Research articles for the 2019-05-14
A Dimension-invariant Cascade Model for VIX Futures
SSRN
We propose a new model of volatility by allowing for a cascading structure of volatility components. The cascading feature is achieved by introducing an increasing structure to the speed of mean reversion. It allows us to add as many components as desired with no additional parameter, effectively defeating the curse of dimensionality often seen in traditional models. The flexibility in choosing the number of components enables rich dynamics in the term structure of both spot VIX and VIX futures, without the need to introduce price jumps. We derive a semi-closed form solution to the VIX futures price, and find that our 6-factor model with only 6 parameters can closely fit spot VIX and VIX futures data from 2004 to 2015 and produce out of sample pricing errors of magnitudes similar to those of in-sample errors.
SSRN
We propose a new model of volatility by allowing for a cascading structure of volatility components. The cascading feature is achieved by introducing an increasing structure to the speed of mean reversion. It allows us to add as many components as desired with no additional parameter, effectively defeating the curse of dimensionality often seen in traditional models. The flexibility in choosing the number of components enables rich dynamics in the term structure of both spot VIX and VIX futures, without the need to introduce price jumps. We derive a semi-closed form solution to the VIX futures price, and find that our 6-factor model with only 6 parameters can closely fit spot VIX and VIX futures data from 2004 to 2015 and produce out of sample pricing errors of magnitudes similar to those of in-sample errors.
A New Take on the Relationship between Interest rates and Credit Spreads
SSRN
We revisit the link between interest rates and corporate bond credit spreads by applying Rigobon’s (2003) heteroskedasticity identification methodology to their interconnected dynamics through a bivariate VAR system. This novel approach allows us to account for endogeneity issues and to use this framework to test the various possible explanations for the credit spread â€" interest rate relation that have been proposed by the literature over the years. This innovative methodology allows us to conclude that credit spreads do indeed respond negatively to interest rates, yet that this negative relation is surprisingly robust to macroeconomic shocks, interest rates characteristics, different volatility regimes, and bond ratings. We also find the magnitude of the negative relation to be larger for high-yield bonds than for investment-grade bonds. Additionally, we are also able to rule out business cycles, the optionlike feature of callable bonds proposed by Duffee (1998), as well as the term spread as the main drivers of the negative nature of the relationship.
SSRN
We revisit the link between interest rates and corporate bond credit spreads by applying Rigobon’s (2003) heteroskedasticity identification methodology to their interconnected dynamics through a bivariate VAR system. This novel approach allows us to account for endogeneity issues and to use this framework to test the various possible explanations for the credit spread â€" interest rate relation that have been proposed by the literature over the years. This innovative methodology allows us to conclude that credit spreads do indeed respond negatively to interest rates, yet that this negative relation is surprisingly robust to macroeconomic shocks, interest rates characteristics, different volatility regimes, and bond ratings. We also find the magnitude of the negative relation to be larger for high-yield bonds than for investment-grade bonds. Additionally, we are also able to rule out business cycles, the optionlike feature of callable bonds proposed by Duffee (1998), as well as the term spread as the main drivers of the negative nature of the relationship.
A Solvable Two-dimensional Optimal Stopping Problem in the Presence of Ambiguity
arXiv
arXiv
According to conventional wisdom, ambiguity accelerates optimal timing by decreasing the value of waiting in comparison with the unambiguous benchmark case. We study this mechanism in a multidimensional setting and show that in a multifactor model ambiguity does not only influence the rate at which the underlying processes are expected to grow, it also affects the rate at which the problem is discounted. This mechanism where nature also selects the rate at which the problem is discounted cannot appear in a one-dimensional setting and as such we identify an indirect way of how ambiguity affects optimal timing.
An Elementary Approach to the Fundamental Theorems of Asset Pricing in Jump-Diffusion Markets with Credit Risks, Funding Risks, and Collateral
SSRN
We present an elementary approach to fundamental theorems of asset and derivative pricing for a wide class of jump-diffusion markets in which there are credit risks, funding risks, and collateral. The approach yields new and intuitive proofs of both the first and second Fundamental Theorems of Asset Pricing. We give examples of how the framework incorporates the gamut of industry pricing techniques from simple Black-Scholes pricing to recent results known as Funding Valuation Adjustments (FVA). The main contribution is the insight and intuition into the nature of the fundamental theorems that is afforded by the simplicity of the setup and the consequent reliance on only the most basic results from linear algebra.
SSRN
We present an elementary approach to fundamental theorems of asset and derivative pricing for a wide class of jump-diffusion markets in which there are credit risks, funding risks, and collateral. The approach yields new and intuitive proofs of both the first and second Fundamental Theorems of Asset Pricing. We give examples of how the framework incorporates the gamut of industry pricing techniques from simple Black-Scholes pricing to recent results known as Funding Valuation Adjustments (FVA). The main contribution is the insight and intuition into the nature of the fundamental theorems that is afforded by the simplicity of the setup and the consequent reliance on only the most basic results from linear algebra.
Approximation of Optimal Transport problems with marginal moments constraints
arXiv
arXiv
Optimal Transport (OT) problems arise in a wide range of applications, from physics to economics. Getting numerical approximate solution of these problems is a challenging issue of practical importance. In this work, we investigate the relaxation of the OT problem when the marginal constraints are replaced by some moment constraints. Using Tchakaloff's theorem, we show that the Moment Constrained Optimal Transport problem (MCOT) is achieved by a finite discrete measure. Interestingly, for multimarginal OT problems, the number of points weighted by this measure scales linearly with the number of marginal laws, which is encouraging to bypass the curse of dimension. This approximation method is also relevant for Martingale OT problems. We show the convergence of the MCOT problem toward the corresponding OT problem. In some fundamental cases, we obtain rates of convergence in $O(1/n)$ or $O(1/n^2)$ where $n$ is the number of moments, which illustrates the role of the moment functions. Last, we present algorithms exploiting the fact that the MCOT is reached by a finite discrete measure and provide numerical examples of approximations.
Asset Pricing with Heterogeneous Beliefs and Illiquidity
arXiv
arXiv
This paper studies the equilibrium price of an asset that is traded in continuous time between N agents who have heterogeneous beliefs about the state process underlying the asset's payoff. We propose a tractable model where agents maximize expected returns under quadratic costs on inventories and trading rates. The unique equilibrium price is characterized by a weakly coupled system of linear parabolic equations which shows that holding and liquidity costs play dual roles. We derive the leading-order asymptotics for small transaction and holding costs which give further insight into the equilibrium and the consequences of illiquidity.
Bankacılıkta Kapasite Planlama: Şube Operasyon Faaliyetleri Üzerine Kavramsal Bir İnceleme (Capacity Planning in Banking: A Conceptual Review upon Branch Operation Activities)
SSRN
Turkish Abstract: Türk Bankacılık Sektörü finansal göstergeler açısından büyümesini sürdürmektedir. Buna karşın son zamanlarda sektördeki personel sayısının azaldığı görülmektedir. Bu gelişmenin temelinde bankaların kapasite planlama faaliyetlerine ağırlık vermeleri ve atıl kapasiteleri tasfiye etmeleri yer almaktadır. Son zamanlarda artan önemi nedeni ile bankacılıkta kapasite planlamaya yönelik bu çalışma hazırlanmıştır. Söz konusu çalışma ile bankacılıkta kapasite planlamaya ilişkin kavramsal çerçevenin ortaya konması amaçlanmıştır. Ek olarak, bankaların kapasite planlama faaliyetlerinde dikkat etmesi gereken hususlar vurgulanmış ve şube operasyon faaliyetleri üzerine bir kapasite planlama örneğine yer verilmiştir. Ayrıca çalışma sonucunda, kapasite planlama faaliyetlerinin sağlıklı şekilde yürütülebilmesi ve bankaların bu faaliyetlerden fayda sağlayabilmeleri için bankalarda menfaat çatışması olmaksızın çalışacak merkezi kapasite planlaması bölümlerinin kurulması önerilmiştir. Türkiye’de bankacılıkta kapasite planlamaya yönelik çalışma bulunmadığından yapılan çalışma bu yönüyle öncü bir çalışma olma özelliği taşımaktadır. English Abstract: Turkish Banking Sector has been continuing growth in terms of financial indicators. Despite that, it is seen that the number of personnel in the sector has been declining recently. Focus of banks on capacity planning activities and liquidation of idle capacities are at the core of these developments. This work on capacity planning in banking is prepared due to increasing importance in recent times. It is aimed to present the conceptual framework regarding capacity planning in banking with the study. In addition, the issues that banks should pay attention to in capacity planning activities are emphasized and an example of capacity planning on branch operation is given. Also, it is suggested that central capacity planning departments should be set up to work without conflicts of interest in banks so that capacity planning activities can be carried out in a healthy way and that the banks can benefit from these activities. This paper is pioneer study because of the fact that there is no study about capacity planning in banking sector in Turkey.
