Research articles for the 2020-08-19
A Short Tour of Global Risks
SSRN
This article is based on the author's Homer Jones Memorial Lecture delivered at the Federal Reserve Bank of St. Louis, Wednesday, June 25, 2019.
SSRN
This article is based on the author's Homer Jones Memorial Lecture delivered at the Federal Reserve Bank of St. Louis, Wednesday, June 25, 2019.
Adverse Selection and Intermediation Chains
SSRN
We propose a parsimonious model of over-the-counter trading with asymmetric information to rationalize the existence of intermediation chains that stand between buyers and sellers of assets. Trading an asset through several heterogeneously informed intermediaries can preserve the efficiency of trade by reallocating an information asymmetry over many sequential transactions. Such an intermediation chain ensures that the adverse selection problems counterparties face in each transaction are small enough to allow for socially efficient trading strategies by all parties involved. Our model makes novel predictions about network formation and rent extraction when adverse selection problems impede the efficiency of trade.
SSRN
We propose a parsimonious model of over-the-counter trading with asymmetric information to rationalize the existence of intermediation chains that stand between buyers and sellers of assets. Trading an asset through several heterogeneously informed intermediaries can preserve the efficiency of trade by reallocating an information asymmetry over many sequential transactions. Such an intermediation chain ensures that the adverse selection problems counterparties face in each transaction are small enough to allow for socially efficient trading strategies by all parties involved. Our model makes novel predictions about network formation and rent extraction when adverse selection problems impede the efficiency of trade.
Are Sports Betting Markets Semi-Strong Efficient? Evidence from the COVID-19 Pandemic
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This paper examines whether sports betting markets are semi-strong form efficient, i.e., whether new information is rapidly and completely incorporated into betting prices. We use the news of ghost matches in the top European football leagues due to the COVID-19 pandemic as arrival of public information. Because spectators are absent in ghost games, the home field advantage is reduced, and we test whether this information is fully reflected in betting prices. Our results show that bookmakers systematically overestimate a home team’s winning probability during the first period of the ghost games. This suggests that betting markets are, at least temporally, not semi-strong form efficient. We exploit a betting strategy that yields a positive net payoff over more than one month.
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This paper examines whether sports betting markets are semi-strong form efficient, i.e., whether new information is rapidly and completely incorporated into betting prices. We use the news of ghost matches in the top European football leagues due to the COVID-19 pandemic as arrival of public information. Because spectators are absent in ghost games, the home field advantage is reduced, and we test whether this information is fully reflected in betting prices. Our results show that bookmakers systematically overestimate a home team’s winning probability during the first period of the ghost games. This suggests that betting markets are, at least temporally, not semi-strong form efficient. We exploit a betting strategy that yields a positive net payoff over more than one month.
Are temporary value-added tax reductions passed on to consumers? Evidence from Germany's stimulus
arXiv
arXiv
This paper provides the first estimates of the pass-through rate of the ongoing temporary value-added tax (VAT) reduction, which is part of the German fiscal response to COVID-19. Using a unique dataset containing the universe of price changes at fuel stations in Germany and France in June and July 2020, we employ a difference-in-differences strategy and find that pass-through is fast and substantial but remains incomplete for all fuel types. Furthermore, we find a high degree of heterogeneity between the pass-through estimates for different fuel types. Our results are consistent with the interpretation that pass-through rates are higher for customer groups who are more likely to exert competitive pressure by shopping for lower prices. Our results have important implications for the effectiveness of the stimulus measure and the cost-effective design of unconventional fiscal policy.
Asset Pricing Through the Lens of the Hansen-Jagannathan Bound
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Stochastic discount factor (SDF) models are the dominant framework for modern asset pricing. The Hansen-Jagannathan bound is a characterization of the admissible set of SDFs, given a vector of asset returns.
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Stochastic discount factor (SDF) models are the dominant framework for modern asset pricing. The Hansen-Jagannathan bound is a characterization of the admissible set of SDFs, given a vector of asset returns.
Authority, Consensus and Governance
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We characterize optimal corporate boards when shareholders face a trade-off between improving information sharing between the board and management and reducing distortions in decision making arising out of managerial agency. We show that allocating authority to management is suboptimal. Authority should be held by a supervisory board that may be imperfectly aligned with both shareholders and management. Even when management has captured all authority and the board only has an advisory role, the optimal board may be designed to withhold information from management. Optimal advisory boards must however be able to create consensus with management, making the allocation of authority irrelevant.
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We characterize optimal corporate boards when shareholders face a trade-off between improving information sharing between the board and management and reducing distortions in decision making arising out of managerial agency. We show that allocating authority to management is suboptimal. Authority should be held by a supervisory board that may be imperfectly aligned with both shareholders and management. Even when management has captured all authority and the board only has an advisory role, the optimal board may be designed to withhold information from management. Optimal advisory boards must however be able to create consensus with management, making the allocation of authority irrelevant.
Backtesting Macroprudential Stress Tests
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In this paper, we consider models of price-mediated contagion in a banking networkof common asset holdings. For these models, the literature proposed two alternativeclasses of liquidation dynamics:threshold dynamics(banks liquidate their invest-ment portfolios only after they have defaulted), andleverage targeting dynamics(banks constantly rebalance their portfolios to maintain a target leverage ratio).We introduce a one-parameter family of non-linear liquidation functions that inter-polates between these two extremes. We then test the capability of these modelsto predict actual bank defaults (and survivals) in the United States for the years2008-10. We show that the model performance depends on the type of shock be-ing imposed (idiosyncratic versus systematic). We identify the two most relevantasset classes, for which the model has predictive power when these asset classes areexposed to an initial shock. In these cases, the model performs better than alter-native benchmarks that do not account for the network of common asset holdings,irrespective of the assumed liquidation dynamics. We also show how the best per-forming liquidation dynamics depend on the combination of the initial shock leveland the market impact parameter, on the cross-sectional variation in the marketimpact parameter, and on the number of asset liquidation rounds.
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In this paper, we consider models of price-mediated contagion in a banking networkof common asset holdings. For these models, the literature proposed two alternativeclasses of liquidation dynamics:threshold dynamics(banks liquidate their invest-ment portfolios only after they have defaulted), andleverage targeting dynamics(banks constantly rebalance their portfolios to maintain a target leverage ratio).We introduce a one-parameter family of non-linear liquidation functions that inter-polates between these two extremes. We then test the capability of these modelsto predict actual bank defaults (and survivals) in the United States for the years2008-10. We show that the model performance depends on the type of shock be-ing imposed (idiosyncratic versus systematic). We identify the two most relevantasset classes, for which the model has predictive power when these asset classes areexposed to an initial shock. In these cases, the model performs better than alter-native benchmarks that do not account for the network of common asset holdings,irrespective of the assumed liquidation dynamics. We also show how the best per-forming liquidation dynamics depend on the combination of the initial shock leveland the market impact parameter, on the cross-sectional variation in the marketimpact parameter, and on the number of asset liquidation rounds.
CEO Departure and Stock Price Crashes: The Effects of Crepuscular Behavior
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This study investigates CEOs’ opportunistic activities in the years prior to their departures. The findings show that the occurrence of a stock price crash is heightened prior to the departure of the CEO. Particularly, one and two years before the CEO departure, firms experience 24.5% and 23.9% more stock price crashes than the rest years of CEO tenure. We ascribe this phenomenon to a “crepuscular behaviorâ€, whereby CEOs in their final years in office appear to act opportunistically by overly hiding negative news from investors. This behavior has certain wealth effects because, for instance, departing CEOs appear to significantly reduce their options and stock ownership, in comparison with their non-departing peers. Finally, this study investigates the corporate governance environment implications surrounding CEO departures.
