Research articles for the 2020-02-15
A New European Investor Sentiment Index (Eursent) and its Return and Volatility Predictability
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This study presents a new European investor sentiment index, EURsent, based on new and tested sentiment proxies, and studies the spillover and contagion between the United States and Europe. Furthermore, it analyses the simultaneous influence of this new sentiment measure index on both volatility and stock returns, including causality. Applying well-established statistical techniques, such as principal component analysis, ordinary least squares, autoregressive conditional heteroskedasticity (ARCH), generalized ARCH (GARCH), and threshold GARCH models, the findings demonstrate how EURsent is closely interrelated with the most universally recognized sentiment index in academia demonstrating a strong co-movement between the United States and European stock markets, mainly prior to the global subprime crisis. The study concludes that EURsent is a strong predictor of market returns and is closely tied to Europe’s market volatility, coupled with a strong connection to several crisis periods since 1999. This study is the first, as far as our knowledge is concerned, to create a European investor sentiment measure comparable to that of the United States, interlinking a holistic sentiment measure index, and not just a single proxy, with conditionally market volatility and market returns, suggesting causality. Moreover, we use several statistical techniques and apply them to a broad range of periods. EURsent could thus be a tool for investment managers, investors, and financial service providers as well as regulators to monitor the evolution of stock markets.
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This study presents a new European investor sentiment index, EURsent, based on new and tested sentiment proxies, and studies the spillover and contagion between the United States and Europe. Furthermore, it analyses the simultaneous influence of this new sentiment measure index on both volatility and stock returns, including causality. Applying well-established statistical techniques, such as principal component analysis, ordinary least squares, autoregressive conditional heteroskedasticity (ARCH), generalized ARCH (GARCH), and threshold GARCH models, the findings demonstrate how EURsent is closely interrelated with the most universally recognized sentiment index in academia demonstrating a strong co-movement between the United States and European stock markets, mainly prior to the global subprime crisis. The study concludes that EURsent is a strong predictor of market returns and is closely tied to Europe’s market volatility, coupled with a strong connection to several crisis periods since 1999. This study is the first, as far as our knowledge is concerned, to create a European investor sentiment measure comparable to that of the United States, interlinking a holistic sentiment measure index, and not just a single proxy, with conditionally market volatility and market returns, suggesting causality. Moreover, we use several statistical techniques and apply them to a broad range of periods. EURsent could thus be a tool for investment managers, investors, and financial service providers as well as regulators to monitor the evolution of stock markets.
Alpha by Affiliation
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Using novel data establishing hedge fund families, we show that changes in overlapping hedge fund family positions predict abnormal returns in U.S. stocks. A long-short portfolio of unanimous family entries and exits in overlapping positions earns an annualized alpha of 7.32%. Panel regressions and double-sorts provide evidence for a mispricing-based explanation as results are consistent with fund families facing binding short sale constraints to coordinated exits. The returns are larger for high information asymmetry stocks and suggest that hedge fund families coordinate on information, despite having no shared legal structure like mutual fund families.
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Using novel data establishing hedge fund families, we show that changes in overlapping hedge fund family positions predict abnormal returns in U.S. stocks. A long-short portfolio of unanimous family entries and exits in overlapping positions earns an annualized alpha of 7.32%. Panel regressions and double-sorts provide evidence for a mispricing-based explanation as results are consistent with fund families facing binding short sale constraints to coordinated exits. The returns are larger for high information asymmetry stocks and suggest that hedge fund families coordinate on information, despite having no shared legal structure like mutual fund families.
Can Long-Term Institutional Owners Improve Market Efficiency in Parsing Complex Legal Disputes?
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Long-horizon institutional investors can help mitigate information asymmetries around securities class action (SCA) lawsuits. We find that the machine readability of SCA complaint filings can predict the outcome and duration of class actions. Long-term institutional investor ownership leads to a more positive post-SCA announcement price reaction and increases the volatility ratio of prices as a measure of price informativeness. Furthermore, there is a significant interaction effect between long-term institutional ownership and SCA complexity on price informativeness consistent with a superior information processing ability about complex corporate events affecting portfolio firms.
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Long-horizon institutional investors can help mitigate information asymmetries around securities class action (SCA) lawsuits. We find that the machine readability of SCA complaint filings can predict the outcome and duration of class actions. Long-term institutional investor ownership leads to a more positive post-SCA announcement price reaction and increases the volatility ratio of prices as a measure of price informativeness. Furthermore, there is a significant interaction effect between long-term institutional ownership and SCA complexity on price informativeness consistent with a superior information processing ability about complex corporate events affecting portfolio firms.