SSRN
Turkish Abstract: Türk Bankacılık Sektörü finansal göstergeler açısından büyümesini sürdürmektedir. Buna karşın son zamanlarda sektördeki personel sayısının azaldığı görülmektedir. Bu gelişmenin temelinde bankaların kapasite planlama faaliyetlerine ağırlık vermeleri ve atıl kapasiteleri tasfiye etmeleri yer almaktadır. Son zamanlarda artan önemi nedeni ile bankacılıkta kapasite planlamaya yönelik bu çalışma hazırlanmıştır. Söz konusu çalışma ile bankacılıkta kapasite planlamaya ilişkin kavramsal çerçevenin ortaya konması amaçlanmıştır. Ek olarak, bankaların kapasite planlama faaliyetlerinde dikkat etmesi gereken hususlar vurgulanmış ve şube operasyon faaliyetleri üzerine bir kapasite planlama örneğine yer verilmiştir. Ayrıca çalışma sonucunda, kapasite planlama faaliyetlerinin sağlıklı şekilde yürütülebilmesi ve bankaların bu faaliyetlerden fayda sağlayabilmeleri için bankalarda menfaat çatışması olmaksızın çalışacak merkezi kapasite planlaması bölümlerinin kurulması önerilmiştir. Türkiye’de bankacılıkta kapasite planlamaya yönelik çalışma bulunmadığından yapılan çalışma bu yönüyle öncü bir çalışma olma özelliği taşımaktadır. English Abstract: Turkish Banking Sector has been continuing growth in terms of financial indicators. Despite that, it is seen that the number of personnel in the sector has been declining recently. Focus of banks on capacity planning activities and liquidation of idle capacities are at the core of these developments. This work on capacity planning in banking is prepared due to increasing importance in recent times. It is aimed to present the conceptual framework regarding capacity planning in banking with the study. In addition, the issues that banks should pay attention to in capacity planning activities are emphasized and an example of capacity planning on branch operation is given. Also, it is suggested that central capacity planning departments should be set up to work without conflicts of interest in banks so that capacity planning activities can be carried out in a healthy way and that the banks can benefit from these activities. This paper is pioneer study because of the fact that there is no study about capacity planning in banking sector in Turkey.
Bitcoin’s Return Behaviour: What Do We Know So Far?
SSRN
In this paper we study the daily return behavior of Bitcoin digital currency. We propose the use of generalized hyperbolic distributions (GH) to model Bitcoin's return. Our, results show that GH is a very good candidate to model this return.
SSRN
In this paper we study the daily return behavior of Bitcoin digital currency. We propose the use of generalized hyperbolic distributions (GH) to model Bitcoin's return. Our, results show that GH is a very good candidate to model this return.
Can Survey-Based Information Help Assess Investment Gaps in the EU?
SSRN
This study illustrates how information from micro-level and survey-based databases can be used, along with macroeconomic indicators, to provide a better understanding of corporate investment obstacles across the EU. To show this, we use a novel dataset merging firm-level data from the European Investment Bank Investment Survey (EIBIS) and hard data from corporations’ balance sheet and P&L information. We show that the indicators of impediments to investment at the country level, which can be derived from aggregating qualitative answers, correlate relatively well with macro-based hard data, which are commonly considered as determinants of investments in macro-based models. After controlling for firm-specific characteristics, the perceived investment gap (the difference between desired and actual investment) remains correlated with the reported impediments. While access to finance is not the most reported obstacle, reporting it has the highest information content. Moreover, the signal intensifies when it is given by “weaker†firms, defined as those that are smaller, and/or more indebted, and/or less profitable and/or with lower liquidity positions. From a policy standpoint, our findings suggest that survey-based information can be a useful input to complement both macro and micro hard data and better inform the design of targeted policies to support investment.
SSRN
This study illustrates how information from micro-level and survey-based databases can be used, along with macroeconomic indicators, to provide a better understanding of corporate investment obstacles across the EU. To show this, we use a novel dataset merging firm-level data from the European Investment Bank Investment Survey (EIBIS) and hard data from corporations’ balance sheet and P&L information. We show that the indicators of impediments to investment at the country level, which can be derived from aggregating qualitative answers, correlate relatively well with macro-based hard data, which are commonly considered as determinants of investments in macro-based models. After controlling for firm-specific characteristics, the perceived investment gap (the difference between desired and actual investment) remains correlated with the reported impediments. While access to finance is not the most reported obstacle, reporting it has the highest information content. Moreover, the signal intensifies when it is given by “weaker†firms, defined as those that are smaller, and/or more indebted, and/or less profitable and/or with lower liquidity positions. From a policy standpoint, our findings suggest that survey-based information can be a useful input to complement both macro and micro hard data and better inform the design of targeted policies to support investment.
Collaboration and Power Laws for Financial Research Institutions
SSRN
A new means to promote collaboration is for one researcher to work across multiple institutions. We show that, accompanying the fast growth of cross-affiliation in financial research, scale-free power laws characterize the resulting highly-skewed distributions of top finance journal publications of worldwide institutions. We propose an explanation of the empirical power laws, based on a network model featuring two identified mechanisms: nonlinear growth and linear preferential attachment. The model indicates that preferential allocation of publications by cumulative advantages effectively engenders dispersion in the research output of the institutions, while accelerated growth in collaboration provides a counterforce that restores their homogeneity.
SSRN
A new means to promote collaboration is for one researcher to work across multiple institutions. We show that, accompanying the fast growth of cross-affiliation in financial research, scale-free power laws characterize the resulting highly-skewed distributions of top finance journal publications of worldwide institutions. We propose an explanation of the empirical power laws, based on a network model featuring two identified mechanisms: nonlinear growth and linear preferential attachment. The model indicates that preferential allocation of publications by cumulative advantages effectively engenders dispersion in the research output of the institutions, while accelerated growth in collaboration provides a counterforce that restores their homogeneity.
Connecting Sharpe ratio and Student t-statistic, and beyond
arXiv
arXiv
Sharpe ratio is widely used in asset management to compare and benchmark funds and asset managers. It computes the ratio of the excess return over the strategy standard deviation. However, the elements to compute the Sharpe ratio, namely, the expected returns and the volatilities are unknown numbers and need to be estimated statistically. This means that the Sharpe ratio used by funds is subject to be error prone because of statistical estimation error. Lo (2002), Mertens (2002) derive explicit expressions for the statistical distribution of the Sharpe ratio using standard asymptotic theory under several sets of assumptions (independent normally distributed - and identically distributed returns). In this paper, we provide the exact distribution of the Sharpe ratio for independent normally distributed return. In this case, the Sharpe ratio statistic is up to a rescaling factor a non centered Student distribution whose characteristics have been widely studied by statisticians. The asymptotic behavior of our distribution provide the result of Lo (2002). We also illustrate the fact that the empirical Sharpe ratio is asymptotically optimal in the sense that it achieves the Cramer Rao bound. We then study the empirical SR under AR(1) assumptions and investigate the effect of compounding period on the Sharpe (computing the annual Sharpe with monthly data for instance). We finally provide general formula in this case of heteroscedasticity and autocorrelation.
Directors’ Ties to Non-CEO Executives: Information Advantage or Entrenchment?
SSRN
We examine how connections between independent directors and non-CEO executives influence board performance. This overlooked form of within-firm ties can increase board effectiveness by improving directors’ access to firm-specific information. Alternatively, such connections may weaken board monitoring by undermining directors’ independence. Consistent with the former, we find that firms with directorâ€"executive ties have stronger CEO turnover-performance sensitivity, make better acquisition decisions, and are less likely to engage in financial misconduct. Overall, the evidence suggests that, unlike directorâ€"CEO ties that were shown to adversely impact board monitoring, directorâ€"executive connections enhance board performance and help reign in the CEO.
