We examine technology enabling dispersed investors to directly trade with each other in over-the-counter markets via the largest electronic trading platform in corporate bonds starting Open Trading (OT) to allow investor-to-investor trading. Over our six-year sample, OT steadily grew to win 12% of trades on the platform, with 2% being investor-to-investor trading, 3% being dealers trading with new clients, and 7% being new liquidity providers acting like dealers. This suggests that investors in corporate bonds prefer intermediation to direct trade. However, OT can enable new dealers to compete in liquidity provision. OT's steady growth facilitates measuring its effect on investors, dealers, and competition to provide liquidity using an auction model.
{"title":"All-to-All Liquidity in Corporate Bonds","authors":"T. Hendershott, Dmitry Livdan, N. Schürhoff","doi":"10.2139/ssrn.3895270","DOIUrl":"https://doi.org/10.2139/ssrn.3895270","url":null,"abstract":"We examine technology enabling dispersed investors to directly trade with each other in over-the-counter markets via the largest electronic trading platform in corporate bonds starting Open Trading (OT) to allow investor-to-investor trading. Over our six-year sample, OT steadily grew to win 12% of trades on the platform, with 2% being investor-to-investor trading, 3% being dealers trading with new clients, and 7% being new liquidity providers acting like dealers. This suggests that investors in corporate bonds prefer intermediation to direct trade. However, OT can enable new dealers to compete in liquidity provision. OT's steady growth facilitates measuring its effect on investors, dealers, and competition to provide liquidity using an auction model.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128624222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We test the theoretical predictions of the differences-of-opinion literature by analyzing the extensive online discussion on Bitcoin to build a time-varying sentiment distribution, defining disagreement as dispersion in sentiment. High disagreement is associated with negative returns, high turnover growth, and high volatility, confirming the theory's predictions. However, we do not find that an increase in disagreement increases the price, which is seemingly at odds with the theoretical prediction of disagreement leading to overpricing. As the theory predicts, the disagreement effect weakens significantly after shorting instruments were introduced at the end of 2017. Our results are economically significant: at the monthly frequency, a one standard deviation increase in disagreement leads to a 9.2 percentage points lower cumulative return over the following eight months, and the adjusted R2 of regressing contemporaneous returns on average sentiment and disagreement is 0.33.
{"title":"Does Dispersed Sentiment Drive Returns, Turnover, and Volatility for Bitcoin?","authors":"Ilja Kantorovitch, J. Heineken","doi":"10.2139/ssrn.3920987","DOIUrl":"https://doi.org/10.2139/ssrn.3920987","url":null,"abstract":"We test the theoretical predictions of the differences-of-opinion literature by analyzing the extensive online discussion on Bitcoin to build a time-varying sentiment distribution, defining disagreement as dispersion in sentiment. High disagreement is associated with negative returns, high turnover growth, and high volatility, confirming the theory's predictions. However, we do not find that an increase in disagreement increases the price, which is seemingly at odds with the theoretical prediction of disagreement leading to overpricing. As the theory predicts, the disagreement effect weakens significantly after shorting instruments were introduced at the end of 2017. Our results are economically significant: at the monthly frequency, a one standard deviation increase in disagreement leads to a 9.2 percentage points lower cumulative return over the following eight months, and the adjusted R2 of regressing contemporaneous returns on average sentiment and disagreement is 0.33.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132055511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper explores the pricing of heterogeneous goods in the presence of market segmentation. We use housing as an example. We extend the theoretical hedonic model of Rosen (1974) and show that, in the presence of market segmentation, the hedonic price line is no longer continuous or unique. Using American Housing Survey data for the Miami and Louisville metropolitan areas and a finite mixture estimation approach, we find distinct market segments based on ethnicity, race, and income.
