Research articles for the 2020-01-15
A Higher-Order Correct Fast Moving-Average Bootstrap for Dependent Data
arXiv
arXiv
We develop and implement a novel fast bootstrap for dependent data. Our scheme is based on the i.i.d. resampling of the smoothed moment indicators. We characterize the class of parametric and semi-parametric estimation problems for which the method is valid. We show the asymptotic refinements of the proposed procedure, proving that it is higher-order correct under mild assumptions on the time series, the estimating functions, and the smoothing kernel. We illustrate the applicability and the advantages of our procedure for Generalized Empirical Likelihood estimation. As a by-product, our fast bootstrap provides higher-order correct asymptotic confidence distributions. Monte Carlo simulations on an autoregressive conditional duration model provide numerical evidence that the novel bootstrap yields higher-order accurate confidence intervals. A real-data application on dynamics of trading volume of stocks illustrates the advantage of our method over the routinely-applied first-order asymptotic theory, when the underlying distribution of the test statistic is skewed or fat-tailed.
A Signaling Theory of Lockups in Mergers
SSRN
Empirical evidence shows that termination fees (“lockupsâ€) in merger agreements of public companies discourage competition for the target company but do not necessarily harm target shareholders. This Article presents a signaling theory consistent with this evidence and considers the theory’s normative implications. The chief argument is that the presence of a lockup in an agreement signals the acquirer’s high valuation of the target, and this discourages other potential acquirers from competing. By increasing the deal price in exchange for the inclusion of a lockup in the agreement and thereby restricting competition, a target company and a high-valuing acquirer are able to divide between them the surplus that results from avoiding the transaction costs of a bidding contest. Building on that analysis, this Article shows that although lockups increase target shareholder wealth, they may nevertheless be socially undesirable.
SSRN
Empirical evidence shows that termination fees (“lockupsâ€) in merger agreements of public companies discourage competition for the target company but do not necessarily harm target shareholders. This Article presents a signaling theory consistent with this evidence and considers the theory’s normative implications. The chief argument is that the presence of a lockup in an agreement signals the acquirer’s high valuation of the target, and this discourages other potential acquirers from competing. By increasing the deal price in exchange for the inclusion of a lockup in the agreement and thereby restricting competition, a target company and a high-valuing acquirer are able to divide between them the surplus that results from avoiding the transaction costs of a bidding contest. Building on that analysis, this Article shows that although lockups increase target shareholder wealth, they may nevertheless be socially undesirable.
A Volatile Mind: Trader's Perceptions and Foreign Exchange Market Volatility
SSRN
Do we make markets volatile? This paper argues that traders’ ‘biases’, stemming from heuristics, impacts strongly forex market heterogeneity. To understand better market participants’ behavior in response to news, we use a simulated trading game experiment together with a survey covering forex traders from the Indian subcontinent. The simulated game experiment addresses the major survey approach lacuna, because we can observe ‘what participants do’ rather than rely what ‘participants say’. Principal component analysis of survey responses shows participants react most to Central Bank News. Simulated game experiment data shows participants are influenced by ‘Recurrence Bias’ and ‘Volatility Perception Bias’. Categorical Probit model analysis suggests market participant biases’ have a statistically significant impact on market heterogeneity, with ‘Bias’ increasing the chance of spread being in the highest bucket by 17.87%. Moreover, trading is strongly individualistic, which influences the market volatility.
SSRN
Do we make markets volatile? This paper argues that traders’ ‘biases’, stemming from heuristics, impacts strongly forex market heterogeneity. To understand better market participants’ behavior in response to news, we use a simulated trading game experiment together with a survey covering forex traders from the Indian subcontinent. The simulated game experiment addresses the major survey approach lacuna, because we can observe ‘what participants do’ rather than rely what ‘participants say’. Principal component analysis of survey responses shows participants react most to Central Bank News. Simulated game experiment data shows participants are influenced by ‘Recurrence Bias’ and ‘Volatility Perception Bias’. Categorical Probit model analysis suggests market participant biases’ have a statistically significant impact on market heterogeneity, with ‘Bias’ increasing the chance of spread being in the highest bucket by 17.87%. Moreover, trading is strongly individualistic, which influences the market volatility.
