Research articles for the 2019-03-22
A Framework for Risk Premia Investing: Anywhere to Hide?
SSRN
Alternative risk premia (ARP) strategies are traditionally assumed to diversify well both equity and bond market risk. We investigate alternative risk premia composites based on investment bank indices to describe the nature and risk characteristics of commonly known investable ARP strategies. While most of the strategies have low full sample betas to both equity and commodity markets, there are several strategies with statistically significant positive betas to bond markets. Additionally, risk characteristics of most of the ARP strategies change in the tails of equity and bond market return distributions, which makes it questionable to use whole sample volatilities and correlations in portfolio construction. Instead, we propose an updated framework for risk premia investing to construct diversified ARP portfolios by using a hierarchical risk allocation process.
SSRN
Alternative risk premia (ARP) strategies are traditionally assumed to diversify well both equity and bond market risk. We investigate alternative risk premia composites based on investment bank indices to describe the nature and risk characteristics of commonly known investable ARP strategies. While most of the strategies have low full sample betas to both equity and commodity markets, there are several strategies with statistically significant positive betas to bond markets. Additionally, risk characteristics of most of the ARP strategies change in the tails of equity and bond market return distributions, which makes it questionable to use whole sample volatilities and correlations in portfolio construction. Instead, we propose an updated framework for risk premia investing to construct diversified ARP portfolios by using a hierarchical risk allocation process.
A Theory of Scenario Generation
SSRN
We show how distributions can be reduced to low-dimensional scenario trees. Applied to intertemporal distributions, the scenarios and their probabilities become time-varying factors. From S&P 500 options, two or three time-varying scenarios suffice to forecast returns, implied variance or skewness on par, or better, than extant multivariate stochastic volatility jump-diffusion models, while reducing the computational effort to fractions of a second.
SSRN
We show how distributions can be reduced to low-dimensional scenario trees. Applied to intertemporal distributions, the scenarios and their probabilities become time-varying factors. From S&P 500 options, two or three time-varying scenarios suffice to forecast returns, implied variance or skewness on par, or better, than extant multivariate stochastic volatility jump-diffusion models, while reducing the computational effort to fractions of a second.
An Empirical Analysis of Corporate Currency Risk Management Policies and Practices
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Using a unique and extremely granular data set of complete currency spot and derivatives positions for 101 large non-financial corporations, we compare the stated currency risk management policies with the actual strategies executed by these companies. We identify a notable discord between their policies and their practices. We next find that these companies engage in a high degree of currency speculation that seems to be driven by market movements with the results strongest for the heaviest derivatives users. Finally, we show that these companies attempt to time the market even when they are engaged in hedging. Thus, the risk management policies and practices of non-financial corporations are far from what companies say they are and are evidence of a high degree of speculation and especially hedge timing in a market outside of their own core lines of business.
SSRN
Using a unique and extremely granular data set of complete currency spot and derivatives positions for 101 large non-financial corporations, we compare the stated currency risk management policies with the actual strategies executed by these companies. We identify a notable discord between their policies and their practices. We next find that these companies engage in a high degree of currency speculation that seems to be driven by market movements with the results strongest for the heaviest derivatives users. Finally, we show that these companies attempt to time the market even when they are engaged in hedging. Thus, the risk management policies and practices of non-financial corporations are far from what companies say they are and are evidence of a high degree of speculation and especially hedge timing in a market outside of their own core lines of business.
Assessing Outsourced Distribution Channels
SSRN
We respond to recent failed initiatives of the Czech banking market to develop business models for the sale of retail deposit products, based on third-party distribution channels. We argue that the issue is the application of inappropriate capital budgeting methods. While static cost-benefit analysis seems to be generally appropriate for conventional banking projects based on branching or internet, they provide grossly misleading estimates of commissioning expenses, which can lead to completely unrealistic project assessments and poorly designed commission schedules. Alternatively, we derive a dynamic model based on statistical simulation (Monte Carlo) and using a real-life case study to illustrate the impacts of particular value drivers on commissioning costs. Our analysis shows that conventional and simulation-based budgeting generates inverse cost functions over time, and the difference becomes operationally tangible in the second and third year of the project, which is commensurate with the apparent timing of the bank’s business strategy revisions. To fulfill the goal of this paper, we demonstrate that statistical simulation is an expedient tool for managerial support and capital budgeting in cases where value drivers are impacted by non-linear dynamic processes.
