Research articles for the 2020-10-08
A big data based method for pass rates optimization in mathematics university lower division courses
arXiv
arXiv
In this paper an algorithm designed for large databases is introduced for the enhancement of pass rates in mathematical university lower division courses with several sections. Using integer programming techniques, the algorithm finds the optimal pairing of students and lecturers in order to maximize the success chances of the students' body. The students-lecturer success probability is computed according to their corresponding profiles stored in the data bases.
Agent Based Computational Model Aided Approach to Improvise the Inequality-Adjusted Human Development Index (IHDI) for Greater Parity in Real Scenario Assessments
arXiv
arXiv
To design, evaluate and tune policies for all-inclusive human development, the primary requisite is to assess the true state of affairs of the society. Statistical indices like GDP, Gini Coefficients have been developed to accomplish the evaluation of the socio-economic systems. They have remained prevalent in the conventional economic theories but little do they have in the offing regarding true well-being and development of humans. Human Development Index (HDI) and thereafter Inequality-adjusted Human Development Index (IHDI) has been the path changing composite-index having the focus on human development. However, even though its fundamental philosophy has an all-inclusive human development focus, the composite-indices appear to be unable to grasp the actual assessment in several scenarios. This happens due to the dynamic non-linearity of social-systems where superposition principle cannot be applied between all of its inputs and outputs of the system as the system's own attributes get altered upon each input. We would discuss the apparent shortcomings and probable refinement of the existing index using an agent based computational system model approach.
An Augmented Macroeconomic Linear Factor Model of South African Industrial Sector Returns
SSRN
This study investigates the impact of the macroeconomic environment on South African industrial sector returns. Using standardized coefficients, we find that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy. We also find that specifications that comprise only macroeconomic factors and proxies for omitted factors in the form of residual market factors are likely to be under-specified. A factor analytic augmentation that accounts for omitted systematic factors can be incorporated to arrive at a specification that is free of omitted factors.
SSRN
This study investigates the impact of the macroeconomic environment on South African industrial sector returns. Using standardized coefficients, we find that global influences are the most important drivers of returns and that industrial sectors are highly integrated with the global economy. We also find that specifications that comprise only macroeconomic factors and proxies for omitted factors in the form of residual market factors are likely to be under-specified. A factor analytic augmentation that accounts for omitted systematic factors can be incorporated to arrive at a specification that is free of omitted factors.
Analysis of Systematic Risk around Firm-specific News in an Emerging Market using High Frequency Data
SSRN
We investigate whether the daily betas of individual stocks vary with the release of firm-specific news in an emerging market. Using intraday prices of all stocks traded on the Borsa Istanbul, Turkey over the period 2005-2013, we find evidence that average market betas increase significantly from two weeks before the earning announcement day, and then revert to their average levels two weeks after the announcement. The increase in betas is greater for larger, positive surprise earnings announcements than for smaller, negative news. The results are consistent with features of the learning model of Patton and Verardo (2012) but not with a number of their empirical results.
SSRN
We investigate whether the daily betas of individual stocks vary with the release of firm-specific news in an emerging market. Using intraday prices of all stocks traded on the Borsa Istanbul, Turkey over the period 2005-2013, we find evidence that average market betas increase significantly from two weeks before the earning announcement day, and then revert to their average levels two weeks after the announcement. The increase in betas is greater for larger, positive surprise earnings announcements than for smaller, negative news. The results are consistent with features of the learning model of Patton and Verardo (2012) but not with a number of their empirical results.
Are Third-Party Fundamental Valuations Relevant in Public-Company Takeovers?
SSRN
In U.S. M&A, target directors are effectively required to consider third-party financial analyses and valuations, summarized in a “fairness opinion,†before accepting a takeover offer. Critics argue that these valuations are not relevant for public companies, which can assess the desirability of the deal in terms of the market premium. I identify conditions under which a target’s pre-deal market price will not provide directors with the information required to assess a takeover offer, and test for whether fairness valuations provide incrementally relevant information. I find that they can signal ex ante fundamental mis-pricing, can impound expected transaction synergies, and can unravel abnormal run-ups in the target’s stock price prior to the public announcement date. I also find that the providers bias their valuations to cater to their clients. This suggests that third-party fundamental valuation has a plausible role as a supplement to market signals in public-company M&A, though the current process has flaws in its design.
SSRN
In U.S. M&A, target directors are effectively required to consider third-party financial analyses and valuations, summarized in a “fairness opinion,†before accepting a takeover offer. Critics argue that these valuations are not relevant for public companies, which can assess the desirability of the deal in terms of the market premium. I identify conditions under which a target’s pre-deal market price will not provide directors with the information required to assess a takeover offer, and test for whether fairness valuations provide incrementally relevant information. I find that they can signal ex ante fundamental mis-pricing, can impound expected transaction synergies, and can unravel abnormal run-ups in the target’s stock price prior to the public announcement date. I also find that the providers bias their valuations to cater to their clients. This suggests that third-party fundamental valuation has a plausible role as a supplement to market signals in public-company M&A, though the current process has flaws in its design.
Boosting access to credit and ensuring financial inclusion for all in Costa Rica
RePEC
Having access to credit is essential for households to address the volatility of their personal finances over time and for firms to fund their investments. Accessing financial services at affordable cost on the other hand, is crucial to ensure financial security of all economic units. Despite recent improvements, there are still large financial inclusion disparities in Costa Rica, notably across regions, by gender, and size of firms. This paper discusses policy reforms that would reduce these disparities. Some of the key policy priorities are to improve transparency by strengthening the credit registry and allocating the development banking credit more effectively. Enhancing financial literacy could help avoid excessive consumer indebtedness. Technological innovation would also help Costa Rica: granting FinTech start-ups direct and full access to the state-of-the-art electronic payments system would increase competition, reduce transactions costs and ensure financial inclusion for all.