Bank Complexity, Governance, and Risk
SSRN
While complexity in bank holding companies (BHCs) raises the costs of bank resolution when organizations fail, the contributions of complexity to the broader risk profiles of BHCs are less well understood. Complexity can engender explicit tradeoffs between the agency problems that increase risk and the diversification, liquidity management and synergy improvements that reduce risk. Outcomes of these tradeoffs may be dependent on bank governance. Using measures of organizational, business, and geographic complexity, we test these conjectures using data on large US BHCs for the period between 1996 and 2018. Organizational complexity and geographic scope tend to provide diversification gains and reduce idiosyncratic and liquidity risks while also increasing BHC systematic and systemic risks. We also find that regulatory tightenings focused on organizational complexity significantly reduced this complexity, with BHC liquidity risk also increasing and systemic risk decreasing. Bank governance in some cases significantly affected the buildup of BHC complexity, but did not moderate the effects of complexity on risk.
SSRN
While complexity in bank holding companies (BHCs) raises the costs of bank resolution when organizations fail, the contributions of complexity to the broader risk profiles of BHCs are less well understood. Complexity can engender explicit tradeoffs between the agency problems that increase risk and the diversification, liquidity management and synergy improvements that reduce risk. Outcomes of these tradeoffs may be dependent on bank governance. Using measures of organizational, business, and geographic complexity, we test these conjectures using data on large US BHCs for the period between 1996 and 2018. Organizational complexity and geographic scope tend to provide diversification gains and reduce idiosyncratic and liquidity risks while also increasing BHC systematic and systemic risks. We also find that regulatory tightenings focused on organizational complexity significantly reduced this complexity, with BHC liquidity risk also increasing and systemic risk decreasing. Bank governance in some cases significantly affected the buildup of BHC complexity, but did not moderate the effects of complexity on risk.
CDS Central Counterparty Clearing Liquidation: Road to Recovery or Invitation to Predation?
SSRN
Recent regulation, mandating the clearing of credit default swaps (CDS) by a Central Clearing Counterparties (CCP), has rendered it's possible failure a serious threat to global nancial stability. This work investigates the potential failure of a CCP initiated by the default of a large dealer bank and the unwinding of its positions. The theoretical model examines variation margin exchange between dealer banks and the price impact of liquidation and predatory selling. It provides a measure of covariance between assets in banks' portfolios; price impact affects assets to varying degrees, based on their relative distance to defaulted assets. Key results show that liquidation lowers CCP profits, and how predation decreases the profits of all members, pushing banks to default. Furthermore, a hybrid CCP (vs. current) structure provides a natural disciplinary mechanism for predation. Also, it is more incentive compatible for the CCP, in expectation of a large loss. A multi-period, dynamic simulation, calibrated to OTC market data, provides parameter sensitivities concerning the magnitude of CCP and predatory bank gains/losses, specifically, the minimisation of those losses with a hybrid fund structure. Furthermore, regulatory implications concerning the timing of liquidity injection for a Lender of Last Resort (LoL) are determined for various liquidity scenarios; stable and decreasing market liquidity, as well as, a liquidity dry-up at the bottom of a financial crisis.
SSRN
Recent regulation, mandating the clearing of credit default swaps (CDS) by a Central Clearing Counterparties (CCP), has rendered it's possible failure a serious threat to global nancial stability. This work investigates the potential failure of a CCP initiated by the default of a large dealer bank and the unwinding of its positions. The theoretical model examines variation margin exchange between dealer banks and the price impact of liquidation and predatory selling. It provides a measure of covariance between assets in banks' portfolios; price impact affects assets to varying degrees, based on their relative distance to defaulted assets. Key results show that liquidation lowers CCP profits, and how predation decreases the profits of all members, pushing banks to default. Furthermore, a hybrid CCP (vs. current) structure provides a natural disciplinary mechanism for predation. Also, it is more incentive compatible for the CCP, in expectation of a large loss. A multi-period, dynamic simulation, calibrated to OTC market data, provides parameter sensitivities concerning the magnitude of CCP and predatory bank gains/losses, specifically, the minimisation of those losses with a hybrid fund structure. Furthermore, regulatory implications concerning the timing of liquidity injection for a Lender of Last Resort (LoL) are determined for various liquidity scenarios; stable and decreasing market liquidity, as well as, a liquidity dry-up at the bottom of a financial crisis.
