Using historical data on post-war financial crises around the world, we show that crises are substantially predictable. The combination of rapid credit and asset price growth over the prior three years, whether in the nonfinancial business or the household sector, is associated with about a 40% probability of entering a financial crisis within the next three years. This compares with a roughly 7% probability in normal times, when neither credit nor asset price growth has been elevated. Our evidence cuts against the view that financial crises are unpredictable “bolts from the sky” and points toward the Kindleberger-Minsky view that crises are the byproduct of predictable, boom-bust credit cycles. The predictability we document favors macro-financial policies that “lean against the wind” of credit market booms. 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":"Predictable Financial Crises","authors":"R. Greenwood, S. Hanson, A. Shleifer, J. Sørensen","doi":"10.3386/w27396","DOIUrl":"https://doi.org/10.3386/w27396","url":null,"abstract":"Using historical data on post-war financial crises around the world, we show that crises are substantially predictable. The combination of rapid credit and asset price growth over the prior three years, whether in the nonfinancial business or the household sector, is associated with about a 40% probability of entering a financial crisis within the next three years. This compares with a roughly 7% probability in normal times, when neither credit nor asset price growth has been elevated. Our evidence cuts against the view that financial crises are unpredictable “bolts from the sky” and points toward the Kindleberger-Minsky view that crises are the byproduct of predictable, boom-bust credit cycles. The predictability we document favors macro-financial policies that “lean against the wind” of credit market booms. \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":123550,"journal":{"name":"Financial Crises eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123830292","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}
Pub Date : 2020-06-01DOI: 10.5089/9781513546759.001
Ippei Shibata
Using the U.S. Current Population Survey data, this paper compares the distributional impacts of the Pandemic Crisis and those of the Global Financial Crisis in terms of (i) worker characteristics, (ii) job characteristics–“social” (where individuals interact to consume goods), “teleworkable” (where individuals have the option of working at home), and “essential” jobs (which were not subject to government mandated shut-downs during the recent recession), and (iii) wage distributions. We find that young and less educated workers have always been affected more in recessions, while women and Hispanics were more severely affected during the Pandemic Recession. Surprisingly, teleworkable, social and essential jobs have been historically less cyclical. This historical acyclicality of teleworkable occupations is attributable to its higher share of skilled workers. Unlike during the Global Financial Crisis, however, employment in social industries fell more whereas employment in teleworkable and essential jobs fell less during the Pandemic Crisis. Lastly, during both recessions, workers at low-income earnings have suffered more than top-income earners, suggesting a significant distributional impact of the two recessions.
{"title":"The Distributional Impact of Recessions: The Global Financial Crisis and the Pandemic Recession","authors":"Ippei Shibata","doi":"10.5089/9781513546759.001","DOIUrl":"https://doi.org/10.5089/9781513546759.001","url":null,"abstract":"Using the U.S. Current Population Survey data, this paper compares the distributional impacts of the Pandemic Crisis and those of the Global Financial Crisis in terms of (i) worker characteristics, (ii) job characteristics–“social” (where individuals interact to consume goods), “teleworkable” (where individuals have the option of working at home), and “essential” jobs (which were not subject to government mandated shut-downs during the recent recession), and (iii) wage distributions. We find that young and less educated workers have always been affected more in recessions, while women and Hispanics were more severely affected during the Pandemic Recession. Surprisingly, teleworkable, social and essential jobs have been historically less cyclical. This historical acyclicality of teleworkable occupations is attributable to its higher share of skilled workers. Unlike during the Global Financial Crisis, however, employment in social industries fell more whereas employment in teleworkable and essential jobs fell less during the Pandemic Crisis. Lastly, during both recessions, workers at low-income earnings have suffered more than top-income earners, suggesting a significant distributional impact of the two recessions.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127667881","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}
Pub Date : 2020-06-01DOI: 10.5089/9781513545080.001
Ronald Heijmans, Froukelien Wendt
Banks and financial market infrastructures (FMIs) that are not able to fulfill their payment obligations can be a source of financial instability. This paper develops a composite risk indicator to evaluate the criticality of participants in a large value payment system network, combining liquidity risk and interconnections in one approach, and applying this to the TARGET2 payment system. Findings suggest that the most critical participants in TARGET2 are other payment systems, because of the size of underlying payment flows. Some banks may be critical, but this is mainly due to their interconnectedness with other TARGET2 participants. Central counterparties and central securities depositories are less critical. These findings can be used in financial stability analysis, and feed into central bank policies on payment system access, oversight, and crisis management.
