Research articles for the 2020-03-16
A Hedonic Metric Approach to Estimating the Demand for Differentiated Products: An Application to Retail Milk Demand
arXiv
arXiv
This article introduces the Hedonic Metric (HM) approach as an original method to model the demand for differentiated products. Using this approach, initially, we create an n-dimensional hedonic space based on the characteristic information available to consumers. Next, we allocate products into this space and estimate the elasticities using distances. Our model makes it possible to estimate a large number of differentiated products in a single demand system. We applied our model to estimate the retail demand for fluid milk products.
A Simple Approach to Project Extreme Old Age Mortality Rates and Value Mortality-Related Financial Instruments
SSRN
This article shows how mortality models that involve age effects can be fitted to ages beyond the sample range using projections of age effects as replacements for age effects that might not be in the sample. This ‘projected age effect’ approach allows insurers to use age-effect mortality models to obtain valuations of financial instruments such as annuities that depend on projections of extreme old age ð'ž rates. Illustrative results suggest that the proposed approach provides a good approximation to both ð'ž rates and term annuity prices. The practical import of this approach is to allow insurers to apply a much wider range of mortality models to such problems than would otherwise be possible.
SSRN
This article shows how mortality models that involve age effects can be fitted to ages beyond the sample range using projections of age effects as replacements for age effects that might not be in the sample. This ‘projected age effect’ approach allows insurers to use age-effect mortality models to obtain valuations of financial instruments such as annuities that depend on projections of extreme old age ð'ž rates. Illustrative results suggest that the proposed approach provides a good approximation to both ð'ž rates and term annuity prices. The practical import of this approach is to allow insurers to apply a much wider range of mortality models to such problems than would otherwise be possible.
An Alpha-Stable Approach to Modelling Highly Speculative Assets and Cryptocurrencies
SSRN
We investigate the behaviour of cryptocurrencies' return data. Using return data for bitcoin, ethereum and ripple which account for over 70% of the cyrptocurrency market, we demonstrate that α-stable distribution models highly speculative cryptocurrencies more robustly compared to other heavy tailed distributions that are used in financial econometrics. We find that the Maximum Likelihood Method proposed by DuMouchel (1971) produces estimates that fit the cryptocurrency return data much better than the quantile based approach of McCulloch (1986) and sample characteristic method by Koutrouvelis (1980). The empirical results show that the leptokurtic feature presented in cryptocurrency return data can be captured by an α-stable distribution. This papers covers predominant literature in cryptocurrencies and stable distributions.
SSRN
We investigate the behaviour of cryptocurrencies' return data. Using return data for bitcoin, ethereum and ripple which account for over 70% of the cyrptocurrency market, we demonstrate that α-stable distribution models highly speculative cryptocurrencies more robustly compared to other heavy tailed distributions that are used in financial econometrics. We find that the Maximum Likelihood Method proposed by DuMouchel (1971) produces estimates that fit the cryptocurrency return data much better than the quantile based approach of McCulloch (1986) and sample characteristic method by Koutrouvelis (1980). The empirical results show that the leptokurtic feature presented in cryptocurrency return data can be captured by an α-stable distribution. This papers covers predominant literature in cryptocurrencies and stable distributions.
An Empirical Study of the Sentiment Capital Asset Pricing Model
SSRN
What is market sentiment? This paper takes a new approach to this question and derives a formula for market sentiment as a function of the risk-free rate, the price/dividend ratio, and the conditional stock market volatility. The formula is derived from a representative agent with a prospect theory probability weighting function. We estimate the model and find that our sentiment measure correlates positively with the leading sentiment indexes. The model matches the equity premium while generating a low and stable risk-free rate with low risk aversion. We also apply the model to explain other anomalies for the aggregate stock market.
SSRN
What is market sentiment? This paper takes a new approach to this question and derives a formula for market sentiment as a function of the risk-free rate, the price/dividend ratio, and the conditional stock market volatility. The formula is derived from a representative agent with a prospect theory probability weighting function. We estimate the model and find that our sentiment measure correlates positively with the leading sentiment indexes. The model matches the equity premium while generating a low and stable risk-free rate with low risk aversion. We also apply the model to explain other anomalies for the aggregate stock market.
Business Group Dominance and Capital Allocation Externalities: Evidence from Korean Chaebols
SSRN
This study investigates how dominant business groups affect investment decisions of other standalone firms in the economy. Using intra-group equity transactions within the top 40 largest business groups in Korea, this study finds that high levels of internal capital allocation within the groups exert a negative influence on investments of standalone firms that require external capital. Due to financial market imperfections associated with low investor protections, business groups prefer internal investment rather than outside investment. However, when internal capital allocation is prevalent in the economy, lots of capital is trapped inside business groups and available capital in external markets becomes scarce. Standalone firms outside business groups have difficulties raising external finance and thus reduce investment. The negative influence on investments of business group dominance is particularly pronounced for private standalone firms and the firms that hold fewer tangible assets. Findings in this study suggest a negative externality that business groups impose on other standalone firms: the bias toward internal investment makes it harder for good projects outside business groups to obtain capital.
SSRN
This study investigates how dominant business groups affect investment decisions of other standalone firms in the economy. Using intra-group equity transactions within the top 40 largest business groups in Korea, this study finds that high levels of internal capital allocation within the groups exert a negative influence on investments of standalone firms that require external capital. Due to financial market imperfections associated with low investor protections, business groups prefer internal investment rather than outside investment. However, when internal capital allocation is prevalent in the economy, lots of capital is trapped inside business groups and available capital in external markets becomes scarce. Standalone firms outside business groups have difficulties raising external finance and thus reduce investment. The negative influence on investments of business group dominance is particularly pronounced for private standalone firms and the firms that hold fewer tangible assets. Findings in this study suggest a negative externality that business groups impose on other standalone firms: the bias toward internal investment makes it harder for good projects outside business groups to obtain capital.
CBDX: A Workhorse Mortality Model from the Cairns-Blake-Dowd Family
SSRN
The purpose of this paper is to identify a workhorse mortality model for the adult age range (i.e., excluding the accident hump and younger ages). It applies the “general procedure†(GP) of Hunt and Blake (2014) to identify an age-period model that fits the data well before adding in a cohort effect that captures the residual year-of-birth effects arising in the original age-period model. The resulting model is intended to be suitable for a variety of populations, but economises on the number of period effects in comparison with a full implementation of the GP. We estimate the model using two different iterative Maximum Likelihood (ML) approaches â€" one Partial ML and the other Full ML â€" that avoid the need to specify identifiability constraints.
SSRN
The purpose of this paper is to identify a workhorse mortality model for the adult age range (i.e., excluding the accident hump and younger ages). It applies the “general procedure†(GP) of Hunt and Blake (2014) to identify an age-period model that fits the data well before adding in a cohort effect that captures the residual year-of-birth effects arising in the original age-period model. The resulting model is intended to be suitable for a variety of populations, but economises on the number of period effects in comparison with a full implementation of the GP. We estimate the model using two different iterative Maximum Likelihood (ML) approaches â€" one Partial ML and the other Full ML â€" that avoid the need to specify identifiability constraints.