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This study investigates CEOs’ opportunistic activities in the years prior to their departures. The findings show that the occurrence of a stock price crash is heightened prior to the departure of the CEO. Particularly, one and two years before the CEO departure, firms experience 24.5% and 23.9% more stock price crashes than the rest years of CEO tenure. We ascribe this phenomenon to a “crepuscular behaviorâ€, whereby CEOs in their final years in office appear to act opportunistically by overly hiding negative news from investors. This behavior has certain wealth effects because, for instance, departing CEOs appear to significantly reduce their options and stock ownership, in comparison with their non-departing peers. Finally, this study investigates the corporate governance environment implications surrounding CEO departures.
Capital Flows-at-Risk: Push, Pull and the Role of Policy
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We characterise the probability distribution of capital flows for a panel of emerging market economies conditional on information contained in financial asset prices, with a focus on ‘tail’ events. Our framework, based on the quantile regression methodology, allows for a separate role of push and pull-type factors, and offers insights into the term-structure of these effects. We find that both push and pull factors have heterogeneous effects across the distribution of capital flows, with the strongest reactions in the left tail. Also, the effect of changes in pull factors is more persistent than that of push factors. Finally, we explore the role of policy, and find that macroprudential and capital flow management measures are associated with changes in the distribution of capital flows.
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We characterise the probability distribution of capital flows for a panel of emerging market economies conditional on information contained in financial asset prices, with a focus on ‘tail’ events. Our framework, based on the quantile regression methodology, allows for a separate role of push and pull-type factors, and offers insights into the term-structure of these effects. We find that both push and pull factors have heterogeneous effects across the distribution of capital flows, with the strongest reactions in the left tail. Also, the effect of changes in pull factors is more persistent than that of push factors. Finally, we explore the role of policy, and find that macroprudential and capital flow management measures are associated with changes in the distribution of capital flows.
Communications Between Borrowers and Servicers: Evidence from the COVID-19 Mortgage Forbearance Program
SSRN
The servicer comments are proprietary and hardly accessible; however, they can offer the single best source for real-time information of the mortgages. We utilize these comments to shed light on borrower responses to the mortgage forbearance program contained in the Coronavirus Aid, Relief, and Economic Security Act. Our analysis reveals that borrowers did not actively seek out mortgage forbearance in response to this policy.
SSRN
The servicer comments are proprietary and hardly accessible; however, they can offer the single best source for real-time information of the mortgages. We utilize these comments to shed light on borrower responses to the mortgage forbearance program contained in the Coronavirus Aid, Relief, and Economic Security Act. Our analysis reveals that borrowers did not actively seek out mortgage forbearance in response to this policy.
Decision Weights for Experimental Asset Prices Based on Visual Salience
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We apply a machine-learning algorithm calibrated from general human vision to predict visual salience of parts of a stock price series. We hypothesize that visual salience of adjacent prices increases decision weights on returns computed from those prices. We analyze the inferred decision impact of these weights in three experimental studies that use either historical individual-stock returns or simpler artificial sequences. We find that decision weights derived from visual salience are associated with experimental investments. Their predictability goes beyond alternative theories over-weighting returns at the tails of the historical distribution, or with respect to salient difference from a reference return.
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We apply a machine-learning algorithm calibrated from general human vision to predict visual salience of parts of a stock price series. We hypothesize that visual salience of adjacent prices increases decision weights on returns computed from those prices. We analyze the inferred decision impact of these weights in three experimental studies that use either historical individual-stock returns or simpler artificial sequences. We find that decision weights derived from visual salience are associated with experimental investments. Their predictability goes beyond alternative theories over-weighting returns at the tails of the historical distribution, or with respect to salient difference from a reference return.
Detecting and explaining changes in various assets' relationships in financial markets
arXiv
arXiv
We study the method for detecting relationship changes in financial markets and providing human-interpretable network visualization to support the decision-making of fund managers dealing with multi-assets. First, we construct co-occurrence networks with each asset as a node and a pair with a strong relationship in price change as an edge at each time step. Second, we calculate Graph-Based Entropy to represent the variety of price changes based on the network. Third, we apply the Differential Network to finance, which is traditionally used in the field of bioinformatics. By the method described above, we can visualize when and what kind of changes are occurring in the financial market, and which assets play a central role in changes in financial markets. Experiments with multi-asset time-series data showed results that were well fit with actual events while maintaining high interpretability.
Do Asset Price Bubbles have Negative Real Effects?
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In the recent recession and current economic recovery, policymakers have supported asset prices in the U.S. treasury and mortgage markets, expecting that improvement in the balance sheet of banks will lead to more commercial lending. In general, we document that increases in housing prices in a bank’s deposit base lead banks to decrease commercial lending. Further, we find that a one-standard deviation increase in housing prices is associated with a 10.3 percentage point decrease in investment of borrowing firms and a 4.2 percentage point decrease in leverage. These results suggest that when asset prices increase in one sector (such as the housing market), banks may respond by reallocating capital away from other sectors (such as commercial lending) towards the supported sectors.
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In the recent recession and current economic recovery, policymakers have supported asset prices in the U.S. treasury and mortgage markets, expecting that improvement in the balance sheet of banks will lead to more commercial lending. In general, we document that increases in housing prices in a bank’s deposit base lead banks to decrease commercial lending. Further, we find that a one-standard deviation increase in housing prices is associated with a 10.3 percentage point decrease in investment of borrowing firms and a 4.2 percentage point decrease in leverage. These results suggest that when asset prices increase in one sector (such as the housing market), banks may respond by reallocating capital away from other sectors (such as commercial lending) towards the supported sectors.
Do Domestic Institutional Investors (DIIs) Neutralize the Impact of Large Reversal by Foreign Institutional Investors (FIIs)? Recent Evidence from Indian Stock Market
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FIIs and DIIs are the two dominant investment categories in the Indian stock market with enough clout to move the market. Inflow of FIIs is crucial for an emerging economy like India. At the outset, it attracts foreign capital to finance economic growth. Inflow of Foreign capital through FIIs is also expected to enhance liquidity in the stock market by widening the investor base and thereby improves the functioning of the secondary market. Hence, the flow of FIIs is expected to indirectly contribute to the economic growth (Lee, 2007). However, on the flip side, they are considered to be voracious, erratic investors that often profit from destabilizing financial markets of host countries. Batra (2003) observes that FPIs are considered to be driven by animal spirits rather than rational investment decisions. Hence, they have often been blamed for large reversal of capital from countries in times of crisis leading to herding behavior in other investors, particularly, domestic institutional investors (DIIs). As a result, these flows tend to make financial markets vulnerable and may end up landing the country in a crisis (Rakshit, 2006). To neuralisze the destabilizing nature of FII trading, it is critical to have powerful DIIs that would provide a cushion against this adverse effect of FIIs. However, this function of DIIs depends on the relationship between FIIs and DIIs. Therefore, the present paper attempts to understand the relationship between foreign institutional investments (FIIs) and domestic institutional investors (DIIs) in India, using the most recent high frequency data. The study finds that FIIs and DIIs follow a different trading strategy in the market. Importantly, the study shows that DIIs negatively affect the FII flows, whereas they are not affected by the FII flows. This suggests that DIIs indeed act as a cushion against the significant withdrawal by FIIs, thereby maintaining stability in the stock market.
SSRN
FIIs and DIIs are the two dominant investment categories in the Indian stock market with enough clout to move the market. Inflow of FIIs is crucial for an emerging economy like India. At the outset, it attracts foreign capital to finance economic growth. Inflow of Foreign capital through FIIs is also expected to enhance liquidity in the stock market by widening the investor base and thereby improves the functioning of the secondary market. Hence, the flow of FIIs is expected to indirectly contribute to the economic growth (Lee, 2007). However, on the flip side, they are considered to be voracious, erratic investors that often profit from destabilizing financial markets of host countries. Batra (2003) observes that FPIs are considered to be driven by animal spirits rather than rational investment decisions. Hence, they have often been blamed for large reversal of capital from countries in times of crisis leading to herding behavior in other investors, particularly, domestic institutional investors (DIIs). As a result, these flows tend to make financial markets vulnerable and may end up landing the country in a crisis (Rakshit, 2006). To neuralisze the destabilizing nature of FII trading, it is critical to have powerful DIIs that would provide a cushion against this adverse effect of FIIs. However, this function of DIIs depends on the relationship between FIIs and DIIs. Therefore, the present paper attempts to understand the relationship between foreign institutional investments (FIIs) and domestic institutional investors (DIIs) in India, using the most recent high frequency data. The study finds that FIIs and DIIs follow a different trading strategy in the market. Importantly, the study shows that DIIs negatively affect the FII flows, whereas they are not affected by the FII flows. This suggests that DIIs indeed act as a cushion against the significant withdrawal by FIIs, thereby maintaining stability in the stock market.