SSRN
We examine how connections between independent directors and non-CEO executives influence board performance. This overlooked form of within-firm ties can increase board effectiveness by improving directors’ access to firm-specific information. Alternatively, such connections may weaken board monitoring by undermining directors’ independence. Consistent with the former, we find that firms with directorâ€"executive ties have stronger CEO turnover-performance sensitivity, make better acquisition decisions, and are less likely to engage in financial misconduct. Overall, the evidence suggests that, unlike directorâ€"CEO ties that were shown to adversely impact board monitoring, directorâ€"executive connections enhance board performance and help reign in the CEO.
Do Financial Analysts Herd?
SSRN
Financial analysts may have strategic incentives to herd or to anti-herd when issuing forecasts of firms' earnings. This paper develops and implements a new test to examine whether such incentives exist and to identify the form of strategic behavior. We use the equilibrium property of the finite-player forecasting game of Kim and Shim (2019) that forecast dispersion decreases as the number of forecasters increases if and only if there is strategic complementarity in their forecasts. We find strong evidence that supports strategic herding behavior of financial analysts. This finding is robust to different forecast horizons and sequential forecast release.
SSRN
Financial analysts may have strategic incentives to herd or to anti-herd when issuing forecasts of firms' earnings. This paper develops and implements a new test to examine whether such incentives exist and to identify the form of strategic behavior. We use the equilibrium property of the finite-player forecasting game of Kim and Shim (2019) that forecast dispersion decreases as the number of forecasters increases if and only if there is strategic complementarity in their forecasts. We find strong evidence that supports strategic herding behavior of financial analysts. This finding is robust to different forecast horizons and sequential forecast release.
Drivers of Productivity in the Spanish Banking Sector: Recent Evidence
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We analyse the drivers of total factor productivity of Spanish banks from early 2000, including the last financial crisis and the post-crisis period. This allows us to study changes in productivity following a major restructuring process in the banking sector such as the one experienced in Spain. Overall, we find that following a period of continued growth, productivity declined after the height of the crisis, though large banks were less affected. We also find that risk, capital levels, competition and input prices were important drivers of the differences in productivity change between banks. Finally, our results suggest that, by the end of our sample period, there was still some room for potential improvements in productivity via exploiting scale economies and enhancing cost efficiency. These opportunities appear to be generally greater for the smaller banks in our sample.
SSRN
We analyse the drivers of total factor productivity of Spanish banks from early 2000, including the last financial crisis and the post-crisis period. This allows us to study changes in productivity following a major restructuring process in the banking sector such as the one experienced in Spain. Overall, we find that following a period of continued growth, productivity declined after the height of the crisis, though large banks were less affected. We also find that risk, capital levels, competition and input prices were important drivers of the differences in productivity change between banks. Finally, our results suggest that, by the end of our sample period, there was still some room for potential improvements in productivity via exploiting scale economies and enhancing cost efficiency. These opportunities appear to be generally greater for the smaller banks in our sample.
Dynamic Incentives for Buy-Side Analysts
SSRN
We develop a dynamic adverse selection model where a career-concerned buy-side analyst advises a fund manager about investment decisions. The analyst's ability is privately known, as is any information she learns over time. The manager wants to elicit information to maximize fund performance while also identifying and retaining high-skill analysts. We characterize the optimal dynamic contract, show that it has several features supported by empirical evidence, and derive novel testable implications. The fund manager's optimal contract both maximizes the value of information and screens out low-skill analysts by incentivizing the analyst to always provide honest advice.
SSRN
We develop a dynamic adverse selection model where a career-concerned buy-side analyst advises a fund manager about investment decisions. The analyst's ability is privately known, as is any information she learns over time. The manager wants to elicit information to maximize fund performance while also identifying and retaining high-skill analysts. We characterize the optimal dynamic contract, show that it has several features supported by empirical evidence, and derive novel testable implications. The fund manager's optimal contract both maximizes the value of information and screens out low-skill analysts by incentivizing the analyst to always provide honest advice.
Dynamic Volatility Management: From Conditional Volatility to Realized Volatility
SSRN
The volatility of concern in conventional volatility-managed strategies such as volatility-targeting strategy and mean-variance optimization is the expected conditional volatility. However for investors, it is the realized volatility that is important, because there is only one realization in the market. Simply managing the conditional volatility may not manage well the realized volatility of the actual portfolio performance. This article provides a multi-period strategy that directly manages the realized volatility over a long horizon. More specifically, the strategy maximizes the expected portfolio value subject to an upper cap on the realized volatility. Our out-of-sample backtesting results show that this novel strategy delivers higher risk-adjusted returns compared to the volatility-targeting strategy, and that it successfully caps the realized volatility below the targeted level. The results are consistent across twelve equity markets and five targeted volatility levels.
SSRN
The volatility of concern in conventional volatility-managed strategies such as volatility-targeting strategy and mean-variance optimization is the expected conditional volatility. However for investors, it is the realized volatility that is important, because there is only one realization in the market. Simply managing the conditional volatility may not manage well the realized volatility of the actual portfolio performance. This article provides a multi-period strategy that directly manages the realized volatility over a long horizon. More specifically, the strategy maximizes the expected portfolio value subject to an upper cap on the realized volatility. Our out-of-sample backtesting results show that this novel strategy delivers higher risk-adjusted returns compared to the volatility-targeting strategy, and that it successfully caps the realized volatility below the targeted level. The results are consistent across twelve equity markets and five targeted volatility levels.
Entrepreneurial Finance, Home Equity, and Monetary Policy
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We model entrepreneurial finance using a combination of fiat money, traditional bank loans, and home equity loans. The banking sector is over-the- counter, where bargaining determines the pass-through from the nominal interest rate to the bank lending rate, characterizing the transmission channel of monetary policy. The results show that the strength of this channel depends on the combination of nominal and real assets used to finance investments, and thus declines in the extent to which housing is accepted as collateral. A calibration to the U.S. economy supports the theoretical results and provides novel insights on entrepreneurial finance between 2000 and 2016.
SSRN
We model entrepreneurial finance using a combination of fiat money, traditional bank loans, and home equity loans. The banking sector is over-the- counter, where bargaining determines the pass-through from the nominal interest rate to the bank lending rate, characterizing the transmission channel of monetary policy. The results show that the strength of this channel depends on the combination of nominal and real assets used to finance investments, and thus declines in the extent to which housing is accepted as collateral. A calibration to the U.S. economy supports the theoretical results and provides novel insights on entrepreneurial finance between 2000 and 2016.
From Currency Volatilities to Global Equity Correlations
SSRN
We derive and empirically test a theoretical link between exchange rate volatility and global equity correlations. Starting with option-implied currency volatilities, we use variants of existing currency models, global capital flows, international parity, the Taylor rule, and some simplifying assumptions to theoretically link foreign exchange options-implied volatilities and future global equity correlations. Using data from January 1999 to June 2015, we test our hypothesis and find that exchange rate implied volatilities â€" coupled with one-period ex-post correlations â€" more accurately predict subsequent equity market correlations than other models. Our findings have implications for portfolio diversification, forecast of overall equity portfolio volatility, and portfolio optimization.
SSRN
We derive and empirically test a theoretical link between exchange rate volatility and global equity correlations. Starting with option-implied currency volatilities, we use variants of existing currency models, global capital flows, international parity, the Taylor rule, and some simplifying assumptions to theoretically link foreign exchange options-implied volatilities and future global equity correlations. Using data from January 1999 to June 2015, we test our hypothesis and find that exchange rate implied volatilities â€" coupled with one-period ex-post correlations â€" more accurately predict subsequent equity market correlations than other models. Our findings have implications for portfolio diversification, forecast of overall equity portfolio volatility, and portfolio optimization.
