working Arrangements and Attitudes. Moving to high-quality, fully reliable home internet service for all Americans (“universal accessâ€) would raise earnings-weighted labor productivity by an estimated 1.1% in the coming years. The implied output gains are $160 billion per year, or $4 trillion when capitalized at a 4% rate. Estimated flow output payoffs to universal access are nearly three times as large in economic disasters like the COVID-19 pandemic. Our survey data also say that subjective well-being was higher during the pandemic for people with better home internet service conditional on age, employment status, earnings, working arrangements, and other controls. In short, universal access would raise productivity, and it would promote greater economic and social resilience during future disasters that inhibit travel and in-person interactions.
Main Challenges and Prospects for the European Banking Sector: A Critical Review of the Ongoing Debate
SSRN
This paper discusses the competing forces that are reshaping the European banking industry and the medium-term consequences for profitability and competition within the sector. The paper highlights that banks are rethinking their business model to address four challenges to emerge in the last decade: low interest rates, tighter regulation, technological innovation, and increasing competition from non-bank intermediaries. The shock generated by the Covid-19 pandemic adds to those developments and has the potential to accelerate them. Our analysis suggests that in order to successfully compete in the medium term banks will likely have to exploit the benefits of digitization, mainly deriving from the reduction in operating costs and the increase in the scale of production. Accommodating the surging demand for green finance is also likely to represent an important source of profits, resulting from the growth of the green market and the development of new specialized products and advisory services. Success in these strategies will presumably require a significant reorganization of banks’ activities to leverage on economies of scale and scope.
SSRN
This paper discusses the competing forces that are reshaping the European banking industry and the medium-term consequences for profitability and competition within the sector. The paper highlights that banks are rethinking their business model to address four challenges to emerge in the last decade: low interest rates, tighter regulation, technological innovation, and increasing competition from non-bank intermediaries. The shock generated by the Covid-19 pandemic adds to those developments and has the potential to accelerate them. Our analysis suggests that in order to successfully compete in the medium term banks will likely have to exploit the benefits of digitization, mainly deriving from the reduction in operating costs and the increase in the scale of production. Accommodating the surging demand for green finance is also likely to represent an important source of profits, resulting from the growth of the green market and the development of new specialized products and advisory services. Success in these strategies will presumably require a significant reorganization of banks’ activities to leverage on economies of scale and scope.
Mapping Judicial Reactions to Shareholder Activism in the UK
SSRN
Shareholder activism â€" defined as dissatisfied investors attempting to initiate change in a company without a change in control â€" has long been a feature of the US investment landscape. The practice is increasingly being exported abroad as funds search for new opportunities in under-explored markets. The UK is a favoured destination for shareholder activists: approximately 50 shareholder activist campaigns occurred in 2018 (Activist Insight, Activist Investing in Europe 2018 Report), and this number is set to increase. It has been suggested that the weak pound, strong shareholder rights and the uncertainty of Brexit have left British listed companies more susceptible. However, most shareholder activism behaviours have yet to be considered by the UK courts. As further discussed below, a particularly important issue is so-called “information leakage†by a shareholder activist-appointed “constituent†director, which, briefly, is when such a director leaks material, non-public information gained from within a company’s boardroom to the shareholder activist sponsor. According to commentators, information leakage appears to occur fairly regularly in the US. The UK legal position on information leakage was recently addressed, for the first time ever, by Russen J. in the seminal case of Stobart Group Ltd. v Tinkler EWHC 258 (Comm).
SSRN
Shareholder activism â€" defined as dissatisfied investors attempting to initiate change in a company without a change in control â€" has long been a feature of the US investment landscape. The practice is increasingly being exported abroad as funds search for new opportunities in under-explored markets. The UK is a favoured destination for shareholder activists: approximately 50 shareholder activist campaigns occurred in 2018 (Activist Insight, Activist Investing in Europe 2018 Report), and this number is set to increase. It has been suggested that the weak pound, strong shareholder rights and the uncertainty of Brexit have left British listed companies more susceptible. However, most shareholder activism behaviours have yet to be considered by the UK courts. As further discussed below, a particularly important issue is so-called “information leakage†by a shareholder activist-appointed “constituent†director, which, briefly, is when such a director leaks material, non-public information gained from within a company’s boardroom to the shareholder activist sponsor. According to commentators, information leakage appears to occur fairly regularly in the US. The UK legal position on information leakage was recently addressed, for the first time ever, by Russen J. in the seminal case of Stobart Group Ltd. v Tinkler EWHC 258 (Comm).
