Research articles for the 2020-09-05
Acquisition Experience and Director Remuneration
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We investigate whether acquisition experience of executive and non-executive directors is priced in their remuneration. We find that acquisition experience generates a contractual premium, and the relative size of this premium is higher for non-executive directors than for executives. Only a director’s track record related to past successful acquisitions is priced. Acquisition experience at the individual director is not remunerated if this type of experience is already abundantly present in the firm through the firm’s past acquisition record or via the experience of the other board members. We verify the results by examining potential endogeneity concerns, by analyzing a broad set of different views on acquisition experience (such as industry specific, broad or international experience, experience on a target’s board), and by ruling out alternative explanations (such as a director’s general skills level or reputation).
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We investigate whether acquisition experience of executive and non-executive directors is priced in their remuneration. We find that acquisition experience generates a contractual premium, and the relative size of this premium is higher for non-executive directors than for executives. Only a director’s track record related to past successful acquisitions is priced. Acquisition experience at the individual director is not remunerated if this type of experience is already abundantly present in the firm through the firm’s past acquisition record or via the experience of the other board members. We verify the results by examining potential endogeneity concerns, by analyzing a broad set of different views on acquisition experience (such as industry specific, broad or international experience, experience on a target’s board), and by ruling out alternative explanations (such as a director’s general skills level or reputation).
Aggregate Corporate Tax Avoidance and Cost of Capital
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We identify a pecuniary externality arising from corporate tax avoidance. Firms share risk with the government via taxation. The lower the tax rate applied to a firm’s earnings, the more risk is borne by its shareholders. As more firms engage in avoidance in the aggregate, the variance of the market’s after-tax cash flow increases. Consequently, the covariance of a firm’s cash flow with the market cash flow, and thereby its cost of capital, increases. This occurs both for firms that avoid taxes and for those that do not. Consistent with our prediction, we find that firms’ implied cost of capital is positively related to aggregate corporate tax avoidance. This result holds not only for tax-avoiding but, crucially, also for non-tax-avoiding firms. As we predict, the pecuniary externality is stronger for firms whose cash flow covaries more with the market cash flow, and is driven by tax avoidance strategies that reduce a firm’s marginal tax rate as opposed to reducing its tax base.
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We identify a pecuniary externality arising from corporate tax avoidance. Firms share risk with the government via taxation. The lower the tax rate applied to a firm’s earnings, the more risk is borne by its shareholders. As more firms engage in avoidance in the aggregate, the variance of the market’s after-tax cash flow increases. Consequently, the covariance of a firm’s cash flow with the market cash flow, and thereby its cost of capital, increases. This occurs both for firms that avoid taxes and for those that do not. Consistent with our prediction, we find that firms’ implied cost of capital is positively related to aggregate corporate tax avoidance. This result holds not only for tax-avoiding but, crucially, also for non-tax-avoiding firms. As we predict, the pecuniary externality is stronger for firms whose cash flow covaries more with the market cash flow, and is driven by tax avoidance strategies that reduce a firm’s marginal tax rate as opposed to reducing its tax base.
Categorization Effects in Capital Markets: Evidence From Unicorn IPOs
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We use the introduction of the Unicorn nomenclature to reference venture-backed firms with valuations in excess of $1 billion to examine how firm categorization influences investor demand and retail trade activity during IPO price formation. We predict and find evidence to suggest that the positive appeal associated with an IPO firm’s Unicorn categorization increases IPO investor demand, as evidenced by the firm’s shares pricing above the proposed IPO pricing range and experiencing higher first-day returns relative to an entropy-matched sample of control firms. Adopting a structural-equation methodology that considers explicitly the sequence of IPO price formation, we also show that Unicorn categorization is informative for understanding retail trade activity both directly and indirectly through the mediating effects of news coverage. We also show that Unicorn categorization relates negatively to post-IPO stock performance, and that Unicorn categorization increases the sensitivity of post-IPO stock performance to pre-IPO profitability. These findings, taken together, provide evidence that categorization hides category members’ individual idiosyncrasies and causes them to assume the category’s affective tone.
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We use the introduction of the Unicorn nomenclature to reference venture-backed firms with valuations in excess of $1 billion to examine how firm categorization influences investor demand and retail trade activity during IPO price formation. We predict and find evidence to suggest that the positive appeal associated with an IPO firm’s Unicorn categorization increases IPO investor demand, as evidenced by the firm’s shares pricing above the proposed IPO pricing range and experiencing higher first-day returns relative to an entropy-matched sample of control firms. Adopting a structural-equation methodology that considers explicitly the sequence of IPO price formation, we also show that Unicorn categorization is informative for understanding retail trade activity both directly and indirectly through the mediating effects of news coverage. We also show that Unicorn categorization relates negatively to post-IPO stock performance, and that Unicorn categorization increases the sensitivity of post-IPO stock performance to pre-IPO profitability. These findings, taken together, provide evidence that categorization hides category members’ individual idiosyncrasies and causes them to assume the category’s affective tone.