Horses for Courses: Mean-Variance for Asset Allocation and 1/N for Stock Selection
SSRN
For various organizational reasons, large investors typically split their portfolio decision into two stages - asset allocation and stock selection. We hypothesise that mean-variance models are superior to equal weighting for asset allocation, while the reverse applies for stock selection, as estimation errors are less of a problem for mean-variance models when used for asset allocation than for stock selection. We confirm this hypothesis in separate analyses of US and international equities using four different types of mean-variance model (Bayes-Stein, Black-Litterman, Bayesian diffuse prior and Markowitz), a range of parameter settings, and a simulation analysis calibrated to US data.
SSRN
For various organizational reasons, large investors typically split their portfolio decision into two stages - asset allocation and stock selection. We hypothesise that mean-variance models are superior to equal weighting for asset allocation, while the reverse applies for stock selection, as estimation errors are less of a problem for mean-variance models when used for asset allocation than for stock selection. We confirm this hypothesis in separate analyses of US and international equities using four different types of mean-variance model (Bayes-Stein, Black-Litterman, Bayesian diffuse prior and Markowitz), a range of parameter settings, and a simulation analysis calibrated to US data.
Macroprudential Policy and Bank Systemic Risk
SSRN
This paper investigates the effectiveness of macroprudential policy to contain the systemic risk of European banks between 2000 and 2017. We use a new database (MaPPED) collected by experts at the ECB and national central banks with narrative information on a broad range of instruments which are tracked over their life cycle. Using a dynamic panel framework at a monthly frequency enables us to assess the impact of macroprudential tools and their design on the banks' systemic risk both in the short and the long run. We furthermore decompose the systemic risk measure in an individual bank risk component and a systemic linkage component. This is of particular interest because microprudential policy focuses on the tail risk of an individual bank while macroprudential policy targets systemic risk by addressing the interlinkages and common exposures across banks. On average, all banks benefit from macroprudential tools in terms of their individual risk. We find that credit growth tools and exposure limits exhibit the most pronounced downward effect on the individual risk component. However, we find evidence for a risk-shifting effect which is more pronounced for retail-oriented banks. The effects are heterogeneous across banks with respect to the systemic linkage component. Liquidity tools and measures aimed at increasing the resilience of banks decrease the systemic linkage of banks. However, these tools appear to be most effective for distressed banks. Our results have implications for the optimal design of macroprudential instruments.
SSRN
This paper investigates the effectiveness of macroprudential policy to contain the systemic risk of European banks between 2000 and 2017. We use a new database (MaPPED) collected by experts at the ECB and national central banks with narrative information on a broad range of instruments which are tracked over their life cycle. Using a dynamic panel framework at a monthly frequency enables us to assess the impact of macroprudential tools and their design on the banks' systemic risk both in the short and the long run. We furthermore decompose the systemic risk measure in an individual bank risk component and a systemic linkage component. This is of particular interest because microprudential policy focuses on the tail risk of an individual bank while macroprudential policy targets systemic risk by addressing the interlinkages and common exposures across banks. On average, all banks benefit from macroprudential tools in terms of their individual risk. We find that credit growth tools and exposure limits exhibit the most pronounced downward effect on the individual risk component. However, we find evidence for a risk-shifting effect which is more pronounced for retail-oriented banks. The effects are heterogeneous across banks with respect to the systemic linkage component. Liquidity tools and measures aimed at increasing the resilience of banks decrease the systemic linkage of banks. However, these tools appear to be most effective for distressed banks. Our results have implications for the optimal design of macroprudential instruments.
Merton's portfolio problem with power utility under Volterra Heston model
arXiv
arXiv
This paper investigates Merton's portfolio problem in a rough stochastic environment described by Volterra Heston model. The model has a non-Markovian and non-semimartingale structure. By considering an auxiliary random process, we solve the portfolio optimization problem with the martingale optimality principle. The optimal strategy is derived in a semi-closed form that depends on the solution of a Riccati-Volterra equation. Numerical studies suggest that investment demand decreases with the roughness of the market.
Moody and Dissatisfied: A Possible Resolution of Asset Pricing Puzzles
SSRN
Based on recent microeconomic evidence, I propose a consumption-based model with power-utility preferences where the local curvature of the utility function explicitly depends on a stationary macroeconomic state variable. The state variable is defined as the log difference between the contemporaneous per capita aggregate consumption rate and a benchmark which is external and predetermined. If this consumption benchmark is sufficiently larger than the per capita aggregate consumption rate at the steady state, and if the local curvature of the utility function is mildly countercyclical, the model can match the high unconditional equity risk premium and Sharpe ratio in the U.S. data while giving a low relative risk aversion over a large interval around the steady state. The model also produces a low unconditional mean and variance for the risk-free rate and a high unconditional mean and variance for the price-dividend ratio. Finally, it gives a countercyclical conditional risk premium, countercyclical conditional Sharpe ratio, return predictability and a downward sloping (annualized) risk premium-maturity curve for long-maturity risky assets.
SSRN
Based on recent microeconomic evidence, I propose a consumption-based model with power-utility preferences where the local curvature of the utility function explicitly depends on a stationary macroeconomic state variable. The state variable is defined as the log difference between the contemporaneous per capita aggregate consumption rate and a benchmark which is external and predetermined. If this consumption benchmark is sufficiently larger than the per capita aggregate consumption rate at the steady state, and if the local curvature of the utility function is mildly countercyclical, the model can match the high unconditional equity risk premium and Sharpe ratio in the U.S. data while giving a low relative risk aversion over a large interval around the steady state. The model also produces a low unconditional mean and variance for the risk-free rate and a high unconditional mean and variance for the price-dividend ratio. Finally, it gives a countercyclical conditional risk premium, countercyclical conditional Sharpe ratio, return predictability and a downward sloping (annualized) risk premium-maturity curve for long-maturity risky assets.
On the consistency of jump-diffusion dynamics for FX rates under inversion
arXiv
arXiv
In this note we investigate the consistency under inversion of jump diffusion processes in the Foreign Exchange (FX) market. In other terms, if the EUR/USD FX rate follows a given type of dynamics, under which conditions will USD/EUR follow the same type of dynamics? In order to give a numerical description of this property, we first calibrate a Heston model and a SABR model to market data, plotting their smiles together with the smiles of the reciprocal processes. Secondly, we determine a suitable local volatility structure ensuring consistency. We subsiquently introduce jumps and analyze both constant jump size (Poisson process) and random jump size (compound Poisson process). In the first scenario, we find that consistency is automatically satisfied, for the jump size of the inverted process is a constant as well. The second case is more delicate, since we need to make sure that the distribution of jumps in the domestic measure is the same as the distribution of jumps in the foreign measure. We determine a fairly general class of admissible densities for the jump size in the domestic measure satisfying the condition.
Portfolio Optimization with Higher-order Stochastic Dominance Constraints
SSRN
A framework is developed for portfolio optimization with higher-order Stochastic Dominance constraints. A finite system of restrictions on the lower partial moments can be used for evaluating the efficiency of a given benchmark and for constructing enhanced portfolios which dominate the benchmark for the relevant class of risk averters. The system can be linearlized for discrete distributions, allowing for implementation using Linear Programming. Imposing higher-order restrictions expands the set of improvement possibilities and mitigates the risk of suboptimality due to estimation error. A simulation study exemplifies these benefits, for a simple hypothetical investment problem. In an empirical application to equity industry rotation, accounting for kurtosis aversion and Decreasing Absolute Prudence improves out-of-sample performance beyond levels achieved using more permissive assumptions.
SSRN
A framework is developed for portfolio optimization with higher-order Stochastic Dominance constraints. A finite system of restrictions on the lower partial moments can be used for evaluating the efficiency of a given benchmark and for constructing enhanced portfolios which dominate the benchmark for the relevant class of risk averters. The system can be linearlized for discrete distributions, allowing for implementation using Linear Programming. Imposing higher-order restrictions expands the set of improvement possibilities and mitigates the risk of suboptimality due to estimation error. A simulation study exemplifies these benefits, for a simple hypothetical investment problem. In an empirical application to equity industry rotation, accounting for kurtosis aversion and Decreasing Absolute Prudence improves out-of-sample performance beyond levels achieved using more permissive assumptions.