Negotiations at the International Whaling Commission
SSRN
An address to the New Zealand Institute of International Affairs on 16 August 2010. The address provides an overview of International Whaling Commission negotiations, a proposal to cap whaling over a period of 10 years, and of an application brought by Australia in the International Court of Justice against Japan’s scientific whaling.
SSRN
An address to the New Zealand Institute of International Affairs on 16 August 2010. The address provides an overview of International Whaling Commission negotiations, a proposal to cap whaling over a period of 10 years, and of an application brought by Australia in the International Court of Justice against Japan’s scientific whaling.
Performance Analysis of Mobile Banking During the COVID-19 Pandemic Period Comparing with the Pre-pandemic Period of Covid-19: An Empirical Study on Bangladesh
RePEC
"Objective - Mobile banking is a growing activity to engage the non-banking people in the banking system in Bangladesh, so researchers of this paper try to find out how much it is affected by the Coronavirus (COVID-19). Basically, this study is developed to assess the performance of mobile banking during the COVID-19 pandemic period comparing with the pre-pandemic period. Methodology/Technique - Authors use descriptive statistics to evaluate the performance of mobile bank during the study period from 2014 to August 2020. Findings - This paper finds that during the COVID period the average change of monthly number of active accounts & registered clients have increased, on the other hand the average change of monthly number of agents have decreased at the same time. Except cash in & cash out, all other types of transactions proportion of mobile banking have increased during the COVID-19 period. Novelty - As the mobile banking is a key resource for banking people as well as non-banking people to transact financial things at setting at the house, so this paper will be beneficial for mobile banking service provider organization to assess the whole things of mobile banking at this ongoing period, and they can take necessary action. Type of Paper - Empirical."
RePEC
"Objective - Mobile banking is a growing activity to engage the non-banking people in the banking system in Bangladesh, so researchers of this paper try to find out how much it is affected by the Coronavirus (COVID-19). Basically, this study is developed to assess the performance of mobile banking during the COVID-19 pandemic period comparing with the pre-pandemic period. Methodology/Technique - Authors use descriptive statistics to evaluate the performance of mobile bank during the study period from 2014 to August 2020. Findings - This paper finds that during the COVID period the average change of monthly number of active accounts & registered clients have increased, on the other hand the average change of monthly number of agents have decreased at the same time. Except cash in & cash out, all other types of transactions proportion of mobile banking have increased during the COVID-19 period. Novelty - As the mobile banking is a key resource for banking people as well as non-banking people to transact financial things at setting at the house, so this paper will be beneficial for mobile banking service provider organization to assess the whole things of mobile banking at this ongoing period, and they can take necessary action. Type of Paper - Empirical."
Recursive Utility with Investment Gains and Losses: Existence, Uniqueness, and Convergence
SSRN
We consider a generalization of the recursive utility model by adding a new component that represents utility of investment gains and losses. We also study the utility process in this generalized model with constant elasticity of intertemporal substitution and relative risk aversion degree, and with infinite time horizon. In a specific, finite-state Markovian setting, we prove that the utility process uniquely exists when the agent derives nonnegative gain-loss utility, and that it can be non-existent or non-unique otherwise. Moreover, we prove that the utility process, when it uniquely exists, can be computed by starting from any initial guess and applying the recursive equation that defines the utility process repeatedly. We then consider a portfolio selection problem with gain-loss utility and solve it by proving that the corresponding dynamic programming equation has a unique solution. Finally, we extend certain previous results to the case in which the state space is infinite.