Codependence (Presentation Slides)
SSRN
Two random variables are codependent when knowing the value of one helps us determine the value of the other. This should not me confounded with the notion of causality.Correlation is perhaps the best known measure of codependence in econometric studies. Despite its popularity among economists, correlation has many known limitations in the contexts of financial studies.In this seminar we will explore more modern measures of codependence, based on information theory, which overcome some of the limitations of correlations.
SSRN
Two random variables are codependent when knowing the value of one helps us determine the value of the other. This should not me confounded with the notion of causality.Correlation is perhaps the best known measure of codependence in econometric studies. Despite its popularity among economists, correlation has many known limitations in the contexts of financial studies.In this seminar we will explore more modern measures of codependence, based on information theory, which overcome some of the limitations of correlations.
Democratization, Inequality, and Risk Premia
SSRN
This paper examines the effect of democratizations on asset returns. Using a panel data set covering 57 countries over 200 years, I show that during periods of democratization, the equity premium and corporate credit spreads are significantly elevated, despite little to no effect on aggregate consumption and dividends. Further, I use a quasi-natural experiment coming from a shift in Catholic church attitudes toward democracy and show that this change was associated with a large increase in average excess returns for majority Catholic and autocratic countries. Finally, I show that these results can be rationalized through a standard political economy model in which the wealthiest segments of society are negatively impacted by the consolidation of democracy. These results are key to understanding how political institutions and the distribution of wealth and political power influence asset returns.
SSRN
This paper examines the effect of democratizations on asset returns. Using a panel data set covering 57 countries over 200 years, I show that during periods of democratization, the equity premium and corporate credit spreads are significantly elevated, despite little to no effect on aggregate consumption and dividends. Further, I use a quasi-natural experiment coming from a shift in Catholic church attitudes toward democracy and show that this change was associated with a large increase in average excess returns for majority Catholic and autocratic countries. Finally, I show that these results can be rationalized through a standard political economy model in which the wealthiest segments of society are negatively impacted by the consolidation of democracy. These results are key to understanding how political institutions and the distribution of wealth and political power influence asset returns.
Did the Recognition of Operating Leases Cause a Decline in Equity Valuations?
SSRN
We examine whether investors react to a significant change in financial statements absent a significant change in underlying economics. Beginning in 2019, ASC 842 requires the recognition of operating leases, which were previously only disclosed in the footnotes. This plausibly exogenous change in accounting standard has no effect on firms’ economics but results in firms with significant operating leases recognizing a considerable increase in debt. We find that firms with significant operating leases, on average, earn negative returns around the first recognition of their operating leases. For example, firms above the 99th, 95th, and 90th percentiles of operating lease intensity experience abnormal returns of -10.5%, -4.7%, and -3.3%, respectively during the two weeks around their first quarter 2019 earnings announcements. Our results suggest that the higher information processing costs inherent in disclosed versus recognized information can lead to mispricing, even in the case of a common and well-known accounting distortion.
SSRN
We examine whether investors react to a significant change in financial statements absent a significant change in underlying economics. Beginning in 2019, ASC 842 requires the recognition of operating leases, which were previously only disclosed in the footnotes. This plausibly exogenous change in accounting standard has no effect on firms’ economics but results in firms with significant operating leases recognizing a considerable increase in debt. We find that firms with significant operating leases, on average, earn negative returns around the first recognition of their operating leases. For example, firms above the 99th, 95th, and 90th percentiles of operating lease intensity experience abnormal returns of -10.5%, -4.7%, and -3.3%, respectively during the two weeks around their first quarter 2019 earnings announcements. Our results suggest that the higher information processing costs inherent in disclosed versus recognized information can lead to mispricing, even in the case of a common and well-known accounting distortion.
Diverse Non-Fundamental Information and Trading Complementarities
SSRN
We explore the interaction between two groups of sophisticated traders that possess different information about the noise incorporated in the market price within a rational expectations framework à la Grossman-Stiglitz. We find that trading against noise constitutes a complementary action. If one group trades stronger against their signal about noise, the uncertainty the other group is confronted with decreases. This makes them trade more aggressively against their respective signal about noise, too. Moreover, we show that trading against noise increases the price informativeness and the welfare of the sophisticated traders as well as of the noise traders. Lastly, we extend the basic model by endogenizing the information acquisition process.