Recent Regulation in Credit Risk Management: A Statistical Framework
SSRN
A recently introduced accounting standard, namely the International Financial Reporting Standard 9, requires banks to build provisions based on forward-looking expected loss models. When there is a significant increase in credit risk of a loan, additional provisions must be charged to the income statement. Banks need to set for each loan a threshold defining what such a significant increase in credit risk constitutes. A low threshold allows banks to recognize credit risk early, but leads to income volatility. We introduce a statistical framework to model this trade-off between early recognition of credit risk and avoidance of excessive income volatility. We analyze the resulting optimization problem for different models, relate it to the banking stress test of the European Union, and illustrate it using default data by Standard and Poor’s.
SSRN
A recently introduced accounting standard, namely the International Financial Reporting Standard 9, requires banks to build provisions based on forward-looking expected loss models. When there is a significant increase in credit risk of a loan, additional provisions must be charged to the income statement. Banks need to set for each loan a threshold defining what such a significant increase in credit risk constitutes. A low threshold allows banks to recognize credit risk early, but leads to income volatility. We introduce a statistical framework to model this trade-off between early recognition of credit risk and avoidance of excessive income volatility. We analyze the resulting optimization problem for different models, relate it to the banking stress test of the European Union, and illustrate it using default data by Standard and Poor’s.
Refined by Fire: The Great Depression and Entrepreneurship
SSRN
Industrial production in the United States declined by 47 percent between 1929 and 1933. Motivated by the potential effects that the Great Depression may have had on family and habit formation, this paper quantifies how the severity of the Great Depression within a location may affect contemporaneous entrepreneurship rates. On one hand, a more severe decline in productivity could have persistent effects that adversely affect entrepreneurship today. On the other hand, a more severe decline could have prompted individuals growing up during the Great Depression to become more entrepreneurial and frugal, thereby influencing the values that they emphasized to their children. Consistent with the latter hypothesis, we find that a one percentage point increase in retail sales growth is associated with a 0.04 percentage point decline in entrepreneurship two generations later. Using the Survey of Consumer Finance, we explore the role of personal experience as a moderating factor, finding that individuals in areas more affected by the Depression are more financially sophisticated.
SSRN
Industrial production in the United States declined by 47 percent between 1929 and 1933. Motivated by the potential effects that the Great Depression may have had on family and habit formation, this paper quantifies how the severity of the Great Depression within a location may affect contemporaneous entrepreneurship rates. On one hand, a more severe decline in productivity could have persistent effects that adversely affect entrepreneurship today. On the other hand, a more severe decline could have prompted individuals growing up during the Great Depression to become more entrepreneurial and frugal, thereby influencing the values that they emphasized to their children. Consistent with the latter hypothesis, we find that a one percentage point increase in retail sales growth is associated with a 0.04 percentage point decline in entrepreneurship two generations later. Using the Survey of Consumer Finance, we explore the role of personal experience as a moderating factor, finding that individuals in areas more affected by the Depression are more financially sophisticated.
Riding the Blockchain Mania: Public Firms’ Speculative 8-K Disclosures
SSRN
This paper provides evidence on public firms’ initial 8-K disclosures that mention Blockchain and investors’ response to these disclosures. We categorize the description of Blockchain activities in firms’ 8-Ks as Speculative (e.g., a vague future plan that involves Blockchain) or Existing (e.g., a description of Blockchain product). We document a sharp increase in the number of initial 8-K disclosures of Blockchain, particularly by Speculative firms, coinciding with the rise of Bitcoin prices and excitement in Blockchain technology in the last quarter of 2017. Investors react positively to the Blockchain 8-Ks issued by Speculative firms in the initial seven-day event window, although the reaction is mostly reversed over the 30 days following the disclosure. The reaction is stronger when Bitcoin returns are more positive. Overall, our results are consistent with a situation that troubles the SEC and the financial press: investors overreact to a firm’s first 8-K disclosure of a potential foray into Blockchain technology and that the overreaction is a function of the Bitcoin price bubble.
SSRN
This paper provides evidence on public firms’ initial 8-K disclosures that mention Blockchain and investors’ response to these disclosures. We categorize the description of Blockchain activities in firms’ 8-Ks as Speculative (e.g., a vague future plan that involves Blockchain) or Existing (e.g., a description of Blockchain product). We document a sharp increase in the number of initial 8-K disclosures of Blockchain, particularly by Speculative firms, coinciding with the rise of Bitcoin prices and excitement in Blockchain technology in the last quarter of 2017. Investors react positively to the Blockchain 8-Ks issued by Speculative firms in the initial seven-day event window, although the reaction is mostly reversed over the 30 days following the disclosure. The reaction is stronger when Bitcoin returns are more positive. Overall, our results are consistent with a situation that troubles the SEC and the financial press: investors overreact to a firm’s first 8-K disclosure of a potential foray into Blockchain technology and that the overreaction is a function of the Bitcoin price bubble.
Sales Growth, CEO Pay, and Corporate Governance in India
SSRN
Although stock return-based performance metrics are common in CEO compensation contracts in the US, similar CEO pay arrangements may not be appropriate in India given higher stock return volatility and lower liquidity. Instead, sales growth as a performance metric could be useful in incentivizing Indian CEOs to pursue earnings growth consistent with shareholder value maximization. In this study, we examine the use of sales growth as a performance metric in extant India CEO pay arrangements and whether the usage is consistent with efficiency. Our findings suggest that the weight placed on sales growth in determining CEO compensation in India is positive and is higher for more powerful CEOs. We also find that board vigilance is effective in moderating the weight placed on sales growth in CEO pay arrangements. Finally, we show that the weight placed on sales growth in assessing CEO pay negatively impacts future firm performance, particularly for firms that are in the later stages of the firm lifecycle, are less profitable, and have weaker shareholder monitoring. Collectively, our findings are consistent with inefficiency (efficiency) in CEO pay contracting in the use of sales growth as a performance metric in later (early) stage firms, less (more) profitable firms, and weaker (stronger) shareholder monitoring firms. More broadly, our findings albeit India-specific are of potential interest to CEO pay arrangement debates in the US and elsewhere where sales growth is an important performance metric in determining CEO compensation.
SSRN
Although stock return-based performance metrics are common in CEO compensation contracts in the US, similar CEO pay arrangements may not be appropriate in India given higher stock return volatility and lower liquidity. Instead, sales growth as a performance metric could be useful in incentivizing Indian CEOs to pursue earnings growth consistent with shareholder value maximization. In this study, we examine the use of sales growth as a performance metric in extant India CEO pay arrangements and whether the usage is consistent with efficiency. Our findings suggest that the weight placed on sales growth in determining CEO compensation in India is positive and is higher for more powerful CEOs. We also find that board vigilance is effective in moderating the weight placed on sales growth in CEO pay arrangements. Finally, we show that the weight placed on sales growth in assessing CEO pay negatively impacts future firm performance, particularly for firms that are in the later stages of the firm lifecycle, are less profitable, and have weaker shareholder monitoring. Collectively, our findings are consistent with inefficiency (efficiency) in CEO pay contracting in the use of sales growth as a performance metric in later (early) stage firms, less (more) profitable firms, and weaker (stronger) shareholder monitoring firms. More broadly, our findings albeit India-specific are of potential interest to CEO pay arrangement debates in the US and elsewhere where sales growth is an important performance metric in determining CEO compensation.
Signal-Herding and Cryptocurrencies: Evidence From Equities, Commodities and Energy Markets
SSRN
The paper examines the influence of signals extracted from the behaviour of exogenous factors on herding intensity in the cryptocurrency market. We propose a novel approach whereby extracted signals are endogenized in investors’ decision-making. The signals may induce investors to converge further to (depart from) the market consensus, contributing to herding amplification (herding dampening). The findings reveal substantial asymmetries with respect to herding intensity, which are indicative of the diversity of signals extracted from exogenous factors.
SSRN
The paper examines the influence of signals extracted from the behaviour of exogenous factors on herding intensity in the cryptocurrency market. We propose a novel approach whereby extracted signals are endogenized in investors’ decision-making. The signals may induce investors to converge further to (depart from) the market consensus, contributing to herding amplification (herding dampening). The findings reveal substantial asymmetries with respect to herding intensity, which are indicative of the diversity of signals extracted from exogenous factors.