{"title":"Hedonic Models and Market Segmentation","authors":"Steven C. Bourassa, M. Dröes, Martin Hoesli","doi":"10.2139/ssrn.3916232","DOIUrl":"https://doi.org/10.2139/ssrn.3916232","url":null,"abstract":"This paper explores the pricing of heterogeneous goods in the presence of market segmentation. We use housing as an example. We extend the theoretical hedonic model of Rosen (1974) and show that, in the presence of market segmentation, the hedonic price line is no longer continuous or unique. Using American Housing Survey data for the Miami and Louisville metropolitan areas and a finite mixture estimation approach, we find distinct market segments based on ethnicity, race, and income.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132530148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We study the selection of private equity managers (GPs) for over 100,000 capital commitments between 1990 and 2019 by global institutional investors (LPs) choosing from a plausible contemporaneous opportunity set. LPs have large propensities to select first-time or young GPs without a performance history, in addition to chasing 4th quartile managers. LPs also have tendency to follow their peers’ investment decisions, to reinvest in the same GP, and to invest in GPs domiciled in the same state/country. These selection criteria, however, do not provide information material for future performance, and in the case of first-time GPs result in lower future performance.
{"title":"Picking Partners: Manager Selection in Private Equity","authors":"Amit Goyal, Sunil Wahal, M. Yavuz","doi":"10.2139/ssrn.3910494","DOIUrl":"https://doi.org/10.2139/ssrn.3910494","url":null,"abstract":"We study the selection of private equity managers (GPs) for over 100,000 capital commitments between 1990 and 2019 by global institutional investors (LPs) choosing from a plausible contemporaneous opportunity set. LPs have large propensities to select first-time or young GPs without a performance history, in addition to chasing 4th quartile managers. LPs also have tendency to follow their peers’ investment decisions, to reinvest in the same GP, and to invest in GPs domiciled in the same state/country. These selection criteria, however, do not provide information material for future performance, and in the case of first-time GPs result in lower future performance.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126430363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces a tractable model of sovereign debt where governments cannot default strategically, but face intertemporal tradeoffs between (i) preferring more primary deficits to less and (ii) avoiding costly defaults. Governments run deficits when debt and, then, the marginal costs of increasing debt are low. However, after an extended period of debt accumulation, default probabilities begin to rise quickly, and so do the marginal costs of running debt. Eventually, debt reaches a critical level relative to the size of the economy, a fiscal tipping point, after which debt accumulation stops, with governments cycling between deficits and surpluses, until perhaps a time of default. The main conclusions are that (i) fiscal tipping points typically occur when distanceto- default is between 10% and 20%; (ii) tipping points are pushed back in a stable macroeconomic environment, such that default premiums are higher in countries that implement austerity earlier and remain positive even when exogenous risk is very small (two “volatility paradoxes”); (iii) liquidity conditions and fiscal reforms may affect default probabilities in an ambiguous way; (iv) fiscal austerity may arrive too late: “debt intolerance” arises around the fiscal tipping point.
{"title":"A Theory of Debt Accumulation and Deficit Cycles","authors":"A. Melé","doi":"10.2139/ssrn.3881063","DOIUrl":"https://doi.org/10.2139/ssrn.3881063","url":null,"abstract":"This paper introduces a tractable model of sovereign debt where governments cannot default strategically, but face intertemporal tradeoffs between (i) preferring more primary deficits to less and (ii) avoiding costly defaults. Governments run deficits when debt and, then, the marginal costs of increasing debt are low. However, after an extended period of debt accumulation, default probabilities begin to rise quickly, and so do the marginal costs of running debt. Eventually, debt reaches a critical level relative to the size of the economy, a fiscal tipping point, after which debt accumulation stops, with governments cycling between deficits and surpluses, until perhaps a time of default. The main conclusions are that (i) fiscal tipping points typically occur when distanceto- default is between 10% and 20%; (ii) tipping points are pushed back in a stable macroeconomic environment, such that default premiums are higher in countries that implement austerity earlier and remain positive even when exogenous risk is very small (two “volatility paradoxes”); (iii) liquidity conditions and fiscal reforms may affect default probabilities in an ambiguous way; (iv) fiscal austerity may arrive too late: “debt intolerance” arises around the fiscal tipping point.