SSRN
We consider a generalization of the recursive utility model by adding a new component that represents utility of investment gains and losses. We also study the utility process in this generalized model with constant elasticity of intertemporal substitution and relative risk aversion degree, and with infinite time horizon. In a specific, finite-state Markovian setting, we prove that the utility process uniquely exists when the agent derives nonnegative gain-loss utility, and that it can be non-existent or non-unique otherwise. Moreover, we prove that the utility process, when it uniquely exists, can be computed by starting from any initial guess and applying the recursive equation that defines the utility process repeatedly. We then consider a portfolio selection problem with gain-loss utility and solve it by proving that the corresponding dynamic programming equation has a unique solution. Finally, we extend certain previous results to the case in which the state space is infinite.
Social Capital and Insider Trading
SSRN
Using a large U.S. dataset on insider purchases and variations in the social capital of U.S. counties, we find that the intensity (profitability) of insider trading is positively (negatively) associated with social capital. These results are more pronounced when we restrict our sample to include only opportunistic (rather than routine) insider purchases. Our results indicate that insiders affiliated with firms headquartered in counties with high levels of social capital are relatively more likely to foster market information efficiency by making additional insider purchases. However, they are less likely than those affiliated with firms outside such counties to time the market to increase the profitability of their insider purchases. Furthermore, we address endogeneity issues and establish that these relationships are causal by applying an instrumental variable approach. Finally, we show that the main driver of the positive (negative) relationship between the intensity (profitability) of insider purchases and social capital is the density of social networks (the strength of civic norms).
SSRN
Using a large U.S. dataset on insider purchases and variations in the social capital of U.S. counties, we find that the intensity (profitability) of insider trading is positively (negatively) associated with social capital. These results are more pronounced when we restrict our sample to include only opportunistic (rather than routine) insider purchases. Our results indicate that insiders affiliated with firms headquartered in counties with high levels of social capital are relatively more likely to foster market information efficiency by making additional insider purchases. However, they are less likely than those affiliated with firms outside such counties to time the market to increase the profitability of their insider purchases. Furthermore, we address endogeneity issues and establish that these relationships are causal by applying an instrumental variable approach. Finally, we show that the main driver of the positive (negative) relationship between the intensity (profitability) of insider purchases and social capital is the density of social networks (the strength of civic norms).
Stress-Testing a Shock to Remittances in a Post-COVID World â€" What Impact on Liquidity?
SSRN
Remittances have historically been a stable source of funding which has played a key role in the development efforts of many nations worldwide. As a consequence of the Covid crisis and the lockdown measures imposed to counteract the spread of the disease, the World Bank estimated a drop of 20% in remittances by the end of 2020. To study the effect that such a conjuncture would have on the financial stability of developing economies, this paper develops a remittance stress test that investigates the impact of the projected shock on banking sector liquidity at a country level. The study encompasses 112 countries and finds that small, emerging economies with underdeveloped financial sectors suffer the most, with six of the ten most affected nations experiencing a drop in their liquid asset ratios that would place their banking sector at significant liquidity risk.
SSRN
Remittances have historically been a stable source of funding which has played a key role in the development efforts of many nations worldwide. As a consequence of the Covid crisis and the lockdown measures imposed to counteract the spread of the disease, the World Bank estimated a drop of 20% in remittances by the end of 2020. To study the effect that such a conjuncture would have on the financial stability of developing economies, this paper develops a remittance stress test that investigates the impact of the projected shock on banking sector liquidity at a country level. The study encompasses 112 countries and finds that small, emerging economies with underdeveloped financial sectors suffer the most, with six of the ten most affected nations experiencing a drop in their liquid asset ratios that would place their banking sector at significant liquidity risk.
The Impact of Complex Financial Instruments on Banks’ Vulnerability: Empirical Evidence on SSM Banks
SSRN
Level 2 (L2) and Level 3 (L3) assets and liabilities represent a substantial portion of European banks’ balance sheets, and valuing them is extremely difficult, since no liquid market prices are available. This paper relies on a large panel of euro-area banks between 2014 and 2019, and two different econometric frameworks, in order to estimate the relationship between the holdings of selected instruments (L2, L3 and Non-Performing Loans, NPLs) and banks’ key performance and risk profile metrics, namely Credit Default Swaps (CDSs), Price-to-Book (PtB) ratios and Z-scores. It finds that larger holdings of L2 tend to be associated with higher CDSs, at least in the short run, while larger amounts of NPLs and L3 tend to characterize banks with higher CDSs, lower PtB ratios and worse Z-scores, other things being equal.