RePEC
Having access to credit is essential for households to address the volatility of their personal finances over time and for firms to fund their investments. Accessing financial services at affordable cost on the other hand, is crucial to ensure financial security of all economic units. Despite recent improvements, there are still large financial inclusion disparities in Costa Rica, notably across regions, by gender, and size of firms. This paper discusses policy reforms that would reduce these disparities. Some of the key policy priorities are to improve transparency by strengthening the credit registry and allocating the development banking credit more effectively. Enhancing financial literacy could help avoid excessive consumer indebtedness. Technological innovation would also help Costa Rica: granting FinTech start-ups direct and full access to the state-of-the-art electronic payments system would increase competition, reduce transactions costs and ensure financial inclusion for all.
Commercialization of Patents and External Financing during the R&D-Phase
SSRN
Using a unique database on individual Swedish patents, a survival model estimates how different factors influence the time it takes until commercialization starts. To the best of my knowledge, such an analysis has not been undertaken before. For external financing of patent projects and small technology-based firms, Sweden has during long time relied on government support rather than private venture capital firms. The empirical results show that the larger share of the patent-owners’ costs during the R&D-phase that are covered by government financial support, the longer time it takes until the patents are commercialized. It seems like the government financing creates a pool of patents with bad perspectives of commercialization. The reasons to the bad performance are: 1) the design of the government loans, where the patent owner can escape from paying back the loan if the project failures; and 2) the competence and incentives of the government institutions, which are not profit maximizing. A policy implication is therefore that the government should either change the conditions of the loans or, preferably, stop acting as a venture capital firm. The government should instead facilitate private solutions and the growth of private venture capital firms.
SSRN
Using a unique database on individual Swedish patents, a survival model estimates how different factors influence the time it takes until commercialization starts. To the best of my knowledge, such an analysis has not been undertaken before. For external financing of patent projects and small technology-based firms, Sweden has during long time relied on government support rather than private venture capital firms. The empirical results show that the larger share of the patent-owners’ costs during the R&D-phase that are covered by government financial support, the longer time it takes until the patents are commercialized. It seems like the government financing creates a pool of patents with bad perspectives of commercialization. The reasons to the bad performance are: 1) the design of the government loans, where the patent owner can escape from paying back the loan if the project failures; and 2) the competence and incentives of the government institutions, which are not profit maximizing. A policy implication is therefore that the government should either change the conditions of the loans or, preferably, stop acting as a venture capital firm. The government should instead facilitate private solutions and the growth of private venture capital firms.
Convolutional Neural Network Case Studies: (1) Anomalies in Mortality Rates (2) Image Recognition
SSRN
We provide a general introduction to convolutional neural networks (CNNs) in this tutorial. CNNs are particularly well suited to find common spatial structure in images or time series. As an insurance related example for life & health insurance we illustrate how to use a CNN to detect anomalies in mortality rates taken from the Human Mortality Database (HMD); the anomalies are caused by migration between countries and other errors. As a second example, we study a CNN to classify images of handwritten digits taken from one of the most widely used benchmark datasets, the Modified National Institute of Standards and Technology (MNIST) dataset. Our aim is to explore and discuss the building blocks and the properties of these CNNs, and we showcase their use.
SSRN
We provide a general introduction to convolutional neural networks (CNNs) in this tutorial. CNNs are particularly well suited to find common spatial structure in images or time series. As an insurance related example for life & health insurance we illustrate how to use a CNN to detect anomalies in mortality rates taken from the Human Mortality Database (HMD); the anomalies are caused by migration between countries and other errors. As a second example, we study a CNN to classify images of handwritten digits taken from one of the most widely used benchmark datasets, the Modified National Institute of Standards and Technology (MNIST) dataset. Our aim is to explore and discuss the building blocks and the properties of these CNNs, and we showcase their use.
Criteria-Based Assessment of Financial Ratios Based on Hierarchical Cluster Analysis
SSRN
The article is devoted to the problems of the financial statements analysis, using the method of financial ratios. The choice of the main financial ratios is made having in mind peculiarities of the Russian Federation extractive industries. The recommended standard values of financial ratios are received branch-wise, using the method of hierarchical cluster analysis.
SSRN
The article is devoted to the problems of the financial statements analysis, using the method of financial ratios. The choice of the main financial ratios is made having in mind peculiarities of the Russian Federation extractive industries. The recommended standard values of financial ratios are received branch-wise, using the method of hierarchical cluster analysis.
Crowding Out Bank Loans: Liquidity-Driven Bond Issuance
SSRN
According to conventional wisdom, banks play a special role in providing liquidity in bad times, while capital markets are used to fund investment in good times. Using micro-data on corporate balance sheets following the COVID-19 shock, we provide evidence that instead, the corporate bond market is central to firms' access to liquidity, crowding out bank loans even when the banking sector is healthy. We first show that, contrary to good times, bond issuance is used to increase holdings of liquid assets rather than for real investment. Second, most issuers, including many riskier "high-yield" firms, prefer issuing bonds to borrowing from their bank. Over 40% of bond issuers leave their credit line untouched in 2020Q1. Moreover, a large share of bond issuance is used to repay existing bank loans. This liquidity-driven bond issuance questions the comparative advantage of banks in liquidity provision, and suggests that the V-shaped recovery of bond markets, propelled by the Federal Reserve, is unlikely to lead to a V-shaped recovery in real activity.
SSRN
According to conventional wisdom, banks play a special role in providing liquidity in bad times, while capital markets are used to fund investment in good times. Using micro-data on corporate balance sheets following the COVID-19 shock, we provide evidence that instead, the corporate bond market is central to firms' access to liquidity, crowding out bank loans even when the banking sector is healthy. We first show that, contrary to good times, bond issuance is used to increase holdings of liquid assets rather than for real investment. Second, most issuers, including many riskier "high-yield" firms, prefer issuing bonds to borrowing from their bank. Over 40% of bond issuers leave their credit line untouched in 2020Q1. Moreover, a large share of bond issuance is used to repay existing bank loans. This liquidity-driven bond issuance questions the comparative advantage of banks in liquidity provision, and suggests that the V-shaped recovery of bond markets, propelled by the Federal Reserve, is unlikely to lead to a V-shaped recovery in real activity.