Changes in Market Uncertainty and Profitability of Idiosyncratic Volatility Anomaly in Korea
SSRN
Purpose - The idiosyncratic volatility (IVOL) puzzle is the anomaly that lower IVOL stocks earn higher future returns. We examine if global market uncertainty and market fear affect idiosyncratic volatility anomaly profits in Korea.Design/methodology/approach - Change in market uncertainty and investor fear is measured by change in the volatility index (VIX). Stocks are sorted into quintile portfolios based on their IVOLs in each month. To measure the anomaly profit, the return spread between two extreme portfolios is computed. Risk-adjusted returns are also calculated relative to capital asset pricing model (CAPM) and the Fama and French model. Then, we compare the difference of the IVOL investing profits in the decreasing and increasing VIX periods.Findings - We find that in the months following a decrease in VIX, stocks with low IVOLs earn 2.5% higher profits than stocks with high IVOLs. However, no such anomaly arises in the months following an increase in the VIX.Research implications or Originality - This result implies that mispricing is more significant when investors’ fears regarding market uncertainty are abated. Also, investors can obtain the IVOL anomaly returns by buying low IVOL stocks when the VIX decreases and selling them the following month. This finding suggests that the Korean stock market is integrated with the global market.
SSRN
Purpose - The idiosyncratic volatility (IVOL) puzzle is the anomaly that lower IVOL stocks earn higher future returns. We examine if global market uncertainty and market fear affect idiosyncratic volatility anomaly profits in Korea.Design/methodology/approach - Change in market uncertainty and investor fear is measured by change in the volatility index (VIX). Stocks are sorted into quintile portfolios based on their IVOLs in each month. To measure the anomaly profit, the return spread between two extreme portfolios is computed. Risk-adjusted returns are also calculated relative to capital asset pricing model (CAPM) and the Fama and French model. Then, we compare the difference of the IVOL investing profits in the decreasing and increasing VIX periods.Findings - We find that in the months following a decrease in VIX, stocks with low IVOLs earn 2.5% higher profits than stocks with high IVOLs. However, no such anomaly arises in the months following an increase in the VIX.Research implications or Originality - This result implies that mispricing is more significant when investors’ fears regarding market uncertainty are abated. Also, investors can obtain the IVOL anomaly returns by buying low IVOL stocks when the VIX decreases and selling them the following month. This finding suggests that the Korean stock market is integrated with the global market.
Coronavirus: Case for Digital Money?
SSRN
We discuss the pros of adapting government-issued digital currencies as well as a supranational digital iCurrency. One such pro is to get rid of paper money (and coinage), a ubiquitous medium for spreading germs, as highlighted by the recent coronavirus outbreak. We set forth three policy recommendations for adapting mobile devices as new digital wallets, regulatory oversight of sovereign digital currencies and user data protection, and a supranational digital iCurrency for facilitating international digital monetary linkages.
SSRN
We discuss the pros of adapting government-issued digital currencies as well as a supranational digital iCurrency. One such pro is to get rid of paper money (and coinage), a ubiquitous medium for spreading germs, as highlighted by the recent coronavirus outbreak. We set forth three policy recommendations for adapting mobile devices as new digital wallets, regulatory oversight of sovereign digital currencies and user data protection, and a supranational digital iCurrency for facilitating international digital monetary linkages.
Creditor Rights, Debt Capacity and Securities Issuance: Evidence from Anti-Recharacterization Laws
SSRN
This paper examines the effects of improvement in creditors' rights protection on firms' financing choices and securities issuance. To address these issues, I exploit exogenous variation in creditors' rights protection induced by the staggered adoption of anti-recharacterization laws by some U.S. states. The laws enhance the ability of creditors to repossess collateral during bankruptcy. Using a difference-in-difference methodology to estimate the causal impacts, I find that: the laws are positively related to debt capacity and debt maturity. Firms increase market leverage and substitute away from costly short-term debt financing into long-term debt financing the laws are positively related to debt issuance the laws are negatively related to equity issuance. My analysis further demonstrates that proactive securities issuers are significantly more responsive to the adoption of anti-recharacterization laws than passive securities issuers.
SSRN
This paper examines the effects of improvement in creditors' rights protection on firms' financing choices and securities issuance. To address these issues, I exploit exogenous variation in creditors' rights protection induced by the staggered adoption of anti-recharacterization laws by some U.S. states. The laws enhance the ability of creditors to repossess collateral during bankruptcy. Using a difference-in-difference methodology to estimate the causal impacts, I find that: the laws are positively related to debt capacity and debt maturity. Firms increase market leverage and substitute away from costly short-term debt financing into long-term debt financing the laws are positively related to debt issuance the laws are negatively related to equity issuance. My analysis further demonstrates that proactive securities issuers are significantly more responsive to the adoption of anti-recharacterization laws than passive securities issuers.
Deep Deterministic Portfolio Optimization
arXiv
arXiv
Can deep reinforcement learning algorithms be exploited as solvers for optimal trading strategies? The aim of this work is to test reinforcement learning algorithms on conceptually simple, but mathematically non-trivial, trading environments. The environments are chosen such that an optimal or close-to-optimal trading strategy is known. We study the deep deterministic policy gradient algorithm and show that such a reinforcement learning agent can successfully recover the essential features of the optimal trading strategies and achieve close-to-optimal rewards.
Degrees of displacement: The impact of household PV battery prosumage on utility generation and storage
arXiv
arXiv
Reductions in the cost of PV and batteries encourage households to invest in PV battery prosumage. We explore the implications for the rest of the power sector by applying two open-source techno-economic models to scenarios in Western Australia for the year 2030. Household PV capacity generally substitutes utility PV, but slightly less so as additional household batteries are installed. Wind power is less affected, especially in scenarios with higher shares of renewables. With household batteries operating to maximise self-consumption, utility battery capacities are hardly substituted. Wholesale prices to supply households, including those not engaging in prosumage, slightly decrease, while prices for other consumers slightly increase. We conclude that the growth of prosumage has implications on the various elements of the power sector and should be more thoroughly considered by investors, regulators, and power sector planners.
Economic Versus Statistical Clustering in Multi-Asset Multi-Factor Strategies
SSRN
Maximizing for diversification in the multi-asset multi-factor universe, the literature advances diversified risk parity strategies across economic clusters. For handling overly complex correlation matrices, hierarchical clustering techniques have recently been put forward to guide risk parity allocations. Indeed, such statistical clusters might be considered natural portfolio building blocks given that they automatically pick up the dependence structure and thus form meaningful ingredients to aid portfolio diversification. We explain the intuition and nature of hierarchical clustering techniques in the context of multi-asset multi-factor investing vis-Ã -vis the use of economic factors in diversified risk-based allocation paradigms such as 1/N, minimum-variance and diversified risk parity.
SSRN
Maximizing for diversification in the multi-asset multi-factor universe, the literature advances diversified risk parity strategies across economic clusters. For handling overly complex correlation matrices, hierarchical clustering techniques have recently been put forward to guide risk parity allocations. Indeed, such statistical clusters might be considered natural portfolio building blocks given that they automatically pick up the dependence structure and thus form meaningful ingredients to aid portfolio diversification. We explain the intuition and nature of hierarchical clustering techniques in the context of multi-asset multi-factor investing vis-Ã -vis the use of economic factors in diversified risk-based allocation paradigms such as 1/N, minimum-variance and diversified risk parity.