{"title":"Measuring the Impact of a Failing Participant in Payment Systems","authors":"Ronald Heijmans, Froukelien Wendt","doi":"10.5089/9781513545080.001","DOIUrl":"https://doi.org/10.5089/9781513545080.001","url":null,"abstract":"Banks and financial market infrastructures (FMIs) that are not able to fulfill their payment\u0000obligations can be a source of financial instability. This paper develops a composite risk indicator to\u0000evaluate the criticality of participants in a large value payment system network, combining\u0000liquidity risk and interconnections in one approach, and applying this to the TARGET2\u0000payment system. Findings suggest that the most critical participants in TARGET2 are other\u0000payment systems, because of the size of underlying payment flows. Some banks may be\u0000critical, but this is mainly due to their interconnectedness with other TARGET2 participants.\u0000Central counterparties and central securities depositories are less critical. These findings can be\u0000used in financial stability analysis, and feed into central bank policies on payment system access,\u0000oversight, and crisis management.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129529378","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}
Business cycles are oscillations in the economy because of recessions and expansions. In this paper we investigate the oscillation of the gross domestic product as a result of its relations with the other main macroeconomic variables such as capital, consumption, and investment. There is a long-standing debate about chaos and non-linear dynamics in economy and even the usefulness of those concepts has been questioned. Stochastic modeling has proven to be able to simulate reality fairly well. However, a stochastic behavior implies that reality is about exogenous randomness, while a chaotic behavior means that reality is deterministic and non-linearities are endogenous. Here we compare an Ornstein-Uhlenbeck stochastic process with a Kaldor-Kalecki deterministic chaotic model to understand which one fits better real data. We show that our chaotic model is able to represent reality as well as the stochastic model taken into consideration. Furthermore, our model may reproduce an extreme event (black swans).
{"title":"Business Cycle Modeling Between Financial Crises and Black Swans: Ornstein-Uhlenbeck Stochastic Process versus Kaldor Deterministic Chaotic Model","authors":"G. Orlando, G. Zimatore","doi":"10.2139/ssrn.3851308","DOIUrl":"https://doi.org/10.2139/ssrn.3851308","url":null,"abstract":"Business cycles are oscillations in the economy because of recessions and expansions. In this paper we investigate the oscillation of the gross domestic product as a result of its relations with the other main macroeconomic variables such as capital, consumption, and investment. There is a long-standing debate about chaos and non-linear dynamics in economy and even the usefulness of those concepts has been questioned. Stochastic modeling has proven to be able to simulate reality fairly well. However, a stochastic behavior implies that reality is about exogenous randomness, while a chaotic behavior means that reality is deterministic and non-linearities are endogenous. Here we compare an Ornstein-Uhlenbeck stochastic process with a Kaldor-Kalecki deterministic chaotic model to understand which one fits better real data. We show that our chaotic model is able to represent reality as well as the stochastic model taken into consideration. Furthermore, our model may reproduce an extreme event (black swans).","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125519448","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}
Itay Goldstein, A. Kopytov, Lin Shen, Haotian Xiang
We study how heterogeneity in banks’ asset holdings affects fragility. In the model, banks face a risk of bank runs and have to liquidate long-term assets in a common market to repay runners. Liquidation prices are depressed when many banks sell their assets at the same time. When banks are homogeneous, their selling behaviors are synchronized, and bank runs are exacerbated. We show that differentiating banks to some extent enhances the stability of all banks, even those whose asset performance ends up being weaker. Our analyses provide new insights about the regulation of banking sector’s architecture and the design of government support during crises.
{"title":"Bank Heterogeneity and Financial Stability","authors":"Itay Goldstein, A. Kopytov, Lin Shen, Haotian Xiang","doi":"10.2139/ssrn.3683725","DOIUrl":"https://doi.org/10.2139/ssrn.3683725","url":null,"abstract":"We study how heterogeneity in banks’ asset holdings affects fragility. In the model, banks face a risk of bank runs and have to liquidate long-term assets in a common market to repay runners. Liquidation prices are depressed when many banks sell their assets at the same time. When banks are homogeneous, their selling behaviors are synchronized, and bank runs are exacerbated. We show that differentiating banks to some extent enhances the stability of all banks, even those whose asset performance ends up being weaker. Our analyses provide new insights about the regulation of banking sector’s architecture and the design of government support during crises.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117037004","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}
Wadima Al Mheiri, Maha Al-Mahmoud, F. Sultan, F. Jumà, Meera Al-Kaabi, H. Al-Alawi, Haitham Nobanee
Al Marai is a Saudi Arab based company that deals in food with its headquarters in Riyadh. This company was centralized with the sole aim of making its products high quality and of improved standard. The mission of Almarai is to provide quality and nutritious food that benefits the lives of consumers. It is the vision of Al Mari to become the first choice of consumers in the market of food and beverage products. The company gradually improved its finances and increased its market value. As a result, the shareholders increased to a high amount of 50 thousand shareholders for Almarai. Al Mari depends more on its inventories to meet the current obligations. Almarai is always at the risk of financial fluctuation because of its market competitors which can only be solved by increasing market shares of the company. The overall performance of Almarai is satisfactory but improvement is required to deal with the competitors.