Dead Man's Switch: Making Options Markets Safer with Active Quote Protection
SSRN
Market makers play a central role in options markets, where they account for 99.9% of open orders. Providing liquidity at this scale is only possible because of quote protection (QP) mechanisms that limit how quickly open orders can be filled â€" say, in the event of a market crash or system failure. But existing QP mechanisms are severely flawed: they are time-window based, which limits the kinds of risk that can be mitigated; they lack a “dead man’s switch,†in that unwanted orders can be implicitly approved via inaction; and they vary subtly across exchanges. As a result, market makers are likely to quote wider spreads, quote less, or step back from the market entirely. Here, we propose ActiveQP, a simpler, safer standard for quote protection based on active two-way communication.
SSRN
Market makers play a central role in options markets, where they account for 99.9% of open orders. Providing liquidity at this scale is only possible because of quote protection (QP) mechanisms that limit how quickly open orders can be filled â€" say, in the event of a market crash or system failure. But existing QP mechanisms are severely flawed: they are time-window based, which limits the kinds of risk that can be mitigated; they lack a “dead man’s switch,†in that unwanted orders can be implicitly approved via inaction; and they vary subtly across exchanges. As a result, market makers are likely to quote wider spreads, quote less, or step back from the market entirely. Here, we propose ActiveQP, a simpler, safer standard for quote protection based on active two-way communication.
Effectiveness of Gender Regulations on Boards of Directors: The Role of the Institutional Environment
SSRN
This article analyses the effectiveness of the different regulations promoting gender diversity on boards of directors and how formal and informal institutional factors influence the relationship between regulations and the presence of female directors on boards. It describes the gender diversity regulations implemented in Europe, and goes on to analyse, for a group of companies forming part of the STOXX Europe 600 index and for the period 2004-2018: i) how the presence of women on boards of directors has evolved in each of the countries represented in the sample; ii) the impact of Corporate Governance Codes with recommendations on gender diversity and gender quotas, with and without sanctions, on the presence of women on boards of directors and board committees, and iii) how formal and informal institutional factors, such as the quality and transparency of governance and cultural aspects, influence the effectiveness of regulations. Lastly, we look at the regulations and institutional environment in Spain. The results show the importance of formal and informal institutions as key instruments to the effectiveness of gender diversity regulations and suggest a number of factors that should be considered when designing future actions and policies in this area.
SSRN
This article analyses the effectiveness of the different regulations promoting gender diversity on boards of directors and how formal and informal institutional factors influence the relationship between regulations and the presence of female directors on boards. It describes the gender diversity regulations implemented in Europe, and goes on to analyse, for a group of companies forming part of the STOXX Europe 600 index and for the period 2004-2018: i) how the presence of women on boards of directors has evolved in each of the countries represented in the sample; ii) the impact of Corporate Governance Codes with recommendations on gender diversity and gender quotas, with and without sanctions, on the presence of women on boards of directors and board committees, and iii) how formal and informal institutional factors, such as the quality and transparency of governance and cultural aspects, influence the effectiveness of regulations. Lastly, we look at the regulations and institutional environment in Spain. The results show the importance of formal and informal institutions as key instruments to the effectiveness of gender diversity regulations and suggest a number of factors that should be considered when designing future actions and policies in this area.
Financial Integration and the Correlation between International Debt and Equity Flows
SSRN
This paper empirically documents a number of stylized facts of international debt and equity flows and theoretically investigates the roles of these two financial assets in international risk sharing. Using a data set of debt and equity flows since 1970 for a sample of 104 countries, I find that international debt and equity flows have become increasingly volatile in the past decades due to the increased world financial integration. In addition, there is a negative correlation between debt and equity flows and such negative correlation has become stronger over time. Using a simple two-country model with international capital flows, I show that negatively correlated debt and equity flows arise as two countries trade equity assets and bond to hedge against income uncertainties. The numerical analysis shows that the model can replicate the dynamics of the volatilities and correlation between debt and equity flows in the data as the financial integration progresses.
SSRN
This paper empirically documents a number of stylized facts of international debt and equity flows and theoretically investigates the roles of these two financial assets in international risk sharing. Using a data set of debt and equity flows since 1970 for a sample of 104 countries, I find that international debt and equity flows have become increasingly volatile in the past decades due to the increased world financial integration. In addition, there is a negative correlation between debt and equity flows and such negative correlation has become stronger over time. Using a simple two-country model with international capital flows, I show that negatively correlated debt and equity flows arise as two countries trade equity assets and bond to hedge against income uncertainties. The numerical analysis shows that the model can replicate the dynamics of the volatilities and correlation between debt and equity flows in the data as the financial integration progresses.
Financial Returns to Household Inventory Management
SSRN
Households tend to hold substantial amounts of non-financial assets in the form of inventory. Households can obtain significant financial returns from strategic shopping and optimally managing these inventories of consumer goods. In addition, they choose to maintain liquid savings - household working capital - not just for precautionary motives but also to support this inventory management. We demonstrate that households earn high returns from inventory management at low levels of inventory, though returns decline rapidly as inventory levels increase. We provide evidence using scanner and survey data that supports this conclusion. High returns from inventory management that are declining in wealth offer a new rationale for poorer households not to participate in risky financial markets, while wealthier households invest in both financial assets and working capital.
SSRN
Households tend to hold substantial amounts of non-financial assets in the form of inventory. Households can obtain significant financial returns from strategic shopping and optimally managing these inventories of consumer goods. In addition, they choose to maintain liquid savings - household working capital - not just for precautionary motives but also to support this inventory management. We demonstrate that households earn high returns from inventory management at low levels of inventory, though returns decline rapidly as inventory levels increase. We provide evidence using scanner and survey data that supports this conclusion. High returns from inventory management that are declining in wealth offer a new rationale for poorer households not to participate in risky financial markets, while wealthier households invest in both financial assets and working capital.