Does Bonus Cap Curb Risk Taking? An Experimental Study of Relative Performance Pay and Bonus Regulation
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We conducted a lab experiment with 253 participants to examine how constraints on bonus akin to bonus regulations, such as bonus cap and malus, could affect individuals’ risk-taking in the presence of relative performance pay. Participants took greater risks when bonus was linked to investment performance relative to that of their peers (relative performance pay) than when it depended on their own performance only. In the absence of relative performance pay, bonus cap and malus reduced risk-taking. With relative performance pay, the risk-mitigating effects of bonus cap and malus were significantly weakened; but participants took less risk when bonus was made conditional on their team avoiding a loss.
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We conducted a lab experiment with 253 participants to examine how constraints on bonus akin to bonus regulations, such as bonus cap and malus, could affect individuals’ risk-taking in the presence of relative performance pay. Participants took greater risks when bonus was linked to investment performance relative to that of their peers (relative performance pay) than when it depended on their own performance only. In the absence of relative performance pay, bonus cap and malus reduced risk-taking. With relative performance pay, the risk-mitigating effects of bonus cap and malus were significantly weakened; but participants took less risk when bonus was made conditional on their team avoiding a loss.
Does Calibration Affect the Complexity of Agent-Based Models? A Multifractal Grid Analysis
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We examine the complexity of financial returns generated by popular agent-based models through studying multifractal properties of such time series. Specifically, we are interested in the sensitivity of the models to their parameter settings and whether some patterns emerge in the connection between complexity and a specific type of parameter. We find that (i) herding behavior mostly boosts the model complexity as measured by multifractality, (ii) various in-built stabilizing factors increase model complexity, (iii) the role of intensity of choice as well as the chartists' representation have rather model-specific effects, and (iv) the number of agents has no statistically significant effect on the model complexity. The heterogeneous set of nine analyzed models thus offers some universal concepts that hold across their range. Our results also indicate that interesting dynamics are observed not only for the benchmark parameter settings but also for other combinations of parameter values for most models. This opens new avenues for future research and specifically motivates examining the models in more detail by focusing on other dynamic properties in addition to the herein presented multifractality.
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We examine the complexity of financial returns generated by popular agent-based models through studying multifractal properties of such time series. Specifically, we are interested in the sensitivity of the models to their parameter settings and whether some patterns emerge in the connection between complexity and a specific type of parameter. We find that (i) herding behavior mostly boosts the model complexity as measured by multifractality, (ii) various in-built stabilizing factors increase model complexity, (iii) the role of intensity of choice as well as the chartists' representation have rather model-specific effects, and (iv) the number of agents has no statistically significant effect on the model complexity. The heterogeneous set of nine analyzed models thus offers some universal concepts that hold across their range. Our results also indicate that interesting dynamics are observed not only for the benchmark parameter settings but also for other combinations of parameter values for most models. This opens new avenues for future research and specifically motivates examining the models in more detail by focusing on other dynamic properties in addition to the herein presented multifractality.
Does Quantitative Easing Boost Bank Lending to the Real Economy or Cause Other Bank Asset Reallocation? The Case of the UK
SSRN
We investigate the impact of the asset purchase program (APP) introduced by the Bank of England (BOE) in 2009 on the composition of assets of UK banks, and the implications for bank lending to the real economy, using a unique database on the program. Knowing the identity of the banks that receive reserves injections through the BOE’s APP (QE banks) provides us with an ideal empirical design for a difference-in-differences exercise. The Monetary Policy Committee (MPC) didn’t expect there to be strong transmission of the APP’s impact through the bank lending channel. In line with that, we find no evidence that suggests that QE directly boosted bank lending to the real economy, even when controlling fully for demand-side effects. The overall reduction of retail lending is more pronounced for treated (QE) banks than for the control group. QE banks reallocated their assets towards lower risk-weighted investments, such as government securities, as suggested by the increased sensitivity of their equity returns to peripheral EU bond returns. Overall, our findings suggest that, if banks are not adequately capitalised, risk-based capital constraints can limit the transmission of expansionary unconventional monetary policies via the bank lending channel, and provide incentives for carry trade activities.
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We investigate the impact of the asset purchase program (APP) introduced by the Bank of England (BOE) in 2009 on the composition of assets of UK banks, and the implications for bank lending to the real economy, using a unique database on the program. Knowing the identity of the banks that receive reserves injections through the BOE’s APP (QE banks) provides us with an ideal empirical design for a difference-in-differences exercise. The Monetary Policy Committee (MPC) didn’t expect there to be strong transmission of the APP’s impact through the bank lending channel. In line with that, we find no evidence that suggests that QE directly boosted bank lending to the real economy, even when controlling fully for demand-side effects. The overall reduction of retail lending is more pronounced for treated (QE) banks than for the control group. QE banks reallocated their assets towards lower risk-weighted investments, such as government securities, as suggested by the increased sensitivity of their equity returns to peripheral EU bond returns. Overall, our findings suggest that, if banks are not adequately capitalised, risk-based capital constraints can limit the transmission of expansionary unconventional monetary policies via the bank lending channel, and provide incentives for carry trade activities.
Dynamic Equity Slope
SSRN
The term structure of equity and its cyclicality are key to understand the risks driving equilibrium asset prices. We propose a general equilibrium model that jointly explains four important features of the term structure of equity: (i) a negative unconditional term premium, (ii) counter-cyclical term premia, (iii) pro-cyclical equity yields, and (iv) premia to value and growth claims respectively increasing and decreasing with the horizon. The economic mechanism hinges on the interaction between heteroskedastic long-run growth â€" which helps price long-term cash flows and leads to counter-cyclical risk premia â€" and homoskedastic short-term shocks in the presence of limited market participation â€" which produce size-able risk premia to short-term cash flows. The slope dynamics hold irrespective of the sign of its unconditional average. We provide empirical support to our model assumptions and predictions.
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The term structure of equity and its cyclicality are key to understand the risks driving equilibrium asset prices. We propose a general equilibrium model that jointly explains four important features of the term structure of equity: (i) a negative unconditional term premium, (ii) counter-cyclical term premia, (iii) pro-cyclical equity yields, and (iv) premia to value and growth claims respectively increasing and decreasing with the horizon. The economic mechanism hinges on the interaction between heteroskedastic long-run growth â€" which helps price long-term cash flows and leads to counter-cyclical risk premia â€" and homoskedastic short-term shocks in the presence of limited market participation â€" which produce size-able risk premia to short-term cash flows. The slope dynamics hold irrespective of the sign of its unconditional average. We provide empirical support to our model assumptions and predictions.
Dynamic Mean-Variance Portfolios With Risk Budget
SSRN
We study a dynamic mean-variance portfolio selection problem subject to possible limit of market risk. Three measures of market risk are considered: value-at-risk, expected shortfall, and median shortfall. They are all calculated in a dynamic consistent sense. After applying the technique of delta-normal approximation, we can explicitly solve for the optimal solution and calculate the economic loss brought by the risk budget constraint. With the analytical results obtained, influential factors of economic loss are then explored by which some guidelines on trading practice are proposed. The guidelines are independent of risk measures, and are valuable to both institutions and regulators, for they suggest that an institutional investor would spontaneously obey good investment discipline to avoid potential impact of risk constraint. This result meets the purpose of external regulation from the perspective of market discipline.