SSRN
Level 2 (L2) and Level 3 (L3) assets and liabilities represent a substantial portion of European banks’ balance sheets, and valuing them is extremely difficult, since no liquid market prices are available. This paper relies on a large panel of euro-area banks between 2014 and 2019, and two different econometric frameworks, in order to estimate the relationship between the holdings of selected instruments (L2, L3 and Non-Performing Loans, NPLs) and banks’ key performance and risk profile metrics, namely Credit Default Swaps (CDSs), Price-to-Book (PtB) ratios and Z-scores. It finds that larger holdings of L2 tend to be associated with higher CDSs, at least in the short run, while larger amounts of NPLs and L3 tend to characterize banks with higher CDSs, lower PtB ratios and worse Z-scores, other things being equal.
The Market Notices Published by the Italian Stock Exchange: A Machine Learning Approach for the Selection of the Relevant Ones
SSRN
Bank of Italy data managers check the market notices published daily by the Italian Stock Exchange (Borsa Italiana) and select those of interest to update the Bank of Italy's Securities Database. This activity is time-consuming and prone to errors should a data manager overlook a relevant notice. In this paper we describe the implementation of a supervised model to automatically select the market notices. The model outperforms the manual approach used by data managers and can therefore be implemented in the regular process to update the Securities Database.
SSRN
Bank of Italy data managers check the market notices published daily by the Italian Stock Exchange (Borsa Italiana) and select those of interest to update the Bank of Italy's Securities Database. This activity is time-consuming and prone to errors should a data manager overlook a relevant notice. In this paper we describe the implementation of a supervised model to automatically select the market notices. The model outperforms the manual approach used by data managers and can therefore be implemented in the regular process to update the Securities Database.
When the Panic Broke Out: Covid-19 and Investment Funds' Portfolio Rebalancing Around the World
SSRN
To contribute to the understanding of investment funds' (IFs) behaviour, the paper exploits the exogenous shock of the COVID-19 pandemic and analyses more than 12 million security sales and purchases during the first four months of 2020 by over 20,000 IFs from more than 40 national jurisdictions and investing in more than 100 economies and 20 industries. Our estimates reveal that, when the emergency strikes, IFs do not sell indiscriminately but divest from assets considered the most vulnerable at the moment, that is, those issued by more COVID-affected countries and industries. Our results also show several dimensions of heterogeneity according to the pandemic outbreak phase, asset type, IF category and performance, extent of unitholders' outflows, and nationality of IFs. Our results, on the one hand, provide new evidence on the intrinsic fragility of IFs and the connection between their choices and fire sales, but, on the other, they also show that IF industry includes heterogeneous institutions that behave very differently. Finally, our results document that monetary policy measures have a reassuring effect also for IFs, which corroborates recent evidence on a non-bank financial institution channel of unconventional monetary policies.
SSRN
To contribute to the understanding of investment funds' (IFs) behaviour, the paper exploits the exogenous shock of the COVID-19 pandemic and analyses more than 12 million security sales and purchases during the first four months of 2020 by over 20,000 IFs from more than 40 national jurisdictions and investing in more than 100 economies and 20 industries. Our estimates reveal that, when the emergency strikes, IFs do not sell indiscriminately but divest from assets considered the most vulnerable at the moment, that is, those issued by more COVID-affected countries and industries. Our results also show several dimensions of heterogeneity according to the pandemic outbreak phase, asset type, IF category and performance, extent of unitholders' outflows, and nationality of IFs. Our results, on the one hand, provide new evidence on the intrinsic fragility of IFs and the connection between their choices and fire sales, but, on the other, they also show that IF industry includes heterogeneous institutions that behave very differently. Finally, our results document that monetary policy measures have a reassuring effect also for IFs, which corroborates recent evidence on a non-bank financial institution channel of unconventional monetary policies.