Deep Learning: Credit Default Prediction from User-Generated Text
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The digital transformation produces vast sources of unstructured data that are storable by and accessible to traditional banks and fintechs. Prior literature indicates that this unstructured information is valuable for decisions of accepting and pricing credit contracts. While processing this kind of information has been very difficult in the past, deep learning offers tools to process parts of these unstructured sources automatically and use it to predict credit defaults. We employ deep learning techniques to extract credit relevant information based on loan descriptions from Lending Club. Our results confirm that even short pieces of user-generated text can improve credit default predictions significantly. The additional information extracted by deep learning is robust towards controlling for credit scores, structured application information, and common theoretically suggested text characteristics.
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The digital transformation produces vast sources of unstructured data that are storable by and accessible to traditional banks and fintechs. Prior literature indicates that this unstructured information is valuable for decisions of accepting and pricing credit contracts. While processing this kind of information has been very difficult in the past, deep learning offers tools to process parts of these unstructured sources automatically and use it to predict credit defaults. We employ deep learning techniques to extract credit relevant information based on loan descriptions from Lending Club. Our results confirm that even short pieces of user-generated text can improve credit default predictions significantly. The additional information extracted by deep learning is robust towards controlling for credit scores, structured application information, and common theoretically suggested text characteristics.
Dynamic Risk Adjustment in Long-Run Event Study Tests
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This study applies a rolling estimation window approach to adjust for time-varying risk parameters in asset pricing models to compute long-run abnormal returns after major corporate events. Abnormal returns are defined as realized returns minus predicted returns on each day in a five-year, post-event period. A variety of asset pricing models are employed to compute out-of-sample predicted returns in different estimation windows for seasoned equity offerings (SEOs) and mergers and acquisitions (M&As). We find that, after an initial significant return response in the month or two after corporate announcements, abnormal returns thereafter disappear over a five-year, post-event period. Robustness checks corroborate our results: (1) with or without matched and random control samples, (2) for different asset pricing models including the CAPM market model, and (3) in robustness tests of share repurchases (SRs) as well as different subperiods. We conclude that, after dynamic risk adjustment, long-run abnormal returns are not evident after these major corporate actions.
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This study applies a rolling estimation window approach to adjust for time-varying risk parameters in asset pricing models to compute long-run abnormal returns after major corporate events. Abnormal returns are defined as realized returns minus predicted returns on each day in a five-year, post-event period. A variety of asset pricing models are employed to compute out-of-sample predicted returns in different estimation windows for seasoned equity offerings (SEOs) and mergers and acquisitions (M&As). We find that, after an initial significant return response in the month or two after corporate announcements, abnormal returns thereafter disappear over a five-year, post-event period. Robustness checks corroborate our results: (1) with or without matched and random control samples, (2) for different asset pricing models including the CAPM market model, and (3) in robustness tests of share repurchases (SRs) as well as different subperiods. We conclude that, after dynamic risk adjustment, long-run abnormal returns are not evident after these major corporate actions.
Managing the Treasury Yield Curve in the 1940s
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This paper examines the efforts of the Federal Open Market Committee (FOMC) to first control, and later decontrol, the level and shape of the Treasury yield curve in the 1940s. The paper begins with a brief review of monetary policy in 1938 and a description of the period between September 1939 and December 1941, when the idea of maintaining a fixed yield curve first appeared. It then discusses the financing of U.S. participation in World War II and the experience with maintaining a fixed curve. The paper concludes with a discussion of how the FOMC regained control of monetary policy in the second half of the 1940s. The Committee’s efforts offer two lessons in yield curve management: (1) the shape of the curve cannot be fixed independently of the volatility of interest rates and debt management policies, and (2) large-scale open market operations may be required in the course of refixing, from time to time, the shape of the yield curve.
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This paper examines the efforts of the Federal Open Market Committee (FOMC) to first control, and later decontrol, the level and shape of the Treasury yield curve in the 1940s. The paper begins with a brief review of monetary policy in 1938 and a description of the period between September 1939 and December 1941, when the idea of maintaining a fixed yield curve first appeared. It then discusses the financing of U.S. participation in World War II and the experience with maintaining a fixed curve. The paper concludes with a discussion of how the FOMC regained control of monetary policy in the second half of the 1940s. The Committee’s efforts offer two lessons in yield curve management: (1) the shape of the curve cannot be fixed independently of the volatility of interest rates and debt management policies, and (2) large-scale open market operations may be required in the course of refixing, from time to time, the shape of the yield curve.