Fast and Furious: The Market Quality Implications of Speed in Cross-Border Trading
SSRN
Using a measure of transmission latency between exchanges located in Frankfurt and London, and exploiting speed-inducing technological upgrades, we investigate the impact of international transmission latency on liquidity and volatility. We find that a decrease in transmission latency increases liquidity and volatility. In line with existing theoretical models, we show that the amplification of liquidity and volatility is associated with variations in adverse selection risk and aggressive trading. We then investigate the net economic effect of high speed and find that the liquidity-enhancing benefit of increased trading speed in financial markets outweighs its volatility-inducing effect.
SSRN
Using a measure of transmission latency between exchanges located in Frankfurt and London, and exploiting speed-inducing technological upgrades, we investigate the impact of international transmission latency on liquidity and volatility. We find that a decrease in transmission latency increases liquidity and volatility. In line with existing theoretical models, we show that the amplification of liquidity and volatility is associated with variations in adverse selection risk and aggressive trading. We then investigate the net economic effect of high speed and find that the liquidity-enhancing benefit of increased trading speed in financial markets outweighs its volatility-inducing effect.
Fighting Fraud in Nigeria Banking Industry. An Examination of the Impact of Forensic Auditing
SSRN
This paper examines the impact and effectiveness of forensic auditing in detecting, investigating, and preventing frauds in digital environment with emphasis on commercial banks in Nigeria. The study sought to find out to what level the forensic auditors are able to fulfill this mandate and investigate problems that hinder forensic auditors to make progress in their operations in Nigeria. It also established the role of forensic auditing in Nigeria banking operations. This paper also discusses four aspects of computer aided fraud detection that are of primary interest to fraud investigators and forensic auditors: data mining techniques for the detection of internal fraud, ratio analysis for the detection of financial statement fraud, the issues surrounding external information sources, and computer forensics during fraud investigations. Questionnaires, personal interviews, and document review are the methods that were used to obtain data for this study. A sample of One hundred and fifty-three respondents from various categories of staff were used from ten commercial banks and four audit firms in Nigeria. The collected data were analyzed using application of non-parametric statistical tests. It was found that the forensic auditing departments suffer from multiple challenges, among them being the lack of material resources, technical know-how, interference from management, and unclear recognition of the profession. In conclusion, forensic auditors must be capacitated materially and technically to improve their effectiveness.
SSRN
This paper examines the impact and effectiveness of forensic auditing in detecting, investigating, and preventing frauds in digital environment with emphasis on commercial banks in Nigeria. The study sought to find out to what level the forensic auditors are able to fulfill this mandate and investigate problems that hinder forensic auditors to make progress in their operations in Nigeria. It also established the role of forensic auditing in Nigeria banking operations. This paper also discusses four aspects of computer aided fraud detection that are of primary interest to fraud investigators and forensic auditors: data mining techniques for the detection of internal fraud, ratio analysis for the detection of financial statement fraud, the issues surrounding external information sources, and computer forensics during fraud investigations. Questionnaires, personal interviews, and document review are the methods that were used to obtain data for this study. A sample of One hundred and fifty-three respondents from various categories of staff were used from ten commercial banks and four audit firms in Nigeria. The collected data were analyzed using application of non-parametric statistical tests. It was found that the forensic auditing departments suffer from multiple challenges, among them being the lack of material resources, technical know-how, interference from management, and unclear recognition of the profession. In conclusion, forensic auditors must be capacitated materially and technically to improve their effectiveness.
Fintech as a Strategy of Financial Inclusion in the Age of Digitalization
SSRN
Inclusive growth is at the top of international organizations’ agenda in recent years and the Asia-Pacific Economic Cooperation (APEC) is no exception. Since the 2008 global financial crisis revealed the intrinsic limitations of market-driven economic system despite its own merits incomparable to other alternatives, civil society and policymakers altogether have called for more shrewd policy actions that can achieve two critical public policy goals at once: promoting financial empowerment of the less privileged and enhancing competition in the financial market. While the emergence of fintech in financial markets in the past few years cannot be attributed to the competence of financial regulators and policymakers as to this call, what fintech has already achieved in terms of financial inclusion and competence of financial markets through disruption of traditional financial market structure demonstrate the importance of fintech as a strategy and policy tool of achieving the goal of inclusive growth. This strategy of achieving financial inclusion and financial market competition via fintech is more relevant to the APEC member countries because the region includes fast-growing fintech markets such as China, India, and Russia. Moreover, the growing significance of fintech services for SMEs (Business-to-Business, B2B) implies that fintech services have more relevance to the APEC economies as SMEs account over 97% of enterprises and employ over half of the workforce in the region.
SSRN
Inclusive growth is at the top of international organizations’ agenda in recent years and the Asia-Pacific Economic Cooperation (APEC) is no exception. Since the 2008 global financial crisis revealed the intrinsic limitations of market-driven economic system despite its own merits incomparable to other alternatives, civil society and policymakers altogether have called for more shrewd policy actions that can achieve two critical public policy goals at once: promoting financial empowerment of the less privileged and enhancing competition in the financial market. While the emergence of fintech in financial markets in the past few years cannot be attributed to the competence of financial regulators and policymakers as to this call, what fintech has already achieved in terms of financial inclusion and competence of financial markets through disruption of traditional financial market structure demonstrate the importance of fintech as a strategy and policy tool of achieving the goal of inclusive growth. This strategy of achieving financial inclusion and financial market competition via fintech is more relevant to the APEC member countries because the region includes fast-growing fintech markets such as China, India, and Russia. Moreover, the growing significance of fintech services for SMEs (Business-to-Business, B2B) implies that fintech services have more relevance to the APEC economies as SMEs account over 97% of enterprises and employ over half of the workforce in the region.
Forward Mortality Rates in Discrete Time I: Calibration and Securities Pricing
SSRN
Many users of mortality models are interested in using them to place values on longevity-linked liabilities and securities. Modern regulatory regimes require that the values of liabilities and reserves are consistent with market prices (if available), whilst the gradual emergence of a traded market in longevity risk needs methods for pricing new types of longevity-linked securities quickly and efficiently. In this study, we develop a new forward mortality framework to enable the efficient pricing of longevity-linked liabilities and securities in a market-consistent fashion. This approach starts from the historical data of the observed mortality rates, i.e., the force of mortality. Building on the dynamics of age/period/cohort models of the observed force of mortality, we develop models of forward mortality rates and then use a change of measure to incorporate whatever market information is available. The resulting forward mortality rates are then used to value a number of different longevity-linked securities, such as q-forwards, s-forwards and longevity swaps.
SSRN
Many users of mortality models are interested in using them to place values on longevity-linked liabilities and securities. Modern regulatory regimes require that the values of liabilities and reserves are consistent with market prices (if available), whilst the gradual emergence of a traded market in longevity risk needs methods for pricing new types of longevity-linked securities quickly and efficiently. In this study, we develop a new forward mortality framework to enable the efficient pricing of longevity-linked liabilities and securities in a market-consistent fashion. This approach starts from the historical data of the observed mortality rates, i.e., the force of mortality. Building on the dynamics of age/period/cohort models of the observed force of mortality, we develop models of forward mortality rates and then use a change of measure to incorporate whatever market information is available. The resulting forward mortality rates are then used to value a number of different longevity-linked securities, such as q-forwards, s-forwards and longevity swaps.
