Research articles for the 2020-11-19
(When) Do Banks React to Anticipated Capital Reliefs?
SSRN
We study how banks react to policy announcements during a representative policy cycle involving consultation and publication using a novel dataset on the population of all mortgage transactions and regulatory risk assessments of banks. We demonstrate that banks likely to benefit from lower capital requirements increase the size of this capital relief by permanently investing into low risk assets after the publication of the policy. In contrast, there is no evidence that they already reacted to the early step of the development of the policy, the publication of the consultation paper. We show how these results can be used to estimate a lower bound on the cost of capital for smaller banks, for which such estimates are typically difficult to obtain.
SSRN
We study how banks react to policy announcements during a representative policy cycle involving consultation and publication using a novel dataset on the population of all mortgage transactions and regulatory risk assessments of banks. We demonstrate that banks likely to benefit from lower capital requirements increase the size of this capital relief by permanently investing into low risk assets after the publication of the policy. In contrast, there is no evidence that they already reacted to the early step of the development of the policy, the publication of the consultation paper. We show how these results can be used to estimate a lower bound on the cost of capital for smaller banks, for which such estimates are typically difficult to obtain.
A Model for Central Bank Digital Currencies: Do CBDCs Disrupt the Financial Sector?
SSRN
Since technological innovations provoked a rethinking of the monetary system, central banks analyze the potentials and risks of CBDCs. While CBDCs offer several benefits, many suggest that they impose a threat to financial stability as they might disintermediate commercial banks and facilitate bank runs. To analyze these concerns, we develop an appropriate New Keynesian DSGE framework. Our focus lies on the effects of interest- and non-interest-bearing CBDCs in times of financial crises and their interaction with the zero lower bound (ZLB). Additionally, we study the role of central bank funding and a rule-based interest rate on CBDCs. We find that CBDCs indeed crowd out bank deposits and affect bank funding. However, this crowding-out effect is not necessarily a threat to financial stability and a cause for economic disturbances when the central bank chooses an adequate policy.
SSRN
Since technological innovations provoked a rethinking of the monetary system, central banks analyze the potentials and risks of CBDCs. While CBDCs offer several benefits, many suggest that they impose a threat to financial stability as they might disintermediate commercial banks and facilitate bank runs. To analyze these concerns, we develop an appropriate New Keynesian DSGE framework. Our focus lies on the effects of interest- and non-interest-bearing CBDCs in times of financial crises and their interaction with the zero lower bound (ZLB). Additionally, we study the role of central bank funding and a rule-based interest rate on CBDCs. We find that CBDCs indeed crowd out bank deposits and affect bank funding. However, this crowding-out effect is not necessarily a threat to financial stability and a cause for economic disturbances when the central bank chooses an adequate policy.
Asset Allocation Via Clustering or, Just How Useful Is My Stylebox? And Are Most Hedge Funds Really the Same?
SSRN
In order to take advantage of the “one true free lunch†in investing, namely the increase in compound return due to the reduction of volatility by regular re-balancing among uncorrelated assets, it is necessary to first establish what those uncorrelated asset classes are. In practice, many investors are disappointed to find their attempts at “style-box†diversification (e.g. large vs. small, and growth vs. value) failed to provide much overall portfolio benefit in terms of this re-balancing effect. Machine-learning algorithms such as cluster identification via hierarchical trees have seen some success in identifying truer sector and industry classifications among individual equities; can such algorithms provide any insights as to the diversification benefits of standard asset classes? We apply various clustering algorithms to asset classes and hedge fund strategies from 1990 to the present to investigate cluster stability and compute the returns of a risk-parity investing approach. Some surprising insights emerge with actionable implications for portfolio construction (a few examples: there are three types of bonds; TIPS are not different; High Yield is mostly Equity; MLPs and Precious Metals are interesting; and all hedge funds except Merger Arbitrage and certain sub-categories of Macro have morphed over time into Equity).
SSRN
In order to take advantage of the “one true free lunch†in investing, namely the increase in compound return due to the reduction of volatility by regular re-balancing among uncorrelated assets, it is necessary to first establish what those uncorrelated asset classes are. In practice, many investors are disappointed to find their attempts at “style-box†diversification (e.g. large vs. small, and growth vs. value) failed to provide much overall portfolio benefit in terms of this re-balancing effect. Machine-learning algorithms such as cluster identification via hierarchical trees have seen some success in identifying truer sector and industry classifications among individual equities; can such algorithms provide any insights as to the diversification benefits of standard asset classes? We apply various clustering algorithms to asset classes and hedge fund strategies from 1990 to the present to investigate cluster stability and compute the returns of a risk-parity investing approach. Some surprising insights emerge with actionable implications for portfolio construction (a few examples: there are three types of bonds; TIPS are not different; High Yield is mostly Equity; MLPs and Precious Metals are interesting; and all hedge funds except Merger Arbitrage and certain sub-categories of Macro have morphed over time into Equity).
Asset Pricing with Realistic Crises Dynamics
SSRN
What causes deep recessions and slow recovery? I revisit this question and develop a macro-finance asset pricing model that quantitatively matches the salient empirical features of financial crises such as a large drop in the output, a high risk premium, reduced financial intermediation, and a long duration of economic distress. The model features leveraged intermediaries who are subjected to both capital and productivity shocks, and face a regime-dependent exit rate. I show that the model without time varying intermediary productivity and exit, which reduces to Brunnermeier and Sannikov (2016), suffers from a tension between the amplification and the persistence of financial crises. In particular, there is a trade-off between the unconditional risk premium, the conditional risk premium, and the probability and duration of crisis. Features that generate high financial amplification also induce faster recovery, at odds with the data. I show that my model resolves this tension and generates realistic crises dynamics. The model is solved using a novel numerical method with active machine learning that is scalable and alleviates the curse of dimensionality.
