Research articles for the 2020-07-02
A Safe Haven Index
SSRN
Gold, U.S. and German government bonds, the Swiss franc and the U.S. dollar and, more recently, Bitcoin are frequently labeled safe havens. This paper proposes a safe haven index (SHI) to benchmark safe haven assets and demonstrates that the SHI exhibits positive returns and increased volatility in crisis periods. Gold has a high safe haven beta and high risk, whereas 10-year U.S.\ and German government bonds have smaller betas and lower risk. In contrast, Bitcoin has a high alpha and an insignificant beta making it a "lucky safe haven''. Finally, a specific analysis of the COVID-19 shock in March 2020 reveals that the safe haven index turned briefly negative, contrasting previous crises over the last 40 years.
SSRN
Gold, U.S. and German government bonds, the Swiss franc and the U.S. dollar and, more recently, Bitcoin are frequently labeled safe havens. This paper proposes a safe haven index (SHI) to benchmark safe haven assets and demonstrates that the SHI exhibits positive returns and increased volatility in crisis periods. Gold has a high safe haven beta and high risk, whereas 10-year U.S.\ and German government bonds have smaller betas and lower risk. In contrast, Bitcoin has a high alpha and an insignificant beta making it a "lucky safe haven''. Finally, a specific analysis of the COVID-19 shock in March 2020 reveals that the safe haven index turned briefly negative, contrasting previous crises over the last 40 years.
Algorithmic market making for options
arXiv
arXiv
In this article, we tackle the problem of a market maker in charge of a book of options on a single liquid underlying asset. By using an approximation of the portfolio in terms of its vega, we show that the seemingly high-dimensional stochastic optimal control problem of an option market maker is in fact tractable. More precisely, when volatility is modeled using a classical stochastic volatility model -- e.g. the Heston model -- the problem faced by an option market maker is characterized by a low-dimensional functional equation that can be solved numerically using a Euler scheme along with interpolation techniques, even for large portfolios. In order to illustrate our findings, numerical examples are provided.
Bank Green Lending and Credit Risk
SSRN
This study empirically investigates the relationship between banks’ green lending and their credit risk, and how Chinese green finance regulations contribute to the solvency of individual banks and the resilience of the financial system as a whole. Using a sample of 41 Chinese banks for the period 2007-2018, we find that the association between a bank’s (relative) green lending as a proportion of its overall loan portfolio, and its credit risk, depends critically on the size and structure of state ownership. While the implementation of China’s Green Credit Policy reduces credit risk for the major state-controlled banks, it increases credit risk for the city and regional commercial banks. This performance difference is largely due to information and expertise asymmetries, with city and regional commercial banks having less access to information and expertise necessary to evaluate the credit risk of green lending. Understanding this phenomenon can help policymakers tailor green finance policies according to banks’ characteristics. It also suggests that mechanisms and platforms for city/regional commercial banks to learn from major state-controlled banks could be beneficial.
SSRN
This study empirically investigates the relationship between banks’ green lending and their credit risk, and how Chinese green finance regulations contribute to the solvency of individual banks and the resilience of the financial system as a whole. Using a sample of 41 Chinese banks for the period 2007-2018, we find that the association between a bank’s (relative) green lending as a proportion of its overall loan portfolio, and its credit risk, depends critically on the size and structure of state ownership. While the implementation of China’s Green Credit Policy reduces credit risk for the major state-controlled banks, it increases credit risk for the city and regional commercial banks. This performance difference is largely due to information and expertise asymmetries, with city and regional commercial banks having less access to information and expertise necessary to evaluate the credit risk of green lending. Understanding this phenomenon can help policymakers tailor green finance policies according to banks’ characteristics. It also suggests that mechanisms and platforms for city/regional commercial banks to learn from major state-controlled banks could be beneficial.
Black Boxes and Market Efficiency: A First Estimate in the Italian Motor-Vehicle Insurance Market
SSRN
The paper addresses the research question of whether black boxes affect the market efficiency, particularly by reducing the level of premiums. The case analyzed is the Italian motor-vehicle insurance market, characterized by the greatest amount of black boxes in the world as a consequence of regulatory interventions that fostered the spread of these kinds of devices. Particularly, using the data provided by the Italian Insurance Authority (IVASS), we show a specific relation between the increasing number of these devices and the decreasing trend in average premium. Conclusive remarks outline that in the near future this efficiency effect may increase because of the specific use of information derived from the black box that reveals the behaviors of the drivers and allows for innovative ways of individually profiling the insurance policies.
SSRN
The paper addresses the research question of whether black boxes affect the market efficiency, particularly by reducing the level of premiums. The case analyzed is the Italian motor-vehicle insurance market, characterized by the greatest amount of black boxes in the world as a consequence of regulatory interventions that fostered the spread of these kinds of devices. Particularly, using the data provided by the Italian Insurance Authority (IVASS), we show a specific relation between the increasing number of these devices and the decreasing trend in average premium. Conclusive remarks outline that in the near future this efficiency effect may increase because of the specific use of information derived from the black box that reveals the behaviors of the drivers and allows for innovative ways of individually profiling the insurance policies.
Board of Directors: The Perspective of Independents in the Performance of Private Organizations? Evidences in Brazil
SSRN
Purpose: The study seeks to verify the influence of the board of directors’ independence on the performance of BM&FBOVESPA listed companies and to analyse which agency conflicts influence the performance of the board of directors.Originality/value: The factor of Brazil being an emerging country which lacks a strict legal system and control factors against corruption in these environments and the public sectors emphasizes the importance of applying the best corporate governance practice code in the main developed countries, reflecting the need for effective supervisory bodies that contribute to better financial performance of companies.Design/methodology/approach: The study involved a quantitative survey using a sample of 33 companies in the highway operating segment and 220 reports from 2010 to 2016. A fixed-effects regression model with panel data was used for analysis.Findings: The results were statistically significant for the board’s independence variables, which confirm the theory that the presence of independents as members of the board positively influences financial management and the company that holds the executive member and chairman of the board positions has a negative effect. The size of the board did not present statistical significance.