Forward Mortality Rates in Discrete Time II: Longevity Risk and Hedging Strategies
SSRN
Longevity risk has emerged as an important risk in the early 21st century for the providers of pension benefits and annuities. Any changes in the assumptions for future mortality rates can have a major financial impact on the valuation of these liabilities and motivates many of the longevity-linked securities that have been proposed to hedge this risk. Using the framework developed in Hunt and Blake (Forward mortality rates in discrete time I), we investigate how these assumptions can change over a one-year period and the potential for hedging longevity risk in an illustrative annuity portfolio, and find that relatively simple hedging strategies can significantly mitigate longevity risk over a one-year period.
SSRN
Longevity risk has emerged as an important risk in the early 21st century for the providers of pension benefits and annuities. Any changes in the assumptions for future mortality rates can have a major financial impact on the valuation of these liabilities and motivates many of the longevity-linked securities that have been proposed to hedge this risk. Using the framework developed in Hunt and Blake (Forward mortality rates in discrete time I), we investigate how these assumptions can change over a one-year period and the potential for hedging longevity risk in an illustrative annuity portfolio, and find that relatively simple hedging strategies can significantly mitigate longevity risk over a one-year period.
Gold and Bitcoin Hedging against 10 Exchange Returns
SSRN
Purpose - The purpose of this study was to examine gold and bitcoin hedging against 10 exchange returns.Design/Methodology/Approach - This study collected financial data on exchange, gold, and bitcoin from FRB, St. Louis. A multiple Vector-BEKK regression analysis was used to analyze the data.Findings - First, strong negative effects from exchange markets onto gold were found to exist in the EU, Switzerland, Australia, Brazil, Canada, Japan, and Korea, while there were weak effects in the UK. Bitcoin shows the weak hedging against all markets. Second, the paper also revealed that in EU, the cross-shock term significantly decreased gold volatility, but not bitcoin volatility, while in Japan it decreased bitcoin volatility. The significantly negative asymmetries in gold, but insignificant asymmetries in bitcoin, were found in most exchange markets. Exchange market volatility increases gold volatility in Japan while it decreased in the Indian and Korean markets. Cross-terms among three variables with bi-directional causality are valuable.Research Implications or Originality - The study of the hedging of gold and bitcoin against various exchanges together shows that bi-variate models are useful to reconfirm the strong hedging of gold. Bitcoin, if well prepared to be immune to its deficiencies, might be very carefully used, but not at a magnitude equal to gold as a hedge against exchange. The results may enhance strategic risk management.
SSRN
Purpose - The purpose of this study was to examine gold and bitcoin hedging against 10 exchange returns.Design/Methodology/Approach - This study collected financial data on exchange, gold, and bitcoin from FRB, St. Louis. A multiple Vector-BEKK regression analysis was used to analyze the data.Findings - First, strong negative effects from exchange markets onto gold were found to exist in the EU, Switzerland, Australia, Brazil, Canada, Japan, and Korea, while there were weak effects in the UK. Bitcoin shows the weak hedging against all markets. Second, the paper also revealed that in EU, the cross-shock term significantly decreased gold volatility, but not bitcoin volatility, while in Japan it decreased bitcoin volatility. The significantly negative asymmetries in gold, but insignificant asymmetries in bitcoin, were found in most exchange markets. Exchange market volatility increases gold volatility in Japan while it decreased in the Indian and Korean markets. Cross-terms among three variables with bi-directional causality are valuable.Research Implications or Originality - The study of the hedging of gold and bitcoin against various exchanges together shows that bi-variate models are useful to reconfirm the strong hedging of gold. Bitcoin, if well prepared to be immune to its deficiencies, might be very carefully used, but not at a magnitude equal to gold as a hedge against exchange. The results may enhance strategic risk management.
Grouping Individual Investment Preferences in Retirement Savings: A Cluster Analysis of a USS Members Risk Attitude Survey.
SSRN
Cluster analysis is used to identify homogeneous groups of members of USS in terms of risk attitudes. There are two distinct clusters of members in their 40s and 50s. One had previously ‘engaged’ with USS by making additional voluntary contributions. It typically had higher pay, longer tenure, less interest in ethical investing, lower risk capacity, a higher percentage of males, and a higher percentage of academics than members of the ‘disengaged’ cluster. Conditioning only on the attitude to risk responses, there are 18 clusters, with similar but not identical membership, depending on which clustering method is used. The differences in risk aversion across the 18 clusters could be explained largely by differences in the percentage of females and the percentage of couples. Risk aversion increases as the percentage of females in the cluster increases, while it reduces as the percentage of couples increases because of greater risk sharing within the household. Characteristics that other studies have found important determinants of risk attitudes, such as age, income and (pension) wealth, do not turn out to be as significant for USS members. Further, despite being on average more highly educated than the general population, USS members are marginally more risk averse than the general population, controlling for salary, although the difference is not significant.
SSRN
Cluster analysis is used to identify homogeneous groups of members of USS in terms of risk attitudes. There are two distinct clusters of members in their 40s and 50s. One had previously ‘engaged’ with USS by making additional voluntary contributions. It typically had higher pay, longer tenure, less interest in ethical investing, lower risk capacity, a higher percentage of males, and a higher percentage of academics than members of the ‘disengaged’ cluster. Conditioning only on the attitude to risk responses, there are 18 clusters, with similar but not identical membership, depending on which clustering method is used. The differences in risk aversion across the 18 clusters could be explained largely by differences in the percentage of females and the percentage of couples. Risk aversion increases as the percentage of females in the cluster increases, while it reduces as the percentage of couples increases because of greater risk sharing within the household. Characteristics that other studies have found important determinants of risk attitudes, such as age, income and (pension) wealth, do not turn out to be as significant for USS members. Further, despite being on average more highly educated than the general population, USS members are marginally more risk averse than the general population, controlling for salary, although the difference is not significant.
Growth and inequalities in a physicist's view
arXiv
arXiv
It is still common wisdom amongst economists, politicians and lay people that economic growth is a necessity of our social systems, at least to avoid distributional conflicts. This paper challenges such belief moving from a purely physical theoretical perspective. It formally considers the constraints imposed by a finite environment on the prospect of continuous growth, including the dynamics of costs. As costs grow faster than production it is easy to deduce a final unavoidable global collapse. Then, analyzing and discussing the evolution of the unequal share of wealth under the premises of growth and competition, it is shown that the increase of inequalities is a necessary consequence of the premises.