Combining Penalization and Adaption in High Dimension with Application in Bond Risk Premia Forecasting
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The predictability of a high-dimensional time series model in forecasting with large information sets depends not only on the stability of parameters but also depends heavily on the active covariates in the model. Since the true empirical environment can change as time goes by, the variables that function well at the present may become useless in the future. Combined with the instable parameters, finding the most active covariates in the parameter time-varying situations becomes difficult. In this paper, we aim to propose a new method, the Penalized Adaptive Method (PAM), which can adaptively detect the parameter homogeneous intervals and simultaneously select the active variables in sparse models. The newly developed method is able to identify the parameters stability at one hand and meanwhile, at the other hand, can manage of selecting the active forecasting covariates at every different time point. Comparing with the classical models, the method can be applied to high-dimensional cases with different sources of parameter changes while it steadily reduces the forecast error in high- dimensional data. In the out-of-sample bond risk premia forecasting, the Penalized Adaptive Method can reduce the forecasting error(RMSPE and MAPE) around 24% to 50% comparing with the other forecasting methods.
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The predictability of a high-dimensional time series model in forecasting with large information sets depends not only on the stability of parameters but also depends heavily on the active covariates in the model. Since the true empirical environment can change as time goes by, the variables that function well at the present may become useless in the future. Combined with the instable parameters, finding the most active covariates in the parameter time-varying situations becomes difficult. In this paper, we aim to propose a new method, the Penalized Adaptive Method (PAM), which can adaptively detect the parameter homogeneous intervals and simultaneously select the active variables in sparse models. The newly developed method is able to identify the parameters stability at one hand and meanwhile, at the other hand, can manage of selecting the active forecasting covariates at every different time point. Comparing with the classical models, the method can be applied to high-dimensional cases with different sources of parameter changes while it steadily reduces the forecast error in high- dimensional data. In the out-of-sample bond risk premia forecasting, the Penalized Adaptive Method can reduce the forecasting error(RMSPE and MAPE) around 24% to 50% comparing with the other forecasting methods.
Do Futures Premiums Predict Commodity Producer Returns?
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We derive stock returns for firms producing nonrenewable commodities by employing the investment-based asset pricing approach. By identifying the appropriate time-varying discount rate the investment-based approach allows an alternative test of the Hotelling Valuation Principle. The empirical results support the principle and enable predicting returns from sorting firms into quintiles by expected return, producing a 19 percent realized difference between top and bottom quintile. The return differences cannot be explained by standard systematic risk factors, suggesting that at least one important risk factor is missing from standard models. The approach permits cost-of-capital estimation that circumvents identifying systematic risk factors.
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We derive stock returns for firms producing nonrenewable commodities by employing the investment-based asset pricing approach. By identifying the appropriate time-varying discount rate the investment-based approach allows an alternative test of the Hotelling Valuation Principle. The empirical results support the principle and enable predicting returns from sorting firms into quintiles by expected return, producing a 19 percent realized difference between top and bottom quintile. The return differences cannot be explained by standard systematic risk factors, suggesting that at least one important risk factor is missing from standard models. The approach permits cost-of-capital estimation that circumvents identifying systematic risk factors.
Do Short-term Incentives Hurt Innovation?
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We study how incentives to boost short-term performance affect longer-term innovation output. Share repurchases that are motivated by an incentive to meet current-quarter EPS targets are associated with an increase in the quality of innovation outputs such as forward citation counts and the economic value of patents. These results appear to be driven by a shift in firms’ innovation strategy. Firms are more likely to explore newer technologies and to increase the scope of innovative activities following EPS-driven repurchases. Our evidence points out to a bright side of short-termist pressures, which can nudge firms towards more creative and impactful innovation.
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We study how incentives to boost short-term performance affect longer-term innovation output. Share repurchases that are motivated by an incentive to meet current-quarter EPS targets are associated with an increase in the quality of innovation outputs such as forward citation counts and the economic value of patents. These results appear to be driven by a shift in firms’ innovation strategy. Firms are more likely to explore newer technologies and to increase the scope of innovative activities following EPS-driven repurchases. Our evidence points out to a bright side of short-termist pressures, which can nudge firms towards more creative and impactful innovation.