From Macroeconomic Shocks to Credit Spreads
SSRN
We estimate the response of corporate bond credit spreads to three exogenous shocks: oil supply, investment-specific technology, and government spending. Credit spreads respond significantly to these macroeconomic shocks; the response is similar in magnitude, opposite in sign, and with a slight lag relative to the response of macroeconomic activity. We argue that the lagged counter-cyclical response of credit spreads is to a large extent driven by time-varying credit risk premia, which translates into significant predictability in corporate bond returns. Standard proxies for equity risk premia exhibit similar responses, which provides external validity to this argument. Our findings contribute to understanding the joint dynamics of credit markets and the macro-economy and, more generally, how macroeconomic shocks propagate in financial markets.
SSRN
We estimate the response of corporate bond credit spreads to three exogenous shocks: oil supply, investment-specific technology, and government spending. Credit spreads respond significantly to these macroeconomic shocks; the response is similar in magnitude, opposite in sign, and with a slight lag relative to the response of macroeconomic activity. We argue that the lagged counter-cyclical response of credit spreads is to a large extent driven by time-varying credit risk premia, which translates into significant predictability in corporate bond returns. Standard proxies for equity risk premia exhibit similar responses, which provides external validity to this argument. Our findings contribute to understanding the joint dynamics of credit markets and the macro-economy and, more generally, how macroeconomic shocks propagate in financial markets.
Green Bonds as a Tool for Sustainable Development on Emerging Markets
SSRN
The primary goal of the paper is to determine the impact of new investment tools on the development of global markets. In this regard, environmental finance is a new and powerful means of stimulating economic growth in emerging financial markets. Environmental finance offer more than just access to capital. They can be a valuable tool for issuers to communicate their priorities to investors. Bonds can send important signals to the market about sustainability strategies; demonstrate proactive risk management, and long-term thinking, while offering a financing and communications tool that is tied to measurable results. The study was carried out by Environmental Finance's database. Based on the empirical data, the results on volumes, countries, exchanges, currencies and other indicators, which characterize the development of green bonds, were presented in study. The study used methods of comparison and grouping method, as well as common-size analysis. This paper makes these contributions: 1) presents the impact of environmental finance on the economic indicators of some countries; 2) provides, that significant growth of investments in environmental finance is associated with legislative initiatives of the leading countries in the global financial market; 3) estimates the advantages of green bonds and lists the lost benefits for the Russian economy; 4) presents, that a significant increase in investments in green bonds is related with the legislative initiative in the country.
SSRN
The primary goal of the paper is to determine the impact of new investment tools on the development of global markets. In this regard, environmental finance is a new and powerful means of stimulating economic growth in emerging financial markets. Environmental finance offer more than just access to capital. They can be a valuable tool for issuers to communicate their priorities to investors. Bonds can send important signals to the market about sustainability strategies; demonstrate proactive risk management, and long-term thinking, while offering a financing and communications tool that is tied to measurable results. The study was carried out by Environmental Finance's database. Based on the empirical data, the results on volumes, countries, exchanges, currencies and other indicators, which characterize the development of green bonds, were presented in study. The study used methods of comparison and grouping method, as well as common-size analysis. This paper makes these contributions: 1) presents the impact of environmental finance on the economic indicators of some countries; 2) provides, that significant growth of investments in environmental finance is associated with legislative initiatives of the leading countries in the global financial market; 3) estimates the advantages of green bonds and lists the lost benefits for the Russian economy; 4) presents, that a significant increase in investments in green bonds is related with the legislative initiative in the country.
Hierarchical PCA and Modeling Asset Correlations
arXiv
arXiv
Modeling cross-sectional correlations between thousands of stocks, across countries and industries, can be challenging. In this paper, we demonstrate the advantages of using Hierarchical Principal Component Analysis (HPCA) over the classic PCA. We also introduce a statistical clustering algorithm for identifying of homogeneous clusters of stocks, or "synthetic sectors". We apply these methods to study cross-sectional correlations in the US, Europe, China, and Emerging Markets.
Hometown Lending
SSRN
Banks open more branches and make more lending near their Chief Executive Officers’ (CEOs) childhood hometowns. The effects are stronger among information-ally opaque borrowers and among CEOs who spend more time in their childhood hometowns. Furthermore, loans originated near CEOs’ hometowns contain more soft information and have lower ex-post default rates, implying that hometown loans are more informed. Hometown lending does not affect aggregate bank outcomes, suggesting that credit is being reallocated from regions located farther away to regions proximate to bank CEOs’ hometowns.
SSRN
Banks open more branches and make more lending near their Chief Executive Officers’ (CEOs) childhood hometowns. The effects are stronger among information-ally opaque borrowers and among CEOs who spend more time in their childhood hometowns. Furthermore, loans originated near CEOs’ hometowns contain more soft information and have lower ex-post default rates, implying that hometown loans are more informed. Hometown lending does not affect aggregate bank outcomes, suggesting that credit is being reallocated from regions located farther away to regions proximate to bank CEOs’ hometowns.
How did Retail Investors Respond to the COVID-19 Pandemic? The Effect of Robinhood Brokerage Customers on Market Quality
SSRN
Using data on stocks held by individual investors at retail brokerage firm Robinhood, we document that these investors are actively engaged in both momentum and contrarian trading strategies. In response to the increased volatility and uncertainty in financial markets due to the COVID-19 pandemic in March 2020, we find that retail investors reduce momentum trading and increase contrarian trading activity during the initial phase of this crisis. We also find that the impact of Robinhood investors on market quality varied depending on market conditions, coinciding with better market quality during less-stressful periods and worse market quality during the early weeks of the pandemic in the U.S.