SSRN
What causes deep recessions and slow recovery? I revisit this question and develop a macro-finance asset pricing model that quantitatively matches the salient empirical features of financial crises such as a large drop in the output, a high risk premium, reduced financial intermediation, and a long duration of economic distress. The model features leveraged intermediaries who are subjected to both capital and productivity shocks, and face a regime-dependent exit rate. I show that the model without time varying intermediary productivity and exit, which reduces to Brunnermeier and Sannikov (2016), suffers from a tension between the amplification and the persistence of financial crises. In particular, there is a trade-off between the unconditional risk premium, the conditional risk premium, and the probability and duration of crisis. Features that generate high financial amplification also induce faster recovery, at odds with the data. I show that my model resolves this tension and generates realistic crises dynamics. The model is solved using a novel numerical method with active machine learning that is scalable and alleviates the curse of dimensionality.
Belief Error and Non-Bayesian Social Learning: Experimental Evidence
arXiv
arXiv
This paper experimentally studies whether individuals hold a first-order belief that others apply Bayes' rule to incorporate private information into their beliefs, which is a fundamental assumption in many Bayesian and non-Bayesian social learning models. We design a novel experimental setting in which the first-order belief assumption implies that social information is equivalent to private information. Our main finding is that participants' reported reservation prices of social information are significantly lower than those of private information, which provides evidence that casts doubt on the first-order belief assumption. We also build a novel belief error model in which participants form a random posterior belief with a Bayesian posterior belief kernel to explain the experimental findings. A structural estimation of the model suggests that participants' sophisticated consideration of others' belief error and their exaggeration of the error both contribute to the difference in reservation prices.
Can one hear the shape of a target zone?
arXiv
arXiv
We develop an exchange rate target zone model with finite exit time and non-Gaussian tails. We show how the tails are a consequence of time-varying investor risk aversion, which generates mean-preserving spreads in the fundamental distribution. We solve explicitly for stationary and non-stationary exchange rate paths, and show how both depend continuously on the distance to the exit time and the target zone bands. This enables us to show how central bank intervention is endogenous to both the distance of the fundamental to the band and the underlying risk. We discuss how the feasibility of the target zone is shaped by the set horizon and the degree of underlying risk, and we determine a minimum time at which the required parity can be reached. We prove that increases in risk after a certain threshold can yield endogenous regime shifts where the "honeymoon effects" vanish and the target zone cannot be feasibly maintained. None of these results can be obtained by means of the standard Gaussian or affine models. Numerical simulations allow us to recover all the exchange rate densities established in the target zone literature.
Choosing News Topics to Explain Stock Market Returns
SSRN
We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance through a random search of plain LDA models. A branching procedure that reinforces effective topic assignments often performs best. We test these methods on an archive of over 90,000 news articles about S&P 500 firms.
SSRN
We analyze methods for selecting topics in news articles to explain stock returns. We find, through empirical and theoretical results, that supervised Latent Dirichlet Allocation (sLDA) implemented through Gibbs sampling in a stochastic EM algorithm will often overfit returns to the detriment of the topic model. We obtain better out-of-sample performance through a random search of plain LDA models. A branching procedure that reinforces effective topic assignments often performs best. We test these methods on an archive of over 90,000 news articles about S&P 500 firms.
Competition Networks and Financial Propagation: Natural Experiments with Interference
SSRN
We build a competition network that links industries through common major players in horizontal competition in product markets. Using the network structure, we examine the causal effects of firms’ financial distress risk on their product market behavior and the propagation of these financial shocks through the competition network. The competition intensity on the network is endogenously determined by the capacity of (tacit) cooperation among peers. We identify idiosyncratic shocks to financial distress risk by exploiting the occurrence of local natural disasters in the US. We find that firms hit by disasters exhibit increased financial distress risk and then compete more aggressively in product markets by cutting their profit margins. In response, their industry peers also engage in more aggressive price competition and exhibit their own increased likelihood of financial distress, especially in industries with high entry barriers and balanced market shares. Importantly, financial distress risk can propagate to other industries through common market leaders operating in multiple industries. These results cannot be explained by production network externality.
SSRN
We build a competition network that links industries through common major players in horizontal competition in product markets. Using the network structure, we examine the causal effects of firms’ financial distress risk on their product market behavior and the propagation of these financial shocks through the competition network. The competition intensity on the network is endogenously determined by the capacity of (tacit) cooperation among peers. We identify idiosyncratic shocks to financial distress risk by exploiting the occurrence of local natural disasters in the US. We find that firms hit by disasters exhibit increased financial distress risk and then compete more aggressively in product markets by cutting their profit margins. In response, their industry peers also engage in more aggressive price competition and exhibit their own increased likelihood of financial distress, especially in industries with high entry barriers and balanced market shares. Importantly, financial distress risk can propagate to other industries through common market leaders operating in multiple industries. These results cannot be explained by production network externality.