Hedge Fund Regulation, Performance, and Risk-Taking: Re-Examining the Effect of the Dodd-Frank Act
SSRN
This paper examines the effect of the Dodd-Frank Act (“Dodd-Frankâ€) on the profits and risk-taking of the hedge fund industry. Dodd-Frank subjects most hedge funds to government inspections, requires them to register with the Securities and Exchange Commission (“SECâ€), and imposes a number of disclosure and compliance obligations. According to the SEC and other authorities, these measures were intended to protect investors from misrepresentation of fund performance and increase the control of systemic risk; but the industry opposed the law, claiming that compliance costs would substantially affect the profitability of the industry and that the new obligations were unnecessary given the relatively sophisticated nature of hedge fund investors. The empirical evidence on the effect of Dodd Frank on profitability and risk-taking, however, is limited. This paper, therefore, contributes to filling this gap. The results show that, relative to a control group of funds that were already regulated or largely exempted from regulation, the newly regulated funds experienced a significant decrease in reported profits but not in risk (as proxied by volatility). The funds that became subject to the obligation to file Form PF (a new form created as part of the implementation of Dodd-Frank, which focuses on performance and volatility data) actually experienced a decrease in risk, but this result should only be interpreted as suggestive given some limitations of the data. In addition, the analysis suggests that the decline in reported profits among the newly regulated funds was not driven by compliance costs, as predicted by the industry. Rather, the results indicate that the decline can be reasonably attributed to greater conservativism in financial reporting. Taken together, the results contradict some commentators’ suggestion that the reduction in reported returns following Dodd-Frank represents a “partial government failure.â€
SSRN
This paper examines the effect of the Dodd-Frank Act (“Dodd-Frankâ€) on the profits and risk-taking of the hedge fund industry. Dodd-Frank subjects most hedge funds to government inspections, requires them to register with the Securities and Exchange Commission (“SECâ€), and imposes a number of disclosure and compliance obligations. According to the SEC and other authorities, these measures were intended to protect investors from misrepresentation of fund performance and increase the control of systemic risk; but the industry opposed the law, claiming that compliance costs would substantially affect the profitability of the industry and that the new obligations were unnecessary given the relatively sophisticated nature of hedge fund investors. The empirical evidence on the effect of Dodd Frank on profitability and risk-taking, however, is limited. This paper, therefore, contributes to filling this gap. The results show that, relative to a control group of funds that were already regulated or largely exempted from regulation, the newly regulated funds experienced a significant decrease in reported profits but not in risk (as proxied by volatility). The funds that became subject to the obligation to file Form PF (a new form created as part of the implementation of Dodd-Frank, which focuses on performance and volatility data) actually experienced a decrease in risk, but this result should only be interpreted as suggestive given some limitations of the data. In addition, the analysis suggests that the decline in reported profits among the newly regulated funds was not driven by compliance costs, as predicted by the industry. Rather, the results indicate that the decline can be reasonably attributed to greater conservativism in financial reporting. Taken together, the results contradict some commentators’ suggestion that the reduction in reported returns following Dodd-Frank represents a “partial government failure.â€
Lumpy Investment, Uncertainty, and Monetary Policy
SSRN
This paper studies the roles of lumpy investment and fluctuation in firm-level uncertainty in determining the investment channel of monetary policy. Empirically, I show that higher uncertainty makes firms more cautious about investment when facing monetary stimulus. I then develop a heterogeneous firm New Keynesian model with a comprehensive capital adjustment cost structure, including partial irreversibility, a random fixed cost, and a quadratic cost. These costs lead firms to pursue an asymmetrically generalized (S,s) investment rule. Hence, monetary policy works primarily through the extensive margin of investment. Upon an uncertainty shock, the (S,s) inaction region is enlarged, and a conventional monetary policy shock is not large enough to motivate firms at the extensive margin. As a result, the effectiveness of monetary policy is reduced. I calibrate the model so that it matches the dynamic moments of investment, which is key to generating this result. I show that this calibration implies that an aggregate shock to firm-level uncertainty estimated by Bloom et al. (2018) reduces the impact of a monetary policy shock on investment by about two-third. This reduction is about 90% of what I find in the data. Therefore, the aggregate effect of monetary policy depends on lumpy investment and time-varying uncertainty.
SSRN
This paper studies the roles of lumpy investment and fluctuation in firm-level uncertainty in determining the investment channel of monetary policy. Empirically, I show that higher uncertainty makes firms more cautious about investment when facing monetary stimulus. I then develop a heterogeneous firm New Keynesian model with a comprehensive capital adjustment cost structure, including partial irreversibility, a random fixed cost, and a quadratic cost. These costs lead firms to pursue an asymmetrically generalized (S,s) investment rule. Hence, monetary policy works primarily through the extensive margin of investment. Upon an uncertainty shock, the (S,s) inaction region is enlarged, and a conventional monetary policy shock is not large enough to motivate firms at the extensive margin. As a result, the effectiveness of monetary policy is reduced. I calibrate the model so that it matches the dynamic moments of investment, which is key to generating this result. I show that this calibration implies that an aggregate shock to firm-level uncertainty estimated by Bloom et al. (2018) reduces the impact of a monetary policy shock on investment by about two-third. This reduction is about 90% of what I find in the data. Therefore, the aggregate effect of monetary policy depends on lumpy investment and time-varying uncertainty.
Market states: A new understanding
arXiv
arXiv
We present the clustering analysis of the financial markets of S&P 500 (USA) and Nikkei 225 (JPN) markets over a period of 2006-2019 as an example of a complex system. We investigate the statistical properties of correlation matrices constructed from the sliding epochs. The correlation matrices can be classified into different clusters, named as market states based on the similarity of correlation structures. We cluster the S&P 500 market into four and Nikkei 225 into six market states by optimizing the value of intracluster distances. The market shows transitions between these market states and the statistical properties of the transitions to critical market states can indicate likely precursors to the catastrophic events. We also analyze the same clustering technique on surrogate data constructed from average correlations of market states and the fluctuations arise due to the white noise of short time series. We use the correlated Wishart orthogonal ensemble for the construction of surrogate data whose average correlation equals the average of the real data.
Old Problems, Classical Methods, New Solutions
arXiv
arXiv
We use a powerful extension of the classical method of heat potentials, recently developed by the present author and his collaborators, to solve several significant problems of financial mathematics. We consider the following problems in detail: (A) calibrating the default boundary in the structural default framework to a constant default intensity; (B) calculating default probability for a representative bank in the mean-field framework; (C) finding the hitting time probability density of an Ornstein-Uhlenbeck process. Several other problems, including pricing American put options and finding optimal mean-reverting trading strategies, are mentioned in passing. Besides, two non-financial applications -- the supercooled Stefan problem and the integrate-and-fire neuroscience problem -- are briefly discussed as well.
On the Projection of Mortality Rates to Extreme Old Age
SSRN
This article shows how cohort mortality rate projections of mortality models that involve age effects can be improved and extended to extreme old ages.
SSRN
This article shows how cohort mortality rate projections of mortality models that involve age effects can be improved and extended to extreme old ages.
Pecuniary Externalities, Bank Overleverage, and Macroeconomic Fragility
SSRN
Pecuniary externalities in models with financial friction justify macroprudential policies for preventing economic agents’ excessive risk taking. We extend the Diamond and Rajan (2012) model of banks with the production factors and explore how a pecuniary externality affects a bank’s leverage. We show that the laissez-faire banks in our model take on excessive risks compared with the constrained social optimum. Our numerical simulations suggest that the crisis probability is 2-3 percentage points higher in the laissez-faire economy than in the constrained social optimum.
SSRN
Pecuniary externalities in models with financial friction justify macroprudential policies for preventing economic agents’ excessive risk taking. We extend the Diamond and Rajan (2012) model of banks with the production factors and explore how a pecuniary externality affects a bank’s leverage. We show that the laissez-faire banks in our model take on excessive risks compared with the constrained social optimum. Our numerical simulations suggest that the crisis probability is 2-3 percentage points higher in the laissez-faire economy than in the constrained social optimum.