SSRN
Purpose: The study seeks to verify the influence of the board of directors’ independence on the performance of BM&FBOVESPA listed companies and to analyse which agency conflicts influence the performance of the board of directors.Originality/value: The factor of Brazil being an emerging country which lacks a strict legal system and control factors against corruption in these environments and the public sectors emphasizes the importance of applying the best corporate governance practice code in the main developed countries, reflecting the need for effective supervisory bodies that contribute to better financial performance of companies.Design/methodology/approach: The study involved a quantitative survey using a sample of 33 companies in the highway operating segment and 220 reports from 2010 to 2016. A fixed-effects regression model with panel data was used for analysis.Findings: The results were statistically significant for the board’s independence variables, which confirm the theory that the presence of independents as members of the board positively influences financial management and the company that holds the executive member and chairman of the board positions has a negative effect. The size of the board did not present statistical significance.
Conditional Sig-Wasserstein GANs for Time Series Generation
SSRN
Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high dimensional probability measures. However, these methods struggle to capture the temporal dependence of joint probability distributions induced by time-series data. Furthermore, long time-series data streams hugely increase the dimension of the target space, which may render generative modelling infeasible. To overcome these challenges, we integrate GANs with mathematically principled and efficient path feature extraction called the signature of a path. The signature of a path is a graded sequence of statistics that provides a universal description for a stream of data, and its expected value characterises the law of the time-series model. In particular, we develop a new metric, (conditional) Sig-$W_1$, that captures the (conditional) joint law of time series models, and use it as a discriminator. The signature feature space enables the explicit representation of the proposed discriminators which alleviates the need for expensive training. Furthermore, we develop a novel generator, called the conditional AR-FNN, which is designed to capture the temporal dependence of time series and can be efficiently trained. We validate our method on both synthetic and empirical dataset and observe that our method consistently and significantly outperforms state-of-the-art benchmarks with respect to measures of similarity and predictive ability.
SSRN
Generative adversarial networks (GANs) have been extremely successful in generating samples, from seemingly high dimensional probability measures. However, these methods struggle to capture the temporal dependence of joint probability distributions induced by time-series data. Furthermore, long time-series data streams hugely increase the dimension of the target space, which may render generative modelling infeasible. To overcome these challenges, we integrate GANs with mathematically principled and efficient path feature extraction called the signature of a path. The signature of a path is a graded sequence of statistics that provides a universal description for a stream of data, and its expected value characterises the law of the time-series model. In particular, we develop a new metric, (conditional) Sig-$W_1$, that captures the (conditional) joint law of time series models, and use it as a discriminator. The signature feature space enables the explicit representation of the proposed discriminators which alleviates the need for expensive training. Furthermore, we develop a novel generator, called the conditional AR-FNN, which is designed to capture the temporal dependence of time series and can be efficiently trained. We validate our method on both synthetic and empirical dataset and observe that our method consistently and significantly outperforms state-of-the-art benchmarks with respect to measures of similarity and predictive ability.
Corporate Culture and Firm Value: Evidence from Crisis
SSRN
We score 10-K text to measure company culture in four dimensions (collaborative, controlling, competitive, and creative). Investigating culture’s role in stability, firms with higher controlling culture fared significantly better during the 2008-09 crisis. The results are robust to alternative crisis episodes and further endogeneity tests. Such positive effect is more evident during bad than normal times. Due to persistence, culture measured up to 10 years prior still predicts returns during the crisis. Finally, firms with stronger controlling culture experienced fewer layoffs, smaller investment cuts, and greater debt issuance. Overall, the controlling culture improves firm stability through reduced capital constraints.
SSRN
We score 10-K text to measure company culture in four dimensions (collaborative, controlling, competitive, and creative). Investigating culture’s role in stability, firms with higher controlling culture fared significantly better during the 2008-09 crisis. The results are robust to alternative crisis episodes and further endogeneity tests. Such positive effect is more evident during bad than normal times. Due to persistence, culture measured up to 10 years prior still predicts returns during the crisis. Finally, firms with stronger controlling culture experienced fewer layoffs, smaller investment cuts, and greater debt issuance. Overall, the controlling culture improves firm stability through reduced capital constraints.
Do Bank Insiders Impede Equity Issuances?
SSRN
We evaluate the role of insider ownership in shaping banks’ equity issuances in response to the global financial crisis. We construct a unique dataset on the ownership structure of U.S. banks and their equity issuances and discover that greater insider ownership leads to less equity issuances. Several tests are consistent with the view that bank insiders are reluctant to reduce their private benefits of control by diluting their ownership through equity issuances. Given the connection between bank equity and lending, the results stress that ownership structure can shape the resilience of banks â€" and hence the entire economy â€" to aggregate shocks.
SSRN
We evaluate the role of insider ownership in shaping banks’ equity issuances in response to the global financial crisis. We construct a unique dataset on the ownership structure of U.S. banks and their equity issuances and discover that greater insider ownership leads to less equity issuances. Several tests are consistent with the view that bank insiders are reluctant to reduce their private benefits of control by diluting their ownership through equity issuances. Given the connection between bank equity and lending, the results stress that ownership structure can shape the resilience of banks â€" and hence the entire economy â€" to aggregate shocks.
Downside Risk in Cryptocurrency Market
SSRN
I look at the cryptocurrency market through the prism of standard multi-factor asset-pricing models with particular attention to the downside market risk. The analysis for 1,700 coins reveals that there is a significant heterogeneity in the exposure to the downside market risk, and that a higher downside risk exposure is associated with higher average returns. The extra downside risk is priced with a statistically significant premium in cross-sectional regressions. Adding the downside risk component to the CAPM and the 3-factor model for cryptocurrencies improves the explanatory power of the models significantly. The downside risk is orthogonal to the size and momentum risks and constitutes an important forth component in the multi-factor cryptocurrency pricing model.