SSRN
Using data on stocks held by individual investors at retail brokerage firm Robinhood, we document that these investors are actively engaged in both momentum and contrarian trading strategies. In response to the increased volatility and uncertainty in financial markets due to the COVID-19 pandemic in March 2020, we find that retail investors reduce momentum trading and increase contrarian trading activity during the initial phase of this crisis. We also find that the impact of Robinhood investors on market quality varied depending on market conditions, coinciding with better market quality during less-stressful periods and worse market quality during the early weeks of the pandemic in the U.S.
Identifying Information Increases in Public Credit Registries
SSRN
Academics and policy research strives to understand the role of public credit registries (PCRs) and information sharing in the development of financial markets. To provide insights into this question, the empirical literature exploits reforms that establish or expand credit registries. Thus, it is crucial to identify the date and the nature of these reforms and events. This endeavor, however, is not straightforward, and prior work does not offer a transparent approach. This note outlines a tractable methodology that identifies PCR-related events based on relevant legislation and supervisory disclosures in Europe. We also verify the data in previously available datasets for a global sample.
SSRN
Academics and policy research strives to understand the role of public credit registries (PCRs) and information sharing in the development of financial markets. To provide insights into this question, the empirical literature exploits reforms that establish or expand credit registries. Thus, it is crucial to identify the date and the nature of these reforms and events. This endeavor, however, is not straightforward, and prior work does not offer a transparent approach. This note outlines a tractable methodology that identifies PCR-related events based on relevant legislation and supervisory disclosures in Europe. We also verify the data in previously available datasets for a global sample.
Identifying Statistical Arbitrage in Interest Rate Markets: A Genetic Algorithm Approach
SSRN
In this paper a multidimensional term structure model is used to find statistical arbitrage opportunities in the interest rates derivatives market. The implied volatility of the model is calibrated by using a genetic algorithm optimization method. Two different options over the same underlying interest rate asset are tested, using data from a weak efficient economy market. The results show that there is no systematic mis-pricing between these two options, but temporary arbitrage opportunities perceptible to the average informed trader are possible.
SSRN
In this paper a multidimensional term structure model is used to find statistical arbitrage opportunities in the interest rates derivatives market. The implied volatility of the model is calibrated by using a genetic algorithm optimization method. Two different options over the same underlying interest rate asset are tested, using data from a weak efficient economy market. The results show that there is no systematic mis-pricing between these two options, but temporary arbitrage opportunities perceptible to the average informed trader are possible.
Innovation Performance and Government Financing
SSRN
External financing is important when inventors and small technology-based firms commercialize their inventions. However, the private information of inventors about the quality of their products causes information asymmetries and moral hazard problems. To help compensate for potentially non-existing capital markets, the Swedish Government has intervened by offering loans with different terms to firms and inventors. This paper analyzes the association between various forms of external financing and performance in profit-terms when patents are commercialized. The empirical work is based on a patent survey sent to Swedish inventors and small firms, where the response rate is 80 %. The estimations show that projects with soft government financing in the R&D-phase have a significantly inferior performance compared to projects without such financing, whereas those receiving government loans on commercial terms perform as the average. Distinguishing between governmental financing alternatives with different terms makes it possible to draw the conclusion that government failure primarily depends on bad financing terms, rather than bad project selection. A policy implication is therefore that public loans should be granted on commercial terms already in the R&D-phase of projects.
SSRN
External financing is important when inventors and small technology-based firms commercialize their inventions. However, the private information of inventors about the quality of their products causes information asymmetries and moral hazard problems. To help compensate for potentially non-existing capital markets, the Swedish Government has intervened by offering loans with different terms to firms and inventors. This paper analyzes the association between various forms of external financing and performance in profit-terms when patents are commercialized. The empirical work is based on a patent survey sent to Swedish inventors and small firms, where the response rate is 80 %. The estimations show that projects with soft government financing in the R&D-phase have a significantly inferior performance compared to projects without such financing, whereas those receiving government loans on commercial terms perform as the average. Distinguishing between governmental financing alternatives with different terms makes it possible to draw the conclusion that government failure primarily depends on bad financing terms, rather than bad project selection. A policy implication is therefore that public loans should be granted on commercial terms already in the R&D-phase of projects.
Insurance With Heterogeneous Preferences
SSRN
This paper studies an optimal insurance problem with finitely many potential policyholders. A monopolistic, risk-neutral insurer offers an insurance contract, and exponential utility maximizing individuals accept the offer or not. We allow for heterogeneity in the preferences of the individuals, while the insurer cannot discriminate in the insurance premium. We show that it is optimal for the insurer to offer only a full insurance contract, and the price optimization problem is reduced to a discrete problem, where the premium is an indifference premium for one individual in the market. Moreover, if individuals can self-select their insurance coverage given the market premium rate, then we find that partial insurance is generally optimal. Since the risk aversion parameters of individuals is generally unobserved, we also present a simulation-based framework. We show its convergence, and provide numerical examples.
SSRN
This paper studies an optimal insurance problem with finitely many potential policyholders. A monopolistic, risk-neutral insurer offers an insurance contract, and exponential utility maximizing individuals accept the offer or not. We allow for heterogeneity in the preferences of the individuals, while the insurer cannot discriminate in the insurance premium. We show that it is optimal for the insurer to offer only a full insurance contract, and the price optimization problem is reduced to a discrete problem, where the premium is an indifference premium for one individual in the market. Moreover, if individuals can self-select their insurance coverage given the market premium rate, then we find that partial insurance is generally optimal. Since the risk aversion parameters of individuals is generally unobserved, we also present a simulation-based framework. We show its convergence, and provide numerical examples.
Kelly Criterion under Model Uncertainty
SSRN
The optimal growth of a wealth process toward a goal is studied under ambiguous markets with first- and second-order moment uncertainties relating to stock returns. Optimal strategies and value functions are solved explicitly. A verification theorem is proved to show that the results solve the original stochastic control problem. Quantitative analyses of the investment strategies indicate that a rational individual with ambiguity aversion reduces market participation when return and volatility are uncorrelated, while there is an exception for synchronous return and volatility. The welfare of shorting a discounted reward is computed, which demonstrates that in an ambiguous pricing economy, investors can generate a positive premium via appropriate asset allocations.