Covariance Crunch Revisited: One Year of Live Performance
SSRN
A previous paper (“The Probability Frontier or, Covariance Crunch: A New Paradigm for Mean-Variance Optimizationâ€) introduced the concept of a Directional Covariance matrix, which reduces market returns to pure directionality (+1 or -1), treating the magnitudes as noise. This is intended to produce better-diversified portfolios with more robust out-of-sample performance than traditional optimization. That paper showed the Directional Covariance matrix did indeed produce more diversified portfolios and better performance than a traditional optimizer in a 13-year back-test simulation for a seven-asset portfolio. We now revisit this test with one full year of new out-of-sample data, and compare its “live†performance against the hedge fund industry. While the traditional optimizer happened to do very well over the last year, the Directional Covariance technique produced a more diverse portfolio and outperformed the HFRI Fund-Weighted Composite index on an absolute basis and by nearly 2:1 on a risk-adjusted basis, with a beta of 0.53, an annual alpha of +2.6%, and R2 of 78%. Having a hedge fund-like risk profile and being fully liquid, this particular strategy is thus well-suited as a holding vehicle for committed (but uncalled) Private Equity capital, to avoid the dreaded “cash drag†effect. Don’t just shrink that covariance matrix; crush it!
SSRN
A previous paper (“The Probability Frontier or, Covariance Crunch: A New Paradigm for Mean-Variance Optimizationâ€) introduced the concept of a Directional Covariance matrix, which reduces market returns to pure directionality (+1 or -1), treating the magnitudes as noise. This is intended to produce better-diversified portfolios with more robust out-of-sample performance than traditional optimization. That paper showed the Directional Covariance matrix did indeed produce more diversified portfolios and better performance than a traditional optimizer in a 13-year back-test simulation for a seven-asset portfolio. We now revisit this test with one full year of new out-of-sample data, and compare its “live†performance against the hedge fund industry. While the traditional optimizer happened to do very well over the last year, the Directional Covariance technique produced a more diverse portfolio and outperformed the HFRI Fund-Weighted Composite index on an absolute basis and by nearly 2:1 on a risk-adjusted basis, with a beta of 0.53, an annual alpha of +2.6%, and R2 of 78%. Having a hedge fund-like risk profile and being fully liquid, this particular strategy is thus well-suited as a holding vehicle for committed (but uncalled) Private Equity capital, to avoid the dreaded “cash drag†effect. Don’t just shrink that covariance matrix; crush it!
Demand for Money, Structural Break and Money's Role in Monetary Policy in Ghana: An Empirical Evidence
SSRN
We examine the (in)stability of real money demand function and the relevance of money in the contemporary monetary policy framework in Ghana. Both Bai-Perron (2003) structural stability and Quandt-Andrews unknown break tests were applied to ascertain possible structural breaks in Ghana’s money demand function, while impulse responses and variance decomposition techniques based on structural VAR framework were employed to determine the pass through of money demand growth to inflation and exchange rate. Our empirical results showed evidence of an unstable money demand function for Ghana over the sample period (1996Q1 â€" 2015Q2). In spite of the observed instability, Ghanaian demand for money was found to be positively affected by real income, exchange rate depreciation and financial innovation, but negatively influenced by interest rates (both foreign and domestic) and real dollarization. The study also uncovered that growth in money demand has a strong indirect positive impact on inflation, principally via the exchange rate channel. Our empirical results remit cogent policy proposition that money still contains useful information for future prediction of inflation in Ghana. The empirical findings thus proffer strong support for a continuous monitoring of the monetary aggregates (alongside other real sector and financial information) in order to rein in inflation in Ghana.
SSRN
We examine the (in)stability of real money demand function and the relevance of money in the contemporary monetary policy framework in Ghana. Both Bai-Perron (2003) structural stability and Quandt-Andrews unknown break tests were applied to ascertain possible structural breaks in Ghana’s money demand function, while impulse responses and variance decomposition techniques based on structural VAR framework were employed to determine the pass through of money demand growth to inflation and exchange rate. Our empirical results showed evidence of an unstable money demand function for Ghana over the sample period (1996Q1 â€" 2015Q2). In spite of the observed instability, Ghanaian demand for money was found to be positively affected by real income, exchange rate depreciation and financial innovation, but negatively influenced by interest rates (both foreign and domestic) and real dollarization. The study also uncovered that growth in money demand has a strong indirect positive impact on inflation, principally via the exchange rate channel. Our empirical results remit cogent policy proposition that money still contains useful information for future prediction of inflation in Ghana. The empirical findings thus proffer strong support for a continuous monitoring of the monetary aggregates (alongside other real sector and financial information) in order to rein in inflation in Ghana.
Direct Listing or IPO?
SSRN
Direct listing (DL) firms go public without capital-raising and bypass underwriters. Theory and evidence from U.S. and U.K. markets show that (1) DL and IPO markets cater to different types of firms. (2) DL market is more vulnerable to breakdown. Certification intermediaries are essential in maintaining a well-functioning DL market, which leads to more public listings and improved social welfare. (3) After DL innovation, firms and intermediaries enjoy welfare gains, while public investors may face higher risks. These results highlight severe informational frictions in the going-public markets and imply that better-developed private capital and stock trading markets motivate DL innovation.
SSRN
Direct listing (DL) firms go public without capital-raising and bypass underwriters. Theory and evidence from U.S. and U.K. markets show that (1) DL and IPO markets cater to different types of firms. (2) DL market is more vulnerable to breakdown. Certification intermediaries are essential in maintaining a well-functioning DL market, which leads to more public listings and improved social welfare. (3) After DL innovation, firms and intermediaries enjoy welfare gains, while public investors may face higher risks. These results highlight severe informational frictions in the going-public markets and imply that better-developed private capital and stock trading markets motivate DL innovation.