SSRN
I look at the cryptocurrency market through the prism of standard multi-factor asset-pricing models with particular attention to the downside market risk. The analysis for 1,700 coins reveals that there is a significant heterogeneity in the exposure to the downside market risk, and that a higher downside risk exposure is associated with higher average returns. The extra downside risk is priced with a statistically significant premium in cross-sectional regressions. Adding the downside risk component to the CAPM and the 3-factor model for cryptocurrencies improves the explanatory power of the models significantly. The downside risk is orthogonal to the size and momentum risks and constitutes an important forth component in the multi-factor cryptocurrency pricing model.
Dynamic Noisy Rational Expectations Equilibrium with Insider Information
SSRN
We study equilibria in multi-asset and multi-agent continuous-time economies with asymmetric information and bounded rational noise traders. We establish existence of two equilibria. First, a full communication one where the informed agents' signal is disclosed to the market, and static policies are optimal. Second, a partial communication one where the signal disclosed is affine in the informed and noise traders' signals, and dynamic policies are optimal. Here, information asymmetry creates demand for two public funds, as well as a dark pool where private information trades can be implemented. Markets are endogenously complete and equilibrium returns have a three factor structure, with stochastic factors and loadings. Results are valid for constant absolute risk averse investors; general vector diffusions for fundamentals; non-linear terminal payoffs, and non-Gaussian noise trading. Asset price dynamics and public information flows are endogenous, and rational expectations equilibria are special cases of the general results.
SSRN
We study equilibria in multi-asset and multi-agent continuous-time economies with asymmetric information and bounded rational noise traders. We establish existence of two equilibria. First, a full communication one where the informed agents' signal is disclosed to the market, and static policies are optimal. Second, a partial communication one where the signal disclosed is affine in the informed and noise traders' signals, and dynamic policies are optimal. Here, information asymmetry creates demand for two public funds, as well as a dark pool where private information trades can be implemented. Markets are endogenously complete and equilibrium returns have a three factor structure, with stochastic factors and loadings. Results are valid for constant absolute risk averse investors; general vector diffusions for fundamentals; non-linear terminal payoffs, and non-Gaussian noise trading. Asset price dynamics and public information flows are endogenous, and rational expectations equilibria are special cases of the general results.
Effect of COVID-19 on Capital Market with Reference to S&P 500
SSRN
This paper has analyzed the movement of US stock market during the COVID-19 pandemic. The paper has used time series analysis using Vector Autoregression (VAR) model using data from Jan 23, 2020 to June 19, 2020. The finding suggests that Standard and Poor Index which has been used as reference for capital market has shown negative causality with increase in number of new cases at global level.
SSRN
This paper has analyzed the movement of US stock market during the COVID-19 pandemic. The paper has used time series analysis using Vector Autoregression (VAR) model using data from Jan 23, 2020 to June 19, 2020. The finding suggests that Standard and Poor Index which has been used as reference for capital market has shown negative causality with increase in number of new cases at global level.
Emergency Powers in Response to COVID-19: Policy diffusion, Democracy, and Preparedness
arXiv
arXiv
We examine COVID-19-related states of emergency (SOEs) using data on 180 countries in the period January 1 through June 12, 2020. The results suggest that states' declaration of SOEs is driven by both external and internal factors. A permissive regional environment, characterized by many and simultaneously declared SOEs, may have diminished reputational and political costs, making employment of emergency powers more palatable for a wider range of governments. At the same time, internal characteristics, specifically democratic institutions and pandemic preparedness, shaped governments' decisions. Weak democracies with poor pandemic preparedness were considerably more likely to opt for SOEs than dictatorships and robust democracies with higher preparedness. We find no significant association between pandemic impact, measured as national COVID-19-related deaths, and SOEs, suggesting that many states adopted SOEs proactively before the disease spread locally.
General Implied Processes and Direct Implementation of the Fundamental Theorem of Asset Pricing
SSRN
This paper studies the following conceptual question: in what sense is the Fundamental Theorem of Asset Pricing similar to the two-period no-arbitrage theorem (a.k.a., Farkas lemma)? The purpose of studying this question is (1) to study the information that can be extracted from prices of derivatives in a multi-period context, generalizing the result in a two-period case in Breeden and Litzenberger (1978); (2) to find a way to write down explicitly a multi-period arbitrage process, just as a two-period arbitrage can be written down as a vector.To answer the above conceptual question, I break it down into three more specific questions: (1) How to generalize the concept of states to a multi-period model? (2) How to generalize the concept of state price to a multi-period model? (3) In what sense is a multi-period arbitrage process similar to a two-period arbitrage strategy which is just a vector?The key to answering those questions is to explicitly describe the probability space on which price processes are defined, especially what “information flow†means. I adopt the canonical probability space (i.e., the space of all possible paths of some price process) and propose to consider the whole path of as the state variable and the “path pricesâ€(i.e., the equivalent martingale measure) as the analogue of state prices. This paper discusses how we can recover prices of paths using prices of associated derivative securities and then use them to price other derivatives, which contributes to the literature of implied processes. In addition, it also shows that a multi-period arbitrage process can be reduced to a random vector. The theoretical contribution of this paper is that it sheds new light on the nature of arbitrage processes and the Fundamental Theorem of Asset Pricing. Practically it provides a general framework to precisely extract the information contained in prices of frequently-traded derivatives and then price other derivatives.
SSRN
This paper studies the following conceptual question: in what sense is the Fundamental Theorem of Asset Pricing similar to the two-period no-arbitrage theorem (a.k.a., Farkas lemma)? The purpose of studying this question is (1) to study the information that can be extracted from prices of derivatives in a multi-period context, generalizing the result in a two-period case in Breeden and Litzenberger (1978); (2) to find a way to write down explicitly a multi-period arbitrage process, just as a two-period arbitrage can be written down as a vector.To answer the above conceptual question, I break it down into three more specific questions: (1) How to generalize the concept of states to a multi-period model? (2) How to generalize the concept of state price to a multi-period model? (3) In what sense is a multi-period arbitrage process similar to a two-period arbitrage strategy which is just a vector?The key to answering those questions is to explicitly describe the probability space on which price processes are defined, especially what “information flow†means. I adopt the canonical probability space (i.e., the space of all possible paths of some price process) and propose to consider the whole path of as the state variable and the “path pricesâ€(i.e., the equivalent martingale measure) as the analogue of state prices. This paper discusses how we can recover prices of paths using prices of associated derivative securities and then use them to price other derivatives, which contributes to the literature of implied processes. In addition, it also shows that a multi-period arbitrage process can be reduced to a random vector. The theoretical contribution of this paper is that it sheds new light on the nature of arbitrage processes and the Fundamental Theorem of Asset Pricing. Practically it provides a general framework to precisely extract the information contained in prices of frequently-traded derivatives and then price other derivatives.