Al Marai是一家总部位于沙特阿拉伯的食品公司，总部设在利雅得。这家公司集中经营的唯一目的是提高产品的质量和标准。Almarai的使命是提供优质和营养的食品，使消费者的生活受益。成为消费者在食品和饮料产品市场上的首选是Al Mari的愿景。公司逐渐改善了财务状况，增加了市场价值。因此，Almarai的股东数量增加到5万名。Al Mari更多地依靠其库存来履行目前的义务。由于市场竞争对手的存在，Almarai一直面临着财务波动的风险，只有通过增加公司的市场份额才能解决这个问题。Almarai的整体性能令人满意，但需要改进以应对竞争对手。
{"title":"Financial Analysis of Al Marai Company","authors":"Wadima Al Mheiri, Maha Al-Mahmoud, F. Sultan, F. Jumà, Meera Al-Kaabi, H. Al-Alawi, Haitham Nobanee","doi":"10.2139/ssrn.3594800","DOIUrl":"https://doi.org/10.2139/ssrn.3594800","url":null,"abstract":"Al Marai is a Saudi Arab based company that deals in food with its headquarters in Riyadh. This company was centralized with the sole aim of making its products high quality and of improved standard. The mission of Almarai is to provide quality and nutritious food that benefits the lives of consumers. It is the vision of Al Mari to become the first choice of consumers in the market of food and beverage products. The company gradually improved its finances and increased its market value. As a result, the shareholders increased to a high amount of 50 thousand shareholders for Almarai. Al Mari depends more on its inventories to meet the current obligations. Almarai is always at the risk of financial fluctuation because of its market competitors which can only be solved by increasing market shares of the company. The overall performance of Almarai is satisfactory but improvement is required to deal with the competitors.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127429382","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}
The paper proposes a practical alternative to a traditional theory of storage, which is difficult to apply to oil markets due to structural differences, such as low-price elasticities of demand and supply, and the dominant role of oil as an investment asset. We model futures time spreads as a derivative of the observable state variable, oil inventories. Inventories, normalized by the storage capacity, are assumed to follow a mean-reverting stochastic process. The boundary condition at the futures expiry is specified by a pair of Dirac delta functions which correspond to the events of default by the futures trader when either oil inventory or the storage capacity are no longer available. The model is calibrated to data for Cushing, Oklahoma, the delivery location for WTI futures, and is used to analyze the market dynamics that led to negative oil prices. We argue that while the limitation of storage capacity was the initial catalyst leading to the event, the actual episode of negative prices was the result of the financial squeeze in the futures market.
{"title":"A Stylized Model of the Oil Squeeze","authors":"Ilia Bouchouev","doi":"10.2139/ssrn.3781158","DOIUrl":"https://doi.org/10.2139/ssrn.3781158","url":null,"abstract":"The paper proposes a practical alternative to a traditional theory of storage, which is difficult to apply to oil markets due to structural differences, such as low-price elasticities of demand and supply, and the dominant role of oil as an investment asset. We model futures time spreads as a derivative of the observable state variable, oil inventories. Inventories, normalized by the storage capacity, are assumed to follow a mean-reverting stochastic process. The boundary condition at the futures expiry is specified by a pair of Dirac delta functions which correspond to the events of default by the futures trader when either oil inventory or the storage capacity are no longer available. The model is calibrated to data for Cushing, Oklahoma, the delivery location for WTI futures, and is used to analyze the market dynamics that led to negative oil prices. We argue that while the limitation of storage capacity was the initial catalyst leading to the event, the actual episode of negative prices was the result of the financial squeeze in the futures market.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127711866","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}
M. Barigozzi, M. Hallin, Stefano Soccorsi, R. von Sachs
Ripple effects in financial markets associated with crashes, systemic risk and contagion are characterized by non-trivial lead-lag dynamics which is crucial for understanding how crises spread and, therefore, central in risk management. In the spirit of Diebold and Yilmaz (2014), we investigate connectedness among financial firms via an analysis of impulse response functions of adjusted intraday log-ranges to market shocks involving network theory methods. Motivated by overwhelming evidence that the interdependence structure of financial markets is varying over time, we are basing that analysis on the so-called time-varying General Dynamic Factor Model proposed by Eichler et al. (2011), which extends to the locally stationary context the framework developed by Forni et al. (2000) under stationarity assumptions. The estimation methods in Eichler et al. (2011), however, present the major drawback of involving two-sided filters which make it impossible to recover impulse response functions. We therefore introduce a novel approach extending to the time-varying context the one-sided method of Forni et al. (2017). The resulting estimators of time-varying impulse response functions are shown to be consistent, hence can be used in the analysis of (time-varying) connectedness. Our empirical analysis on a large and strongly comoving panel of intraday price ranges of US stocks indicates that large increases in mid to long-run connectedness are associated with the main financial turmoils.