SSRN
We study a dynamic mean-variance portfolio selection problem subject to possible limit of market risk. Three measures of market risk are considered: value-at-risk, expected shortfall, and median shortfall. They are all calculated in a dynamic consistent sense. After applying the technique of delta-normal approximation, we can explicitly solve for the optimal solution and calculate the economic loss brought by the risk budget constraint. With the analytical results obtained, influential factors of economic loss are then explored by which some guidelines on trading practice are proposed. The guidelines are independent of risk measures, and are valuable to both institutions and regulators, for they suggest that an institutional investor would spontaneously obey good investment discipline to avoid potential impact of risk constraint. This result meets the purpose of external regulation from the perspective of market discipline.
Estimating Corporate Bankruptcy Forecasting Models by Maximizing Discriminatory Power
SSRN
In this paper, we estimate coefficients of bankruptcy forecasting models, such as logistic and neural network models, by maximizing their discriminatory power as measured by the Area Under Receiver Operating Characteristics (AUROC) curve. A method is introduced and compared with traditional logistic and neural network models, using out-of-sample analysis, in terms of discriminatory power, information content and economic impact while we forecast bankruptcy one year ahead, two years ahead but also financial distress-a state that precedes bankruptcy. Using US public firms over the period 1990-2015, in all, we find that training models to maximize AUROC, provides more accurate out-of-sample forecasts relative to training them with traditional methods, such as maximizing the log-likelihood function, highlighting the benefits arising by using models with maximized AUROC. Among all models, however, a neural network trained with our method is the best performing one, even when we compare it with other methods proposed in the literature to maximize AUROC. Finally, our results are more pronounced when we increase the difficulty of forecasting, such as forecasting financial distress. The implementation of our method to train bankruptcy models is robust in various settings and therefore well-justified.
SSRN
In this paper, we estimate coefficients of bankruptcy forecasting models, such as logistic and neural network models, by maximizing their discriminatory power as measured by the Area Under Receiver Operating Characteristics (AUROC) curve. A method is introduced and compared with traditional logistic and neural network models, using out-of-sample analysis, in terms of discriminatory power, information content and economic impact while we forecast bankruptcy one year ahead, two years ahead but also financial distress-a state that precedes bankruptcy. Using US public firms over the period 1990-2015, in all, we find that training models to maximize AUROC, provides more accurate out-of-sample forecasts relative to training them with traditional methods, such as maximizing the log-likelihood function, highlighting the benefits arising by using models with maximized AUROC. Among all models, however, a neural network trained with our method is the best performing one, even when we compare it with other methods proposed in the literature to maximize AUROC. Finally, our results are more pronounced when we increase the difficulty of forecasting, such as forecasting financial distress. The implementation of our method to train bankruptcy models is robust in various settings and therefore well-justified.
Examining the Effect of COVID-19 on Foreign Exchange Rate and Stock Market -- An Applied Insight into the Variable Effects of Lockdown on Indian Economy
arXiv
arXiv
Since March 25, 2020, India had been under a nation-wide lockdown announced as a response to the spread of SARS-CoV-2 and COVID-19 and has resorted to a process of 'unlocking' the lockdown over the past couple of months. This work attempts to examine the effect of novel coronavirus 2019 (COVID-19) and its resulting disease, the COVID-19, on the foreign exchange rates and stock market performances of India using secondary data over a span of 112 days spanning between March 11 and June 30, 2020. The study explores whether the causal relationships and directions among the growth rate of confirmed cases (GROWTHC), exchange rate (GEX) and SENSEX value (GSENSEX) are remaining the same across different pre and post-lockdown phases, attempting to capture any potential changes over time via the vector autoregressive (VAR) models. A positive correlation is found between the growth rate of confirmed cases and the growth rate of exchange rate, and a negative correlation between the growth rate of confirmed cases and the growth rate of SENSEX value. However, on applying a vector autoregressive (VAR) model, it is observed that an increase in the confirmed COVID-19 cases causes no significant change in the values of the exchange rate and SENSEX index. The result varies if the analysis is split across different time periods - before lockdown, the four phases of lockdown, and the first phase of unlock. Nuanced and sensible interpretations of the numeric results indicate significant variability across time in terms of the relation between the variables of interest. The detailed knowledge about the varying patterns of dependence could potentially help the policy makers and investors of India in order to develop their strategies to cope up with the situation.
Eyes on the Prize: Do Industry Tournament Incentives Shape the Structure of Executive Compensation?
SSRN
We investigate whether external industry tournament incentives influence the design of executive compensation contracts. Using staggered negative mobility shocks as exogenous disruptions to tournament incentives, we show that firms treated by these shocks act to restore their executives’ diminished implicit risk-taking incentives by increasing explicit risk-taking incentives (vega) in compensation contracts. Among treated executives, these adjustments are far from uniform. Executives with strong tournament incentives and high ex-ante mobility experience the sharpest upward adjustments in compensation vega. Our results shed light on the extent to which firms optimize explicit risk-taking incentives with respect to their executives’ career concerns.
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We investigate whether external industry tournament incentives influence the design of executive compensation contracts. Using staggered negative mobility shocks as exogenous disruptions to tournament incentives, we show that firms treated by these shocks act to restore their executives’ diminished implicit risk-taking incentives by increasing explicit risk-taking incentives (vega) in compensation contracts. Among treated executives, these adjustments are far from uniform. Executives with strong tournament incentives and high ex-ante mobility experience the sharpest upward adjustments in compensation vega. Our results shed light on the extent to which firms optimize explicit risk-taking incentives with respect to their executives’ career concerns.
Financing Failure: Bankruptcy Lending, Credit Market Conditions, and the Financial Crisis
SSRN
When contemplating Chapter 11, firms often need to seek financing for their continuing operations in bankruptcy. Because such financing would otherwise be hard to find, the Bankruptcy Code authorizes debtors to offer sweeteners to debtor-in-possession (DIP) lenders. These inducements can be effective in attracting financing, but because they are thought to come at the expense of other stakeholders, the Code permits these inducements only if no less generous a package would have been sufficient to obtain the loan.Anecdotal evidence suggests that the use of certain controversial inducementsâ€"I focus on roll-ups and milestonesâ€"has skyrocketed in recent years, leading critics to question whether DIP lenders were abusing their power. Lenders, however, respond that DIP loan terms simply reflect economic conditions: when credit is tight, as it was in recent years because of the Financial Crisis, more sweeteners are needed to induce lending.Using a hand-collected dataset reflecting contractual detail in DIP loan agreements, I examine the relationship between changes in credit availability and DIP loan terms before, during, and after the Crisis. As one might expect, I find that ordinary loan provisions like pricing and reporting covenants are sensitive to changes in credit availability. By contrast, I also find that the incidence of so-called “extraordinary provisions†has no statistically meaningful relationship with changes in credit availability. These findings have important implications for bankruptcy policymakers and judges struggling to evaluate whether extraordinary DIP lending inducements are necessary. Too generous loan terms come at the expense of junior claimants and may distort the bankruptcy process in favor of senior claimants.
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When contemplating Chapter 11, firms often need to seek financing for their continuing operations in bankruptcy. Because such financing would otherwise be hard to find, the Bankruptcy Code authorizes debtors to offer sweeteners to debtor-in-possession (DIP) lenders. These inducements can be effective in attracting financing, but because they are thought to come at the expense of other stakeholders, the Code permits these inducements only if no less generous a package would have been sufficient to obtain the loan.Anecdotal evidence suggests that the use of certain controversial inducementsâ€"I focus on roll-ups and milestonesâ€"has skyrocketed in recent years, leading critics to question whether DIP lenders were abusing their power. Lenders, however, respond that DIP loan terms simply reflect economic conditions: when credit is tight, as it was in recent years because of the Financial Crisis, more sweeteners are needed to induce lending.Using a hand-collected dataset reflecting contractual detail in DIP loan agreements, I examine the relationship between changes in credit availability and DIP loan terms before, during, and after the Crisis. As one might expect, I find that ordinary loan provisions like pricing and reporting covenants are sensitive to changes in credit availability. By contrast, I also find that the incidence of so-called “extraordinary provisions†has no statistically meaningful relationship with changes in credit availability. These findings have important implications for bankruptcy policymakers and judges struggling to evaluate whether extraordinary DIP lending inducements are necessary. Too generous loan terms come at the expense of junior claimants and may distort the bankruptcy process in favor of senior claimants.