Investor Attention and Global Market Returns during the COVID-19 Crisis
SSRN
The financial market response to the COVID-19 pandemic provides the first example of a market crash instigated by a health crisis. The crisis provides a unique setting in which to examine the market response to changes in investor attention. We utilise Google search volume (GSV) as a proxy for investor attention. GSV for the “coronavirus†keyword increases substantially from late-February and peaks in mid-March before declining substantially. Our results are broadly consistent with Da et al. (2015), indicating that GSV is primarily a proxy for the attention of retail investors and confirming that investor attention negatively influences global stock returns. A rise in the number of internet searches during the COVID-19 crisis induces a faster rate of information flow into financial markets and so is also associated with higher volatility. The identified relationships are economically and statistically significant even after controlling for macroeconomic effects. Increases in GSV have less impact on government bond yields, with Italian yields rising with investor attention. The more limited role of GSV is likely due to lower participation of retail investors in bond markets. The results suggest that, rather than searching for information on potential stocks to buy (Barber and Odean, 2008), retail investors are searching for information to resolve uncertainty about household FEARS (Da et al., 2015) during the COVID-19 crisis.
SSRN
The financial market response to the COVID-19 pandemic provides the first example of a market crash instigated by a health crisis. The crisis provides a unique setting in which to examine the market response to changes in investor attention. We utilise Google search volume (GSV) as a proxy for investor attention. GSV for the “coronavirus†keyword increases substantially from late-February and peaks in mid-March before declining substantially. Our results are broadly consistent with Da et al. (2015), indicating that GSV is primarily a proxy for the attention of retail investors and confirming that investor attention negatively influences global stock returns. A rise in the number of internet searches during the COVID-19 crisis induces a faster rate of information flow into financial markets and so is also associated with higher volatility. The identified relationships are economically and statistically significant even after controlling for macroeconomic effects. Increases in GSV have less impact on government bond yields, with Italian yields rising with investor attention. The more limited role of GSV is likely due to lower participation of retail investors in bond markets. The results suggest that, rather than searching for information on potential stocks to buy (Barber and Odean, 2008), retail investors are searching for information to resolve uncertainty about household FEARS (Da et al., 2015) during the COVID-19 crisis.
Luck versus Skill in the Cross-Section of Mutual Fund Returns: Reexamining the Evidence
SSRN
Can fund managers beat the market? This is a key economic question as well as an important practical issue for investors. However, prominent academic research offers conflicting answers. Even though Kosowski et al. (2006) and Fama and French (2010) use bootstrap methods to evaluate whether mutual funds outperform, their conclusions are very different. We reconcile their findings. Fama and French capture the cross-section of mutual fund returns, which is attractive from an economic perspective, whereas Kosowski et al. conduct a fund-by-fund analysis. We show that the Fama and French method suffers from an undersampling problem that leads to a failure to reject the null hypothesis of zero alpha, even when some funds generate economically large risk-adjusted returns. In contrast, Kosowski et al. avoid the undersampling problem, but substantially over reject the null hypothesis, even when all funds have a zero alpha. Hence, the truth about mutual fund performance likely lies between the two findings. We present a novel bootstrapping approach that should be useful to future researchers who are choosing between the two approaches.
SSRN
Can fund managers beat the market? This is a key economic question as well as an important practical issue for investors. However, prominent academic research offers conflicting answers. Even though Kosowski et al. (2006) and Fama and French (2010) use bootstrap methods to evaluate whether mutual funds outperform, their conclusions are very different. We reconcile their findings. Fama and French capture the cross-section of mutual fund returns, which is attractive from an economic perspective, whereas Kosowski et al. conduct a fund-by-fund analysis. We show that the Fama and French method suffers from an undersampling problem that leads to a failure to reject the null hypothesis of zero alpha, even when some funds generate economically large risk-adjusted returns. In contrast, Kosowski et al. avoid the undersampling problem, but substantially over reject the null hypothesis, even when all funds have a zero alpha. Hence, the truth about mutual fund performance likely lies between the two findings. We present a novel bootstrapping approach that should be useful to future researchers who are choosing between the two approaches.
Moving Forward from Predictive Regressions: Boosting Asset Allocation Decisions
SSRN
We introduce a flexible utility-based empirical approach to directly determine asset allocation decisions between risky and risk-free assets. This is in contrast to the commonly used two-step approach where least squares optimal statistical equity premium predictions are first constructed to form portfolio weights before economic criteria are used to evaluate resulting portfolio performance. Our singlestep customized gradient boosting method is specifically designed to find optimal portfolio weights in a direct utility maximization. Empirical results of the monthly U.S. data show the superiority of boosted portfolio weights over several benchmarks, generating interpretable results and profitable asset allocation decisions.
SSRN
We introduce a flexible utility-based empirical approach to directly determine asset allocation decisions between risky and risk-free assets. This is in contrast to the commonly used two-step approach where least squares optimal statistical equity premium predictions are first constructed to form portfolio weights before economic criteria are used to evaluate resulting portfolio performance. Our singlestep customized gradient boosting method is specifically designed to find optimal portfolio weights in a direct utility maximization. Empirical results of the monthly U.S. data show the superiority of boosted portfolio weights over several benchmarks, generating interpretable results and profitable asset allocation decisions.