Peer R&D Disclosure and Corporate Innovation: Evidence From American Depositary Receipt Firms
SSRN
In this paper, we examine the effect of peer research and development (R&D) disclosures on corporate innovation. R&D disclosures can generate externalities for related firms, enabling those firms to better infer a project’s likely payoffs and thus prioritize projects with higher net present values. We use a sample of foreign firms cross-listed on U.S. exchanges to investigate whether U.S. peer firms experience externalities from the cross-listing firm’s R&D disclosures. We find that R&D disclosures by cross-listing firms are associated with greater innovation for industry peers in the U.S. market, especially when product market competition is high. The effect also varies with the home country’s legal protection systems, disclosure environments, and accounting reporting rules. Cross-sectional analyses indicate that the externalities are more pronounced in industries or firms that rely more on external financing and firms subject to higher financial constraints; disclosures of higher quality appear to promote innovation by ameliorating financing frictions. Overall, this study provides evidence of R&D disclosure as an industry-wide determinant of innovation, thereby contributing to literature on the real effects of peer disclosures.
SSRN
In this paper, we examine the effect of peer research and development (R&D) disclosures on corporate innovation. R&D disclosures can generate externalities for related firms, enabling those firms to better infer a project’s likely payoffs and thus prioritize projects with higher net present values. We use a sample of foreign firms cross-listed on U.S. exchanges to investigate whether U.S. peer firms experience externalities from the cross-listing firm’s R&D disclosures. We find that R&D disclosures by cross-listing firms are associated with greater innovation for industry peers in the U.S. market, especially when product market competition is high. The effect also varies with the home country’s legal protection systems, disclosure environments, and accounting reporting rules. Cross-sectional analyses indicate that the externalities are more pronounced in industries or firms that rely more on external financing and firms subject to higher financial constraints; disclosures of higher quality appear to promote innovation by ameliorating financing frictions. Overall, this study provides evidence of R&D disclosure as an industry-wide determinant of innovation, thereby contributing to literature on the real effects of peer disclosures.
Performance of S&P 500 ESG Indices: The Impact of Weighting Methodologies and ESG Ratings
SSRN
Index providers increasingly offer sustainable stock indices based on ESG (Environmental, Social, and Governance) ratings of firms. The performance of such indices with ESG tilts is driven by the impact of the applied weighting methodology and by the ESG firm ratings. In this paper, we focus on the S&P 500 ESG Factor Weighted Index, which outperforms the conventional S&P 500 index in terms of raw returns. Based on a simulation analysis, we find the ESG ratings to contribute little to the index return. Rather, the used weighting methodology mainly causes this outperformance which is connected to exposures to the well-established size, investment and momentum factors. Interestingly, the S&P 500 Equal Weighted Index shows comparable exposures to these factors. The weighting methodologies of both indices result in a relative high weighting of smaller stocks with similar return characteristics. Thus, our key finding is that the weighting methodologies of sustainable indices can be a main return driver, which has to be taken into account by investors evaluating the risk and return profile of stock indices with ESG tilts.
SSRN
Index providers increasingly offer sustainable stock indices based on ESG (Environmental, Social, and Governance) ratings of firms. The performance of such indices with ESG tilts is driven by the impact of the applied weighting methodology and by the ESG firm ratings. In this paper, we focus on the S&P 500 ESG Factor Weighted Index, which outperforms the conventional S&P 500 index in terms of raw returns. Based on a simulation analysis, we find the ESG ratings to contribute little to the index return. Rather, the used weighting methodology mainly causes this outperformance which is connected to exposures to the well-established size, investment and momentum factors. Interestingly, the S&P 500 Equal Weighted Index shows comparable exposures to these factors. The weighting methodologies of both indices result in a relative high weighting of smaller stocks with similar return characteristics. Thus, our key finding is that the weighting methodologies of sustainable indices can be a main return driver, which has to be taken into account by investors evaluating the risk and return profile of stock indices with ESG tilts.
Pricing European and American Options under Heston Model using Discontinuous Galerkin Finite Elements
arXiv
arXiv
This paper deals with pricing of European and American options, when the underlying asset price follows Heston model, via the interior penalty discontinuous Galerkin finite element method (dGFEM). The advantages of dGFEM space discretization with Rannacher smoothing as time integrator with nonsmooth initial and boundary conditions are illustrated for European vanilla options, digital call and American put options. The convection dominated Heston model for vanishing volatility is efficiently solved utilizing the adaptive dGFEM. For fast solution of the linear complementary problem of the American options, a projected successive over relaxation (PSOR) method is developed with the norm preconditioned dGFEM. We show the efficiency and accuracy of dGFEM for option pricing by conducting comparison analysis with other methods and numerical experiments.
Quantifying Loss Aversion: Evidence from a UK Population Survey
SSRN
We estimate loss aversion using on an online survey of a representative sample of over 4,000 UK residents. The average aversion to a loss of £500 relative to a gain of the same amount is 2.41, but loss aversion varies significantly with characteristics such as gender, age, education, financial knowledge, social class, employment status, management responsibility, income, savings and home ownership. Other influencing factors include marital status, number of children, ease of savings, rainy day fund, personality type, emotional state, newspaper and political party. However, once we condition on all the profiling characteristics of the respondents, some factors, in particular gender, cease to be significant, suggesting that gender differences in risk and loss attitudes might be due to other factors, such as income differences.
SSRN
We estimate loss aversion using on an online survey of a representative sample of over 4,000 UK residents. The average aversion to a loss of £500 relative to a gain of the same amount is 2.41, but loss aversion varies significantly with characteristics such as gender, age, education, financial knowledge, social class, employment status, management responsibility, income, savings and home ownership. Other influencing factors include marital status, number of children, ease of savings, rainy day fund, personality type, emotional state, newspaper and political party. However, once we condition on all the profiling characteristics of the respondents, some factors, in particular gender, cease to be significant, suggesting that gender differences in risk and loss attitudes might be due to other factors, such as income differences.
Realized Semibetas: Signs of Things to Come
SSRN
We propose a new decomposition of the traditional market beta into four semibetas depending on the signed covariation between the market and individual asset returns. Consistent with the pricing implications from a mean-semivariance framework, we show that higher semibetas defined by negative market and negative (positive) asset return covariation predict significantly higher (lower) future returns, while the other two semibetas do not appear to be priced. The results are robust to an array of alternative test specifications and additional controls. Rather than betting on or against beta, we conclude that it is better to bet on and against the ``right'' semibetas.
SSRN
We propose a new decomposition of the traditional market beta into four semibetas depending on the signed covariation between the market and individual asset returns. Consistent with the pricing implications from a mean-semivariance framework, we show that higher semibetas defined by negative market and negative (positive) asset return covariation predict significantly higher (lower) future returns, while the other two semibetas do not appear to be priced. The results are robust to an array of alternative test specifications and additional controls. Rather than betting on or against beta, we conclude that it is better to bet on and against the ``right'' semibetas.