SSRN
We respond to recent failed initiatives of the Czech banking market to develop business models for the sale of retail deposit products, based on third-party distribution channels. We argue that the issue is the application of inappropriate capital budgeting methods. While static cost-benefit analysis seems to be generally appropriate for conventional banking projects based on branching or internet, they provide grossly misleading estimates of commissioning expenses, which can lead to completely unrealistic project assessments and poorly designed commission schedules. Alternatively, we derive a dynamic model based on statistical simulation (Monte Carlo) and using a real-life case study to illustrate the impacts of particular value drivers on commissioning costs. Our analysis shows that conventional and simulation-based budgeting generates inverse cost functions over time, and the difference becomes operationally tangible in the second and third year of the project, which is commensurate with the apparent timing of the bank’s business strategy revisions. To fulfill the goal of this paper, we demonstrate that statistical simulation is an expedient tool for managerial support and capital budgeting in cases where value drivers are impacted by non-linear dynamic processes.
Demand for Information and Stock Returns: Evidence from EDGAR
SSRN
This paper studies the information acquisition process by investors using a novel dataset that tracks filing downloads on the SEC's EDGAR. Demand for 10-K filings predicts short-term positive return spread, and demand for 8-K filings predicts long-term negative return spread. The striking difference in the effects of 10-K and 8-K attention on stock prices can be contributed to the different viewing patterns. Demand for 10-K filings represents a general demand for assets, where 10-K visitors are typically infrequent visitors who never download any filings of the firm in past quarters. The effects are higher conditional on attention-grabbing stocks. 8-K visitors are typically frequent and local visitors with a potential information advantage. The demand for 8-K filings reduces information asymmetry of the firm, which decreases the cost of capital and explains the persistent underperformance of high 8-K attention stocks.
SSRN
This paper studies the information acquisition process by investors using a novel dataset that tracks filing downloads on the SEC's EDGAR. Demand for 10-K filings predicts short-term positive return spread, and demand for 8-K filings predicts long-term negative return spread. The striking difference in the effects of 10-K and 8-K attention on stock prices can be contributed to the different viewing patterns. Demand for 10-K filings represents a general demand for assets, where 10-K visitors are typically infrequent visitors who never download any filings of the firm in past quarters. The effects are higher conditional on attention-grabbing stocks. 8-K visitors are typically frequent and local visitors with a potential information advantage. The demand for 8-K filings reduces information asymmetry of the firm, which decreases the cost of capital and explains the persistent underperformance of high 8-K attention stocks.
Earnings management of state-owned enterprises as a target: Evidence from China
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We investigate earnings management of state-owned enterprises (SOEs) being a block trade target in China. Some block trades transfer control rights of SOEs to private parties (STP transactions) while others sell shares to another SOE (STS transactions). We find that SOEs manage earnings more upward in STP transactions than in STS transactions. Meanwhile, we find no evidence that SOEs charge higher prices when in STP than in STS. These results are consistent with the idea that target firms engage in earnings management especially when there is serious information asymmetry between bidders and targets.
SSRN
We investigate earnings management of state-owned enterprises (SOEs) being a block trade target in China. Some block trades transfer control rights of SOEs to private parties (STP transactions) while others sell shares to another SOE (STS transactions). We find that SOEs manage earnings more upward in STP transactions than in STS transactions. Meanwhile, we find no evidence that SOEs charge higher prices when in STP than in STS. These results are consistent with the idea that target firms engage in earnings management especially when there is serious information asymmetry between bidders and targets.
Full Payment Algorithm
SSRN
Clearing payments between firms are usually computed under the assumption that firms that cannot fully meet their obligations exhaust their cash resources to make partial payments. In practice, however, firms might wait and see whether they receive payments that would help them to meet their obligations in full before making any payments themselves, thereby avoiding partial payments. In this paper, we model this situation by introducing the Full Payment Algorithm (FPA). We fully characterize the steady state of the FPA, and we prove necessary and sufficient conditions under which it is equivalent to the widely used Eisenberg and Noe model.
SSRN
Clearing payments between firms are usually computed under the assumption that firms that cannot fully meet their obligations exhaust their cash resources to make partial payments. In practice, however, firms might wait and see whether they receive payments that would help them to meet their obligations in full before making any payments themselves, thereby avoiding partial payments. In this paper, we model this situation by introducing the Full Payment Algorithm (FPA). We fully characterize the steady state of the FPA, and we prove necessary and sufficient conditions under which it is equivalent to the widely used Eisenberg and Noe model.
Informed Trading of Options, Option Expiration Risk, and Stock Return Predictability
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The percentage difference between implied stock prices from options and actual stock prices, which we term the implied price difference (‘IPD’), predicts stock returns up to ten months into the future. IPD predicts stock returns even after including a number of other option-based variables, and among both the largest stocks as well as small cap stocks. Information about future stock returns comes from long-term, not short-term options. This suggests that informed investors who do not know when their longer-term information will be impounded in prices tend to trade long-term options to avoid expiration risk.