Mutual Fund Liquidity Transformation and Reverse Flight to Liquidity
SSRN
We document that traditionally liquid asset markets, such as those for Treasuries and high-quality corporate bonds, experienced significant strains from unusually high selling pressures during the COVID-19 pandemic, which contrasts with the conventional wisdom of flight to liquidity during crises. We identify the increased reliance on fixed-income mutual funds for liquidity provision as an important contributing factor to this phenomenon. Theoretically and empirically, we show that fixed-income mutual funds transform liquidity by issuing redeemable fund shares backed by a portfolio of liquid and illiquid assets while meeting redemption requests by first selling more liquid assets in their portfolios. Therefore, when investors redeem their fund shares en masse, funds' pecking order of liquidation generates pronounced selling pressure for liquid assets, effectively turning investors' flight to liquidity into the observed reverse flight to liquidity in financial markets. Such volatility in asset markets can be alleviated when financial intermediation is provided by commercial banks.
SSRN
We document that traditionally liquid asset markets, such as those for Treasuries and high-quality corporate bonds, experienced significant strains from unusually high selling pressures during the COVID-19 pandemic, which contrasts with the conventional wisdom of flight to liquidity during crises. We identify the increased reliance on fixed-income mutual funds for liquidity provision as an important contributing factor to this phenomenon. Theoretically and empirically, we show that fixed-income mutual funds transform liquidity by issuing redeemable fund shares backed by a portfolio of liquid and illiquid assets while meeting redemption requests by first selling more liquid assets in their portfolios. Therefore, when investors redeem their fund shares en masse, funds' pecking order of liquidation generates pronounced selling pressure for liquid assets, effectively turning investors' flight to liquidity into the observed reverse flight to liquidity in financial markets. Such volatility in asset markets can be alleviated when financial intermediation is provided by commercial banks.
Optimal Tracking Portfolio with A Ratcheting Capital Benchmark
arXiv
arXiv
This paper studies the finite horizon portfolio management by optimally tracking a ratcheting capital benchmark process. To formulate such an optimal tracking problem, we envision that the fund manager can dynamically inject capital into the portfolio account such that the total capital dominates the nondecreasing benchmark floor process at each intermediate time. The control problem is to minimize the cost of the accumulative capital injection. We first transform the original problem with floor constraints into an unconstrained control problem, however, under a running maximum cost. By identifying a controlled state process with reflection, we next transform the problem further into an equivalent auxiliary problem, which leads to a nonlinear Hamilton-Jacobi-Bellman (HJB) with a Neumann boundary condition. By employing the dual transform, the probabilistic representation approach and some stochastic flow arguments, the existence of the unique classical solution to the dual HJB is established. The verification theorem is carefully proved, which gives the complete characterization of the primal value function and the feedback optimal portfolio.
Performance analysis of Zero Black-Derman-Toy interest rate model in catastrophic events: COVID-19 case study
arXiv
arXiv
In this paper we continue the research of our recent interest rate tree model called Zero Black-Derman-Toy (ZBDT) model, which includes the possibility of a jump at each step to a practically zero interest rate. This approach allows to better match to risk of financial slowdown caused by catastrophic events. We present how to valuate wide range of financial derivatives for such model. The classical Black-Derman-Toy (BDT) model and novel model are described and analogies in their calibration methodology are established. Finally two cases of applications of the novel ZBDT model were introduced. The first of them is the hypothetical case of an S-shape term structure and decreasing volatility of yields. The second case is an application in the structure of United State sovereign bonds of the ZBDT model in the current $2020$ economic slowdown caused by the Coronavirus pandemic. The objective of this study is to understand the differences presented by the valuation in both models for different derivatives.
Principal Portfolios
SSRN
We propose a new asset-pricing framework in which all securities’ signals are used to predict each individual return. While the literature focuses on each security’s own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes cross-predictabilityâ€"leading to three main results. First, we derive the optimal strategy in closed form. It consists of eigenvectors of a “prediction matrix,†which we call “principal portfolios.†Second, we decompose the problem into alpha and beta, yielding optimal strategies with, respectively, zero and positive factor exposure. Third, we provide a new test of asset pricing models. Empirically, principal portfolios deliver significant out-of-sample alphas to standard factors in several data sets.
SSRN
We propose a new asset-pricing framework in which all securities’ signals are used to predict each individual return. While the literature focuses on each security’s own- signal predictability, assuming an equal strength across securities, our framework is flexible and includes cross-predictabilityâ€"leading to three main results. First, we derive the optimal strategy in closed form. It consists of eigenvectors of a “prediction matrix,†which we call “principal portfolios.†Second, we decompose the problem into alpha and beta, yielding optimal strategies with, respectively, zero and positive factor exposure. Third, we provide a new test of asset pricing models. Empirically, principal portfolios deliver significant out-of-sample alphas to standard factors in several data sets.
Proximity to COVID-19 Cases and REIT Equity Returns
SSRN
This paper uses a difference-in-differences approach to examine the role of proximity to COVID-19 infections on the returns of real estate investment trusts (REITs). Using a database from Hong Kong of addresses that COVID-19 patients have resided or visited (i.e. their “geographical footprintâ€), we assess the proximity of properties owned by Hong Kong REITs to COVID-19 cases. Controlling for property-level and REIT characteristics, firm, time and location fixed effects, we find significantly negative effects of COVID-19 cases on stock returns. A REIT with a property within 2 miles of a COVID-19 case had a 0.02% lower daily stock return one day after the COVID-19 case disclosure. This effect is moderated if the REIT property is a residential building.
SSRN
This paper uses a difference-in-differences approach to examine the role of proximity to COVID-19 infections on the returns of real estate investment trusts (REITs). Using a database from Hong Kong of addresses that COVID-19 patients have resided or visited (i.e. their “geographical footprintâ€), we assess the proximity of properties owned by Hong Kong REITs to COVID-19 cases. Controlling for property-level and REIT characteristics, firm, time and location fixed effects, we find significantly negative effects of COVID-19 cases on stock returns. A REIT with a property within 2 miles of a COVID-19 case had a 0.02% lower daily stock return one day after the COVID-19 case disclosure. This effect is moderated if the REIT property is a residential building.