Solving Euler Equations via Two-Stage Nonparametric Penalized Splines
SSRN
This study proposes a novel nonparametric estimation approach to solving asset-pricing models. Our method is robust to misspecification errors and it inherits a closed-form solution that facilitates ease of implementation. By transforming the Euler equation, our estimate is fully identified, and we establish large sample properties of the proposed estimate for a broad class of stationary Markov state variables. Using the merit of penalized splines, we design a fast data-based algorithm to e↵ectively tune the smoothing parameter. Our approach exhibits superior performance even with a small sample size. For application, using US data from 1947 to 2017, we reinvestigate the return predictability and find that high implied dividend yield, obtained from our misspecification-free approach, significantly predicts lower future cash flows and higher interest rates at short horizons.
SSRN
This study proposes a novel nonparametric estimation approach to solving asset-pricing models. Our method is robust to misspecification errors and it inherits a closed-form solution that facilitates ease of implementation. By transforming the Euler equation, our estimate is fully identified, and we establish large sample properties of the proposed estimate for a broad class of stationary Markov state variables. Using the merit of penalized splines, we design a fast data-based algorithm to e↵ectively tune the smoothing parameter. Our approach exhibits superior performance even with a small sample size. For application, using US data from 1947 to 2017, we reinvestigate the return predictability and find that high implied dividend yield, obtained from our misspecification-free approach, significantly predicts lower future cash flows and higher interest rates at short horizons.
Stock Market Uncertainty and U.S. Monetary Policy: Evidence from Intraday Option Data
SSRN
We empirically study the behavior of stock market uncertainty around U.S. monetary policy decisions using high-frequency option quotes. We find that FOMC announcements trigger sudden and large movements in uncertainty, with highly significant drops for horizons of up to one year. These moves are particularly strong for tail uncertainty, with average changes of more than 15 percentage points for left tail and 21 percentage points for right tail uncertainty. We thereby confirm that the Fed promotes financial stability. Our results are not driven by realizing risks but by a reduction of downside and upside potential in the market. We further classify the meetings into rate cuts, surprises, type of news conveyed, and press conferences to provide evidence for the many faces of stock market uncertainty around FOMC announcements.
SSRN
We empirically study the behavior of stock market uncertainty around U.S. monetary policy decisions using high-frequency option quotes. We find that FOMC announcements trigger sudden and large movements in uncertainty, with highly significant drops for horizons of up to one year. These moves are particularly strong for tail uncertainty, with average changes of more than 15 percentage points for left tail and 21 percentage points for right tail uncertainty. We thereby confirm that the Fed promotes financial stability. Our results are not driven by realizing risks but by a reduction of downside and upside potential in the market. We further classify the meetings into rate cuts, surprises, type of news conveyed, and press conferences to provide evidence for the many faces of stock market uncertainty around FOMC announcements.
Supply Chain Finance and Impacts of Consumers’ Sustainability Awareness
SSRN
Several new methods have been proposed for supply chain finance (SCF) with bank credits, but none of them mentions how to solve the borrowers' moral hazard problems in SCF. This paper examines the moral hazard problem in supply chain financing with procurement contract (or purchase order). We show that since supply chain is an up-down directed structure, when financing with the procurement contract, the supplier's effort monitoring task can be rendered to the procurement contract, which can secure the supplier's optimal effort and capital choices in production. Hence, compared to separate lending, the supplier's credit rationing problem can be mitigated, and most importantly, banks' under-estimation on the supplier's default risk and the over-estimation on the retailer's default risk will both decrease. We further show that the retailer's corporate social responsibility expenditure can increase consumers' brand recognition, thus when facing demand shocks arising from consumer's unexpected concerns, the retailer can better stabilize the firm value.
SSRN
Several new methods have been proposed for supply chain finance (SCF) with bank credits, but none of them mentions how to solve the borrowers' moral hazard problems in SCF. This paper examines the moral hazard problem in supply chain financing with procurement contract (or purchase order). We show that since supply chain is an up-down directed structure, when financing with the procurement contract, the supplier's effort monitoring task can be rendered to the procurement contract, which can secure the supplier's optimal effort and capital choices in production. Hence, compared to separate lending, the supplier's credit rationing problem can be mitigated, and most importantly, banks' under-estimation on the supplier's default risk and the over-estimation on the retailer's default risk will both decrease. We further show that the retailer's corporate social responsibility expenditure can increase consumers' brand recognition, thus when facing demand shocks arising from consumer's unexpected concerns, the retailer can better stabilize the firm value.
Sustainable Investing and the Cross-Section of Maximum Drawdown
arXiv
arXiv
We use supervised learning to identify factors that predict the cross-section of maximum drawdown for stocks in the US equity market. Our data run from January 1980 to June 2018 and our analysis includes ordinary least squares, penalized linear regressions, tree-based models, and neural networks. We find that the most important predictors tended to be consistent across models, and that non-linear models had better predictive power than linear models. Predictive power was higher in calm periods than stressed periods, and environmental, social, and governance indicators augmented predictive power for non-linear models.
The Blurring of Corporate Investor Nationality and Complex Ownership Structures
SSRN
Recent years have seen a significant increase in complexity of multinational enterprises (MNEs) ownership structures. Complex corporate structures raise concerns on the effectiveness of national and international investment policies, based on the notion of investors' nationality. This motivates this research effort aimed at analysing the ownership structures of some 700 thousand foreign affiliates (FAs). A new methodology, the bottom-up approach, is introduced. The main objective is to empirically map the "shareholder space" of FAs, along the vertical dimension, from the direct shareholders to the ultimate owners. We find that FAs are often part of transnational investment chains; more than 40\% of foreign affiliates have direct and ultimate shareholders in different jurisdictions ("double or multiple passports"). Based on shareholders' nationality, we then propose and empirically analyse the salient features of four main archetypes of FAs ownership structure: plain foreign, conduit structures, round-tripping and domestic hubs. Each poses specific challenges to the policy-maker.
SSRN
Recent years have seen a significant increase in complexity of multinational enterprises (MNEs) ownership structures. Complex corporate structures raise concerns on the effectiveness of national and international investment policies, based on the notion of investors' nationality. This motivates this research effort aimed at analysing the ownership structures of some 700 thousand foreign affiliates (FAs). A new methodology, the bottom-up approach, is introduced. The main objective is to empirically map the "shareholder space" of FAs, along the vertical dimension, from the direct shareholders to the ultimate owners. We find that FAs are often part of transnational investment chains; more than 40\% of foreign affiliates have direct and ultimate shareholders in different jurisdictions ("double or multiple passports"). Based on shareholders' nationality, we then propose and empirically analyse the salient features of four main archetypes of FAs ownership structure: plain foreign, conduit structures, round-tripping and domestic hubs. Each poses specific challenges to the policy-maker.
The Design and Regulation of High Frequency Traders
SSRN
Central to the ability of a high frequency trader to make money is speed. In order to be first to trading opportunities firms invest in the fastest hardware and the shortest connections between their machines and the markets. This, however, is not enough, algorithms must be short, no more than a few lines of code. As a result there is a trade-off in the design of optimal HFT strategies: being the fastest necessitates being less sophisticated. To understand the effect of this tension a computational model is presented that captures latency, both of code execution and information transmission. Trading algorithms are modelled through genetic programmes with longer programmes allowing more sophisticated decisions at the cost of slower execution times. It is shown that depending on the market composition short fast strategies and slower more sophisticated strategies may both be viable and exploit different trading opportunities. The relative profits of these different approaches vary, however, slow traders benefit from their presence. A suite of regulations are tested to manage the risks associated with high frequency trading, the majority are found to be ineffective, however, constraining the ratio of orders to trades may be promising.
SSRN
Central to the ability of a high frequency trader to make money is speed. In order to be first to trading opportunities firms invest in the fastest hardware and the shortest connections between their machines and the markets. This, however, is not enough, algorithms must be short, no more than a few lines of code. As a result there is a trade-off in the design of optimal HFT strategies: being the fastest necessitates being less sophisticated. To understand the effect of this tension a computational model is presented that captures latency, both of code execution and information transmission. Trading algorithms are modelled through genetic programmes with longer programmes allowing more sophisticated decisions at the cost of slower execution times. It is shown that depending on the market composition short fast strategies and slower more sophisticated strategies may both be viable and exploit different trading opportunities. The relative profits of these different approaches vary, however, slow traders benefit from their presence. A suite of regulations are tested to manage the risks associated with high frequency trading, the majority are found to be ineffective, however, constraining the ratio of orders to trades may be promising.