Does Codetermination Reduce Shareholders Value? Board-Level Employee Representation, Corporate Diversification, and Investors’ Perceptions
SSRN
This study analyzes the relationship between board-level codetermination and shareholder value against the backdrop of diversification strategies which allows us to investigate direct as well as indirect effects of codetermination. We use a unique dataset of listed German companies that enables us to precisely identify codetermination and overcome otherwise common identification issues. Our results suggest that codetermination reduces firms’ market performance. However, we also find evidence for the ability of codetermination to reduce agency problems and, hence, increase shareholder value. Moreover, we find codetermination to be associated with a higher propensity to diversify, while employees’ risk-reduction incentives do not reduce market performance. In additional analyses, we find that investors do not react to a number of codetermination mechanism that prior research has shown to exert significant influence on firm-wide decisions. Further, we find inconsistent effects of codetermination on operating performance. Thus, we conclude that the negative relationship between codetermination and market performance is driven by investors’ negative perceptions of codetermination rather than by the effect of codetermination on a firm’s decision-making process. We contribute to the current discussion of board-level employee representation and its economic consequences.
SSRN
This study analyzes the relationship between board-level codetermination and shareholder value against the backdrop of diversification strategies which allows us to investigate direct as well as indirect effects of codetermination. We use a unique dataset of listed German companies that enables us to precisely identify codetermination and overcome otherwise common identification issues. Our results suggest that codetermination reduces firms’ market performance. However, we also find evidence for the ability of codetermination to reduce agency problems and, hence, increase shareholder value. Moreover, we find codetermination to be associated with a higher propensity to diversify, while employees’ risk-reduction incentives do not reduce market performance. In additional analyses, we find that investors do not react to a number of codetermination mechanism that prior research has shown to exert significant influence on firm-wide decisions. Further, we find inconsistent effects of codetermination on operating performance. Thus, we conclude that the negative relationship between codetermination and market performance is driven by investors’ negative perceptions of codetermination rather than by the effect of codetermination on a firm’s decision-making process. We contribute to the current discussion of board-level employee representation and its economic consequences.
FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
arXiv
arXiv
As deep reinforcement learning (DRL) has been recognized as an effective approach in quantitative finance, getting hands-on experiences is attractive to beginners. However, to train a practical DRL trading agent that decides where to trade, at what price, and what quantity involves error-prone and arduous development and debugging. In this paper, we introduce a DRL library FinRL that facilitates beginners to expose themselves to quantitative finance and to develop their own stock trading strategies. Along with easily-reproducible tutorials, FinRL library allows users to streamline their own developments and to compare with existing schemes easily. Within FinRL, virtual environments are configured with stock market datasets, trading agents are trained with neural networks, and extensive backtesting is analyzed via trading performance. Moreover, it incorporates important trading constraints such as transaction cost, market liquidity and the investor's degree of risk-aversion. FinRL is featured with completeness, hands-on tutorial and reproducibility that favors beginners: (i) at multiple levels of time granularity, FinRL simulates trading environments across various stock markets, including NASDAQ-100, DJIA, S&P 500, HSI, SSE 50, and CSI 300; (ii) organized in a layered architecture with modular structure, FinRL provides fine-tuned state-of-the-art DRL algorithms (DQN, DDPG, PPO, SAC, A2C, TD3, etc.), commonly-used reward functions and standard evaluation baselines to alleviate the debugging workloads and promote the reproducibility, and (iii) being highly extendable, FinRL reserves a complete set of user-import interfaces. Furthermore, we incorporated three application demonstrations, namely single stock trading, multiple stock trading, and portfolio allocation. The FinRL library will be available on Github at link https://github.com/AI4Finance-LLC/FinRL-Library.
Financial Media as a Money Doctor: Evidence from Refinancing Decisions
SSRN
We find that the viewership of business television raises the propensity of households to refinance their homes when doing so is financially advantageous. To estimate the effect of business TV, we exploit the staggered entry of Fox Business Network (FBN) into zip codes across the U.S. Exposure to FBN is associated with a 14% increase in local refinancing volume in response to a 100 bps drop in mortgage interest rates. We confirm the media effect on refinancing by using an instrument for TV viewership, which exploits exogenous variation in the channels’ ordinal positions. The media influence is stronger for minority and lower-income applicants. Overall, business TV likely raises financial awareness and serves as a nudge against inertia.
SSRN
We find that the viewership of business television raises the propensity of households to refinance their homes when doing so is financially advantageous. To estimate the effect of business TV, we exploit the staggered entry of Fox Business Network (FBN) into zip codes across the U.S. Exposure to FBN is associated with a 14% increase in local refinancing volume in response to a 100 bps drop in mortgage interest rates. We confirm the media effect on refinancing by using an instrument for TV viewership, which exploits exogenous variation in the channels’ ordinal positions. The media influence is stronger for minority and lower-income applicants. Overall, business TV likely raises financial awareness and serves as a nudge against inertia.