Enhanced Informal Networks: Costly State Verification and the Village Fund Intervention
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Using data for over 600 households in 16 villages from Townsend Thai project, we find that the role of preexisting informal kinship networks in Thailand was enhanced following a quasi-formal village fund program in 2001. Transfers (gifts) among poor households play a crucial role in funding investment. This transfer mechanism and its role in investment were amplified for the poor households after the village fund, especially those with kinship ties. Moreover, we document a financial regime shift using maximum-likelihood estimation. Two exogenously incomplete regimes (saving only and lending/borrowing) dominated in the full sample and for the relatively poor before the village fund, but costly state verification, a less incomplete financial regime, dominates in the subsample of poor households following the village fund. The structurally-estimated cost of verification of the households with kinship is also significantly lower than the one without kinship after 2001, relative to before, suggesting the role of kinship was enhanced.
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Using data for over 600 households in 16 villages from Townsend Thai project, we find that the role of preexisting informal kinship networks in Thailand was enhanced following a quasi-formal village fund program in 2001. Transfers (gifts) among poor households play a crucial role in funding investment. This transfer mechanism and its role in investment were amplified for the poor households after the village fund, especially those with kinship ties. Moreover, we document a financial regime shift using maximum-likelihood estimation. Two exogenously incomplete regimes (saving only and lending/borrowing) dominated in the full sample and for the relatively poor before the village fund, but costly state verification, a less incomplete financial regime, dominates in the subsample of poor households following the village fund. The structurally-estimated cost of verification of the households with kinship is also significantly lower than the one without kinship after 2001, relative to before, suggesting the role of kinship was enhanced.
Hedge Fund Family Ties
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Using a novel dataset, I show that hedge fund managers connected through shared employment histories hold and co-trade more of the same stocks than unconnected managers. Results are greater between fund pairs with stronger social connections and longer dated relationships, implying a socially reinforcing channel is responsible. A long-short portfolio of overlapped socially connected versus unconnected stocks generates alpha of 13.3% per year. Findings herein support models of manager coordination and identifies employment linked hedge funds as a common source of correlated risk and return.
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Using a novel dataset, I show that hedge fund managers connected through shared employment histories hold and co-trade more of the same stocks than unconnected managers. Results are greater between fund pairs with stronger social connections and longer dated relationships, implying a socially reinforcing channel is responsible. A long-short portfolio of overlapped socially connected versus unconnected stocks generates alpha of 13.3% per year. Findings herein support models of manager coordination and identifies employment linked hedge funds as a common source of correlated risk and return.
How Do Regulatory Costs Affect M&A Decisions and Outcomes?
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Regulations introduce significant fixed costs, and add to operating leverage. “Regulatory operating leverageâ€, introduced by Ince and Ozsoylev (2020), quantifies the ratio of regulatory fixed costs over a firm’s cost structure. Regulatory operating leverage decreases a firm’s value through implied cost of equity and profitability channels. Due to economies of scale, large firms are less exposed to the negative value implications of regulatory operating leverage. This motivates large firms with high regulatory operating leverage to acquire other firms in the same industry. Moreover, it increases the likelihood of a small firm being target. Finally, regulatory operating leverage driven acquisitions are value increasing.
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Regulations introduce significant fixed costs, and add to operating leverage. “Regulatory operating leverageâ€, introduced by Ince and Ozsoylev (2020), quantifies the ratio of regulatory fixed costs over a firm’s cost structure. Regulatory operating leverage decreases a firm’s value through implied cost of equity and profitability channels. Due to economies of scale, large firms are less exposed to the negative value implications of regulatory operating leverage. This motivates large firms with high regulatory operating leverage to acquire other firms in the same industry. Moreover, it increases the likelihood of a small firm being target. Finally, regulatory operating leverage driven acquisitions are value increasing.
Insider Trading with Temporary Price Impact
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We model an informed agent with information about the future value of an asset trying to maximize profits when subjected to a transaction cost as well as a market maker tasked with setting fair transaction prices. In a single auction model, equilibrium is characterized by the unique root of a particular polynomial. Analysis of this polynomial with small levels of risk-aversion and transaction costs reveal a dimensionless parameter which captures several orders of asymptotic accuracy of the equilibrium behaviour. In a continuous time analogue of the single auction model, incorporation of a transaction costs allows the informed agent's optimal trading strategy to be obtained in feedback form. Linear equilibrium is characterized by the unique solution to a system of two ordinary differential equations, of which one is forward in time and one is backward. When transaction costs are in effect, the price set by the market maker in equilibrium is not fully revealing of the informed agent's private signal, leaving an information gap at the end of the trading interval. When considering vanishing transaction costs, the equilibrium trading strategy and pricing rules converge to their frictionless counterparts.