SSRN
We explore the interaction between two groups of sophisticated traders that possess different information about the noise incorporated in the market price within a rational expectations framework à la Grossman-Stiglitz. We find that trading against noise constitutes a complementary action. If one group trades stronger against their signal about noise, the uncertainty the other group is confronted with decreases. This makes them trade more aggressively against their respective signal about noise, too. Moreover, we show that trading against noise increases the price informativeness and the welfare of the sophisticated traders as well as of the noise traders. Lastly, we extend the basic model by endogenizing the information acquisition process.
Does Performance-Sensitive Debt Mitigate Debt Overhang?
SSRN
We model the expansion decision of a levered firm. Straight debt distorts both timing and scaling: the firm invests less and later than its all-equity financed counterpart. The inclusion of performance sensitivity in the debt contract mitigates such distortions. Moreover, performance sensitivity is consistent with firm value maximization within a standard trade-off theory of capital structure. As a result, our model rationalizes the widespread use of performance sensitive debt (PSD), especially amongst fast growth firms.
SSRN
We model the expansion decision of a levered firm. Straight debt distorts both timing and scaling: the firm invests less and later than its all-equity financed counterpart. The inclusion of performance sensitivity in the debt contract mitigates such distortions. Moreover, performance sensitivity is consistent with firm value maximization within a standard trade-off theory of capital structure. As a result, our model rationalizes the widespread use of performance sensitive debt (PSD), especially amongst fast growth firms.
Does the Quantile Regression Forest Learn More Information on Chinese Systemic Risk?
SSRN
This article applies the quantile regression forest (QRF), which is an improved method for predicting future macroeconomic shocks. We summarize 31 different indexes of Chinese systemic risk and construct predictors using principal component analysis to predict Chinese macroeconomic downside risk. The two forecasting methods, the multiple quantile regression forest (MQRF) and the principal component quantile regression forest (PCQRF), both outperform the quantile regression (QR), the multiple quantile regression (MQR) and the principal component quantile regression (PCQR). Furthermore, we find that with increased systemic risk indexes, more information about the left tail of macroeconomic shocks could be identified by the QRF.
SSRN
This article applies the quantile regression forest (QRF), which is an improved method for predicting future macroeconomic shocks. We summarize 31 different indexes of Chinese systemic risk and construct predictors using principal component analysis to predict Chinese macroeconomic downside risk. The two forecasting methods, the multiple quantile regression forest (MQRF) and the principal component quantile regression forest (PCQRF), both outperform the quantile regression (QR), the multiple quantile regression (MQR) and the principal component quantile regression (PCQR). Furthermore, we find that with increased systemic risk indexes, more information about the left tail of macroeconomic shocks could be identified by the QRF.
Executive Pay for Luck: New Evidence Over the Last 20 Years
SSRN
Pay for non-performance is among the most prominent arguments of executive rent extraction, especially Bertrand and Mullainathan’s (2001) pay for luck. We revisit their finding over the last two decades, 1997 through 2016. Pay for luck presents in the first decade but declines in the second decade. This decrease is robust to different measures of luck, various industry subsamples, and the financial crisis of 2008-9. The structural break in pay for luck associates with transparency-based regulations, such as option expensing and new performance pay disclosures. These regimes plausibly enhance shareholder monitoring, which pushes compensation committees to decrease pay for luck.
SSRN
Pay for non-performance is among the most prominent arguments of executive rent extraction, especially Bertrand and Mullainathan’s (2001) pay for luck. We revisit their finding over the last two decades, 1997 through 2016. Pay for luck presents in the first decade but declines in the second decade. This decrease is robust to different measures of luck, various industry subsamples, and the financial crisis of 2008-9. The structural break in pay for luck associates with transparency-based regulations, such as option expensing and new performance pay disclosures. These regimes plausibly enhance shareholder monitoring, which pushes compensation committees to decrease pay for luck.