Financing the Litigation Arms Race
SSRN
Using a continuous-time model of litigation, we show that the increasingly popular practice of third-party litigation financing has ambiguous welfare implications. A defendant and a plaintiff bargain over a settlement payment. The defendant takes costly actions to avoid deadweight losses associated with large transfers to the plaintiff. Litigation financing bolsters the plaintiff, leading to larger deadweight losses. However, by endogenously deterring the defendant from taking costly actions, litigation financing can nonetheless improve the joint surplus of the plaintiff and the defendant. In contrast to popular opinion, litigation financing does not necessarily encourage high-risk frivolous lawsuits.
SSRN
Using a continuous-time model of litigation, we show that the increasingly popular practice of third-party litigation financing has ambiguous welfare implications. A defendant and a plaintiff bargain over a settlement payment. The defendant takes costly actions to avoid deadweight losses associated with large transfers to the plaintiff. Litigation financing bolsters the plaintiff, leading to larger deadweight losses. However, by endogenously deterring the defendant from taking costly actions, litigation financing can nonetheless improve the joint surplus of the plaintiff and the defendant. In contrast to popular opinion, litigation financing does not necessarily encourage high-risk frivolous lawsuits.
Impact of Financial Inclusion on the Women SME Entrepreneurs in Bangladesh
SSRN
Financial inclusion is a critical issue for enhancing the welfare of an economy as well as reducing income inequality by providing access to efficient financial services to both the privileged and the poor people of the country .Financial inclusion is a significant issue in Bangladesh as the majority of the population- especially women, farmers, and individuals do not have access to basic financial services such as credit, insurance, payment, etc. Thus, this paper aims at identifying the impacts of financial inclusion on the women SME entrepreneurs of Bangladesh .To conduct this research, 207 respondents were chosen from those women who either initiated their own SME or worked as an employee in one .A structured questionnaire with 5 points Likert scale was used to collect primary data .Multivariate analysis techniques like factor analysis, multiple regression analysis were performed to identify the impacts of financial inclusions on the women SME entrepreneurs of Bangladesh. The study finds the impact factors of financial inclusion on women SME entrepreneurs in Bangladesh. Factors such as, easiness in payment, comfortable in transaction, reduced unemployment problem due to the creation of agents, no network problem in transaction, and secured area coverage were found significant impact factors of financial inclusion on the women SME entrepreneurs in Bangladesh.
SSRN
Financial inclusion is a critical issue for enhancing the welfare of an economy as well as reducing income inequality by providing access to efficient financial services to both the privileged and the poor people of the country .Financial inclusion is a significant issue in Bangladesh as the majority of the population- especially women, farmers, and individuals do not have access to basic financial services such as credit, insurance, payment, etc. Thus, this paper aims at identifying the impacts of financial inclusion on the women SME entrepreneurs of Bangladesh .To conduct this research, 207 respondents were chosen from those women who either initiated their own SME or worked as an employee in one .A structured questionnaire with 5 points Likert scale was used to collect primary data .Multivariate analysis techniques like factor analysis, multiple regression analysis were performed to identify the impacts of financial inclusions on the women SME entrepreneurs of Bangladesh. The study finds the impact factors of financial inclusion on women SME entrepreneurs in Bangladesh. Factors such as, easiness in payment, comfortable in transaction, reduced unemployment problem due to the creation of agents, no network problem in transaction, and secured area coverage were found significant impact factors of financial inclusion on the women SME entrepreneurs in Bangladesh.
Indian Individual Investor Behaviour: A Model Based Study to Meet Sustainable and Inclusive Growth
SSRN
This study investigates the contextual and psychological factors influencing individual investor’s decision making in the currently volatile and emerging Indian investment market. Primary information was collected through a multi-segment questionnaire. Responses were obtained from 384 individuals and a model was thus developed using exploratory factor analysis and structural equation modelling to show the impact of psychological factors and contextual factors on financial satisfaction. On the basis of exploratory factor analysis six relatively homogenous groups of contextual factors that influence individual investor behaviour were identified. SEM analysis depicted that psychological factors/biases and contextual factors could explain 13% of variation in financial satisfaction. This paper can act as a guide to the investors, financial service providers, government and the policy makers. This analysis also contributes to the literature of behavioural research, in terms of generating financial satisfaction through behavioural, psychological and contextual factors.
SSRN
This study investigates the contextual and psychological factors influencing individual investor’s decision making in the currently volatile and emerging Indian investment market. Primary information was collected through a multi-segment questionnaire. Responses were obtained from 384 individuals and a model was thus developed using exploratory factor analysis and structural equation modelling to show the impact of psychological factors and contextual factors on financial satisfaction. On the basis of exploratory factor analysis six relatively homogenous groups of contextual factors that influence individual investor behaviour were identified. SEM analysis depicted that psychological factors/biases and contextual factors could explain 13% of variation in financial satisfaction. This paper can act as a guide to the investors, financial service providers, government and the policy makers. This analysis also contributes to the literature of behavioural research, in terms of generating financial satisfaction through behavioural, psychological and contextual factors.
Investment Funds, Monetary Policy, and the Global Financial Cycle
SSRN
This paper studies the role of international investment funds in the transmission of global financial conditions to the euro area using structural Bayesian vector auto regressions. While cross-border banking sector capital flows receded significantly in the aftermath of the global financial crisis, portfolio flows of investors actively searching for yield on financial markets world-wide gained importance during the post-crisis “second phase of global liquidity†(Shin, 2013). The analysis presented in this paper shows that a loosening of US monetary policy leads to higher investment fund inflows to equities and debt globally. Focussing on the euro area, these inflows do not only imply elevated asset prices, but also coincide with increased debt and equity issuance. The findings demonstrate the growing importance of non-bank financial intermediation over the last decade and have important policy implications for monetary and financial stability.