Haste Makes Waste: Banking Organization Growth and Operational Risk
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This study shows that banking organization growth is associated with higher operational losses per dollar of total assets and incidence of tail risks. Event studies using M&A activity and instrumental variable regressions provide consistent evidence. The relationship between banking organization growth and operational risk varies by loss event types and balance sheet categories. We demonstrate that higher growth predicts worse operational risk realizations during the global financial crisis. These findings have implications for bank performance, risk management and supervision in a continually consolidating banking industry.
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This study shows that banking organization growth is associated with higher operational losses per dollar of total assets and incidence of tail risks. Event studies using M&A activity and instrumental variable regressions provide consistent evidence. The relationship between banking organization growth and operational risk varies by loss event types and balance sheet categories. We demonstrate that higher growth predicts worse operational risk realizations during the global financial crisis. These findings have implications for bank performance, risk management and supervision in a continually consolidating banking industry.
How Broadly Do Product Preannouncement Performance Effects Generalize? Product Life Cycle and Switching Cost Perspectives
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Firms use preannouncements to inform customers about the impending introduction of a new product or service. These preannouncements are significant events because they provide customers with product specific information while signaling the health, strategic intent, and future of a company. One important area of research in this field investigates the performance consequences of product preannouncements (PPA). However, a notable gap in our knowledge exists because the focus of past research has been on studying wealth effects rather narrowly in certain industries, e.g., high-tech, or under certain contingencies. This restrictive approach is surprising because PPA are observed in a broad range of product categories. Moreover, product life cycle and consumer switching cost theories predict performance effects of PPA irrespective of category or context. We address this lack of generalizability by using switching cost and life cycle theories to hypothesize positive performance effects of PPA independent of context and contingencies. We use the event study method from finance to empirically test the relationship between PPA and stock prices in a broad sample of events comprising multiple product categories. Using events reported in the Wall Street Journal, we find evidence of a positive effect of PPA on stock prices irrespective of the type of product or context involved. We note several managerial implications of the study and outline avenues for further research.
SSRN
Firms use preannouncements to inform customers about the impending introduction of a new product or service. These preannouncements are significant events because they provide customers with product specific information while signaling the health, strategic intent, and future of a company. One important area of research in this field investigates the performance consequences of product preannouncements (PPA). However, a notable gap in our knowledge exists because the focus of past research has been on studying wealth effects rather narrowly in certain industries, e.g., high-tech, or under certain contingencies. This restrictive approach is surprising because PPA are observed in a broad range of product categories. Moreover, product life cycle and consumer switching cost theories predict performance effects of PPA irrespective of category or context. We address this lack of generalizability by using switching cost and life cycle theories to hypothesize positive performance effects of PPA independent of context and contingencies. We use the event study method from finance to empirically test the relationship between PPA and stock prices in a broad sample of events comprising multiple product categories. Using events reported in the Wall Street Journal, we find evidence of a positive effect of PPA on stock prices irrespective of the type of product or context involved. We note several managerial implications of the study and outline avenues for further research.
Implicit Entropic Market Risk-Premium from Interest Rate Derivatives
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Implicit in interest rate derivatives are Arrow-Debreu prices (or state price densities, SPDs) that contain fundamental information for risk and portfolio management in interest rate markets. To extract such information from interest rate derivatives, we propose a non-parametric method to estimate state prices based on the minimization of the Cressie-Read (Entropic) family function between potential SPDs and the empirical probability measure. An empirical application of the method, in the US interest rates and derivatives market, shows that the entropic based risk-neutral density measure highlights potential risks previous to the 2007/2008 financial crisis, and the potential arbitrage burden during the Quantitative Easing period.
SSRN
Implicit in interest rate derivatives are Arrow-Debreu prices (or state price densities, SPDs) that contain fundamental information for risk and portfolio management in interest rate markets. To extract such information from interest rate derivatives, we propose a non-parametric method to estimate state prices based on the minimization of the Cressie-Read (Entropic) family function between potential SPDs and the empirical probability measure. An empirical application of the method, in the US interest rates and derivatives market, shows that the entropic based risk-neutral density measure highlights potential risks previous to the 2007/2008 financial crisis, and the potential arbitrage burden during the Quantitative Easing period.
Learning From Prices: Information Aggregation and Accumulation in an Asset Price Model
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Can prices convey information about the fundamental value of an asset? This paper considers this problem in relation to the dynamic properties of the fundamental (whether it is constant or time-varying) and the structure of information available to agents. Risk-averse traders receive two potential signals each period: one exogenous and private and the other, prices, endogenous and public. Prices aggregate private information but include aggregate noise. Information can accumulate over time both through endogenous and exogenous signals. With a constant fundamental, the precision of both private and public cumulative information increases over time but agents put progressively more weight on the endogenous signals, asymptotically disregarding private ones. If the fundamental is time-varying, the use of past private signals complicates the role of prices as a source of information, since it introduces endogenous serial correlation in the price signal and cross-correlation between it and innovations in the fundamental. A modified version of the Kalman filter can still be used to extract information from prices and results show that the precision of the endogenous signals converges to a constant, with both private and public information used at all times.
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Can prices convey information about the fundamental value of an asset? This paper considers this problem in relation to the dynamic properties of the fundamental (whether it is constant or time-varying) and the structure of information available to agents. Risk-averse traders receive two potential signals each period: one exogenous and private and the other, prices, endogenous and public. Prices aggregate private information but include aggregate noise. Information can accumulate over time both through endogenous and exogenous signals. With a constant fundamental, the precision of both private and public cumulative information increases over time but agents put progressively more weight on the endogenous signals, asymptotically disregarding private ones. If the fundamental is time-varying, the use of past private signals complicates the role of prices as a source of information, since it introduces endogenous serial correlation in the price signal and cross-correlation between it and innovations in the fundamental. A modified version of the Kalman filter can still be used to extract information from prices and results show that the precision of the endogenous signals converges to a constant, with both private and public information used at all times.
Levels of Total Book Assets and Future Stock Returns: Risk or Mispricing?
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This study investigates whether increases in future stock returns related to levels of total book assets (TBA), after controlling for market value (MV), are due to risk or stock mispricing. Based on a 30 year sample from 1987 to 2016, the findings reveal statistically significant average annual abnormal returns in the range of 5.5 and 10 percent using the Carhart (1997) four-factor model when going from the lowest to the highest TBA quintile portfolio, after sorting stocks into market value quintiles. Abnormal portfolio returns are even higher in the latter seven years of the sample period. These abnormal portfolio returns are supported by firm-level pooled regressions that include a battery of control variables known to be related to future stock returns. Moreover, these abnormal returns are not related to the accruals or asset growth anomalies. However, the evidence lends support to the behavioral explanation of investors not fully incorporating current investments and prior poor performance of firms into stock prices. Taken together, these findings suggest potentially significant abnormal returns for investors and provide support for standard setters who want more fair values in accounting assets.
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This study investigates whether increases in future stock returns related to levels of total book assets (TBA), after controlling for market value (MV), are due to risk or stock mispricing. Based on a 30 year sample from 1987 to 2016, the findings reveal statistically significant average annual abnormal returns in the range of 5.5 and 10 percent using the Carhart (1997) four-factor model when going from the lowest to the highest TBA quintile portfolio, after sorting stocks into market value quintiles. Abnormal portfolio returns are even higher in the latter seven years of the sample period. These abnormal portfolio returns are supported by firm-level pooled regressions that include a battery of control variables known to be related to future stock returns. Moreover, these abnormal returns are not related to the accruals or asset growth anomalies. However, the evidence lends support to the behavioral explanation of investors not fully incorporating current investments and prior poor performance of firms into stock prices. Taken together, these findings suggest potentially significant abnormal returns for investors and provide support for standard setters who want more fair values in accounting assets.