Smooth Transition Regression Models for Non-Stationary Extremes
SSRN
We introduce a smooth transition Generalized Pareto (GP) regression model to study the link between extreme losses and the economic context. The advantage of our approach consists in specifying a time-varying dependence structure between financial factors and the severity distribution of the losses. To do so, the parameters of the GP distribution are related to explanatory variables through regression functions which themselves depend on a time-varying predictor of structural changes. We use this technique to study the dynamics in the monthly severity distribution of losses at UniCredit. Using the VIX as transition variable, our analysis reveals that when the uncertainty is high, a high number of losses in a recent past is indicative of less extreme losses in the future, consistent with a self-inhibition hypothesis. On the contrary, in times of low uncertainty, only the economy’s growth rate seems to be a relevant predictor of the likelihood of extreme losses
SSRN
We introduce a smooth transition Generalized Pareto (GP) regression model to study the link between extreme losses and the economic context. The advantage of our approach consists in specifying a time-varying dependence structure between financial factors and the severity distribution of the losses. To do so, the parameters of the GP distribution are related to explanatory variables through regression functions which themselves depend on a time-varying predictor of structural changes. We use this technique to study the dynamics in the monthly severity distribution of losses at UniCredit. Using the VIX as transition variable, our analysis reveals that when the uncertainty is high, a high number of losses in a recent past is indicative of less extreme losses in the future, consistent with a self-inhibition hypothesis. On the contrary, in times of low uncertainty, only the economy’s growth rate seems to be a relevant predictor of the likelihood of extreme losses
Still Living with Mortality: The Longevity Risk Transfer Market after One Decade
SSRN
This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions â€" buy-outs, buy-ins and longevity insurance â€" have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions â€" longevity-spread bonds, longevity swaps, q-forwards, and tail-risk protection â€" have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customized solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral, and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g., determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognize that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined â€" such as longevity-linked securities and reinsurance sidecars.
SSRN
This paper updates Living with Mortality published in 2006. It describes how the longevity risk transfer market has developed over the intervening period, and, in particular, how insurance-based solutions â€" buy-outs, buy-ins and longevity insurance â€" have triumphed over capital markets solutions that were expected to dominate at the time. Some capital markets solutions â€" longevity-spread bonds, longevity swaps, q-forwards, and tail-risk protection â€" have come to market, but the volume of business has been disappointingly low. The reason for this is that when market participants compare the index-based solutions of the capital markets with the customized solutions of insurance companies in terms of basis risk, credit risk, regulatory capital, collateral, and liquidity, the former perform on balance less favourably despite a lower potential cost. We discuss the importance of stochastic mortality models for forecasting future longevity and examine some applications of these models, e.g., determining the longevity risk premium and estimating regulatory capital relief. The longevity risk transfer market is now beginning to recognize that there is insufficient capacity in the insurance and reinsurance industries to deal fully with demand and new solutions for attracting capital markets investors are now being examined â€" such as longevity-linked securities and reinsurance sidecars.
The Nexus between Exchange Rate and Foreign Equity Investors Behavior after the Shanghai-Hong Kong Stock Connect
SSRN
Purpose - This paper investigates the causal nexus between the exchange rate and foreign equity investors’ behavior in Shanghai and Hong Kong by using daily time series data after the Shanghai-Hong Kong Stock Connect scheme was launched.Design/methodology/approach - The empirical data period is a sample of all daily trading data from the implementation of the Shanghai-Hong Kong Stock Connect to April 12, 2019. In order to analyze the nexus between the Shanghai Stock Exchange and Hong Kong Stock Exchange, we employed the impulse response function analysis based on the vector autoregression (VAR) model.Findings - From estimation results on the Shanghai stock market, we found that exchange rates have not had a significant impact on foreign equity investors. Conversely, foreign equity flows have had a significant impact on exchange rate of the RMB. From estimation results on the Hong Kong stock market, it was found that mainland Chinese investors have not significantly affected the foreign exchange market of Hong Kong. On the other hand, the results show that exchange rates have had a significant impact on mainland Chinese investors in Hong Kong.Research implications or Originality - In the Shanghai stock market, exchange rates have not had a significant impact on foreign equity investors, which is due to exchange rate risk management by foreign investors. Conversely, a large amount of foreign equity inflows led to the appreciation of the RMB. In the Hong Kong stock market, mainland Chinese investors have not significantly affected the foreign exchange market of Hong Kong, which is due to a limited share of mainland Chinese investment in Hong Kong market capitalization. Conversely, exchange rates have had a significant impact on mainland Chinese investors in Hong Kong, which reveal that mainland Chinese equity flows into Hong Kong increased when the RMB depreciated against the Hong Kong dollar.
SSRN
Purpose - This paper investigates the causal nexus between the exchange rate and foreign equity investors’ behavior in Shanghai and Hong Kong by using daily time series data after the Shanghai-Hong Kong Stock Connect scheme was launched.Design/methodology/approach - The empirical data period is a sample of all daily trading data from the implementation of the Shanghai-Hong Kong Stock Connect to April 12, 2019. In order to analyze the nexus between the Shanghai Stock Exchange and Hong Kong Stock Exchange, we employed the impulse response function analysis based on the vector autoregression (VAR) model.Findings - From estimation results on the Shanghai stock market, we found that exchange rates have not had a significant impact on foreign equity investors. Conversely, foreign equity flows have had a significant impact on exchange rate of the RMB. From estimation results on the Hong Kong stock market, it was found that mainland Chinese investors have not significantly affected the foreign exchange market of Hong Kong. On the other hand, the results show that exchange rates have had a significant impact on mainland Chinese investors in Hong Kong.Research implications or Originality - In the Shanghai stock market, exchange rates have not had a significant impact on foreign equity investors, which is due to exchange rate risk management by foreign investors. Conversely, a large amount of foreign equity inflows led to the appreciation of the RMB. In the Hong Kong stock market, mainland Chinese investors have not significantly affected the foreign exchange market of Hong Kong, which is due to a limited share of mainland Chinese investment in Hong Kong market capitalization. Conversely, exchange rates have had a significant impact on mainland Chinese investors in Hong Kong, which reveal that mainland Chinese equity flows into Hong Kong increased when the RMB depreciated against the Hong Kong dollar.
The Paradox of Insurance
SSRN
In this Article, we uncover a paradoxical phenomenon that has hitherto largely escaped the attention of legal scholars and economists, yet it has far-reaching implications for insurance law: loss-creation by uninsured parties caused by the presence of insurance. Contrary to the conventional wisdom, we show that insurance can create significant negative externalities by inducing third parties to engage in antisocial, illegal and unethical activities in order to extract money from insureds or insurers. Moreover, as the amount and scope of insurance grows, so does its distortionary effect on third parties. We term this phenomenon the paradox of insurance. The risk and harm-causing effects of insurance are ubiquitous. They can be seen in a myriad of contexts, from medical insurances to automobile liability insurance to kidnapping insurance to directors’ and officers’ liability insurance, and even life insurance. It may even have played a role in the 2008 financial crisis. We also explain the economic, social and psychological reasons for this phenomenon. Our analysis suggests that the downside of insurance is far greater than previously believed; in extreme cases, it may even offset the social benefits of insurance. Against this backdrop, we advance normative recommendations for handing the problem. We start by explaining why the standard techniques that insurers use to curb opportunistic behavior by insureds (deductibles, co-pays, and loss-control or mandatory precautions) are ill-suited to address third party moral hazard; hence, it presents a formidable challenge. We then move on to construct a comprehensive legal response, comprising a combination of self-help, regulatory and technological measures, as well as qui tam suits that allow members of the public to sue opportunistic actors who seek to misappropriate insurance proceeds. Together, these interventions should reduce the incidence of third party moral hazard.