SSRN
This paper studies the role of international investment funds in the transmission of global financial conditions to the euro area using structural Bayesian vector auto regressions. While cross-border banking sector capital flows receded significantly in the aftermath of the global financial crisis, portfolio flows of investors actively searching for yield on financial markets world-wide gained importance during the post-crisis “second phase of global liquidity†(Shin, 2013). The analysis presented in this paper shows that a loosening of US monetary policy leads to higher investment fund inflows to equities and debt globally. Focussing on the euro area, these inflows do not only imply elevated asset prices, but also coincide with increased debt and equity issuance. The findings demonstrate the growing importance of non-bank financial intermediation over the last decade and have important policy implications for monetary and financial stability.
Manpower Constraints and Corporate Policies
SSRN
Manpower constraints are the pervasive lack of specialized high- and low-skill workers, irrespective of the wage firms might offer. For a panel of German firms, we show manpower-constrained firms have higher capacity utilization and longer backlog of orders (measured in months). They are more willing to increase their capital expenditures, and more willing to grow their employment in the following year. Manpower constraints vary substantially over time and across industries, being higher on average in traditional manufacturing industries and lower in high-tech industries. For identification, we exploit the fall of the Berlin Wall in 1989, and the subsequent differential fluxes of Eastern immigrants across Western states, which followed the pre-existing patterns of Eastern German immigration immediately after WWII. We construct a Manpower Constraint (MPC) Index calibrating the loadings on firm-level financials that are also available in commonly used data set for US, European, and Asian firms. Our results help inform relevant debates such as the reform of immigration policies and the investment in public and private education for low-skilled workers.
SSRN
Manpower constraints are the pervasive lack of specialized high- and low-skill workers, irrespective of the wage firms might offer. For a panel of German firms, we show manpower-constrained firms have higher capacity utilization and longer backlog of orders (measured in months). They are more willing to increase their capital expenditures, and more willing to grow their employment in the following year. Manpower constraints vary substantially over time and across industries, being higher on average in traditional manufacturing industries and lower in high-tech industries. For identification, we exploit the fall of the Berlin Wall in 1989, and the subsequent differential fluxes of Eastern immigrants across Western states, which followed the pre-existing patterns of Eastern German immigration immediately after WWII. We construct a Manpower Constraint (MPC) Index calibrating the loadings on firm-level financials that are also available in commonly used data set for US, European, and Asian firms. Our results help inform relevant debates such as the reform of immigration policies and the investment in public and private education for low-skilled workers.
National Culture and Analysts’ Forecasting Behavior
SSRN
We examine whether national culture, in particular, its individualism/collectivism dimension, affects sell-side financial analysts’ forecasting behavior. We find that analysts from individualistic cultures are more likely to issue bold earnings forecasts and stock recommendations than analysts from collectivistic cultures. These results are related to individualistic (collectivistic) analysts’ inclination to over-weight (under-weight) their private information in forming forecasts. The culture’s effect is not permanent: Although slowly, it does decay over time. For market consequences, short-window market reactions are stronger to bold reports by collectivistic analysts than to those by individualistic analysts. For longer-term effects, we find that higher individualism of the covering analysts is associated with lower stock price synchronicity, indicating proportionately more firm-specific information impounded in the stock price. In net, however, we find that individualistic and collectivistic analysts appear to be equally effective in mitigating firms’ information asymmetry.
SSRN
We examine whether national culture, in particular, its individualism/collectivism dimension, affects sell-side financial analysts’ forecasting behavior. We find that analysts from individualistic cultures are more likely to issue bold earnings forecasts and stock recommendations than analysts from collectivistic cultures. These results are related to individualistic (collectivistic) analysts’ inclination to over-weight (under-weight) their private information in forming forecasts. The culture’s effect is not permanent: Although slowly, it does decay over time. For market consequences, short-window market reactions are stronger to bold reports by collectivistic analysts than to those by individualistic analysts. For longer-term effects, we find that higher individualism of the covering analysts is associated with lower stock price synchronicity, indicating proportionately more firm-specific information impounded in the stock price. In net, however, we find that individualistic and collectivistic analysts appear to be equally effective in mitigating firms’ information asymmetry.
Online Appendix for 'Common Fund Flows: Flow Hedging and Factor Pricing'
SSRN
This is the supplemental material to the paper titled "Common Fund Flows: Flow Hedging and Factor Pricing." It includes many useful and interesting additional empirical results. It also includes the detailed proofs for the theoretical results.
SSRN
This is the supplemental material to the paper titled "Common Fund Flows: Flow Hedging and Factor Pricing." It includes many useful and interesting additional empirical results. It also includes the detailed proofs for the theoretical results.
Skilled Labor Mobility and Firm Value: Evidence from Green Card Allocations
SSRN
This paper studies how the labor market frictions of skilled workers affect corporate valuation. The analysis features immigrant workers’ mobility constraints imposed by the U.S. green card application process and exploits exogenous variations caused by imperfections in the current immigration system. The study finds that relaxing mobility constraints negatively influences firm value. This effect is stronger for firms with higher labor adjustment costs. Reductions in investments and increases in labor costs are channels through which labor mobility adversely affects firm value. The findings suggest that monopoly rent over skilled workers is an important economic determinant of shareholder wealth.