Local Product Market Competition and Bank Loans
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We investigate the influences of local product market competition on the cost of private debt. Our evidence suggests that the cost of bank loans is significantly higher for firms headquartered in states with greater local product market competition measured by the Herfindahl-Hirschman Index for resident industries. To establish causality, we examine the recognition of the Inevitable Disclosure Doctrine and firm relocations to identify exogenous shocks to local product market competition. We find that the cost of bank loans is lower for firms facing less intense local product market competition after the adoption of IDD and higher for firms relocated to states with more competitive product markets. The results imply that banks value the characteristics of a firm’s local product market when approving loan contracts.
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We investigate the influences of local product market competition on the cost of private debt. Our evidence suggests that the cost of bank loans is significantly higher for firms headquartered in states with greater local product market competition measured by the Herfindahl-Hirschman Index for resident industries. To establish causality, we examine the recognition of the Inevitable Disclosure Doctrine and firm relocations to identify exogenous shocks to local product market competition. We find that the cost of bank loans is lower for firms facing less intense local product market competition after the adoption of IDD and higher for firms relocated to states with more competitive product markets. The results imply that banks value the characteristics of a firm’s local product market when approving loan contracts.
Making no-arbitrage discounting-invariant: a new FTAP beyond NFLVR and NUPBR
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In the simplest formulation, this paper addresses the following question: Given two positive asset prices on a right-open interval, how can one decide, in an economically natural manner, whether or not this is an arbitrage-free model?In general multi-asset models of financial markets, the classic notions NFLVR and NUPBR depend crucially on how prices are discounted. To avoid such issues, we introduce a discounting-invariant absence-of-arbitrage concept. Like in earlier work, this rests on zero or some basic strategies being 'maximal'; the novelty is that maximality of a strategy is defined in terms of 'share' holdings instead of 'value'. This allows us to generalise both NFLVR, by dynamic share efficiency, and NUPBR, by dynamic share viability. These concepts are the same for discounted or undiscounted prices, and they can be used in open-ended models under minimal assumptions on asset prices. We establish corresponding versions of the FTAP, i.e., dual characterisations in terms of martingale properties. As one expects, “properly anticipated prices fluctuate randomlyâ€, but with an 'endogenous' discounting process which must not be chosen a priori. The classic Blackâ€"Scholes model on [0,∞) is arbitrage-free in this sense if and only if its parameters satisfy mâˆ'r ∈ {0, σ²} or, equivalently, either bond-discounted or stock-discounted prices are martingales.
SSRN
In the simplest formulation, this paper addresses the following question: Given two positive asset prices on a right-open interval, how can one decide, in an economically natural manner, whether or not this is an arbitrage-free model?In general multi-asset models of financial markets, the classic notions NFLVR and NUPBR depend crucially on how prices are discounted. To avoid such issues, we introduce a discounting-invariant absence-of-arbitrage concept. Like in earlier work, this rests on zero or some basic strategies being 'maximal'; the novelty is that maximality of a strategy is defined in terms of 'share' holdings instead of 'value'. This allows us to generalise both NFLVR, by dynamic share efficiency, and NUPBR, by dynamic share viability. These concepts are the same for discounted or undiscounted prices, and they can be used in open-ended models under minimal assumptions on asset prices. We establish corresponding versions of the FTAP, i.e., dual characterisations in terms of martingale properties. As one expects, “properly anticipated prices fluctuate randomlyâ€, but with an 'endogenous' discounting process which must not be chosen a priori. The classic Blackâ€"Scholes model on [0,∞) is arbitrage-free in this sense if and only if its parameters satisfy mâˆ'r ∈ {0, σ²} or, equivalently, either bond-discounted or stock-discounted prices are martingales.
Market Uncertainty and Sentiment Around Usda Announcements
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We examine empirically the impact of scheduled USDA information releases on uncertainty and sentiment in grains and oil-seeds markets. We document that, for up to five trading days after the release of a scheduled USDA report (WASDE, stocks, prospective plantings, and acreage), agricultural option-implied (forward-looking) volatilities are significantly lower than they were a week before the release. These reports’ uncertainty-resolution power is similar in magnitude in the corn, soybeans, and wheat markets. In the case of WASDE, the implied volatility drops more when there had been greater disagreement among market experts in the run-up to a report. For corn and beans (but not wheat), the implied volatility drop following a WASDE or a grain stock report is smaller when the USDA information surprises the market. Except for wheat, we find little evidence that the tightness of grain inventories prior to a USDA report affects the market’s reaction. Finally, we show that contemporaneous changes in broad financial-market sentiment and macroeconomic uncertainty (jointly captured by the VIX event-day return) affects the extent to which agricultural markets respond to the USDA report.
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We examine empirically the impact of scheduled USDA information releases on uncertainty and sentiment in grains and oil-seeds markets. We document that, for up to five trading days after the release of a scheduled USDA report (WASDE, stocks, prospective plantings, and acreage), agricultural option-implied (forward-looking) volatilities are significantly lower than they were a week before the release. These reports’ uncertainty-resolution power is similar in magnitude in the corn, soybeans, and wheat markets. In the case of WASDE, the implied volatility drops more when there had been greater disagreement among market experts in the run-up to a report. For corn and beans (but not wheat), the implied volatility drop following a WASDE or a grain stock report is smaller when the USDA information surprises the market. Except for wheat, we find little evidence that the tightness of grain inventories prior to a USDA report affects the market’s reaction. Finally, we show that contemporaneous changes in broad financial-market sentiment and macroeconomic uncertainty (jointly captured by the VIX event-day return) affects the extent to which agricultural markets respond to the USDA report.
Media-Driven High Frequency Trading: Evidence from News Analytics
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We investigate whether providers of high frequency media analytics affect the stock market. This question is difficult to answer as the response to news analytics usually cannot be distinguished from the reaction to the news itself. We exploit a unique experiment based on differences in news event classifications between different product releases of a major provider of news analytics for algorithmic traders. Comparing the market reaction to similar news items depending on whether the news has been released to customers or not, we are able to determine the causal effect of news analytics on stock prices, irrespective of the informational content of the news. We show that coverage in news analytics speeds up the market reaction by both increasing the stock price update and the trading volume in the first few seconds after the news event. Such coverage also increases prices if the content of the news is positive. Placebo tests and econometric robustness checks, either based on difference-in-difference specifications or different samples, confirm the results. The fact that a provider of media analytics impacts the market in a separate and distinct way from the underlying information content of the news has important normative implications for the regulatory debate.
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We investigate whether providers of high frequency media analytics affect the stock market. This question is difficult to answer as the response to news analytics usually cannot be distinguished from the reaction to the news itself. We exploit a unique experiment based on differences in news event classifications between different product releases of a major provider of news analytics for algorithmic traders. Comparing the market reaction to similar news items depending on whether the news has been released to customers or not, we are able to determine the causal effect of news analytics on stock prices, irrespective of the informational content of the news. We show that coverage in news analytics speeds up the market reaction by both increasing the stock price update and the trading volume in the first few seconds after the news event. Such coverage also increases prices if the content of the news is positive. Placebo tests and econometric robustness checks, either based on difference-in-difference specifications or different samples, confirm the results. The fact that a provider of media analytics impacts the market in a separate and distinct way from the underlying information content of the news has important normative implications for the regulatory debate.
Payment Banks: Changing Indian Payments Landscape
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The banking system and financial transactions have taken paradigm shift in recent decade in India. The present era has entered into smartphone to smart wallet and they have become mainstream mode of online payment. Mobile users use digital payment gateway and e-commerce applications to facilitate financial transactions to online retailers and e-businesses. Demonetization has also envisaged progressive shift to cashless economy. The study was conducted to find out the dimensions and impact of various demographic factors on the usage of payment banks in the Ahmedabad district of Gujarat. The payment banks show a rapid growth and identified dimensions for the usage of payment banks are; user friendly, convenience, cost effectiveness, security and easy cash management. People look for the aforesaid factors while they transact through payment banks. It is observed that most of the people use Paytm, Freecharge and Jio money payment banks to transact and awareness has impact on the usability of payment banks for bill payment, recharge, ticket booking and shopping. Considering the demographic factors and its impact on the occupation, annual income and education on the usage of payment banks whereas age and annual income both impact the frequency of usage and average spending through payment banks.