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We model an informed agent with information about the future value of an asset trying to maximize profits when subjected to a transaction cost as well as a market maker tasked with setting fair transaction prices. In a single auction model, equilibrium is characterized by the unique root of a particular polynomial. Analysis of this polynomial with small levels of risk-aversion and transaction costs reveal a dimensionless parameter which captures several orders of asymptotic accuracy of the equilibrium behaviour. In a continuous time analogue of the single auction model, incorporation of a transaction costs allows the informed agent's optimal trading strategy to be obtained in feedback form. Linear equilibrium is characterized by the unique solution to a system of two ordinary differential equations, of which one is forward in time and one is backward. When transaction costs are in effect, the price set by the market maker in equilibrium is not fully revealing of the informed agent's private signal, leaving an information gap at the end of the trading interval. When considering vanishing transaction costs, the equilibrium trading strategy and pricing rules converge to their frictionless counterparts.
Interested Intermediaries
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We examine the implications of interested intermediaries on corporate actions, stock prices, and investors' portfolio decisions. An interested intermediary is an asset manager who has private preferences over corporate actions, which could relate to corporate governance policies, social or environmental performance, payout policy, etc. While large intermediaries can help solve the free-riding problem that prevents small investors from exerting beneficial influence activities, the free-rider problem persists as investors optimally choose not to delegate to the intermediary, absent frictions. We show that, due to free riding, intermediaries benefit from mechanisms that allow them to economize on costly influence efforts, such as interests aligned with managers, negative externalities across portfolio firms, and similarly-interested insiders. Our findings have implications for research and policy-making related to asset management, investor activism, and corporate social responsibility.
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We examine the implications of interested intermediaries on corporate actions, stock prices, and investors' portfolio decisions. An interested intermediary is an asset manager who has private preferences over corporate actions, which could relate to corporate governance policies, social or environmental performance, payout policy, etc. While large intermediaries can help solve the free-riding problem that prevents small investors from exerting beneficial influence activities, the free-rider problem persists as investors optimally choose not to delegate to the intermediary, absent frictions. We show that, due to free riding, intermediaries benefit from mechanisms that allow them to economize on costly influence efforts, such as interests aligned with managers, negative externalities across portfolio firms, and similarly-interested insiders. Our findings have implications for research and policy-making related to asset management, investor activism, and corporate social responsibility.
Intraday Jumps, Liquidity, and U.S. Macroeconomic News: Evidence from Exchange Traded Funds
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This paper uses two highly liquid S&P 500 and gold exchange-traded funds (ETFs) to evaluate the impact of liquidity and macroeconomic news surprises on the frequency of observing intraday jumps. It explicitly addresses market microstructure noise-induced biases in realized estimators used in jump detection tests and applies non-parametric intraday jump detection tests. The results show a significant increase in trading costs and elevated levels of information asymmetry before observing jumps. Depth, resiliency, and trading activity are associated with the frequency of observing intraday jumps and cojumps. The ability of liquidity variables to predict intraday jumps persists after controlling for news surprises. Results show that intraday jump realizations affect the price discovery of ETFs.
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This paper uses two highly liquid S&P 500 and gold exchange-traded funds (ETFs) to evaluate the impact of liquidity and macroeconomic news surprises on the frequency of observing intraday jumps. It explicitly addresses market microstructure noise-induced biases in realized estimators used in jump detection tests and applies non-parametric intraday jump detection tests. The results show a significant increase in trading costs and elevated levels of information asymmetry before observing jumps. Depth, resiliency, and trading activity are associated with the frequency of observing intraday jumps and cojumps. The ability of liquidity variables to predict intraday jumps persists after controlling for news surprises. Results show that intraday jump realizations affect the price discovery of ETFs.
Investor Sophistication and Portfolio Dynamics
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We develop a dynamic general-equilibrium framework with multiple households and multiple risky assets to explain how less- and more-sophisticated households differ in their portfolio and wealth dynamics. Differences in sophistication are modeled via heterogeneous confidence about asset returns, coupled with Bayesian learning. Consistent with recent empirical evidence, less-sophisticated households overinvest in safe assets, hold underdiversified portfolios concentrated in familiar assets, are trend chasers, and earn lower absolute and risk-adjusted investment returns. Notably, this behavior is a consequence of optimal choices rather than investment mistakes. The model explains why this behavior, despite learning, persists for long periods, thereby exacerbating wealth inequality.
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We develop a dynamic general-equilibrium framework with multiple households and multiple risky assets to explain how less- and more-sophisticated households differ in their portfolio and wealth dynamics. Differences in sophistication are modeled via heterogeneous confidence about asset returns, coupled with Bayesian learning. Consistent with recent empirical evidence, less-sophisticated households overinvest in safe assets, hold underdiversified portfolios concentrated in familiar assets, are trend chasers, and earn lower absolute and risk-adjusted investment returns. Notably, this behavior is a consequence of optimal choices rather than investment mistakes. The model explains why this behavior, despite learning, persists for long periods, thereby exacerbating wealth inequality.