Financial Market Implications of Trade War
SSRN
The trade war between the United States and China has a significant impact on high-yield spreads, long-term interest rates, and stock prices. However, the 10-year-minus-2-year Treasury yield spread, whose inversion generated significant media chatter about a looming recession, does not seem to be influenced by news about the trade war. These results are consistent with the relatively modest macroeconomic impact of the trade war predicted by previous studies and suggest that the financial-market impact is primarily driven by changes in risk premia.
SSRN
The trade war between the United States and China has a significant impact on high-yield spreads, long-term interest rates, and stock prices. However, the 10-year-minus-2-year Treasury yield spread, whose inversion generated significant media chatter about a looming recession, does not seem to be influenced by news about the trade war. These results are consistent with the relatively modest macroeconomic impact of the trade war predicted by previous studies and suggest that the financial-market impact is primarily driven by changes in risk premia.
Forecasting Value at Risk and Expected Shortfall with Mixed Data Sampling
SSRN
I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence in short-horizon returns to directly forecast the tail dynamics at the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially at multi-day forecast horizons. My analysis advocates models featuring asymmetric conditional quantile and the use of Asymmetric Laplace density to jointly estimate VaR and ES.
SSRN
I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence in short-horizon returns to directly forecast the tail dynamics at the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially at multi-day forecast horizons. My analysis advocates models featuring asymmetric conditional quantile and the use of Asymmetric Laplace density to jointly estimate VaR and ES.
How Do Machine Learning and Non-Traditional Data Affect Credit Scoring? New Evidence from a Chinese Fintech Firm
SSRN
This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the performance of different models to predict losses and defaults both in normal times and when the economy is subject to a shock. In particular, we analyse the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. We find that the model based on machine learning and non-traditional data is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in a period of stress. Finally, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning and big data tends to decline for borrowers with a longer credit history.
SSRN
This paper compares the predictive power of credit scoring models based on machine learning techniques with that of traditional loss and default models. Using proprietary transaction-level data from a leading fintech company in China for the period between May and September 2017, we test the performance of different models to predict losses and defaults both in normal times and when the economy is subject to a shock. In particular, we analyse the case of an (exogenous) change in regulation policy on shadow banking in China that caused lending to decline and credit conditions to deteriorate. We find that the model based on machine learning and non-traditional data is better able to predict losses and defaults than traditional models in the presence of a negative shock to the aggregate credit supply. One possible reason for this is that machine learning can better mine the non-linear relationship between variables in a period of stress. Finally, the comparative advantage of the model that uses the fintech credit scoring technique based on machine learning and big data tends to decline for borrowers with a longer credit history.
How social interactions matter when distance dies?
arXiv
arXiv
We consider an economic geography model with two inter-regional proximity structures, one due to trade linkages and the other due to social interactions. We investigate how the network structure of social interactions, or the social proximity structure, affects the timing of endogenous agglomeration and the spatial distribution of workers across regions. Endogenous agglomeration emerges when inter-regional trade and/or social interactions incur high transportation costs, and the uniform dispersion occurs when these costs become negligibly small (i.e., when distance dies). In many-region geography, the network structure of social proximity emerges as the determinant of the geographical distribution of workers when trade becomes freer. If social proximity is governed by geographical distance (as in ground transportation), a mono-centric concentration emerges. If geographically distant pairs of regions are ``socially close'' (due to, e.g., passenger transportation modes with strong distance economy such as regional airlines), then geographically multi-centric spatial distribution can be sustainable.
In Search of Liquidity Risk in Bank Stock Returns
SSRN
We document that higher measures of liquidity risk on banks balance sheets are associated with lower expected stock returns. We first calculate a measure of liquidity risk, referred to as the liquidity gap (LG), which reflects how much of a bank's volatile liabilities are covered by its stock of liquid assets. We show that the standard factor models (even when augmented with bond risk, market liquidity, and financial-size factors) do not fully explain the cross section of bank stock returns sorted according to this measure. A portfolio that is long in low liquidity risk banks and short in high liquidity risk banks delivers a statistically significant alpha of 6 percent annually. This effect is not driven by bank characteristics such as size, profitability, or risk measures related to leverage or asset quality, but appears to be partly due to the degree of complexity of banking organizations and potential valuation errors pre-crisis.