Monetary Policy and Exchange Rate Returns: Time-Varying Risk Regimes
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We develop an empirical model of exchange rate returns, applied separately to samples of developed (DM) and developing (EM) economies’ currencies against the dollar. Monetary policy stance of the global central banks, measured via a natural-language-based approach, has a large effect on exchange rate returns over the ensuing year, is closely linked to the VIX, and becomes increasingly important in the post-crisis era. We document an important spillover effect: monetary policy of the Bank of England, the Bank of Japan and the ECB is as important as Fed policy in forecasting currency returns against the dollar. In the post-crisis era, a one standard deviation increase in dovishness of all four central banks forecasts a 5.8% (4.0%) one-year excess return of DM (EM) currencies. Furthermore, we find that the relation between a DM country’s interest rate differential relative to the dollar (carry) and the future returns from investing in its currency switches sign from the pre- to the post-crisis subperiod, while for EMs the carry variable is never a significant predictor of returns. The high profit from the carry trade for EM currencies reflects persistent country characteristics likely reflective of risk rather than the interest differential per se. While measures of global monetary policy stance forecast exchange rate returns against the dollar, they do not predict exchange rate returns against other base currencies. Results regarding returns from carry, however, are insensitive to the choice of the base currency. We construct a no-arbitrage pricing model which reconciles many of our empirical findings.
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We develop an empirical model of exchange rate returns, applied separately to samples of developed (DM) and developing (EM) economies’ currencies against the dollar. Monetary policy stance of the global central banks, measured via a natural-language-based approach, has a large effect on exchange rate returns over the ensuing year, is closely linked to the VIX, and becomes increasingly important in the post-crisis era. We document an important spillover effect: monetary policy of the Bank of England, the Bank of Japan and the ECB is as important as Fed policy in forecasting currency returns against the dollar. In the post-crisis era, a one standard deviation increase in dovishness of all four central banks forecasts a 5.8% (4.0%) one-year excess return of DM (EM) currencies. Furthermore, we find that the relation between a DM country’s interest rate differential relative to the dollar (carry) and the future returns from investing in its currency switches sign from the pre- to the post-crisis subperiod, while for EMs the carry variable is never a significant predictor of returns. The high profit from the carry trade for EM currencies reflects persistent country characteristics likely reflective of risk rather than the interest differential per se. While measures of global monetary policy stance forecast exchange rate returns against the dollar, they do not predict exchange rate returns against other base currencies. Results regarding returns from carry, however, are insensitive to the choice of the base currency. We construct a no-arbitrage pricing model which reconciles many of our empirical findings.
Organization Capital and Corporate Cash Holdings
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This paper investigates the relationship between organization capital and corporate cash holdings. We develop two competing hypotheses in relating organization capital with cash holding. Our analysis reveals that organization capital is related to high levels of cash holdings. Moreover, we find that the effect of organization capital on corporate cash holdings is stronger for firms experiencing high levels of financing constraint and cash flow risk. Our results remain robust to alternative measures of organization capital and corporate cash holdings, and are not driven by omitted variable bias or endogeneity issues. We also find that the positive relation between organization capital and cash holdings is not confounded by sample period or industry group. Overall, we provide robust evidence that supports the precautionary motive for corporate cash holding.
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This paper investigates the relationship between organization capital and corporate cash holdings. We develop two competing hypotheses in relating organization capital with cash holding. Our analysis reveals that organization capital is related to high levels of cash holdings. Moreover, we find that the effect of organization capital on corporate cash holdings is stronger for firms experiencing high levels of financing constraint and cash flow risk. Our results remain robust to alternative measures of organization capital and corporate cash holdings, and are not driven by omitted variable bias or endogeneity issues. We also find that the positive relation between organization capital and cash holdings is not confounded by sample period or industry group. Overall, we provide robust evidence that supports the precautionary motive for corporate cash holding.
Prime and Punishment: Can Enforcements Stop Illicit Sellers on E-Commerce Platforms?
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This paper provides the first exploration of how illicit sellers operate on e-commerce platforms and how they respond to enforcements. I use a novel data set of 71 million illicit â€" i.e., fraudulent, counterfeit, or replica â€" items that were removed from online marketplaces. By using natural language processing and computer vision techniques on these products and by quietly tracking business activities of the illicit sellers, I identify a large number of similar but previously unnoticed illicit products (UIPs) that are currently sold online. For each illicit product that was previously removed, I detect 16.91 UIPs. Of these, 84% remained on the market during the one-year period after the removal of the initial illicit product. Nonetheless, the total market value of these products decreased by up to 80% after enforcements. My findings suggest that enforcements against illicit products on e-commerce platforms encourage separating equilibria, in which illicit sellers have weaker incentives to pool with authentic producers than to be revealed as low-quality producers.