SSRN
This paper studies how the labor market frictions of skilled workers affect corporate valuation. The analysis features immigrant workers’ mobility constraints imposed by the U.S. green card application process and exploits exogenous variations caused by imperfections in the current immigration system. The study finds that relaxing mobility constraints negatively influences firm value. This effect is stronger for firms with higher labor adjustment costs. Reductions in investments and increases in labor costs are channels through which labor mobility adversely affects firm value. The findings suggest that monopoly rent over skilled workers is an important economic determinant of shareholder wealth.
Structural Stochastic Volatility
SSRN
We use a local (in time) expansion of the characteristic function of the equity process in continuous time to derive short-maturity option prices. The prices, along with data on short-maturity options, are employed to jointly identify equity characteristics (spot volatility, spot leverage and spot volatility of volatility) which have been the focus of separate strands of the literature. We show that the proposed identification method yields measurements which are statistically accurate and economically revealing. Interpreting equity as a call option on asset values, all equity characteristics should depend on fundamental state variables, such as the variance of the firm’s assets and the extent of the firm’s financial leverage. Among other findings, consistent with economic logic, we document a strong link between spot leverage (the generally-negative correlation between equity returns and spot volatility) and financial leverage (the firm’s debt-to-equity ratio), a relation invariably found to be elusive in the data. We conclude that the economic content of option-implied measurements can be put to work to study the structural drivers of equity (and debt) return dynamics from a novel vantage point.
SSRN
We use a local (in time) expansion of the characteristic function of the equity process in continuous time to derive short-maturity option prices. The prices, along with data on short-maturity options, are employed to jointly identify equity characteristics (spot volatility, spot leverage and spot volatility of volatility) which have been the focus of separate strands of the literature. We show that the proposed identification method yields measurements which are statistically accurate and economically revealing. Interpreting equity as a call option on asset values, all equity characteristics should depend on fundamental state variables, such as the variance of the firm’s assets and the extent of the firm’s financial leverage. Among other findings, consistent with economic logic, we document a strong link between spot leverage (the generally-negative correlation between equity returns and spot volatility) and financial leverage (the firm’s debt-to-equity ratio), a relation invariably found to be elusive in the data. We conclude that the economic content of option-implied measurements can be put to work to study the structural drivers of equity (and debt) return dynamics from a novel vantage point.
The Brexit Premium
SSRN
I quantify the impact of no-deal Brexit (the potential departure of UK from EU without a withdrawal agreement) on European equity prices. I document their overwhelmingly negative response upon Brexit referendum results announcements and show that varying degrees of Brexit exposure explain differences in returns on European stocks between July 2016 and December 2019. I show that both results are far more pronounced in the UK than they are in the rest of the EU-15 region - numerous negative projections for various sectors and individual firms in the EU-14 economy are not corroborated by the equity market response. I exploit the cross-sectional variation in European equity returns to construct a Brexit mimicking portfolio tracking latent Brexit shocks over time. I show that it can explain significant amount of time-series variation of European stock market in the post-referendum period. Finally, its correlations with the European stock market indices suggest Brexit constitutes far greater and more lasting a shock to the local UK than the EU economy.
SSRN
I quantify the impact of no-deal Brexit (the potential departure of UK from EU without a withdrawal agreement) on European equity prices. I document their overwhelmingly negative response upon Brexit referendum results announcements and show that varying degrees of Brexit exposure explain differences in returns on European stocks between July 2016 and December 2019. I show that both results are far more pronounced in the UK than they are in the rest of the EU-15 region - numerous negative projections for various sectors and individual firms in the EU-14 economy are not corroborated by the equity market response. I exploit the cross-sectional variation in European equity returns to construct a Brexit mimicking portfolio tracking latent Brexit shocks over time. I show that it can explain significant amount of time-series variation of European stock market in the post-referendum period. Finally, its correlations with the European stock market indices suggest Brexit constitutes far greater and more lasting a shock to the local UK than the EU economy.
The Commercial Bank Leverage Factor in U.S. Asset Prices
SSRN
I present novel results on a commercial bank leverage factor that drives U.S. asset prices with important implications for both the time-series and the cross-section of returns. To motivate these findings, I modify the recovery rate of assets in a disaster model to include aggregate credit growth as an additional macroeconomic risk factor. It turns out there is a positive relationship between the postulated "resilience" of an asset and the stage of aggregate credit recovery. The intuition is behavioral in nature: credit expansions (contractions) breed investor overoptimism (pessimism), asset "resilience" increases (decreases) and the risk-premium decreases (increases). Additional implications in the cross-section are generated by the interaction of the credit cycle with the stock-specific recovery rate. The commercial bank leverage factor has a larger effect on small-, less profitable-, and value-stocks. A simple buy-and-hold strategy of the market index at short- and medium-horizons illustrates how investors can earn significantly higher excess returns and Sharpe ratios in recoveries and early stages of an expansion as opposed to credit booms.
SSRN
I present novel results on a commercial bank leverage factor that drives U.S. asset prices with important implications for both the time-series and the cross-section of returns. To motivate these findings, I modify the recovery rate of assets in a disaster model to include aggregate credit growth as an additional macroeconomic risk factor. It turns out there is a positive relationship between the postulated "resilience" of an asset and the stage of aggregate credit recovery. The intuition is behavioral in nature: credit expansions (contractions) breed investor overoptimism (pessimism), asset "resilience" increases (decreases) and the risk-premium decreases (increases). Additional implications in the cross-section are generated by the interaction of the credit cycle with the stock-specific recovery rate. The commercial bank leverage factor has a larger effect on small-, less profitable-, and value-stocks. A simple buy-and-hold strategy of the market index at short- and medium-horizons illustrates how investors can earn significantly higher excess returns and Sharpe ratios in recoveries and early stages of an expansion as opposed to credit booms.