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126612240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We develop a framework to theoretically and empirically analyze the fluctuations of the aggregate stock market. Households allocate capital to institutions, which are fairly constrained, for example operating with a mandate to maintain a fixed equity share or with moderate scope for variation in response to changing market conditions. As a result, the price elasticity of demand of the aggregate stock market is small, and flows in and out of the stock market have large impacts on prices.Using the recent method of granular instrumental variables, we find that investing $1 in the stock market increases the market's aggregate value by about $5. We also develop a new measure of capital flows into the market, consistent with our theory. We relate it to prices, macroeconomic variables, and survey expectations of returns.We analyze how key parts of macro-finance change if markets are inelastic. We show how general equilibrium models and pricing kernels can be generalized to incorporate flows, which makes them amenable to use in more realistic macroeconomic models and to policy analysis.Our framework allows us to give a dynamic economic structure to old and recent datasets comprising holdings and flows in various segments of the market. The mystery of apparently random movements of the stock market, hard to link to fundamentals, is replaced by the more manageable problem of understanding the determinants of flows in inelastic markets. We delineate a research agenda that can explore a number of questions raised by this analysis, and might lead to a more concrete understanding of the origins of financial fluctuations across markets. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
{"title":"In Search of the Origins of Financial Fluctuations: The Inelastic Markets Hypothesis","authors":"X. Gabaix, R. Koijen","doi":"10.2139/ssrn.3686935","DOIUrl":"https://doi.org/10.2139/ssrn.3686935","url":null,"abstract":"We develop a framework to theoretically and empirically analyze the fluctuations of the aggregate stock market. Households allocate capital to institutions, which are fairly constrained, for example operating with a mandate to maintain a fixed equity share or with moderate scope for variation in response to changing market conditions. As a result, the price elasticity of demand of the aggregate stock market is small, and flows in and out of the stock market have large impacts on prices.Using the recent method of granular instrumental variables, we find that investing $1 in the stock market increases the market's aggregate value by about $5. We also develop a new measure of capital flows into the market, consistent with our theory. We relate it to prices, macroeconomic variables, and survey expectations of returns.We analyze how key parts of macro-finance change if markets are inelastic. We show how general equilibrium models and pricing kernels can be generalized to incorporate flows, which makes them amenable to use in more realistic macroeconomic models and to policy analysis.Our framework allows us to give a dynamic economic structure to old and recent datasets comprising holdings and flows in various segments of the market. The mystery of apparently random movements of the stock market, hard to link to fundamentals, is replaced by the more manageable problem of understanding the determinants of flows in inelastic markets. We delineate a research agenda that can explore a number of questions raised by this analysis, and might lead to a more concrete understanding of the origins of financial fluctuations across markets. \u0000 \u0000Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115784320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rajna Gibson, Simon Glossner, Philipp Krueger, Pedro Matos, Tom Steffen
We explore a novel survey on responsible investing by institutional investors around the world and match it to archival data on equity portfolio holdings. We document that institutions that commit to responsible investing exhibit different environmental, social and governance (ESG) portfolio-level scores but this is not the case for US-domiciled institutions. We also examine if different ESG implementation strategies (e.g., screening, integration, engagement) affect portfolio-level ESG scores but find limited evidence. Finally, we find that responsible investing does not enhance portfolio returns but acts more as a risk mitigation tool.
{"title":"Do Responsible Investors Invest Responsibly?","authors":"Rajna Gibson, Simon Glossner, Philipp Krueger, Pedro Matos, Tom Steffen","doi":"10.2139/ssrn.3525530","DOIUrl":"https://doi.org/10.2139/ssrn.3525530","url":null,"abstract":"We explore a novel survey on responsible investing by institutional investors around the world and match it to archival data on equity portfolio holdings. We document that institutions that commit to responsible investing exhibit different environmental, social and governance (ESG) portfolio-level scores but this is not the case for US-domiciled institutions. We also examine if different ESG implementation strategies (e.g., screening, integration, engagement) affect portfolio-level ESG scores but find limited evidence. Finally, we find that responsible investing does not enhance portfolio returns but acts more as a risk mitigation tool.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114439330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
From 2004 to 2008, a bubble formed in clean technologies, such as solar, biofuels, batteries, and other renewable energy sources. In this paper, we analyze this clean-tech bubble through the lens of the Social Bubble Hypothesis, which holds that strong social interactions between enthusiastic supporters weave a network of reinforcing feedbacks that lead to widespread endorsement and extraordinary commitment by those involved. We present a detailed synthesis of the development of the clean-tech bubble, its history, and the role of venture capital and government funding in catalyzing it. In particular, we dissect the underlying narrative that was fueling the bubble. As bubbles can be essential in the process of accelerating the development of emerging technologies and diffusion of technological innovations, we present evidence that the clean-tech bubble constituted an example of an innovation-accelerating process.