SSRN
In this Article, we uncover a paradoxical phenomenon that has hitherto largely escaped the attention of legal scholars and economists, yet it has far-reaching implications for insurance law: loss-creation by uninsured parties caused by the presence of insurance. Contrary to the conventional wisdom, we show that insurance can create significant negative externalities by inducing third parties to engage in antisocial, illegal and unethical activities in order to extract money from insureds or insurers. Moreover, as the amount and scope of insurance grows, so does its distortionary effect on third parties. We term this phenomenon the paradox of insurance. The risk and harm-causing effects of insurance are ubiquitous. They can be seen in a myriad of contexts, from medical insurances to automobile liability insurance to kidnapping insurance to directors’ and officers’ liability insurance, and even life insurance. It may even have played a role in the 2008 financial crisis. We also explain the economic, social and psychological reasons for this phenomenon. Our analysis suggests that the downside of insurance is far greater than previously believed; in extreme cases, it may even offset the social benefits of insurance. Against this backdrop, we advance normative recommendations for handing the problem. We start by explaining why the standard techniques that insurers use to curb opportunistic behavior by insureds (deductibles, co-pays, and loss-control or mandatory precautions) are ill-suited to address third party moral hazard; hence, it presents a formidable challenge. We then move on to construct a comprehensive legal response, comprising a combination of self-help, regulatory and technological measures, as well as qui tam suits that allow members of the public to sue opportunistic actors who seek to misappropriate insurance proceeds. Together, these interventions should reduce the incidence of third party moral hazard.
The Valuation of No-Negative Equity Guarantees and Equity Release Mortgages
SSRN
We outline the valuation process for a No-Negative Equity Guarantee in an Equity Release Mortgage loan and for an Equity Release Mortgage that has such a guarantee. Illustrative valuations are provided based on the Black ’76 put pricing formula and mortality projections based on the M5, M6 and M7 mortality versions of the Cairns-Blake-Dowd (CBD) family of mortality models. Results indicate that the valuations of No-Negative Equity Guarantees are high relative to loan amounts and subject to considerable model risk but that the valuations of Equity Release Mortgage loans are robust to the choice of mortality model. Results have significant ramifications for industry practice and prudential regulation.
SSRN
We outline the valuation process for a No-Negative Equity Guarantee in an Equity Release Mortgage loan and for an Equity Release Mortgage that has such a guarantee. Illustrative valuations are provided based on the Black ’76 put pricing formula and mortality projections based on the M5, M6 and M7 mortality versions of the Cairns-Blake-Dowd (CBD) family of mortality models. Results indicate that the valuations of No-Negative Equity Guarantees are high relative to loan amounts and subject to considerable model risk but that the valuations of Equity Release Mortgage loans are robust to the choice of mortality model. Results have significant ramifications for industry practice and prudential regulation.
Time-inconsistency with rough volatility
arXiv
arXiv
Motivated by recent advances in rough volatility, this paper investigates the impact of roughness on equilibrium feedback strategies for time-inconsistent objectives. Under a general framework embracing non-Markovian and non-semimartingale models, we develop an extended path-dependent Hamilton-Jacobi-Bellman (PHJB) equation system. A verification theorem is provided. By deriving explicit solutions to three problems, including mean-variance portfolio problem (MVP) with constant risk aversion, MVP for log-returns, and an investment/consumption problem with non-exponential discounting, we present that volatility roughness adjusts the equilibrium strategies considerably, up to 40% in certain settings. Since rough volatility models capture the near-term downside risk by fitting the volatility skews, we interpret the adjustments as a hedge for this risk.
To Be or Not to Be (In): The International Economic Effects of Brexit Uncertainty
SSRN
This paper evaluates the impact of Brexit-related uncertainty on the economies of the UK, EU, and the US. We propose a measure of Brexit uncertainty that has not been employed before in the literature. We first construct a binary variable by listing and selecting Brexit-related events according to their coverage in the front page of Financial Times. We subsequently employ the Qual VAR model of Dueker (2005) to transform this variable to a continuous latent variable that captures uncertainty on important economic and financial variables. Next, this latent variable enters a structural Factor-Augmented Vector AutoRegression (FAVAR) model (Bernanke et al., 2005) combined with 452 macro and financial variables for the sample countries. Overall our results indicate that the prolonged uncertainty about a potential Brexit and, in the case of a Leave vote the terms and the outcome of the negotiations with the EU, had a positive effect on the economies of major EU countries like France, Spain and Italy and negative effects for the UK economy. Domestic activity and gross investment seem to be significantly affected while there is a weaker effect on financial variables and economic sentiment. No effect from the Brexit uncertainty was detected for the US economy. Finally, by employing the Diebold and Yilmaz spillover matrix (2009, 2012) we find that the UK is the most important net sender of uncertainty spillovers in the EU, while Germany and France are among the most important net receivers of uncertainty shocks.
SSRN
This paper evaluates the impact of Brexit-related uncertainty on the economies of the UK, EU, and the US. We propose a measure of Brexit uncertainty that has not been employed before in the literature. We first construct a binary variable by listing and selecting Brexit-related events according to their coverage in the front page of Financial Times. We subsequently employ the Qual VAR model of Dueker (2005) to transform this variable to a continuous latent variable that captures uncertainty on important economic and financial variables. Next, this latent variable enters a structural Factor-Augmented Vector AutoRegression (FAVAR) model (Bernanke et al., 2005) combined with 452 macro and financial variables for the sample countries. Overall our results indicate that the prolonged uncertainty about a potential Brexit and, in the case of a Leave vote the terms and the outcome of the negotiations with the EU, had a positive effect on the economies of major EU countries like France, Spain and Italy and negative effects for the UK economy. Domestic activity and gross investment seem to be significantly affected while there is a weaker effect on financial variables and economic sentiment. No effect from the Brexit uncertainty was detected for the US economy. Finally, by employing the Diebold and Yilmaz spillover matrix (2009, 2012) we find that the UK is the most important net sender of uncertainty spillovers in the EU, while Germany and France are among the most important net receivers of uncertainty shocks.
Trump's Effect on the Chinese Stock Market
SSRN
The U.S. president, Donald Trump, frequently tweets to communicate his thoughts to the public. We evaluate the impact of Trump's China-related tweets on the Chinese stock market. The results suggest that after his presidential inauguration, Trump's tweets with positive sentiment significantly increase the abnormal returns of manufacturing firms listed on the Chinese stock market. Furthermore, an increase in the absolute value of sentiment increases trading volume and market volatility. The positive effect is more pronounced for those subindustries with high exposure to international trade with the United States. The results are robust to various sensitivity tests.
SSRN
The U.S. president, Donald Trump, frequently tweets to communicate his thoughts to the public. We evaluate the impact of Trump's China-related tweets on the Chinese stock market. The results suggest that after his presidential inauguration, Trump's tweets with positive sentiment significantly increase the abnormal returns of manufacturing firms listed on the Chinese stock market. Furthermore, an increase in the absolute value of sentiment increases trading volume and market volatility. The positive effect is more pronounced for those subindustries with high exposure to international trade with the United States. The results are robust to various sensitivity tests.