SSRN
The percentage difference between implied stock prices from options and actual stock prices, which we term the implied price difference (‘IPD’), predicts stock returns up to ten months into the future. IPD predicts stock returns even after including a number of other option-based variables, and among both the largest stocks as well as small cap stocks. Information about future stock returns comes from long-term, not short-term options. This suggests that informed investors who do not know when their longer-term information will be impounded in prices tend to trade long-term options to avoid expiration risk.
Pay What Your Dad Paid: Commitment and Price Rigidity in the Market for Life Insurance
SSRN
Life insurance premiums display signiï¬cant rigidity in the data, on average adjusting once every 3 years by more than 10%. This contrasts with the underlying marginal cost which exhibits considerable volatility due to the movements in interest and mortality rates. We build and calibrate a model where policyholders are held-up by long-term insurance contracts, resulting in a time inconsistency problem for the ï¬rms. The optimal contract takes the form of a simple cutoff rule: premiums are rigid for cost realizations smaller than the threshold, while adjustments must be large and are only possible when cost realizations exceed it.
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Life insurance premiums display signiï¬cant rigidity in the data, on average adjusting once every 3 years by more than 10%. This contrasts with the underlying marginal cost which exhibits considerable volatility due to the movements in interest and mortality rates. We build and calibrate a model where policyholders are held-up by long-term insurance contracts, resulting in a time inconsistency problem for the ï¬rms. The optimal contract takes the form of a simple cutoff rule: premiums are rigid for cost realizations smaller than the threshold, while adjustments must be large and are only possible when cost realizations exceed it.
Strategic Timing in Closed-End Fund Portfolio Holdings Disclosure
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Using a sample of equity closed-end funds, we document significant portfolio holdings disclosure valuation effects and strategic disclosure timing by portfolio managers. An event study analysis reveals statistically significant positive (negative) abnormal returns associated with early (late) disclosure. We find that the returns of a long-short arbitrage strategy portfolio become statistically significant exactly when the implementation of such a strategy is facilitated by the timely disclosure of portfolio holdings. Our findings support the argument that managers of funds trading at high discounts are more likely to disclose earlier in order to reduce discounts and protect themselves from activist investor attacks. This is despite the documented strong motives for late disclosure stemming from copycatting and front running threats shared with open-end fund managers.
SSRN
Using a sample of equity closed-end funds, we document significant portfolio holdings disclosure valuation effects and strategic disclosure timing by portfolio managers. An event study analysis reveals statistically significant positive (negative) abnormal returns associated with early (late) disclosure. We find that the returns of a long-short arbitrage strategy portfolio become statistically significant exactly when the implementation of such a strategy is facilitated by the timely disclosure of portfolio holdings. Our findings support the argument that managers of funds trading at high discounts are more likely to disclose earlier in order to reduce discounts and protect themselves from activist investor attacks. This is despite the documented strong motives for late disclosure stemming from copycatting and front running threats shared with open-end fund managers.
The Environment of the Masuria Lakeland and Biebrza National Park, North-Eastern Poland (Presentation Slides)
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This presentation discusses environmental and geographic features of the Masurian Lakeland and Biebrza National Park â€" wetland ecosystems of the North-Eastern Poland. Special focus of attention is uniqueness of the biodiversity if the area richness of species diversity rare types of species.
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This presentation discusses environmental and geographic features of the Masurian Lakeland and Biebrza National Park â€" wetland ecosystems of the North-Eastern Poland. Special focus of attention is uniqueness of the biodiversity if the area richness of species diversity rare types of species.
The Predictable Behavior of Security Returns: A Comparative Study Between US and China Markets
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Jegadeesh (1990) examines the serial correlation in monthly stock returns and tests its economic significance by designing three trading strategies. In this study, we follow his research design to compare the security return predictability between US market and China market. The findings suggest that the significant strong predictability Jegadeesh (1990) finds over the period from 1934 to 1987 in US market is much weaker during recent years from 2001 to 2015. Furthermore, the comparison shows that the security return predictability in China market is even stronger than that in US market in recent period.
SSRN
Jegadeesh (1990) examines the serial correlation in monthly stock returns and tests its economic significance by designing three trading strategies. In this study, we follow his research design to compare the security return predictability between US market and China market. The findings suggest that the significant strong predictability Jegadeesh (1990) finds over the period from 1934 to 1987 in US market is much weaker during recent years from 2001 to 2015. Furthermore, the comparison shows that the security return predictability in China market is even stronger than that in US market in recent period.