The Leverage Bearing Capacity: A New Tool for Intermediary Asset Pricing
SSRN
We introduce a new proxy for the health of financial intermediariesâ€"the Leverage Bearing Capacity (LBC). LBC is the leverage of a fictitious intermediary that targets a fixed level of risk and rebalances its capital structure on an ongoing basis. Our proposed measure is based on market values, available at any frequency, forward-looking, and relies solely on no-arbitrage. Building on an intermediary asset pricing model, we validate LBC theoretically and show that it proxies the marginal wealth of intermediaries. We conduct two event studies to highlight that LBC incorporates uncertainty about the assets of financial intermediaries. Lastly, we show that these features translate into superior asset pricing performance.
SSRN
We introduce a new proxy for the health of financial intermediariesâ€"the Leverage Bearing Capacity (LBC). LBC is the leverage of a fictitious intermediary that targets a fixed level of risk and rebalances its capital structure on an ongoing basis. Our proposed measure is based on market values, available at any frequency, forward-looking, and relies solely on no-arbitrage. Building on an intermediary asset pricing model, we validate LBC theoretically and show that it proxies the marginal wealth of intermediaries. We conduct two event studies to highlight that LBC incorporates uncertainty about the assets of financial intermediaries. Lastly, we show that these features translate into superior asset pricing performance.
The Role of Credit Ratings on Capital Structure and Its Speed of Adjustment: An International Study
SSRN
Using an international data set, we examine the role of issuers’ credit ratings in explaining corporate leverage and the speed with which firms adjust toward their optimal level of leverage. We find that, in countries with a more market-oriented financial system, the impact of credit ratings on firms’ capital structure is more significant and that firms with a poorer credit rating adjust more rapidly. Furthermore, our results show some striking differences in the speed of adjusting capital structure between firms rated as speculative and investment grade, with the former adjusting much more rapidly. As hypothesized, those differences are statistically significant only for firms based in a more market-oriented economy.
SSRN
Using an international data set, we examine the role of issuers’ credit ratings in explaining corporate leverage and the speed with which firms adjust toward their optimal level of leverage. We find that, in countries with a more market-oriented financial system, the impact of credit ratings on firms’ capital structure is more significant and that firms with a poorer credit rating adjust more rapidly. Furthermore, our results show some striking differences in the speed of adjusting capital structure between firms rated as speculative and investment grade, with the former adjusting much more rapidly. As hypothesized, those differences are statistically significant only for firms based in a more market-oriented economy.
What Can China Learn about the Way Property Price Bubbles Affect GDP Growth? A Bubble Economics Perspective
SSRN
How far do China’s property prices need to drop in order to trigger a GDP reaction that looks like a price bubble bursting? What does this question tell us about the way Bubble Economies work? In this paper, argue for a separate analysis of ‘Bubble Economics’ â€" as the non-linear and often “systemic†(in the mathematical sense of the word) forces which cause significant misallocations of resources. Even the term Bubble Economics can help us keep in mind that when we look at such events, we are witnessing discontinuous jumps representing the radical change in underlying economic structures and fundamentals -- if even for a limited time.
SSRN
How far do China’s property prices need to drop in order to trigger a GDP reaction that looks like a price bubble bursting? What does this question tell us about the way Bubble Economies work? In this paper, argue for a separate analysis of ‘Bubble Economics’ â€" as the non-linear and often “systemic†(in the mathematical sense of the word) forces which cause significant misallocations of resources. Even the term Bubble Economics can help us keep in mind that when we look at such events, we are witnessing discontinuous jumps representing the radical change in underlying economic structures and fundamentals -- if even for a limited time.
Who Listens to Corporate Conference Calls? The Effect of 'Soft Information' on Institutional Trading
SSRN
Conference calls provide a public venue through which stock analysts simultaneously interact, in large numbers, with firm management. Using a comprehensive database of transcribed U.S. corporate conference calls from 2006 to 2018, we find that institutional investors significantly react to the tone of calls in their trades and holdings of stocks. Institutions trade on the tone immediately, and up to four weeks after the call, and continue to trade on conference call-driven analyst recommendation revisions. The trade reaction of institutions to tone is more pronounced when the marginal value of information is higher, e.g., in the question section of the call, in earnings calls, and when the stock exhibits a higher degree of information asymmetry. Our paper suggests that conference calls are an important channel for stock price discovery in the post Reg-FD era.
SSRN
Conference calls provide a public venue through which stock analysts simultaneously interact, in large numbers, with firm management. Using a comprehensive database of transcribed U.S. corporate conference calls from 2006 to 2018, we find that institutional investors significantly react to the tone of calls in their trades and holdings of stocks. Institutions trade on the tone immediately, and up to four weeks after the call, and continue to trade on conference call-driven analyst recommendation revisions. The trade reaction of institutions to tone is more pronounced when the marginal value of information is higher, e.g., in the question section of the call, in earnings calls, and when the stock exhibits a higher degree of information asymmetry. Our paper suggests that conference calls are an important channel for stock price discovery in the post Reg-FD era.