SSRN
The optimal growth of a wealth process toward a goal is studied under ambiguous markets with first- and second-order moment uncertainties relating to stock returns. Optimal strategies and value functions are solved explicitly. A verification theorem is proved to show that the results solve the original stochastic control problem. Quantitative analyses of the investment strategies indicate that a rational individual with ambiguity aversion reduces market participation when return and volatility are uncorrelated, while there is an exception for synchronous return and volatility. The welfare of shorting a discounted reward is computed, which demonstrates that in an ambiguous pricing economy, investors can generate a positive premium via appropriate asset allocations.
On Line Financial Trading & Stock Market Simulations
SSRN
The worldwide computer games market, worth around £969m in sales in the UK alone, is highly competitive and dangerously risky. Companies that get it right scoop the pot but just a few wrong moves spells disaster. “Close but no cigar†is not an option â€" games typically take two years and around £1m to develop but 10% of games take 90% of revenues.Technology drives success and the growth of processing power on the Internet is beginning to change the computer games marketplace. Games can now be released in beta-test on the Web, bug-tested and customer reviewed before full commercial launch leading to speedier development and testing of ideas without blowing the whole company on a gamble. This aids diversification of genres. Although traditional action/adventure/flight simulations still account for most of the market, the popularity of “God†games such as SimCity and The Sims shows a willingness for customers to try out other ideas if the underlying premise is attractive and the presentation is good.Customers are also becoming less and less keen to spend money on a game, usually around £35 to £40 per CD-ROM, before trying it out first. This is leading to new business models. For example, Freeloader.com, officially launched 30 May 2000, offers users the ability to download the first level of popular computer games for free. The next level can be downloaded once users have built up enough credits by clicking on the site’s advertising.The Internet is also opening up the marketplace to new competitors as online games can be developed at a fraction of the cost of PC-based packages. Not only for other games companies but anyone who wants to enhance their existing site with a fun or educational add-on.Most of all, the Internet offers true multiplayer interaction. This creates the opportunity for games where players no longer purely to pre-determined or external events outside their control but by playing the game, actively influence how it proceeds.Internet online gaming is still in its infancy, but the potential is substantial.
SSRN
The worldwide computer games market, worth around £969m in sales in the UK alone, is highly competitive and dangerously risky. Companies that get it right scoop the pot but just a few wrong moves spells disaster. “Close but no cigar†is not an option â€" games typically take two years and around £1m to develop but 10% of games take 90% of revenues.Technology drives success and the growth of processing power on the Internet is beginning to change the computer games marketplace. Games can now be released in beta-test on the Web, bug-tested and customer reviewed before full commercial launch leading to speedier development and testing of ideas without blowing the whole company on a gamble. This aids diversification of genres. Although traditional action/adventure/flight simulations still account for most of the market, the popularity of “God†games such as SimCity and The Sims shows a willingness for customers to try out other ideas if the underlying premise is attractive and the presentation is good.Customers are also becoming less and less keen to spend money on a game, usually around £35 to £40 per CD-ROM, before trying it out first. This is leading to new business models. For example, Freeloader.com, officially launched 30 May 2000, offers users the ability to download the first level of popular computer games for free. The next level can be downloaded once users have built up enough credits by clicking on the site’s advertising.The Internet is also opening up the marketplace to new competitors as online games can be developed at a fraction of the cost of PC-based packages. Not only for other games companies but anyone who wants to enhance their existing site with a fun or educational add-on.Most of all, the Internet offers true multiplayer interaction. This creates the opportunity for games where players no longer purely to pre-determined or external events outside their control but by playing the game, actively influence how it proceeds.Internet online gaming is still in its infancy, but the potential is substantial.
On the solution uniqueness in portfolio optimization and risk analysis
arXiv
arXiv
We consider the issue of solution uniqueness for portfolio optimization problem and its inverse for asset returns with a finite number of possible scenarios. The risk is assessed by deviation measures introduced by [Rockafellar et al., Mathematical Programming, Ser. B, 108 (2006), pp. 515-540] instead of variance as in the Markowitz optimization problem. We prove that in general one can expect uniqueness neither in forward nor in inverse problems. We discuss consequences of that non-uniqueness for several problems in risk analysis and portfolio optimization, including capital allocation, risk sharing, cooperative investment, and the Black-Litterman methodology. In all cases, the issue with non-uniqueness is closely related to the fact that subgradient of a convex function is non-unique at the points of non-differentiability. We suggest methodology to resolve this issue by identifying a unique "special" subgradient satisfying some natural axioms. This "special" subgradient happens to be the Stainer point of the subdifferential set.
Opportunities For Standards In Insurance
SSRN
Following the publication in November 2013 of a joint BSI, CISI and Long Finance report titled “Backing Market Forces: How to Make Voluntary Standards Markets Work for Financial Services Regulationâ€, BSI asked Z/Yen Group and Long Finance to assist in identifying opportunities for voluntary standards development in selected sectors of financial services, starting with insurance and investment & asset management.These two industry studies are the outcomes of this research project conducted between June and October 2014. The studies analyse the needs, gaps and opportunities for voluntary standards development in insurance and in investment & asset management.
SSRN
Following the publication in November 2013 of a joint BSI, CISI and Long Finance report titled “Backing Market Forces: How to Make Voluntary Standards Markets Work for Financial Services Regulationâ€, BSI asked Z/Yen Group and Long Finance to assist in identifying opportunities for voluntary standards development in selected sectors of financial services, starting with insurance and investment & asset management.These two industry studies are the outcomes of this research project conducted between June and October 2014. The studies analyse the needs, gaps and opportunities for voluntary standards development in insurance and in investment & asset management.