SSRN
We document that higher measures of liquidity risk on banks balance sheets are associated with lower expected stock returns. We first calculate a measure of liquidity risk, referred to as the liquidity gap (LG), which reflects how much of a bank's volatile liabilities are covered by its stock of liquid assets. We show that the standard factor models (even when augmented with bond risk, market liquidity, and financial-size factors) do not fully explain the cross section of bank stock returns sorted according to this measure. A portfolio that is long in low liquidity risk banks and short in high liquidity risk banks delivers a statistically significant alpha of 6 percent annually. This effect is not driven by bank characteristics such as size, profitability, or risk measures related to leverage or asset quality, but appears to be partly due to the degree of complexity of banking organizations and potential valuation errors pre-crisis.
Institutional Characteristics, Investment Sensitivity to Cash Flow and Tobin’s q: Evidence From the Mena Region
SSRN
We examine the sensitivity of corporate investment to stock-market valuations (measured by Tobin’s q) and internal funds (measured by cash flow) in a setting that captures the unique country institutional characteristics of the Middle East and North Africa (MENA) region. We report a higher sensitivity of investments to cash flow than Tobin’s q. However, both sensitivities are unaffected by the country institutional characteristics. By examining the sensitivity of investments to cash flow and Tobin’s q before and after the 2008 global financial crisis, we document that the investment-cash flow relation has weakened over time, while the investment-Tobin’s q relation has significantly strengthened. Finally, after dividing our country sample into resource-rich and resource-poor countries, the importance of cash flow over Tobin’s q in the determination of corporate investment levels is asserted and the role of financial markets is found to be restricted to resource-rich countries only.
SSRN
We examine the sensitivity of corporate investment to stock-market valuations (measured by Tobin’s q) and internal funds (measured by cash flow) in a setting that captures the unique country institutional characteristics of the Middle East and North Africa (MENA) region. We report a higher sensitivity of investments to cash flow than Tobin’s q. However, both sensitivities are unaffected by the country institutional characteristics. By examining the sensitivity of investments to cash flow and Tobin’s q before and after the 2008 global financial crisis, we document that the investment-cash flow relation has weakened over time, while the investment-Tobin’s q relation has significantly strengthened. Finally, after dividing our country sample into resource-rich and resource-poor countries, the importance of cash flow over Tobin’s q in the determination of corporate investment levels is asserted and the role of financial markets is found to be restricted to resource-rich countries only.
Liquidity and Corporate Governance
SSRN
This paper discusses the relationship between stock market liquidity and corporate governance. Both concepts are widely investigated from different angles in the literature. It is generally agreed that they are related so that better corporate governance implies higher liquidity for shares of listed companies. However, the importance of good corporate governance for the market liquidity of the share will differ depending on the characteristics of the firm’s business. Good corporate governance will be particularly important in reducing agency problems in firms subject to a high degree of uncertainty. Proper corporate governance, in other words, matters most in cases where external assessment of the firm’s business prospects is difficult, while it is less important for value creation in firms where the business is easier to understand.
SSRN
This paper discusses the relationship between stock market liquidity and corporate governance. Both concepts are widely investigated from different angles in the literature. It is generally agreed that they are related so that better corporate governance implies higher liquidity for shares of listed companies. However, the importance of good corporate governance for the market liquidity of the share will differ depending on the characteristics of the firm’s business. Good corporate governance will be particularly important in reducing agency problems in firms subject to a high degree of uncertainty. Proper corporate governance, in other words, matters most in cases where external assessment of the firm’s business prospects is difficult, while it is less important for value creation in firms where the business is easier to understand.
Machine learning with kernels for portfolio valuation and risk management
arXiv
arXiv
We introduce a computational framework for dynamic portfolio valuation and risk management building on machine learning with kernels. We learn the replicating martingale of a portfolio from a finite sample of its terminal cumulative cash flow. The learned replicating martingale is given in closed form thanks to a suitable choice of the kernel. We develop an asymptotic theory and prove convergence and a central limit theorem. We also derive finite sample error bounds and concentration inequalities. Numerical examples show good results for a relatively small training sample size.