Large Order Size Liquidity in Treasury Markets
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We measure market liquidity for large-sized orders in the ten-year treasury futures market estimating mean-variance frontiers for their execution cost during the period of 2012 to 2017. We identify large orders from regulatory transaction data and introduce a methodological innovation to infer the urgency of a large order from the pattern of its execution. We find that the mean-variance frontier becomes significantly worse as order size increases, but that the frontier has improved over the time period studied. We also find that the costs of executing large orders on behalf of customers are significantly greater than the costs of executing orders for house accounts.
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We measure market liquidity for large-sized orders in the ten-year treasury futures market estimating mean-variance frontiers for their execution cost during the period of 2012 to 2017. We identify large orders from regulatory transaction data and introduce a methodological innovation to infer the urgency of a large order from the pattern of its execution. We find that the mean-variance frontier becomes significantly worse as order size increases, but that the frontier has improved over the time period studied. We also find that the costs of executing large orders on behalf of customers are significantly greater than the costs of executing orders for house accounts.
Media-Expressed Tone, Option Characteristics, and Stock Return Predictability
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We distill tone from a huge assortment of NASDAQ articles to examine the predictive power of media-expressed tone in single-stock option markets and equity markets. We find that (1) option markets are impacted by media tone; (2) option variables predict stock returns along with tone; (3) option variables orthogonalized to public information and tone are more effective predictors of stock returns; (4) overnight tone appears to be more informative than trading- time tone, possibly due to a different thematic coverage of the trading versus the overnight archive; (5) tone disagreement commands a strong positive risk premium above and beyond market volatility.
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We distill tone from a huge assortment of NASDAQ articles to examine the predictive power of media-expressed tone in single-stock option markets and equity markets. We find that (1) option markets are impacted by media tone; (2) option variables predict stock returns along with tone; (3) option variables orthogonalized to public information and tone are more effective predictors of stock returns; (4) overnight tone appears to be more informative than trading- time tone, possibly due to a different thematic coverage of the trading versus the overnight archive; (5) tone disagreement commands a strong positive risk premium above and beyond market volatility.
Policy Uncertainty in Australian Financial Markets
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Economic policy touches most facets of corporate decision-making and variations in policy can elicit significant changes in financial performance and asset prices. We utilise the EPU measure of Baker et al. (2016) to investigate the extent to which policy uncertainty influences Australian financial market returns. Our empirical results demonstrate that both domestic and global uncertainty have a significant negative impact on excess stock returns, changes in bond yields and AUD returns. The relationship is concentrated in the left tail of the return distribution and largely driven by increases in policy uncertainty. Although the identified relationship is negative throughout the sample period, the magnitude of the relationship appears to be state dependent and is influenced by periods of high uncertainty, recession, and the lead-up to federal elections. The most plausible explanation for our results is that uncertainty about economic policy is channelled to financial markets via the discount rate effect, resulting in a higher risk premium. Our results are important for investors, corporate managers, and policy makers wishing to navigate periods of policy uncertainty.
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Economic policy touches most facets of corporate decision-making and variations in policy can elicit significant changes in financial performance and asset prices. We utilise the EPU measure of Baker et al. (2016) to investigate the extent to which policy uncertainty influences Australian financial market returns. Our empirical results demonstrate that both domestic and global uncertainty have a significant negative impact on excess stock returns, changes in bond yields and AUD returns. The relationship is concentrated in the left tail of the return distribution and largely driven by increases in policy uncertainty. Although the identified relationship is negative throughout the sample period, the magnitude of the relationship appears to be state dependent and is influenced by periods of high uncertainty, recession, and the lead-up to federal elections. The most plausible explanation for our results is that uncertainty about economic policy is channelled to financial markets via the discount rate effect, resulting in a higher risk premium. Our results are important for investors, corporate managers, and policy makers wishing to navigate periods of policy uncertainty.
Risk of Bitcoin Market: Volatility, Jumps, and Forecasts
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Among all the emerging markets, the cryptocurrency market is considered the most controversial and simultaneously the most interesting one. The visibly significant market capitalization of cryptos motivates modern financial instruments such as futures and options. Those will depend on the dynamics, volatility, or even the jumps of cryptos. In this paper, the risk characteristics for Bitcoin are analyzed from a realized volatility dynamics view. The realized variance RV is estimated with (threshold-)jump components (T)J, semivariance RSV+(âˆ'), and signed jumps (T)J+(âˆ'). Our empirical results show that the Bitcoin market is far riskier than any other developed financial market. Up to 68% of the sample days are identified to entangle jumps. However, the discontinuities do not contribute to the variance significantly. By employing a 90-day rolling-window method, the in-sample evidence suggests that the impacts of predictors change over time systematically under HAR-type models. The out-of-sample forecasting results reveal that the forecasting horizon plays an important role in choosing forecasting models. For long-horizon risk forecast, a finer model calibrated with jumps gives extra utility up to 20 basis points annually, while an approach based on the roughest estimators suits the short-horizon risk forecast best. Last but not least, a simple equal-weighted portfolio not only significantly reduces the size and quantity of jumps but also gives investors higher utility in short-horizon risk forecast case.