The Effect of Foreign Institutional Ownership on Corporate Tax Avoidance: International Evidence
SSRN
This study examines whether foreign institutional investors (FIIs) help explain variation in corporate tax avoidance and whether mechanisms such as tax morality, investment horizon, and corporate governance underlie the relation between FIIs and tax avoidance. We find robust evidence that FIIs are negatively associated with corporate tax avoidance. Moreover, this negative association is dominated by FIIs from countries with high tax morality, FIIs with long-term investment horizons, and FIIs from countries with high corporate governance quality. We conclude that FIIs play an active role in shaping corporate tax avoidance policy.
SSRN
This study examines whether foreign institutional investors (FIIs) help explain variation in corporate tax avoidance and whether mechanisms such as tax morality, investment horizon, and corporate governance underlie the relation between FIIs and tax avoidance. We find robust evidence that FIIs are negatively associated with corporate tax avoidance. Moreover, this negative association is dominated by FIIs from countries with high tax morality, FIIs with long-term investment horizons, and FIIs from countries with high corporate governance quality. We conclude that FIIs play an active role in shaping corporate tax avoidance policy.
The Effects of Ownership Concentration and Corporate Governance on Corporate Risk-Taking: The Case of Thailand
SSRN
We investigate the effects of ownership concentration and corporate governance on the extent of risk-taking in an important emerging economy- Thailand. Ownership in Thai firms are substantially more concentrated than that in developed economies, providing a unique opportunity to study the effect of highly concentrated ownership on risk-taking. Large owners are under-diversified and are thus more vulnerable to the firm’s idiosyncratic risk. Therefore, they tend to advocate less risky corporate policies and strategies. Consistent with this notion, we find that more concentrated ownership induces firms to take significantly less risk. The results are corroborated by additional analysis, including an instrumental-variable analysis and propensity score matching. Finally, we also document a non-monotonic effect of corporate governance on risk-taking.
SSRN
We investigate the effects of ownership concentration and corporate governance on the extent of risk-taking in an important emerging economy- Thailand. Ownership in Thai firms are substantially more concentrated than that in developed economies, providing a unique opportunity to study the effect of highly concentrated ownership on risk-taking. Large owners are under-diversified and are thus more vulnerable to the firm’s idiosyncratic risk. Therefore, they tend to advocate less risky corporate policies and strategies. Consistent with this notion, we find that more concentrated ownership induces firms to take significantly less risk. The results are corroborated by additional analysis, including an instrumental-variable analysis and propensity score matching. Finally, we also document a non-monotonic effect of corporate governance on risk-taking.
The Impact of the 2012 NZX Listing Rule Change on Board Composition and Company Performance
SSRN
We examine the impact of the December 2012 NZX listing rule change that introduced compulsory disclosure about gender diversity on New Zealand boards. Most notably, the rate of growth in female-held directorships increased significantly after the introduction of the new rule, resulting in, by 2016, average female board representation being approximately double what it had been in 2012. However, we find no relationship between this response and company performance. Across six measures of operating and financial performance, firms that responded most strongly to the listing rule change fared, on average, no better or worse than those that stuck closer to the status quo.
SSRN
We examine the impact of the December 2012 NZX listing rule change that introduced compulsory disclosure about gender diversity on New Zealand boards. Most notably, the rate of growth in female-held directorships increased significantly after the introduction of the new rule, resulting in, by 2016, average female board representation being approximately double what it had been in 2012. However, we find no relationship between this response and company performance. Across six measures of operating and financial performance, firms that responded most strongly to the listing rule change fared, on average, no better or worse than those that stuck closer to the status quo.
Uncertainty, Financial Markets, and Monetary Policy over the Last Century
SSRN
What has been the effect of uncertainty shocks in the U.S. economy over the last century? What are the historical roles of the financial channel and monetary policy channel in propagating uncertainty shocks? Our empirical strategies enable us to distinguish between the effects of uncertainty shocks on key macroeconomic and financial variables transmitted through each channel. A hundred years of data further allow us to answer these questions from a novel historical perspective. This paper finds robust evidence that financial conditions have played a crucial role in propagating uncertainty shocks over the last century, supporting many theoretical and empirical studies emphasizing the role of financial frictions in understanding uncertainty shocks. However, heightened uncertainty does not amplify the adverse effect of financial shocks, suggesting an asymmetric interaction between uncertainty and financial shocks. Interestingly, the stance of monetary policy seems to play only a minor role in propagating uncertainty shocks, which is in sharp contrast to the recent claim that binding zero-lower-bound amplifies the negative effect of uncertainty shocks. We argue that the contribution of constrained monetary policy to amplifying uncertainty shocks is largely masked by the joint concurrence of binding zero-lower-bound and tightened financial conditions.
SSRN
What has been the effect of uncertainty shocks in the U.S. economy over the last century? What are the historical roles of the financial channel and monetary policy channel in propagating uncertainty shocks? Our empirical strategies enable us to distinguish between the effects of uncertainty shocks on key macroeconomic and financial variables transmitted through each channel. A hundred years of data further allow us to answer these questions from a novel historical perspective. This paper finds robust evidence that financial conditions have played a crucial role in propagating uncertainty shocks over the last century, supporting many theoretical and empirical studies emphasizing the role of financial frictions in understanding uncertainty shocks. However, heightened uncertainty does not amplify the adverse effect of financial shocks, suggesting an asymmetric interaction between uncertainty and financial shocks. Interestingly, the stance of monetary policy seems to play only a minor role in propagating uncertainty shocks, which is in sharp contrast to the recent claim that binding zero-lower-bound amplifies the negative effect of uncertainty shocks. We argue that the contribution of constrained monetary policy to amplifying uncertainty shocks is largely masked by the joint concurrence of binding zero-lower-bound and tightened financial conditions.
Under-reaction in the Sovereign CDS Market
SSRN
The sovereign CDS market has been growing rapidly in recent years, with a gross notional amount of around 2 trillion dollars in 2015. We document a strong momentum effect in this market. Its unique feature is that this momentum strategy returns are positively skewed and higher during recessions. Hence, this effect cannot be attributed to momentum crash risk or exposure to business cycles. Our evidence is consistent with the interpretation that the effect is due to investors’ initial underreaction to sovereign credit information followed by corrections, especially during public announcements of credit rating or outlook changes of the underlying countries.
SSRN
The sovereign CDS market has been growing rapidly in recent years, with a gross notional amount of around 2 trillion dollars in 2015. We document a strong momentum effect in this market. Its unique feature is that this momentum strategy returns are positively skewed and higher during recessions. Hence, this effect cannot be attributed to momentum crash risk or exposure to business cycles. Our evidence is consistent with the interpretation that the effect is due to investors’ initial underreaction to sovereign credit information followed by corrections, especially during public announcements of credit rating or outlook changes of the underlying countries.
Underreaction to Macroeconomic News Announcements and the Downward-Sloping Security Market Line
SSRN
The relationship between betas and expected returns is positive on days with pre-scheduled macroeconomic news announcements (MNAs), but negative on the other days. This paper shows that stock price underreaction to MNAs explains the negative relation on non-MNA days. First, I use high-frequency S&P 500 futures data to identify positive (good) and negative (bad) news from macro announcements. Stocks with low sensitivities to bad macro news perform poorly on the following non-announcement days. Moreover, the under-performance of low sensitivity stocks is most pronounced when investor disagreement is high and short-selling constraints are binding. Subsequently, I show that the security market line on non-announcement days is particularly downward-sloping among stocks with low sensitivities to bad macro news. The results are consistent with stocks, especially those with high market betas, underreact to bad news on MNA days when high shorting costs prevent prices from reflecting pessimists’ beliefs, and experience low returns on the following non-announcement days.