Recent Characteristics of FX Markets in Asia \A Comparison of Japan, Singapore, and Hong Kong SAR \
RePEC
In recent years, turnovers of Foreign Exchange (FX) trading in Singapore and Hong Kong SAR have outweighed those of Japan, and the gap between the two cities and Japan continues to stretch. The two cities consolidate trading of G10 currencies by institutional investors and others by advancing electronic trading. Additionally, a number of treasury departments of overseas financial/non-financial firms are attracted to the two cities, contributing to the increasing trading of Asian currencies in tandem with expanding goods and services trades between China and the ASEAN countries. At this juncture, FX trading related to capital account transactions is relatively small in Asia partly due to capital control measures. However, in the medium to long term, capital account transactions could increase, which would positively affect FX trading. Thinking ahead on post-COVID-19, receiving such capital flows would positively impact on revitalizing the Tokyo FX market, thereby developing Japan fs overall financial markets including capital markets.
RePEC
In recent years, turnovers of Foreign Exchange (FX) trading in Singapore and Hong Kong SAR have outweighed those of Japan, and the gap between the two cities and Japan continues to stretch. The two cities consolidate trading of G10 currencies by institutional investors and others by advancing electronic trading. Additionally, a number of treasury departments of overseas financial/non-financial firms are attracted to the two cities, contributing to the increasing trading of Asian currencies in tandem with expanding goods and services trades between China and the ASEAN countries. At this juncture, FX trading related to capital account transactions is relatively small in Asia partly due to capital control measures. However, in the medium to long term, capital account transactions could increase, which would positively affect FX trading. Thinking ahead on post-COVID-19, receiving such capital flows would positively impact on revitalizing the Tokyo FX market, thereby developing Japan fs overall financial markets including capital markets.
Risk Management and Return Prediction
arXiv
arXiv
With the good development in the financial industry, the market starts to catch people's eyes, not only by the diversified investing choices ranging from bonds and stocks to futures and options but also by the general "high-risk, high-reward" mindset prompting people to put money in the financial market. People are interested in reducing risk at a given level of return since there is no way of having both high returns and low risk. Many researchers have been studying this issue, and the most pioneering one is Harry Markowitz's Modern Portfolio Theory developed in 1952, which is the cornerstone of investment portfolio management and aims at "maximum the return at the given risk". In contrast to that, fifty years later, E. Robert Fernholz's Stochastic Portfolio Theory, as opposed to the normative assumption served as the basis of earlier modern portfolio theory, is consistent with the observable characteristics of actual portfolios and markets. In this paper, after introducing some basic theories of Markowitz's MPT and Fernholz's SPT, then we step across to the application side, trying to figure out under four basic models based on Markowitz Efficient Frontier, including Markowitz Model, Constant Correlation Model, Single Index Model, and Multi-Factor Model, which portfolios will be selected and how do these portfolios perform in the real world. Here we also involve universal Portfolio Algorithmby Thomas M. Cover to select portfolios as a comparison. Besides, each portfolio value at Risk, Expected Shortfall, and corresponding bootstrap confidence interval for risk management will be evaluated. Finally, by utilizing factor analysis and time series models, we could predict the future performance of our four models.
Sensitivity and Simulation Analysis in Excel Without Programming
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Most finance textbooks talk about the benefits of conducting sensitivity and/or Monte Carlo simulation analyses in financial modeling, but mostly limit coverage to commenting on these techniques in passing. This is particularly true when it comes to simulation analysis, which typically requires the use of a third-party add-in or a significant level of programming expertise in VBA. We provide an extensive, step-by-step guide demonstrating how data tables in Excel can be used to easily implement sensitivity and simulation analyses. This approach requires only minor modifications to the base-case model; without the need for any programming experience.
SSRN
Most finance textbooks talk about the benefits of conducting sensitivity and/or Monte Carlo simulation analyses in financial modeling, but mostly limit coverage to commenting on these techniques in passing. This is particularly true when it comes to simulation analysis, which typically requires the use of a third-party add-in or a significant level of programming expertise in VBA. We provide an extensive, step-by-step guide demonstrating how data tables in Excel can be used to easily implement sensitivity and simulation analyses. This approach requires only minor modifications to the base-case model; without the need for any programming experience.
The Challenge of Regulatory Excellence
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Regulation is a high-stakes enterprise marked by tremendous challenges and relentless public pressure. Regulators are expected to protect the public from harms associated with economic activity and technological change without unduly impeding economic growth or efficiency. Regulators today also face new demands, such as adapting to rapidly changing and complex financial instruments, the emergence of the sharing economy, and the potential hazards of synthetic biology and other innovations. Faced with these challenges, regulators need a lodestar for what constitutes high-quality regulation and guidance on how to improve their organizations’ performance. In the book Achieving Regulatory Excellence, leading regulatory experts across various disciplines seek to provide the guidance regulators so often lack, and to elucidate what it means to be an excellent regulator. This introductory chapter sets the stage for defining regulatory excellence by clarifying regulators’ primary challenges, functions, and ultimate goals. The chapter also emphasizes that even though regulation is widely associated with technical expertise, excellent regulators must also focus on “people excellence†by building an internal culture that fosters and reinforces humility, openness, empathy, and a steadfast commitment to public service.
SSRN
Regulation is a high-stakes enterprise marked by tremendous challenges and relentless public pressure. Regulators are expected to protect the public from harms associated with economic activity and technological change without unduly impeding economic growth or efficiency. Regulators today also face new demands, such as adapting to rapidly changing and complex financial instruments, the emergence of the sharing economy, and the potential hazards of synthetic biology and other innovations. Faced with these challenges, regulators need a lodestar for what constitutes high-quality regulation and guidance on how to improve their organizations’ performance. In the book Achieving Regulatory Excellence, leading regulatory experts across various disciplines seek to provide the guidance regulators so often lack, and to elucidate what it means to be an excellent regulator. This introductory chapter sets the stage for defining regulatory excellence by clarifying regulators’ primary challenges, functions, and ultimate goals. The chapter also emphasizes that even though regulation is widely associated with technical expertise, excellent regulators must also focus on “people excellence†by building an internal culture that fosters and reinforces humility, openness, empathy, and a steadfast commitment to public service.