Opportunities For Standards In Investment & Asset Management
SSRN
Following the publication in November 2013 of a joint BSI, CISI and Long Finance report titled “Backing Market Forces: How to Make Voluntary Standards Markets Work for Financial Services Regulationâ€, BSI asked Z/Yen Group and Long Finance to assist in identifying opportunities for voluntary standards development in selected sectors of financial services, starting with insurance and investment & asset management.These two industry studies are the outcomes of this research project conducted between June and October 2014. The studies analyse the needs, gaps and opportunities for voluntary standards development in insurance and in investment & asset management.
SSRN
Following the publication in November 2013 of a joint BSI, CISI and Long Finance report titled “Backing Market Forces: How to Make Voluntary Standards Markets Work for Financial Services Regulationâ€, BSI asked Z/Yen Group and Long Finance to assist in identifying opportunities for voluntary standards development in selected sectors of financial services, starting with insurance and investment & asset management.These two industry studies are the outcomes of this research project conducted between June and October 2014. The studies analyse the needs, gaps and opportunities for voluntary standards development in insurance and in investment & asset management.
Optimal Network Compression
SSRN
This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial inter-bank network. We prove that this problem is, generically, NP-hard. We focus on objective functions generated by systemic risk measures under systematic shocks to the financial network. We conclude by studying the optimal compression problem for specific networks; this permits us to study the so-called robust fragility of certain network topologies more generally as well as the potential benefits and costs of network compression.
SSRN
This paper introduces a formulation of the optimal network compression problem for financial systems. This general formulation is presented for different levels of network compression or rerouting allowed from the initial inter-bank network. We prove that this problem is, generically, NP-hard. We focus on objective functions generated by systemic risk measures under systematic shocks to the financial network. We conclude by studying the optimal compression problem for specific networks; this permits us to study the so-called robust fragility of certain network topologies more generally as well as the potential benefits and costs of network compression.
Predicting High-Frequency Industry Returns: Machine Learners Meet News Watchers
SSRN
This paper uses machine learning-based as well as fundamental-driven, news-based approaches to uncover patterns of high-frequency return predictability for sector exchange-traded funds (ETFs). A LASSO predictor that aggregates high-frequency price movements of a broad universe of individual stocks predicts ETF returns out-of-sample. The news-driven return on ETF constituent firms positively predicts ETF returns, but the component of ETF returns orthogonal to the news return negatively predicts them. These different signals contain independent information, and have different strengths, with the LASSO predictor providing continuous flows of information most powerful during trading hours and the news return offering sporadic information particularly useful during market close. A composite signal combining all three signals with Gradient Boosted Regression Trees (GBRT) has very strong power to forecast ETF returns, especially during the COVID-19 pandemic.
SSRN
This paper uses machine learning-based as well as fundamental-driven, news-based approaches to uncover patterns of high-frequency return predictability for sector exchange-traded funds (ETFs). A LASSO predictor that aggregates high-frequency price movements of a broad universe of individual stocks predicts ETF returns out-of-sample. The news-driven return on ETF constituent firms positively predicts ETF returns, but the component of ETF returns orthogonal to the news return negatively predicts them. These different signals contain independent information, and have different strengths, with the LASSO predictor providing continuous flows of information most powerful during trading hours and the news return offering sporadic information particularly useful during market close. A composite signal combining all three signals with Gradient Boosted Regression Trees (GBRT) has very strong power to forecast ETF returns, especially during the COVID-19 pandemic.
Propagation of minimality in the supercooled Stefan problem
arXiv
arXiv
Supercooled Stefan problems describe the evolution of the boundary between the solid and liquid phases of a substance, where the liquid is assumed to be cooled below its freezing point. Following the methodology of Delarue, Nadtochiy and Shkolnikov, we construct solutions to the one-phase one-dimensional supercooled Stefan problem through a certain McKean-Vlasov equation, which allows to define global solutions even in the presence of blow-ups. Solutions to the McKean-Vlasov equation arise as mean-field limits of particle systems interacting through hitting times, which is important for systemic risk modeling. Our main contributions are: (i) we prove a general tightness theorem for the Skorokhod M1-topology which applies to processes that can be decomposed into a continuous and a monotone part. (ii) We prove propagation of chaos for a perturbed version of the particle system for general initial conditions. (iii) We prove a conjecture of Delarue, Nadtochiy and Shkolnikov, relating the solution concepts of so-called minimal and physical solutions, showing that minimal solutions of the McKean-Vlasov equation are physical whenever the initial condition is integrable.
Renewal of Patents and Government Financing
SSRN
I apply a survival model to a detailed data set of Swedish patents to estimate how different factors affect the likelihood of patent renewal. Since the owners know more about the patents than potential external financiers, there is a problem of asymmetric information. To overcome this, Sweden has for a long time relied on government support rather than private venture capital. The empirical results show that patents which have received soft government financing in the R&D-phase have a higher probability of expiring than patents without such financing. But patents that have received more market-oriented government loans during the commercialization phase are renewed for as long as other commercialized patents. This finding indicates that it is the financing terms rather than bad choices of projects that explain the low renewal of patents with government financing.
SSRN
I apply a survival model to a detailed data set of Swedish patents to estimate how different factors affect the likelihood of patent renewal. Since the owners know more about the patents than potential external financiers, there is a problem of asymmetric information. To overcome this, Sweden has for a long time relied on government support rather than private venture capital. The empirical results show that patents which have received soft government financing in the R&D-phase have a higher probability of expiring than patents without such financing. But patents that have received more market-oriented government loans during the commercialization phase are renewed for as long as other commercialized patents. This finding indicates that it is the financing terms rather than bad choices of projects that explain the low renewal of patents with government financing.