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Among all the emerging markets, the cryptocurrency market is considered the most controversial and simultaneously the most interesting one. The visibly significant market capitalization of cryptos motivates modern financial instruments such as futures and options. Those will depend on the dynamics, volatility, or even the jumps of cryptos. In this paper, the risk characteristics for Bitcoin are analyzed from a realized volatility dynamics view. The realized variance RV is estimated with (threshold-)jump components (T)J, semivariance RSV+(âˆ'), and signed jumps (T)J+(âˆ'). Our empirical results show that the Bitcoin market is far riskier than any other developed financial market. Up to 68% of the sample days are identified to entangle jumps. However, the discontinuities do not contribute to the variance significantly. By employing a 90-day rolling-window method, the in-sample evidence suggests that the impacts of predictors change over time systematically under HAR-type models. The out-of-sample forecasting results reveal that the forecasting horizon plays an important role in choosing forecasting models. For long-horizon risk forecast, a finer model calibrated with jumps gives extra utility up to 20 basis points annually, while an approach based on the roughest estimators suits the short-horizon risk forecast best. Last but not least, a simple equal-weighted portfolio not only significantly reduces the size and quantity of jumps but also gives investors higher utility in short-horizon risk forecast case.
SONIC: SOcial Network with Influencers and Communities
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The integration of social media characteristics into an econometric framework requires modeling a high dimensional dynamic network with dimensions of parameter Θ typically much larger than the number of observations. To cope with this problem, we introduce a new structural model â€" SONIC which assumes that (1) a few influencers drive the network dynamics; (2) the community structure of the network is characterized as the homogeneity of response to the specific influencer, implying their underlying similarity. An estimation procedure is proposed based on a greedy algorithm and LASSO regularization. Through theoretical study and simulations, we show that the matrix parameter can be estimated even when the observed time interval is smaller than the size of the network. Using a novel dataset retrieved from a leading social media platform â€" StockTwits and quantifying their opinions via natural language processing, we model the opinions network dynamics among a select group of users and further detect the latent communities. With a sparsity regularization, we can identify important nodes in the network.
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The integration of social media characteristics into an econometric framework requires modeling a high dimensional dynamic network with dimensions of parameter Θ typically much larger than the number of observations. To cope with this problem, we introduce a new structural model â€" SONIC which assumes that (1) a few influencers drive the network dynamics; (2) the community structure of the network is characterized as the homogeneity of response to the specific influencer, implying their underlying similarity. An estimation procedure is proposed based on a greedy algorithm and LASSO regularization. Through theoretical study and simulations, we show that the matrix parameter can be estimated even when the observed time interval is smaller than the size of the network. Using a novel dataset retrieved from a leading social media platform â€" StockTwits and quantifying their opinions via natural language processing, we model the opinions network dynamics among a select group of users and further detect the latent communities. With a sparsity regularization, we can identify important nodes in the network.
Securitization of Assets with Payment Delay Risk: A Financial Innovation in the Real Estate Market
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We study a new type of securitization, mortgage-receivable-backed securities (MRBSs) issued by real estate developers. Unlike traditional mortgage-backed securities (MBSs), the major risk of underlying assets of MRBSs is payment delay instead of default and prepayment. Using unique loan-level data, we estimate proportional hazard models and detect factors that affect the risk of underlying assets of MRBSs, including bank characteristics, property-loan-household characteristics, local market conditions, and macroeconomic conditions. Especially, we find that the effects of house prices and LTVs on MRBS risk are the opposite of those on traditional MBS risk. Based on the estimates, we simulate cash flows of an underlying-asset pool and analyze the shortfall risk of the corresponding security tranches. Our analyses provide a benchmark for conducting appropriate security designs based on the composition of the underlying asset pool, increase the transparency for investors on the risk pattern of MRBSs, and provide implications for pricing and regulation.
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We study a new type of securitization, mortgage-receivable-backed securities (MRBSs) issued by real estate developers. Unlike traditional mortgage-backed securities (MBSs), the major risk of underlying assets of MRBSs is payment delay instead of default and prepayment. Using unique loan-level data, we estimate proportional hazard models and detect factors that affect the risk of underlying assets of MRBSs, including bank characteristics, property-loan-household characteristics, local market conditions, and macroeconomic conditions. Especially, we find that the effects of house prices and LTVs on MRBS risk are the opposite of those on traditional MBS risk. Based on the estimates, we simulate cash flows of an underlying-asset pool and analyze the shortfall risk of the corresponding security tranches. Our analyses provide a benchmark for conducting appropriate security designs based on the composition of the underlying asset pool, increase the transparency for investors on the risk pattern of MRBSs, and provide implications for pricing and regulation.