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This paper provides the first exploration of how illicit sellers operate on e-commerce platforms and how they respond to enforcements. I use a novel data set of 71 million illicit â€" i.e., fraudulent, counterfeit, or replica â€" items that were removed from online marketplaces. By using natural language processing and computer vision techniques on these products and by quietly tracking business activities of the illicit sellers, I identify a large number of similar but previously unnoticed illicit products (UIPs) that are currently sold online. For each illicit product that was previously removed, I detect 16.91 UIPs. Of these, 84% remained on the market during the one-year period after the removal of the initial illicit product. Nonetheless, the total market value of these products decreased by up to 80% after enforcements. My findings suggest that enforcements against illicit products on e-commerce platforms encourage separating equilibria, in which illicit sellers have weaker incentives to pool with authentic producers than to be revealed as low-quality producers.
Review on Recent Application of Financial Sector Assessment Program (FSAP): Has FSAP Adopted Proposed Islamic Financial Sector Assessment Program (IFSAP) Template?
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The Financial Sector Assessment Program (FSAP) states that a sound and well functioning financial system is supported by three pillars to sustain orderly financial development and stability which relate to the macroeconomic factors, regulatory and supervisory framework, and the infrastructures. Three years after the proposed paper, there is an urgency to review to what extent FSAP has adopted Proposed Islamic Financial Sector Assessment Program (IFSAP) Template. This note will try to review the FSAP on some selected countries and analyze the influence of proposed IFSAP to the FSAP. This result of this review shows that the IMF-World Bank has adopted in a limited way the proposed template by IRTI-IDB. Overall, there is a very limited significance of change in the of FSAP model.
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The Financial Sector Assessment Program (FSAP) states that a sound and well functioning financial system is supported by three pillars to sustain orderly financial development and stability which relate to the macroeconomic factors, regulatory and supervisory framework, and the infrastructures. Three years after the proposed paper, there is an urgency to review to what extent FSAP has adopted Proposed Islamic Financial Sector Assessment Program (IFSAP) Template. This note will try to review the FSAP on some selected countries and analyze the influence of proposed IFSAP to the FSAP. This result of this review shows that the IMF-World Bank has adopted in a limited way the proposed template by IRTI-IDB. Overall, there is a very limited significance of change in the of FSAP model.
Tax Savvy Executives
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We investigate why firms include individuals with significant professional tax experience on their senior management team and the consequences associated with the presence of these tax-savvy senior executives. We find that past performance, network connections, geographic location, and tax rate level relative to industry peers are all significant determinants in having a tax-savvy executive on the senior management team. Using propensity score matching, we find that effective tax rates decrease substantially after a tax-savvy executive is added to senior management and revert following the departure of a tax-savvy executive from senior management. We connect the changes in effective tax rates to changes in the usage of foreign subsidiaries in low tax jurisdictions.
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We investigate why firms include individuals with significant professional tax experience on their senior management team and the consequences associated with the presence of these tax-savvy senior executives. We find that past performance, network connections, geographic location, and tax rate level relative to industry peers are all significant determinants in having a tax-savvy executive on the senior management team. Using propensity score matching, we find that effective tax rates decrease substantially after a tax-savvy executive is added to senior management and revert following the departure of a tax-savvy executive from senior management. We connect the changes in effective tax rates to changes in the usage of foreign subsidiaries in low tax jurisdictions.
The Determinants of Credit Union Failure in the United Kingdom: How Important Are Macroeconomic Factors?
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Using regulatory data on credit unions, this paper provides empirical evidence on the determinants of credit union failure in the United Kingdom. We find that a small set of financial attributes related to capital adequacy, asset quality, earnings performance and liquidity is useful for early identification of troubled credit unions. In and out-of-sample results indicate that this parsimonious set of firm-level characteristics, augmented with national and regional unemployment rates, reliably identifies failures while keeping false alarm rates at modest levels. The results provide support for establishing early warning criteria for supervisory use in monitoring credit unions.
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Using regulatory data on credit unions, this paper provides empirical evidence on the determinants of credit union failure in the United Kingdom. We find that a small set of financial attributes related to capital adequacy, asset quality, earnings performance and liquidity is useful for early identification of troubled credit unions. In and out-of-sample results indicate that this parsimonious set of firm-level characteristics, augmented with national and regional unemployment rates, reliably identifies failures while keeping false alarm rates at modest levels. The results provide support for establishing early warning criteria for supervisory use in monitoring credit unions.