{"title":"Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness","authors":"M. Barigozzi, M. Hallin, Stefano Soccorsi, R. von Sachs","doi":"10.2139/ssrn.3329445","DOIUrl":"https://doi.org/10.2139/ssrn.3329445","url":null,"abstract":"Ripple effects in financial markets associated with crashes, systemic risk and contagion are characterized by non-trivial lead-lag dynamics which is crucial for understanding how crises spread and, therefore, central in risk management. In the spirit of Diebold and Yilmaz (2014), we investigate connectedness among financial firms via an analysis of impulse response functions of adjusted intraday log-ranges to market shocks involving network theory methods. Motivated by overwhelming evidence that the interdependence structure of financial markets is varying over time, we are basing that analysis on the so-called time-varying General Dynamic Factor Model proposed by Eichler et al. (2011), which extends to the locally stationary context the framework developed by Forni et al. (2000) under stationarity assumptions. The estimation methods in Eichler et al. (2011), however, present the major drawback of involving two-sided filters which make it impossible to recover impulse response functions. We therefore introduce a novel approach extending to the time-varying context the one-sided method of Forni et al. (2017). The resulting estimators of time-varying impulse response functions are shown to be consistent, hence can be used in the analysis of (time-varying) connectedness. Our empirical analysis on a large and strongly comoving panel of intraday price ranges of US stocks indicates that large increases in mid to long-run connectedness are associated with the main financial turmoils.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"467 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130691507","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}
Americans aged sixty or older stand to lose 153 to 222 days of life expectancy from contracting COVID-19. Over 90 percent of the U.S. population was under stay at home orders by April 2020. These social distancing measures to slow the spread of the SARS-CoV-2 or novel coronavirus have led to over 20 million new applications for unemployment benefits. Are these economic losses justified? We find the value of statistical lives lost (VSL) from an unconstrained spread of the virus which hypothetically infected 81 percent of the population would amount to $8 to $60 trillion.
{"title":"Estimating the Value of Statistical Life (VSL) Losses from COVID-19 Infections in the United States","authors":"Linus Wilson","doi":"10.2139/ssrn.3580414","DOIUrl":"https://doi.org/10.2139/ssrn.3580414","url":null,"abstract":"Americans aged sixty or older stand to lose 153 to 222 days of life expectancy from contracting COVID-19. Over 90 percent of the U.S. population was under stay at home orders by April 2020. These social distancing measures to slow the spread of the SARS-CoV-2 or novel coronavirus have led to over 20 million new applications for unemployment benefits. Are these economic losses justified? We find the value of statistical lives lost (VSL) from an unconstrained spread of the virus which hypothetically infected 81 percent of the population would amount to $8 to $60 trillion.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"379 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131995766","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}
Some financial supervisors worry that liquidity transformation within the “shadow banking” sector might threaten financial stability. For example, a mutual fund promising overnight liquidity based on illiquid assets (such as corporate bonds) runs the risk of needing to “fire sale” some assets, with potentially deleterious external effects. One protection against this possibility would be a broker-dealer sector that stands ready to stabilize prices by buying (or selling) for its own inventory. I evaluate the extent to which bond mutual funds’ flows are reflected in broker-dealers’ inventories. Although brokers generally trade in the same direction as the mutual funds, high-yield corporate bonds present an exception. Flows out of high-yield bond funds are associated with a significant increase in dealers’ high-yield bond inventories. These results provide further information about how various types of bond mutual funds handle liquidity demands.
{"title":"Bond Mutual Fund Flows, Fund Liquidity, and Broker-Dealer Inventories","authors":"M. Flannery","doi":"10.2139/ssrn.3623218","DOIUrl":"https://doi.org/10.2139/ssrn.3623218","url":null,"abstract":"Some financial supervisors worry that liquidity transformation within the “shadow banking” sector might threaten financial stability. For example, a mutual fund promising overnight liquidity based on illiquid assets (such as corporate bonds) runs the risk of needing to “fire sale” some assets, with potentially deleterious external effects. One protection against this possibility would be a broker-dealer sector that stands ready to stabilize prices by buying (or selling) for its own inventory. I evaluate the extent to which bond mutual funds’ flows are reflected in broker-dealers’ inventories. Although brokers generally trade in the same direction as the mutual funds, high-yield corporate bonds present an exception. Flows out of high-yield bond funds are associated with a significant increase in dealers’ high-yield bond inventories. These results provide further information about how various types of bond mutual funds handle liquidity demands.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131017398","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：