Static Versus Dynamic ESG Classification of Mutual Funds, Green-Washing and Investor’s Opportunity Set
SSRN
In this paper I document the heterogeneous response of investors to fund performance across Socially Responsible Investing (SRI) funds versus conventional funds. I first show that the Morningstar categorization of funds into socially responsible (static classification) versus conventional is inconsistent with the portfolio sustainability scores of the funds (dynamic classification). I use this result to show that the SRI investors are more responsive to positive return along both static and dynamic axes of classification, but economic magnitude of this heterogeneity is lesser than that documented by Bollen(2007). I further show that this heterogeneity is even more pronounced within static SRI funds but insignificant within static conventional funds. Lastly, I provide indicative evidence that investors within SRI funds are more responsive to changes in sustainability score compared to conventional funds.
SSRN
In this paper I document the heterogeneous response of investors to fund performance across Socially Responsible Investing (SRI) funds versus conventional funds. I first show that the Morningstar categorization of funds into socially responsible (static classification) versus conventional is inconsistent with the portfolio sustainability scores of the funds (dynamic classification). I use this result to show that the SRI investors are more responsive to positive return along both static and dynamic axes of classification, but economic magnitude of this heterogeneity is lesser than that documented by Bollen(2007). I further show that this heterogeneity is even more pronounced within static SRI funds but insignificant within static conventional funds. Lastly, I provide indicative evidence that investors within SRI funds are more responsive to changes in sustainability score compared to conventional funds.
The Bond, Equity, and Real Estate Term Structures
SSRN
We construct a Stochastic Discount Factor (SDF) that prices bond, equity, and real estate portfolios sorted on cash flow duration. Using this SDF and the dynamics of cash flow yields in these three asset classes, we estimate the bond, equity, and real estate term structures monthly from 1974 to 2019. We find that while (nominally) safe and risky cash flows have risk premia term structures that are upward sloping on average and move together over time, the term structure dynamics are fundamentally different after we remove the safe component of the risky cash flows. Specifically, equity and real estate maturity-matched risk premia, on average, increase over short maturities but decline over long maturities. Moreover, their term structures comove positively with each other but negatively with the bond term structure.
SSRN
We construct a Stochastic Discount Factor (SDF) that prices bond, equity, and real estate portfolios sorted on cash flow duration. Using this SDF and the dynamics of cash flow yields in these three asset classes, we estimate the bond, equity, and real estate term structures monthly from 1974 to 2019. We find that while (nominally) safe and risky cash flows have risk premia term structures that are upward sloping on average and move together over time, the term structure dynamics are fundamentally different after we remove the safe component of the risky cash flows. Specifically, equity and real estate maturity-matched risk premia, on average, increase over short maturities but decline over long maturities. Moreover, their term structures comove positively with each other but negatively with the bond term structure.
The English Patient: Evaluating Local Lockdowns Using Real-Time COVID-19 & Consumption Data
arXiv
arXiv
We find UK 'local lockdowns' of cities and sub-regions, focused on limiting contact between households in homes, turn the tide on rising positive COVID-19 cases without the large declines in consumption accompanying the March 2020 national lockdown, which limited all social contact. Our study harnesses a new source of real-time, transaction-level consumption data that we show to be highly correlated with official statistics. The effectiveness of local lockdowns are evaluated applying a difference-in-difference approach which exploits nearby localities not subject to local lockdowns as comparison groups. Our findings indicate that policymakers may be able to contain virus outbreaks without killing local economies. However, the ultimate effectiveness of local lockdowns is expected to be highly dependent on co-ordination between regions and testing.
The Impact of G-Sib Identification on Bank Lending: Evidence from Syndicated Loans
SSRN
This paper uses granular data on syndicated loans to analyse the impact of international reforms for Global Systemically Important Banks (G-SIBs) on bank lending behaviour. Using a difference-in-differences estimation strategy, we find no effect of the reforms on overall credit supply, while at the same time documenting a substantial decline in borrower- and loan-specific risk factors for the affected banks. Moreover, we detect a significant decline in the pricing gap between interest rates charged by G-SIBs and other banks, which we interpret as indirect evidence for a reduction in funding cost subsidies. Overall, our results suggest that the G-SIB reforms have helped to mitigate moral hazard problems associated with systemically important banks, while the consequences for the real economy have been limited.
SSRN
This paper uses granular data on syndicated loans to analyse the impact of international reforms for Global Systemically Important Banks (G-SIBs) on bank lending behaviour. Using a difference-in-differences estimation strategy, we find no effect of the reforms on overall credit supply, while at the same time documenting a substantial decline in borrower- and loan-specific risk factors for the affected banks. Moreover, we detect a significant decline in the pricing gap between interest rates charged by G-SIBs and other banks, which we interpret as indirect evidence for a reduction in funding cost subsidies. Overall, our results suggest that the G-SIB reforms have helped to mitigate moral hazard problems associated with systemically important banks, while the consequences for the real economy have been limited.
The Risk of Being a Fallen Angel and the Corporate Dash for Cash in the Midst of COVID
SSRN
Data on firm-loan-level daily credit line drawdowns in the United States expose a corporate “dash for cash†induced by the COVID-19 pandemic. In the first phase of the crisis, which was characterized by extreme precaution and heightened aggregate risk, all firms drew down bank credit lines and raised cash levels. In the second phase, which followed the adoption of stabilization policies, only the highest-rated firms switched to capital markets to raise cash. Consistent with the risk of becoming a fallen angel, the lowest-quality BBB-rated firms behaved more similarly to non-investment grade firms. The observed corporate behavior reveals the significant impact of credit risk on corporate cash holdings.
SSRN
Data on firm-loan-level daily credit line drawdowns in the United States expose a corporate “dash for cash†induced by the COVID-19 pandemic. In the first phase of the crisis, which was characterized by extreme precaution and heightened aggregate risk, all firms drew down bank credit lines and raised cash levels. In the second phase, which followed the adoption of stabilization policies, only the highest-rated firms switched to capital markets to raise cash. Consistent with the risk of becoming a fallen angel, the lowest-quality BBB-rated firms behaved more similarly to non-investment grade firms. The observed corporate behavior reveals the significant impact of credit risk on corporate cash holdings.