{"title":"“Salvation and Profit”: Deconstructing the Clean-Tech Bubble","authors":"V. Giorgis, Tobias Huber, D. Sornette","doi":"10.2139/ssrn.3852673","DOIUrl":"https://doi.org/10.2139/ssrn.3852673","url":null,"abstract":"From 2004 to 2008, a bubble formed in clean technologies, such as solar, biofuels, batteries, and other renewable energy sources. In this paper, we analyze this clean-tech bubble through the lens of the Social Bubble Hypothesis, which holds that strong social interactions between enthusiastic supporters weave a network of reinforcing feedbacks that lead to widespread endorsement and extraordinary commitment by those involved. We present a detailed synthesis of the development of the clean-tech bubble, its history, and the role of venture capital and government funding in catalyzing it. In particular, we dissect the underlying narrative that was fueling the bubble. As bubbles can be essential in the process of accelerating the development of emerging technologies and diffusion of technological innovations, we present evidence that the clean-tech bubble constituted an example of an innovation-accelerating process.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123179157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper looks at the credit rating adjustments on Eurozone banks that followed the post-crisis regulation of bank resolution in Europe in 2014. The empirical assessment analyses within-bank variation using the credit ratings of the major Eurozone banks. The analysis shows that with the introduction of the bail-in: 1) the ratings of Eurozone banks, as expected, were subject to downward pressures; 2) however, credit rating agencies (CRAs) reacted in a variety of ways, moving to post bail-in ratings for Eurozone banks that were more homogenous across CRAs than pre bail-in ratings. While the credit rating adjustments are rightly justified by the rating methodologies used, the convergence among CRAs suggests some degree of discretion in assigning the rating. These results are consistent with herding behaviour among CRAs.
{"title":"Post-crisis Banking Regulation and Credit Rating Adjustments. How Did the Bail-In Affect Eurozone Banks’ Credit Rating?","authors":"L. Franco","doi":"10.2139/ssrn.3838842","DOIUrl":"https://doi.org/10.2139/ssrn.3838842","url":null,"abstract":"This paper looks at the credit rating adjustments on Eurozone banks that followed the post-crisis regulation of bank resolution in Europe in 2014. The empirical assessment analyses within-bank variation using the credit ratings of the major Eurozone banks. The analysis shows that with the introduction of the bail-in: 1) the ratings of Eurozone banks, as expected, were subject to downward pressures; 2) however, credit rating agencies (CRAs) reacted in a variety of ways, moving to post bail-in ratings for Eurozone banks that were more homogenous across CRAs than pre bail-in ratings. While the credit rating adjustments are rightly justified by the rating methodologies used, the convergence among CRAs suggests some degree of discretion in assigning the rating. These results are consistent with herding behaviour among CRAs.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132948629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elias Oikarinen, Steven C. Bourassa, Martin Hoesli, J. Engblom
We explore long-term patterns of the house price-income relationship across the 70 largest U.S. metropolitan areas. In line with a standard spatial equilibrium model, our empirical findings indicate that house price-income ratios are typically not stable even over the long run. In contrast, panel regression models that relate house prices to aggregate personal income and allow for regional heterogeneity yield stationary long-term relationships in most areas. The relationship between house prices and income varies significantly across locations, underscoring the importance of using estimation techniques that allow for spatial heterogeneity. The substantial differences across metropolitan areas are closely related to the price elasticity of housing supply.
{"title":"Revisiting Metropolitan House Price-Income Relationships","authors":"Elias Oikarinen, Steven C. Bourassa, Martin Hoesli, J. Engblom","doi":"10.2139/ssrn.3830512","DOIUrl":"https://doi.org/10.2139/ssrn.3830512","url":null,"abstract":"We explore long-term patterns of the house price-income relationship across the 70 largest U.S. metropolitan areas. In line with a standard spatial equilibrium model, our empirical findings indicate that house price-income ratios are typically not stable even over the long run. In contrast, panel regression models that relate house prices to aggregate personal income and allow for regional heterogeneity yield stationary long-term relationships in most areas. The relationship between house prices and income varies significantly across locations, underscoring the importance of using estimation techniques that allow for spatial heterogeneity. The substantial differences across metropolitan areas are closely related to the price elasticity of housing supply.","PeriodicalId":269529,"journal":{"name":"Swiss Finance Institute Research Paper Series","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122317921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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