The Effect of Business Group Affiliation on Trade Credit Financing: Evidence from Korean Firms
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This paper explains how a firm demands and supplies trade credit financing in short-term debt markets of Korea. In particular, we examine the effect of business group affiliation on trade credit financing, finding that a firm’s affiliation to a large business group has a positive effect on trade credit demand but a negative effect on trade credit supply. The results suggest that the extra bargaining power of large business groups enables group-affiliates to provide substantially less trade credits but to demand more when they face financial constraints. However, we do not find evidence that trade credit financing functions as an instrument to subsidize member firms through internal capital markets. These findings shed new lights on the role of business group affiliation in determining the demand and supply of trade credit financing in short-term debt markets.
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This paper explains how a firm demands and supplies trade credit financing in short-term debt markets of Korea. In particular, we examine the effect of business group affiliation on trade credit financing, finding that a firm’s affiliation to a large business group has a positive effect on trade credit demand but a negative effect on trade credit supply. The results suggest that the extra bargaining power of large business groups enables group-affiliates to provide substantially less trade credits but to demand more when they face financial constraints. However, we do not find evidence that trade credit financing functions as an instrument to subsidize member firms through internal capital markets. These findings shed new lights on the role of business group affiliation in determining the demand and supply of trade credit financing in short-term debt markets.
The Effect of Credit Ratings on Disclosure: Evidence from the Recalibration of Moody's Municipal Ratings
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This paper examines how credit rating levels affect municipal debt issuers’ disclosure decisions. Using exogenous upgrades in credit rating levels caused by the recalibration of Moody's municipal ratings scale in 2010, we find that upgraded municipalities significantly reduce their disclosure of required continuing financial information, relative to unaffected municipalities. Consistent with a reduction in debtholders’ demand for information driving these results, the reduction in disclosure is greater when municipal bonds are held by investors who relied more on disclosure ex ante. However, we also find that the reduction in disclosure does not manifest when issuers are monitored by underwriters with greater issuerâ€specific expertise and when issuers are subject to direct regulatory enforcement through the receipt of federal funding. Overall, our results suggest that higher credit rating levels lower investor demand for disclosure in the municipal market, and highlight the role of underwriters and direct regulatory enforcement in maintaining disclosure levels when investor demand is low.
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This paper examines how credit rating levels affect municipal debt issuers’ disclosure decisions. Using exogenous upgrades in credit rating levels caused by the recalibration of Moody's municipal ratings scale in 2010, we find that upgraded municipalities significantly reduce their disclosure of required continuing financial information, relative to unaffected municipalities. Consistent with a reduction in debtholders’ demand for information driving these results, the reduction in disclosure is greater when municipal bonds are held by investors who relied more on disclosure ex ante. However, we also find that the reduction in disclosure does not manifest when issuers are monitored by underwriters with greater issuerâ€specific expertise and when issuers are subject to direct regulatory enforcement through the receipt of federal funding. Overall, our results suggest that higher credit rating levels lower investor demand for disclosure in the municipal market, and highlight the role of underwriters and direct regulatory enforcement in maintaining disclosure levels when investor demand is low.
The Effect of Firm-Level ESG Practices on Macroeconomic Performance
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This paper investigates whether the development and adoption of firm-level environmental, social and governance (ESG) practices affects national macroeconomic performance, and whether this differs between developed countries and emerging economies. Using dynamic panel techniques â€" generalised method-of-moments (GMM) estimators â€" we find that an increase of micro-ESG performance can result in the improvement of living standards as measured by GDP per capita. When we test this link by country type, we find that firm-level social performance in a country is positively associated with GDP per capita in both developed countries and emerging economies. As for the other two components of firm-level ESG measures, namely environmental and governance performance, we find that these affect macroeconomic performance in emerging economies, but that the effects remain insignificant in developed countries. While further research is needed, these results may be of particular interest to policymakers and central banks, as they suggest that encouraging the adoption of ESG practices at the firm-level could support macroeconomic performance.
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This paper investigates whether the development and adoption of firm-level environmental, social and governance (ESG) practices affects national macroeconomic performance, and whether this differs between developed countries and emerging economies. Using dynamic panel techniques â€" generalised method-of-moments (GMM) estimators â€" we find that an increase of micro-ESG performance can result in the improvement of living standards as measured by GDP per capita. When we test this link by country type, we find that firm-level social performance in a country is positively associated with GDP per capita in both developed countries and emerging economies. As for the other two components of firm-level ESG measures, namely environmental and governance performance, we find that these affect macroeconomic performance in emerging economies, but that the effects remain insignificant in developed countries. While further research is needed, these results may be of particular interest to policymakers and central banks, as they suggest that encouraging the adoption of ESG practices at the firm-level could support macroeconomic performance.
The Effects of Mobile Phone Technology, Knowledge Creation and Diffusion on Inclusive Human Development in Sub-Saharan Africa
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This paper examines the joint effects of mobile phone technology, knowledge creation and diffusion on inclusive human development in 49 sub-Saharan African (SSA) countries. The empirical evidence is based on Tobit regressions for the period 2000-2012. The net effects of interactions between the mobile phone, knowledge creation and diffusion variables are positive indicating that the combined effects of these variables improve inclusive human development in SSA countries. Further analysis dividing the data set into a number of fundamental characteristics based on economic, legal, religion and political stability associated with African economies show that mobile phone penetration and associated innovation in SSA improve inclusive human development irrespective of the country’s level of income, legal origins, religious orientation and the state of the nation. The pupil-teacher ratio exerts a negative influence on the outcome variable which is favorable for inclusive human development because higher ratios denote lower education quality since more pupils are accommodated by fewer teachers. The study contributes to innovation diffusion theory and economic development literature.
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This paper examines the joint effects of mobile phone technology, knowledge creation and diffusion on inclusive human development in 49 sub-Saharan African (SSA) countries. The empirical evidence is based on Tobit regressions for the period 2000-2012. The net effects of interactions between the mobile phone, knowledge creation and diffusion variables are positive indicating that the combined effects of these variables improve inclusive human development in SSA countries. Further analysis dividing the data set into a number of fundamental characteristics based on economic, legal, religion and political stability associated with African economies show that mobile phone penetration and associated innovation in SSA improve inclusive human development irrespective of the country’s level of income, legal origins, religious orientation and the state of the nation. The pupil-teacher ratio exerts a negative influence on the outcome variable which is favorable for inclusive human development because higher ratios denote lower education quality since more pupils are accommodated by fewer teachers. The study contributes to innovation diffusion theory and economic development literature.