Meeting the Liquidity Challenge in Resolution: the US Approach (Presentation Slides)
SSRN
This presentation addresses the liquidity problem a failing bank faces and how resolution procedures can contribute to the mitigate this problem and the risk of contagion. The Orderly Liquidation Procedures in Dodd-Frank are discussed.
SSRN
This presentation addresses the liquidity problem a failing bank faces and how resolution procedures can contribute to the mitigate this problem and the risk of contagion. The Orderly Liquidation Procedures in Dodd-Frank are discussed.
On the Extraction of Cyber Risks using Structured Products
SSRN
The aim of this paper is to develop an approach to extract information about cyber risks from structured financial products. We consider decision makers that are interested in extracting information about the uncertainty of Cyber risks. The value of information can be evaluated using recently developed entropy approaches in Finance. The underlying idea is that what we call Arrow-Debreu Cyber Risk state prices can be extracted provided the right structured products be “createdâ€. It is shown that different market based approaches can be used to get a better idea of the shape of the loss distribution facing firms. This information is potentially of interest to evaluate the risk premiums of insurance products. Comparisons between extracted market expectations can also be informative for risk evaluation, notably the distribution of unexpected losses and the eventual shortfall calculations. Finally, recent information-theoretic approaches enable us to make the link between pricing and the value of information to investors.
SSRN
The aim of this paper is to develop an approach to extract information about cyber risks from structured financial products. We consider decision makers that are interested in extracting information about the uncertainty of Cyber risks. The value of information can be evaluated using recently developed entropy approaches in Finance. The underlying idea is that what we call Arrow-Debreu Cyber Risk state prices can be extracted provided the right structured products be “createdâ€. It is shown that different market based approaches can be used to get a better idea of the shape of the loss distribution facing firms. This information is potentially of interest to evaluate the risk premiums of insurance products. Comparisons between extracted market expectations can also be informative for risk evaluation, notably the distribution of unexpected losses and the eventual shortfall calculations. Finally, recent information-theoretic approaches enable us to make the link between pricing and the value of information to investors.
Opacity: Insurance and Fragility
SSRN
What are the effects of banks holding opaque, complex assets? Should regulators require bank assets to be more transparent? I study these questions in a model of financial intermediation where opacity determines how long the realized value of an asset remains unknown. By allowing a bank to sell assets before the realization is known, opacity provides insurance to the bank's depositors. However, higher opacity also increases depositors' incentives to join a bank run. In choosing the level of opacity, therefore, a bank faces a trade-off between providing insurance and increasing fragility. If depositors can accurately observe the level of opacity, banks will choose the socially efficient level. If depositors are unable to observe this choice, however, banks will have an incentive to become overly opaque and regulation to limit opacity can improve welfare.
SSRN
What are the effects of banks holding opaque, complex assets? Should regulators require bank assets to be more transparent? I study these questions in a model of financial intermediation where opacity determines how long the realized value of an asset remains unknown. By allowing a bank to sell assets before the realization is known, opacity provides insurance to the bank's depositors. However, higher opacity also increases depositors' incentives to join a bank run. In choosing the level of opacity, therefore, a bank faces a trade-off between providing insurance and increasing fragility. If depositors can accurately observe the level of opacity, banks will choose the socially efficient level. If depositors are unable to observe this choice, however, banks will have an incentive to become overly opaque and regulation to limit opacity can improve welfare.
Options Trading Activities and Corporate Cash Holdings
SSRN
This paper examines the effects of options trading activities on corporate liquidity management. Based on a sample of 45,045 U.S. non-financial firms from 1996 to 2016, we document a positive relationship between equity options trading intensity and corporate cash holdings. We address endogeneity concerns by using the instrumental variable approach, along with the CBOE's Penny Pilot Program as an exogenous shock. At the extensive margin, we find option listing to be associated with higher cash holdings, thus corroborating a causality interpretation of our baseline results. Studying the heterogeneous effects, we find the positive impact of options trading on cash reserves to be driven by firms where financial distress risk is high and debt-financed investments are constrained by liquidity issues. Moreover, options trading is positively associated with the cost of debt and marginal value of cash. Overall, these results suggest a precautionary saving motive due to active options markets that provide risk-shifting incentives to firms at the expense of outside creditors.