The Impact of Socio-Demographic Variables on Personal Financial Well-being of International Students in Turkey
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The issue of personal financial wellbeing vis-Ã -vis university students has been paid attention in academics. This paper aims to examine the impact of socio-demographic variables on the personal financial wellbeing of international students in Turkey. 201 students were surveyed from undergraduate and graduate students who are currently studying at different universities in Turkey. Socio-demographic variables of students such as age, gender, marital status, level of education, childhood place of residence, work condition, continent, type of scholarship and current residence have been taken into account. To measure the personal financial wellness of students, The Personal Financial Wellness Scaleâ„¢ (PFW Scaleâ„¢), an eight-question, self-report measure of perceived financial distress and financial well-being, was employed. It measures how people are doing along a continuum extending from negative to positive feelings about and reactions to their financial situations. The results show that gender and continent have weak but positive significant relationship whereas marital status has weak but negative significant relationship with personal financial wellbeing of students. Besides, type of scholarship and work condition demonstrate weak but positive and negative significant relationship with confidence regarding financial emergency respectively.
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The issue of personal financial wellbeing vis-Ã -vis university students has been paid attention in academics. This paper aims to examine the impact of socio-demographic variables on the personal financial wellbeing of international students in Turkey. 201 students were surveyed from undergraduate and graduate students who are currently studying at different universities in Turkey. Socio-demographic variables of students such as age, gender, marital status, level of education, childhood place of residence, work condition, continent, type of scholarship and current residence have been taken into account. To measure the personal financial wellness of students, The Personal Financial Wellness Scaleâ„¢ (PFW Scaleâ„¢), an eight-question, self-report measure of perceived financial distress and financial well-being, was employed. It measures how people are doing along a continuum extending from negative to positive feelings about and reactions to their financial situations. The results show that gender and continent have weak but positive significant relationship whereas marital status has weak but negative significant relationship with personal financial wellbeing of students. Besides, type of scholarship and work condition demonstrate weak but positive and negative significant relationship with confidence regarding financial emergency respectively.
Using Natural Language Processing Techniques for Stock Return Predictions
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Our Applied Finance Project aims to develop a framework to determine if financial news headlines have meaningful impact on stock prices. This framework is a novel structure that primarily leverages on existing Natural Language Processing, including Name Entity Recognition, and Global Vector for Word Representation (GloVe) model, before combining them with techniques such as k-means clustering and portfolio optimization. The subsequent study on events with predictive abilities could be of interest to institutional investors.
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Our Applied Finance Project aims to develop a framework to determine if financial news headlines have meaningful impact on stock prices. This framework is a novel structure that primarily leverages on existing Natural Language Processing, including Name Entity Recognition, and Global Vector for Word Representation (GloVe) model, before combining them with techniques such as k-means clustering and portfolio optimization. The subsequent study on events with predictive abilities could be of interest to institutional investors.
Willingness to Pay of the Expo-Power Utility Decision Maker to Limit Climate Change
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This paper extends the work of Pindyck [1] by taking into consideration a large class family of different utility functions of economic agents. As in Pindyck [1], instead of considering a social utility function that is characterized by constant relative risk aversion (C.R.R.A), we use the expo-power utility function of Saha [2]. In fact, depending on the choice of the expo-power utility function parameters, we cover a diverse range1 of utility functions and besides covering the other utility functions that a C.R.R.A omits, Expo-power function permits us to discern if under the other behaviors of economic agents, the willingness to pay remains more affected by uncertain outcomes than certain outcomes, when we vary the expectation and standard deviation of the temperature distribution probability. Our paper has maintained the small-tailed gamma distributions of temperature and economic impact of Pindyck [1], not only because they hinder infinite future welfare losses (for an exponential utility function), but because it is easy to change some moments of the distribution (jointly or holding the others fixed) while studying how uncertainty influences the willingness to pay as explained in Pindyck [1].
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This paper extends the work of Pindyck [1] by taking into consideration a large class family of different utility functions of economic agents. As in Pindyck [1], instead of considering a social utility function that is characterized by constant relative risk aversion (C.R.R.A), we use the expo-power utility function of Saha [2]. In fact, depending on the choice of the expo-power utility function parameters, we cover a diverse range1 of utility functions and besides covering the other utility functions that a C.R.R.A omits, Expo-power function permits us to discern if under the other behaviors of economic agents, the willingness to pay remains more affected by uncertain outcomes than certain outcomes, when we vary the expectation and standard deviation of the temperature distribution probability. Our paper has maintained the small-tailed gamma distributions of temperature and economic impact of Pindyck [1], not only because they hinder infinite future welfare losses (for an exponential utility function), but because it is easy to change some moments of the distribution (jointly or holding the others fixed) while studying how uncertainty influences the willingness to pay as explained in Pindyck [1].