The Price and Volume Response to Earnings Announcements in the Corporate Bond Market
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We examine abnormal returns and trading activity in bond markets around earnings announcements. Previous work provides mixed evidence on the relative impact of positive and negative surprises and the degree of response in investment-grade and speculative-grade bonds. We find that these announcements convey value-relevant information for both positive and negative earnings surprises in both investment and speculative-grade bonds. We also document significant heterogeneity in the response across industries, with muted responses in both abnormal returns and trading activity for bonds of firms in the financial and utilities industries.
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We examine abnormal returns and trading activity in bond markets around earnings announcements. Previous work provides mixed evidence on the relative impact of positive and negative surprises and the degree of response in investment-grade and speculative-grade bonds. We find that these announcements convey value-relevant information for both positive and negative earnings surprises in both investment and speculative-grade bonds. We also document significant heterogeneity in the response across industries, with muted responses in both abnormal returns and trading activity for bonds of firms in the financial and utilities industries.
Using Supra-Covered Bonds to Enhance Liquidity in the Euro Area: A Proposal for the Post-COVID-19 Recovery
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The discussion on the necessity of a larger volume of very highly quality (VHQLA) and liquid asset in the euro area has been very extensive. The debate on expanding the pool of comparable euro area assets focuses on “safe assetsâ€, often on various combinations of government bonds, most of which would not entail a strong increase in euro VHQLA. This paper explores a different option, complementary to the existing ones, based on the creation of a safe European asset backed by fully private assets. The idea proposed in this paper is the issuance of supra-covered bonds by a central European institution. The latter are bonds issued by the central issuer and backed by covered bonds, which banks would have created using their mortgages as their cover pool. The aim is to increase substantially the outstanding amount of euro VHQLA. Such an asset would be very beneficial also during crisis periods, like the current COVID-19 crisis, by allowing banks to transform mortgages into very high quality and liquid assets that can be used for funding and as a collateral in operations with the Eurosystem, thus enhancing the possible credit sustain to the SMEs. This paper assesses the main effects of such proposal on banks under different possible scenarios.
SSRN
The discussion on the necessity of a larger volume of very highly quality (VHQLA) and liquid asset in the euro area has been very extensive. The debate on expanding the pool of comparable euro area assets focuses on “safe assetsâ€, often on various combinations of government bonds, most of which would not entail a strong increase in euro VHQLA. This paper explores a different option, complementary to the existing ones, based on the creation of a safe European asset backed by fully private assets. The idea proposed in this paper is the issuance of supra-covered bonds by a central European institution. The latter are bonds issued by the central issuer and backed by covered bonds, which banks would have created using their mortgages as their cover pool. The aim is to increase substantially the outstanding amount of euro VHQLA. Such an asset would be very beneficial also during crisis periods, like the current COVID-19 crisis, by allowing banks to transform mortgages into very high quality and liquid assets that can be used for funding and as a collateral in operations with the Eurosystem, thus enhancing the possible credit sustain to the SMEs. This paper assesses the main effects of such proposal on banks under different possible scenarios.
Why Does the Recovery Theorem Not Work Empirically? An Intrinsic Explanation
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In a recent seminal paper, Ross proposed an attractive strategy to extract the physical distribution and risk aversion from just state prices. However, empirical papers that try to use his Recovery Theorem almost all lead to a depressing conclusion: the recovery theorem does not work. Both the state-price matrix and the recovered physical transition matrix are unreasonable and highly sensitive to subjective specifications and constraints. BoroviÄka, Hansen and Scheinkman (2016) proposes a widely-accepted explanation for the empirical failure: according to the Hansen-Scheinkman decomposition established in Hansen and Scheinkman (2009), the assumption about the stochastic discount factor in Ross (2015) is equivalent to arbitrarily setting the martingale component to be 1, which is quite unlikely in reality.In this paper, I argue that in contrast to BoroviÄka, Hansen and Scheinkman (2016), the assumption about the stochastic discount factor in Ross (2015) actually does not set the martingale component in the Hansen-Scheinkman decomposition to be 1. What causes the empirical failure is actually a time-homogeneous state-price matrix, which induces quite restrictive implications on the underlying price process and those restrictions are easily violated in reality. In particular, when the underlying price is used as the state variable or as one component of the state vector, this restriction becomes an eigenvalue equation that contradicts the important eigenvalue equation in Ross (2015), which in this case makes the Recovery Theorem not just empirically implausible, but also logically inconsistent.
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In a recent seminal paper, Ross proposed an attractive strategy to extract the physical distribution and risk aversion from just state prices. However, empirical papers that try to use his Recovery Theorem almost all lead to a depressing conclusion: the recovery theorem does not work. Both the state-price matrix and the recovered physical transition matrix are unreasonable and highly sensitive to subjective specifications and constraints. BoroviÄka, Hansen and Scheinkman (2016) proposes a widely-accepted explanation for the empirical failure: according to the Hansen-Scheinkman decomposition established in Hansen and Scheinkman (2009), the assumption about the stochastic discount factor in Ross (2015) is equivalent to arbitrarily setting the martingale component to be 1, which is quite unlikely in reality.In this paper, I argue that in contrast to BoroviÄka, Hansen and Scheinkman (2016), the assumption about the stochastic discount factor in Ross (2015) actually does not set the martingale component in the Hansen-Scheinkman decomposition to be 1. What causes the empirical failure is actually a time-homogeneous state-price matrix, which induces quite restrictive implications on the underlying price process and those restrictions are easily violated in reality. In particular, when the underlying price is used as the state variable or as one component of the state vector, this restriction becomes an eigenvalue equation that contradicts the important eigenvalue equation in Ross (2015), which in this case makes the Recovery Theorem not just empirically implausible, but also logically inconsistent.