Separation in the Municipal Debt Market Following GASB 34 Implementation
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Governmental Accounting Standards Board Statement No. 34 (GASB 34), issued in 1999 with required implementation beginning in 2002, comprehensively and substantially changed the financial reporting model for state and local governments. Evidence reported in this study supports the notion that GASB 34 implementation created meaningful separation in the municipal debt market. High financial governments delayed, and low financial quality governments accelerated, new debt issuances in anticipation of GASB 34 implementation. Following GASB 34, high financial quality governments issued less insured debt and used greater debt relative to alternative financing sources (when compared with low financial quality governments). These results both support the efficacy of GASB 34 implementation and inform ongoing GASB deliberations regarding the financial reporting model for state and local governments.
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Governmental Accounting Standards Board Statement No. 34 (GASB 34), issued in 1999 with required implementation beginning in 2002, comprehensively and substantially changed the financial reporting model for state and local governments. Evidence reported in this study supports the notion that GASB 34 implementation created meaningful separation in the municipal debt market. High financial governments delayed, and low financial quality governments accelerated, new debt issuances in anticipation of GASB 34 implementation. Following GASB 34, high financial quality governments issued less insured debt and used greater debt relative to alternative financing sources (when compared with low financial quality governments). These results both support the efficacy of GASB 34 implementation and inform ongoing GASB deliberations regarding the financial reporting model for state and local governments.
Tail Risk Interdependence
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We present a framework focused on the interdependence of high-dimensional tail events. This framework allows us to analyze and quantify tail interdependence at different levels of extremity, decompose it into systemic and residual part and to measure the contribution of a constituent to the interdependence of a system. In particular, tail interdependence can capture simultaneous distress of the constituents of a (financial or economic) system and measure its systemic risk. We investigate systemic distress in several financial datasets confirming some known stylized facts and discovering some new findings. Further, we devise statistical tests of interdependence in the tails and outline some additional extensions.
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We present a framework focused on the interdependence of high-dimensional tail events. This framework allows us to analyze and quantify tail interdependence at different levels of extremity, decompose it into systemic and residual part and to measure the contribution of a constituent to the interdependence of a system. In particular, tail interdependence can capture simultaneous distress of the constituents of a (financial or economic) system and measure its systemic risk. We investigate systemic distress in several financial datasets confirming some known stylized facts and discovering some new findings. Further, we devise statistical tests of interdependence in the tails and outline some additional extensions.
The Channels of Banks’ Response to Negative Interest Rates
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Facing a potential zero lower bound on retail deposit interest rates, how do banks pass on the fall in net interest income due to negative interest rates? This paper aims to investigate the different channels of banks’ responses to negative interest rates using a detailed breakdown of the profit and loss account of 3645 banks in 59 countries from 2011 to 2018. We find that the decrease in interest income due to negative interest rates has been mitigated only partially by an increase in non-interest income. We show that banks responded to that shock by reducing the interest paid on non-customer deposit liabilities and their personnel expenses. We also show that banks’ responses are not instantaneous and that banks adjust their response as negative interest rates persist over time such that how long negative interest rates are implemented matters.
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Facing a potential zero lower bound on retail deposit interest rates, how do banks pass on the fall in net interest income due to negative interest rates? This paper aims to investigate the different channels of banks’ responses to negative interest rates using a detailed breakdown of the profit and loss account of 3645 banks in 59 countries from 2011 to 2018. We find that the decrease in interest income due to negative interest rates has been mitigated only partially by an increase in non-interest income. We show that banks responded to that shock by reducing the interest paid on non-customer deposit liabilities and their personnel expenses. We also show that banks’ responses are not instantaneous and that banks adjust their response as negative interest rates persist over time such that how long negative interest rates are implemented matters.