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The banking system and financial transactions have taken paradigm shift in recent decade in India. The present era has entered into smartphone to smart wallet and they have become mainstream mode of online payment. Mobile users use digital payment gateway and e-commerce applications to facilitate financial transactions to online retailers and e-businesses. Demonetization has also envisaged progressive shift to cashless economy. The study was conducted to find out the dimensions and impact of various demographic factors on the usage of payment banks in the Ahmedabad district of Gujarat. The payment banks show a rapid growth and identified dimensions for the usage of payment banks are; user friendly, convenience, cost effectiveness, security and easy cash management. People look for the aforesaid factors while they transact through payment banks. It is observed that most of the people use Paytm, Freecharge and Jio money payment banks to transact and awareness has impact on the usability of payment banks for bill payment, recharge, ticket booking and shopping. Considering the demographic factors and its impact on the occupation, annual income and education on the usage of payment banks whereas age and annual income both impact the frequency of usage and average spending through payment banks.
Pension Benefits, Early Retirement and Human Capital Depreciation in Late Adulthood
arXiv
arXiv
Historically, economists have mainly focused on human capital accumulation and considerably less so on the causes and consequences of human capital depreciation in late adulthood. Studying human capital depreciation over the life cycle has powerful economic consequences for decision-making in old age. Using data from the introduction of a retirement program in China, we examine how the introduction of a retirement program influences individual cognition. We find large negative effects of pension benefits on cognitive functioning among the elderly. We detect the most substantial impact of the program to be on delayed recall, which is a significant predictor of the onset of dementia. We show suggestive evidence that the program leads to larger negative impacts among women. We show that retirement plays a significant role in explaining cognitive decline at older ages.
Public Thrift, Private Perks: Signaling Board Independence with Executive Pay
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We analyze how boards' reputational concerns influence executive compensation and the use of hidden pay. Independent boards reduce disclosed pay to signal their independence, but are more likely than manager-friendly boards to use hidden pay or to distort incentive contracts. Stronger reputational pressures lead to lower disclosed pay, weaker managerial incentives, and higher hidden pay, whereas greater transparency of executive compensation has the opposite effects. Although reputational concerns can induce boards to choose compensation contracts more favorable to shareholders, we show there is a threshold beyond which stronger reputational concerns harm shareholders. Similarly, excessive pay transparency can harm shareholders.
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We analyze how boards' reputational concerns influence executive compensation and the use of hidden pay. Independent boards reduce disclosed pay to signal their independence, but are more likely than manager-friendly boards to use hidden pay or to distort incentive contracts. Stronger reputational pressures lead to lower disclosed pay, weaker managerial incentives, and higher hidden pay, whereas greater transparency of executive compensation has the opposite effects. Although reputational concerns can induce boards to choose compensation contracts more favorable to shareholders, we show there is a threshold beyond which stronger reputational concerns harm shareholders. Similarly, excessive pay transparency can harm shareholders.
Saving Markowitz: A Risk Parity Approach Based on the Cauchy Interlacing Theorem
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It is well known that Markowitz Portfolio Optimization often leads to unreasonable and unbalanced portfolios that are optimal in-sample but perform very poorly out-of-sample. There is a strong relationship between these poor returns and the fact that covariance matrices that are used within the Markowitz framework are degenerated and ill-posed, leading to unstable results by inverting them, as a consequence of very small eigenvalues. In this paper we circumvent this problem in two steps: the enhancement of traditional risk parity techniques, which consider only volatility, aiming to avoid matrix inversions (including the widespread Naive Risk Parity model) within the Markowitz framework; the preservation of the correlation structure, as much as possible, aiming to isolate a "healthy" portion of the correlation matrix, that can be inverted without generating unstable and risky portfolios, aiming to rescue the original Markowitz framework, by means of using the Cauchy Interlacing Theorem. Using Brazilian and US market data, we show that the discussed framework enables one to build portfolios that outperform the traditional and the newest risk parity techniques.
SSRN
It is well known that Markowitz Portfolio Optimization often leads to unreasonable and unbalanced portfolios that are optimal in-sample but perform very poorly out-of-sample. There is a strong relationship between these poor returns and the fact that covariance matrices that are used within the Markowitz framework are degenerated and ill-posed, leading to unstable results by inverting them, as a consequence of very small eigenvalues. In this paper we circumvent this problem in two steps: the enhancement of traditional risk parity techniques, which consider only volatility, aiming to avoid matrix inversions (including the widespread Naive Risk Parity model) within the Markowitz framework; the preservation of the correlation structure, as much as possible, aiming to isolate a "healthy" portion of the correlation matrix, that can be inverted without generating unstable and risky portfolios, aiming to rescue the original Markowitz framework, by means of using the Cauchy Interlacing Theorem. Using Brazilian and US market data, we show that the discussed framework enables one to build portfolios that outperform the traditional and the newest risk parity techniques.
Series expansions and direct inversion for the Heston model
arXiv
arXiv
Efficient sampling for the conditional time integrated variance process in the Heston stochastic volatility model is key to the simulation of the stock price based on its exact distribution. We construct a new series expansion for this integral in terms of double infinite weighted sums of particular independent random variables through a change of measure and the decomposition of squared Bessel bridges. When approximated by series truncations, this representation has exponentially decaying truncation errors. We propose feasible strategies to largely reduce the implementation of the new series to simulations of simple random variables that are independent of any model parameters. We further develop direct inversion algorithms to generate samples for such random variables based on Chebyshev polynomial approximations for their inverse distribution functions. These approximations can be used under any market conditions. Thus, we establish a strong, efficient and almost exact sampling scheme for the Heston model.
Shocks to Transition Risk
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We propose and implement a method to identify shocks to transition risk. We identify transition risk shocks as instances where a strong differential valuation of green versus brown firms coincides with significant information on climate change. For that purpose, we combine information from long-short equity portfolios sorted on firms' carbon footprints with information from textual analysis of newspaper archives. We find that shocks increasing transition risk (negative abnormal returns of brown firms) induce a decline in aggregate and sectoral industrial production. Moreover, they significantly affect financial stability, as measured by the excess bond premium or credit conditions more generally. Finally, we document a pronounced asymmetry in the economy's response to shocks increasing or decreasing transition risk.
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We propose and implement a method to identify shocks to transition risk. We identify transition risk shocks as instances where a strong differential valuation of green versus brown firms coincides with significant information on climate change. For that purpose, we combine information from long-short equity portfolios sorted on firms' carbon footprints with information from textual analysis of newspaper archives. We find that shocks increasing transition risk (negative abnormal returns of brown firms) induce a decline in aggregate and sectoral industrial production. Moreover, they significantly affect financial stability, as measured by the excess bond premium or credit conditions more generally. Finally, we document a pronounced asymmetry in the economy's response to shocks increasing or decreasing transition risk.
Strategic Review and Beyond: Rethinking Monetary Policy and Independence
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I survey monetary policy strategy, regulation, and central banks’ mandates and independence. I do not think strongly negative interest rates, vastly expanded quantitative easing, or extensive forward guidance can or should stimulate in the next recession.
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I survey monetary policy strategy, regulation, and central banks’ mandates and independence. I do not think strongly negative interest rates, vastly expanded quantitative easing, or extensive forward guidance can or should stimulate in the next recession.