SSRN
The relationship between betas and expected returns is positive on days with pre-scheduled macroeconomic news announcements (MNAs), but negative on the other days. This paper shows that stock price underreaction to MNAs explains the negative relation on non-MNA days. First, I use high-frequency S&P 500 futures data to identify positive (good) and negative (bad) news from macro announcements. Stocks with low sensitivities to bad macro news perform poorly on the following non-announcement days. Moreover, the under-performance of low sensitivity stocks is most pronounced when investor disagreement is high and short-selling constraints are binding. Subsequently, I show that the security market line on non-announcement days is particularly downward-sloping among stocks with low sensitivities to bad macro news. The results are consistent with stocks, especially those with high market betas, underreact to bad news on MNA days when high shorting costs prevent prices from reflecting pessimists’ beliefs, and experience low returns on the following non-announcement days.
Understanding Sovereign Credit Ratings: Text-Based Evidence From the Credit Rating Reports
SSRN
In this paper we apply a novel approach to identifying the qualitative judgement of the rating committee in sovereign credit ratings. We extend the traditional regression with new measures - sentiment and subjectivity scores - obtained by textual sentiment analysis methods. By using an ordered logit with random effects for 98 countries in the period from 1996 to 2017, we find evidence that the subjectivity score provides additional information not captured by previously identified determinants of sovereign credit ratings, even after controlling for political risk, institutional strength and potential bias. The results from the bivariate and multivariate analysis confirm differences in textual sentiment between emerging markets and advanced economies, as well as before and after the 2008 global financial crisis.
SSRN
In this paper we apply a novel approach to identifying the qualitative judgement of the rating committee in sovereign credit ratings. We extend the traditional regression with new measures - sentiment and subjectivity scores - obtained by textual sentiment analysis methods. By using an ordered logit with random effects for 98 countries in the period from 1996 to 2017, we find evidence that the subjectivity score provides additional information not captured by previously identified determinants of sovereign credit ratings, even after controlling for political risk, institutional strength and potential bias. The results from the bivariate and multivariate analysis confirm differences in textual sentiment between emerging markets and advanced economies, as well as before and after the 2008 global financial crisis.
Using Column Generation to Solve Extensions to the Markowitz Model
arXiv
arXiv
We introduce a solution scheme for portfolio optimization problems with cardinality constraints. Typical portfolio optimization problems are extensions of the classical Markowitz mean-variance portfolio optimization model. We solve such type of problems using a method similar to column generation. In this scheme, the original problem is restricted to a subset of the assets resulting in a master convex quadratic problem. Then the dual information of the master problem is used in a sub-problem to propose more assets to consider. We also consider other extensions to the Markowitz model to diversify the portfolio selection within the given intervals for active weights.
Why Do Proxy Advisors Wield So Much Influence? Insights From U.S.-U.K. Comparative Analysis
SSRN
The reform of proxy advisors is on the U.S. regulatory agenda, with debate focusing on the extent of influence that these actors exert over institutional investors and corporate managers. But the debate examines the U.S. position in isolation from other systems. If we broaden our focus, we see that the factors usually cited for proxy advisors’ influence exist similarly in the United Kingdom but that proxy advisors there exert significantly weaker influence than they do in the United States. Why this difference when we would expect a similar role for proxy advisors in both systems based on the presence of the usual explanatory factors? This article examines this question, identifying other explanations â€" the role of institutional investor trade groups, the level of agreement on governance best practices, the strength of shareholder rights, and the role of the State â€" to help explain proxy advisors’ greater influence in the United States. The article then explores the implications of this analysis for proxy advisor reform in the United States.
SSRN
The reform of proxy advisors is on the U.S. regulatory agenda, with debate focusing on the extent of influence that these actors exert over institutional investors and corporate managers. But the debate examines the U.S. position in isolation from other systems. If we broaden our focus, we see that the factors usually cited for proxy advisors’ influence exist similarly in the United Kingdom but that proxy advisors there exert significantly weaker influence than they do in the United States. Why this difference when we would expect a similar role for proxy advisors in both systems based on the presence of the usual explanatory factors? This article examines this question, identifying other explanations â€" the role of institutional investor trade groups, the level of agreement on governance best practices, the strength of shareholder rights, and the role of the State â€" to help explain proxy advisors’ greater influence in the United States. The article then explores the implications of this analysis for proxy advisor reform in the United States.
ИÑÑледование и прогнозирование ÑоÑтоÑÐ½Ð¸Ñ Ñ„Ð¸Ð½Ð°Ð½Ñовой ÑиÑтемы РеÑпублики КазахÑтан методом регреÑÑионного анализа. (Research and Forecasting of the State of the Financial System of the Republic of Kazakhstan Using Regression Analysis)
SSRN
Russian Abstract: ÐннотациÑ. Ð"Ð°Ð½Ð½Ð°Ñ ÑÑ‚Ð°Ñ‚ÑŒÑ Ð¿Ð¾ÑвÑщена анализу финанÑовой ÑиÑтемы РеÑпублики КазахÑтан на оÑнове группы параметров, которые отражают такие аÑпекты, как финанÑÐ¾Ð²Ð°Ñ ÑтабильноÑÑ‚ÑŒ, ÑоÑтоÑние гоÑударÑтвенных финанÑов, уровень Ñ€Ð°Ð·Ð²Ð¸Ñ‚Ð¸Ñ Ð±Ð°Ð½ÐºÐ¾Ð²Ñкого Ñектора и финанÑового рынка. English Abstract: This article is devoted to the analysis of the financial system of the Republic of Kazakhstan, which is based on a group of parameters: financial stability, the state of public finances, the level of development of the banking sector and the financial market.
SSRN
Russian Abstract: ÐннотациÑ. Ð"Ð°Ð½Ð½Ð°Ñ ÑÑ‚Ð°Ñ‚ÑŒÑ Ð¿Ð¾ÑвÑщена анализу финанÑовой ÑиÑтемы РеÑпублики КазахÑтан на оÑнове группы параметров, которые отражают такие аÑпекты, как финанÑÐ¾Ð²Ð°Ñ ÑтабильноÑÑ‚ÑŒ, ÑоÑтоÑние гоÑударÑтвенных финанÑов, уровень Ñ€Ð°Ð·Ð²Ð¸Ñ‚Ð¸Ñ Ð±Ð°Ð½ÐºÐ¾Ð²Ñкого Ñектора и финанÑового рынка. English Abstract: This article is devoted to the analysis of the financial system of the Republic of Kazakhstan, which is based on a group of parameters: financial stability, the state of public finances, the level of development of the banking sector and the financial market.
‘Up’ and ‘Down’ Lévy Jumps and the Risk Premia in Options and Returns
SSRN
We model the SPX index options dynamics via the Levy approach, using the CGMY distribution, which allows the ‘up’ and ‘down’ returns to be independent jumps. The intensities (volatilities) of these return jumps can themselves be modeled as evolving stochastically. When we allow the up and down returns, and their stochastic evolutions, to have separate parameterisations, the fitted intensities have very different characteristics, and this can account for the options smirk.Our separate-parameterization approach is preferred to the standard approach for fitting the options smirk, which is to introduce correlation between the return intensities and the returns themselves.We filter the ‘up’ and ‘down’ return intensities from the data, and study associated risk premia. Our up and down intensities themselves have +ve and âˆ've risk premia respectively. Also, they are associated with âˆ've and +ve risk premia respectively, for the index returns. The estimated magnitudes of these premia are consistent with the ‘equity premium puzzle’, and suggest that our up and down factors are relevant to resolving this puzzle.
SSRN
We model the SPX index options dynamics via the Levy approach, using the CGMY distribution, which allows the ‘up’ and ‘down’ returns to be independent jumps. The intensities (volatilities) of these return jumps can themselves be modeled as evolving stochastically. When we allow the up and down returns, and their stochastic evolutions, to have separate parameterisations, the fitted intensities have very different characteristics, and this can account for the options smirk.Our separate-parameterization approach is preferred to the standard approach for fitting the options smirk, which is to introduce correlation between the return intensities and the returns themselves.We filter the ‘up’ and ‘down’ return intensities from the data, and study associated risk premia. Our up and down intensities themselves have +ve and âˆ've risk premia respectively. Also, they are associated with âˆ've and +ve risk premia respectively, for the index returns. The estimated magnitudes of these premia are consistent with the ‘equity premium puzzle’, and suggest that our up and down factors are relevant to resolving this puzzle.