The Digital Programmable Euro, Libra and CBDC: Implications for European Banks
SSRN
Existing payment systems get more and more disrupted. As a consequence of the global trend of digitizing payments and generating new business models from the use of blockchain-based digital programmable money, several new payment initiatives have been announced recently. Besides “classical†crypto assets, also stablecoins become increasingly important. The announcement of the Facebook-initiated Libra stablecoin is mainly perceived as a game-changer for the financial sector. Today, also central banks discuss the introduction of their own digital currencies, so-called CBDCs. To date, these payment innovations are not sufficiently discussed and analyzed from the perspective of different sectors and industries, as its implications remain unclear since most initiatives have not yet been introduced. At this point, the literature does not sufficiently discuss the implications of these innovations on the financial sector. This paper sheds light on the perception of these payment initiatives by interviewing more than 50 senior experts. In this study, we analyze the impact of digital programmable Euro initiatives, such as the Libra stablecoin, and CBDCs, on banks. We find that both Libra and a Euro CBDC might heavily affect European banks. Experts fear that large-scale financial disintermediation of the financial sector could take place, and digital bank runs could be triggered. Besides these risks, our findings suggest that banks also have the opportunity to develop new business models stemming from these initiatives. Therefore, Libra and a CBDC Euro should not only be seen as threats but also as opportunities.
SSRN
Existing payment systems get more and more disrupted. As a consequence of the global trend of digitizing payments and generating new business models from the use of blockchain-based digital programmable money, several new payment initiatives have been announced recently. Besides “classical†crypto assets, also stablecoins become increasingly important. The announcement of the Facebook-initiated Libra stablecoin is mainly perceived as a game-changer for the financial sector. Today, also central banks discuss the introduction of their own digital currencies, so-called CBDCs. To date, these payment innovations are not sufficiently discussed and analyzed from the perspective of different sectors and industries, as its implications remain unclear since most initiatives have not yet been introduced. At this point, the literature does not sufficiently discuss the implications of these innovations on the financial sector. This paper sheds light on the perception of these payment initiatives by interviewing more than 50 senior experts. In this study, we analyze the impact of digital programmable Euro initiatives, such as the Libra stablecoin, and CBDCs, on banks. We find that both Libra and a Euro CBDC might heavily affect European banks. Experts fear that large-scale financial disintermediation of the financial sector could take place, and digital bank runs could be triggered. Besides these risks, our findings suggest that banks also have the opportunity to develop new business models stemming from these initiatives. Therefore, Libra and a CBDC Euro should not only be seen as threats but also as opportunities.
The End of an Era: Who Pays the Price when the Livestock Futures Pits Close?
SSRN
This paper evaluates how the closure of the futures pits impacted the execution costs of customer orders in the livestock futures market. Our results indicate that the execution cost of electronic orders placed by customers who were active in the pit increase after the pit closure. We find no evidence that this is due to an increase in trading with high-frequency traders. However, we find that the overall per contract unit execution costs, including pit and electronic orders, has declined for pit users, after the pit closure. Our findings suggest that this decline in overall execution costs can be attributed to the complete or partial withdrawal of some pit users from the market, while the detected increase in their execution costs in the electronic market is likely due to the migration of some informed pit orders to the electronic order book.
SSRN
This paper evaluates how the closure of the futures pits impacted the execution costs of customer orders in the livestock futures market. Our results indicate that the execution cost of electronic orders placed by customers who were active in the pit increase after the pit closure. We find no evidence that this is due to an increase in trading with high-frequency traders. However, we find that the overall per contract unit execution costs, including pit and electronic orders, has declined for pit users, after the pit closure. Our findings suggest that this decline in overall execution costs can be attributed to the complete or partial withdrawal of some pit users from the market, while the detected increase in their execution costs in the electronic market is likely due to the migration of some informed pit orders to the electronic order book.
The Influence of Short Selling on the Production and Market Consequences of Negative Press Coverage
SSRN
The production, dissemination and market consequences of firm-specific information are shaped by the incentives of market players operating within the constraints imposed by securities regulation. In this paper we focus on constraints to short selling activity and address two questions: Do short sale constraints influence (1) the extent to which the business press reports negative news stories?; and (2) the speed and intensity with which market participants respond to the publication of negative news reports? Following exogenous relief of short sale constraints, we find that treated firms’ press coverage tilts significantly more negative relative to untreated firms still facing higher constraints. This result is stronger for media-initiated articles than for firm-initiated press releases. With respect to market consequences we find that for treated firms, stock returns and open short interest become significantly more sensitive to negative news reports, and news sentiment-based trading strategies earn lower abnormal returns.
SSRN
The production, dissemination and market consequences of firm-specific information are shaped by the incentives of market players operating within the constraints imposed by securities regulation. In this paper we focus on constraints to short selling activity and address two questions: Do short sale constraints influence (1) the extent to which the business press reports negative news stories?; and (2) the speed and intensity with which market participants respond to the publication of negative news reports? Following exogenous relief of short sale constraints, we find that treated firms’ press coverage tilts significantly more negative relative to untreated firms still facing higher constraints. This result is stronger for media-initiated articles than for firm-initiated press releases. With respect to market consequences we find that for treated firms, stock returns and open short interest become significantly more sensitive to negative news reports, and news sentiment-based trading strategies earn lower abnormal returns.