Synthetic Governance
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Scholars, practitioners and policymakers continue to debate what constitutes “good†corporate governance. Academic efforts to evaluate the effect of governance provisions such as dual class voting structures, staggered boards of directors and separating the positions of CEO and Chairman of the Board, have produced inconsistent or inconclusive results. The consequence is that the debate over corporate governance is increasingly political and discordant.We offer a way to address this debate. The rise of index-based investing provides a market-based alternative to governance regulation. Through the creation of bespoke governance index funds, asset managers can offer investors the opportunity to choose an index that corresponds to their governance preferences. We term this approach synthetic governance. At the same time, synthetic governance offers a new tool to collect evidence on the economic impact of corporate governance by providing a market-based tool for evaluating the relationship between corporate governance and stock returns. We illustrate the potential of synthetic governance with the creation of a new governance-based index, the Dual Index, which selects portfolio companies on the basis of a dual class voting structure. We compare the performance of the Dual Index to various benchmarks and demonstrate the potential, through governance-based indexing, for investors to realize superior returns. We further modify the Dual Index by implementing synthetic sunsets to highlight the value creation of dual-class companies in their early years and provide evidence on the appropriate length of a time-based sunset provision. Finally, we expand our analysis of synthetic governance with a second index â€" the Split Index â€" which tests the effect of separating the positions of CEO and Chairman of the Board. We conclude that synthetic governance offers a meaningful way for investors and issuers to more economically adopt and invest in governance provisions. We thus provide a way out of the corporate current war over what exactly constitutes “good†governance.
SSRN
Scholars, practitioners and policymakers continue to debate what constitutes “good†corporate governance. Academic efforts to evaluate the effect of governance provisions such as dual class voting structures, staggered boards of directors and separating the positions of CEO and Chairman of the Board, have produced inconsistent or inconclusive results. The consequence is that the debate over corporate governance is increasingly political and discordant.We offer a way to address this debate. The rise of index-based investing provides a market-based alternative to governance regulation. Through the creation of bespoke governance index funds, asset managers can offer investors the opportunity to choose an index that corresponds to their governance preferences. We term this approach synthetic governance. At the same time, synthetic governance offers a new tool to collect evidence on the economic impact of corporate governance by providing a market-based tool for evaluating the relationship between corporate governance and stock returns. We illustrate the potential of synthetic governance with the creation of a new governance-based index, the Dual Index, which selects portfolio companies on the basis of a dual class voting structure. We compare the performance of the Dual Index to various benchmarks and demonstrate the potential, through governance-based indexing, for investors to realize superior returns. We further modify the Dual Index by implementing synthetic sunsets to highlight the value creation of dual-class companies in their early years and provide evidence on the appropriate length of a time-based sunset provision. Finally, we expand our analysis of synthetic governance with a second index â€" the Split Index â€" which tests the effect of separating the positions of CEO and Chairman of the Board. We conclude that synthetic governance offers a meaningful way for investors and issuers to more economically adopt and invest in governance provisions. We thus provide a way out of the corporate current war over what exactly constitutes “good†governance.
The Interplay of Financial Education, Financial Literacy, Financial Inclusion and Financial, Stability: Any Lessons for the Current Big Tech Era?
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The entry of Big Tech firms in the financial ecosystem might affect financial stability through the opportunities and challenges they create for financial inclusion. In this paper we survey the literature to determine the effectiveness of financial education in improving financial literacy and financial inclusion and to assess the impact of financial inclusion on financial stability. Based on our findings, we argue that new empirical research is needed to determine whether financial education can play a role in ensuring that everyone is able to reap the financial-inclusion benefits that Big Tech may bring. We also conclude that financial-inclusion opportunities created by Big Tech might potentially introduce risks for overall financial stability. Because of this, we underline the importance of proper supervision and regulation.
SSRN
The entry of Big Tech firms in the financial ecosystem might affect financial stability through the opportunities and challenges they create for financial inclusion. In this paper we survey the literature to determine the effectiveness of financial education in improving financial literacy and financial inclusion and to assess the impact of financial inclusion on financial stability. Based on our findings, we argue that new empirical research is needed to determine whether financial education can play a role in ensuring that everyone is able to reap the financial-inclusion benefits that Big Tech may bring. We also conclude that financial-inclusion opportunities created by Big Tech might potentially introduce risks for overall financial stability. Because of this, we underline the importance of proper supervision and regulation.
The Monetization of Innovation
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We develop a dynamic model of the innovative firms that invest in monetization, which represents the process of generating revenues from services provided to customers at no charge. The model reflects the challenges faced by firms that operate via the Internet, whose dynamics are shaped by the decoupling of customer acquisition and revenues growth. Our model captures and explains why such firms often build a large customer base and become highly valued while continuing to suffer losses â€" traditional models would struggle to explain this pattern. Counterfactual analysis reveals that monetization uncertainty slows technological advancement by diverting resources away from innovation.
SSRN
We develop a dynamic model of the innovative firms that invest in monetization, which represents the process of generating revenues from services provided to customers at no charge. The model reflects the challenges faced by firms that operate via the Internet, whose dynamics are shaped by the decoupling of customer acquisition and revenues growth. Our model captures and explains why such firms often build a large customer base and become highly valued while continuing to suffer losses â€" traditional models would struggle to explain this pattern. Counterfactual analysis reveals that monetization uncertainty slows technological advancement by diverting resources away from innovation.
The Sensitivity of Cash Savings to the Cost of Capital
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We show theoretically and empirically that in the presence of time-varying cost of capital (COC), firms have a hedging motive to reduce the overall COC by saving cash when COC is relatively low. The sensitivity of cash savings to COC is especially pronounced with respect to the cost of equity and for firms with greater correlation between COC and financing needs for future investments. Both financially constrained and unconstrained firms respond to low COC by saving cash out of external capital issuance in excess of current financial needs.
SSRN
We show theoretically and empirically that in the presence of time-varying cost of capital (COC), firms have a hedging motive to reduce the overall COC by saving cash when COC is relatively low. The sensitivity of cash savings to COC is especially pronounced with respect to the cost of equity and for firms with greater correlation between COC and financing needs for future investments. Both financially constrained and unconstrained firms respond to low COC by saving cash out of external capital issuance in excess of current financial needs.
Using Equity Market Reactions to Infer Exposure to Trade Liberalization
SSRN
We outline a method for using asset prices to identify firm exposure to changes in policy. We highlight the benefits of this approach for studying trade agreements and apply it to two US trade liberalizations, with China and Canada. We find that abnormal equity returns during key events associated with these liberalizations are correlated with standard measures of import competition, vary across firms even within industries, predict subsequent firm outcomes, and provide a more complete view of distributional implications. In both cases, predicted relative increases in operating profit among the very largest firms dwarf the relative losses of smaller firms.
SSRN
We outline a method for using asset prices to identify firm exposure to changes in policy. We highlight the benefits of this approach for studying trade agreements and apply it to two US trade liberalizations, with China and Canada. We find that abnormal equity returns during key events associated with these liberalizations are correlated with standard measures of import competition, vary across firms even within industries, predict subsequent firm outcomes, and provide a more complete view of distributional implications. In both cases, predicted relative increases in operating profit among the very largest firms dwarf the relative losses of smaller firms.
Volatility, the Macroeconomy and Asset Prices
SSRN
How important are volatility fluctuations for asset prices and the macroeconomy? We find that a rise in macroeconomic volatility is associated with a rise in discount rates and a decline in consumption. To study the impact of volatility we provide a framework in which cashflow, discount-rate, and volatility risks determine risk premia. We show that volatility plays a significant role in jointly accounting for returns to human capital and equity. Volatility risks carry a sizeable positive risk premium and help explain the cross-section of expected returns. Our evidence shows that volatility is important for understanding expected returns and macroeconomic fluctuations.
SSRN
How important are volatility fluctuations for asset prices and the macroeconomy? We find that a rise in macroeconomic volatility is associated with a rise in discount rates and a decline in consumption. To study the impact of volatility we provide a framework in which cashflow, discount-rate, and volatility risks determine risk premia. We show that volatility plays a significant role in jointly accounting for returns to human capital and equity. Volatility risks carry a sizeable positive risk premium and help explain the cross-section of expected returns. Our evidence shows that volatility is important for understanding expected returns and macroeconomic fluctuations.