SSRN
This paper examines the effects of options trading activities on corporate liquidity management. Based on a sample of 45,045 U.S. non-financial firms from 1996 to 2016, we document a positive relationship between equity options trading intensity and corporate cash holdings. We address endogeneity concerns by using the instrumental variable approach, along with the CBOE's Penny Pilot Program as an exogenous shock. At the extensive margin, we find option listing to be associated with higher cash holdings, thus corroborating a causality interpretation of our baseline results. Studying the heterogeneous effects, we find the positive impact of options trading on cash reserves to be driven by firms where financial distress risk is high and debt-financed investments are constrained by liquidity issues. Moreover, options trading is positively associated with the cost of debt and marginal value of cash. Overall, these results suggest a precautionary saving motive due to active options markets that provide risk-shifting incentives to firms at the expense of outside creditors.
Path-dependent volatility models
arXiv
arXiv
We provide a thorough analysis of the path-dependent volatility model introduced by Guyon, proving existence and uniqueness of a strong solution, characterising its behaviour at boundary points, and deriving large deviations estimates. We further develop a numerical algorithm in order to jointly calibrate SP500 and VIX market data.
Political Influence and Corporate Governance: Evidence from Party-Building Reform in China
SSRN
We focus on the recent Dangjian (“party-buildingâ€) reform, a major measure taken by the Chinese Communist Party (CCP) to strengthen its leadership position in Chinese state-owned enterprises (SOEs). We hypothesize that, given the unique governance and ownership structure of Chinese firms, there is a trade-off between the political costs and benefits of the mitigated agency problems. We report negative investor reactions to privately-owned enterprises (POEs) after the Dangjian reform announcements, consistent with the hypothesis that strengthening party control over business is harmful to business efficacy and firm value. We also find evidence that the increased risks of political influence due to the reform undermine the value of SOEs that are considered more independent of political power (i.e., those under corporate pyramids or cross-listed on a foreign market). In addition, the market reacted negatively when firms incorporated the provision to adopt the party’s cadre management principle, which allows the CCP to intervene in firm management.
SSRN
We focus on the recent Dangjian (“party-buildingâ€) reform, a major measure taken by the Chinese Communist Party (CCP) to strengthen its leadership position in Chinese state-owned enterprises (SOEs). We hypothesize that, given the unique governance and ownership structure of Chinese firms, there is a trade-off between the political costs and benefits of the mitigated agency problems. We report negative investor reactions to privately-owned enterprises (POEs) after the Dangjian reform announcements, consistent with the hypothesis that strengthening party control over business is harmful to business efficacy and firm value. We also find evidence that the increased risks of political influence due to the reform undermine the value of SOEs that are considered more independent of political power (i.e., those under corporate pyramids or cross-listed on a foreign market). In addition, the market reacted negatively when firms incorporated the provision to adopt the party’s cadre management principle, which allows the CCP to intervene in firm management.
Priming and Stock Preferences: Evidence From IPO Lotteries
SSRN
Existing studies in social psychology have found that priming has pervasive effects, mostly in laboratory settings and over short periods of time. This study investigates the priming effect in the real financial world and over longer periods of time. We hypothesize that successful lottery-like experiences raise investors’ subsequent demand for other lottery-like stocks by increasing the accessibility of tail events. By exploiting the randomized distribution of IPO shares in China as a natural experiment, we find that, compared with matched control investors, the investors who were allocated IPO shares (lottery winners) substantially shift their non-IPO portfolios toward lottery-like stocks over the three months subsequent to the distribution. This effect is more pronounced for investors winning IPO lotteries with lower winning rates or larger issue-price discounts. Moreover, lottery winners experience a decrease in their overall portfolio return by more than 1% within the three months subsequent to the distribution relative to matched control investors, which is largely in proportion to the increases in their subsequent demand for lottery-like stocks. Our findings are not explained by the house money effect or the wealth effect. Overall, our study suggests that lottery-like cues play a critical role in shaping investors’ gambling preferences in stock markets, providing field-based evidence for the long-term priming effect.
SSRN
Existing studies in social psychology have found that priming has pervasive effects, mostly in laboratory settings and over short periods of time. This study investigates the priming effect in the real financial world and over longer periods of time. We hypothesize that successful lottery-like experiences raise investors’ subsequent demand for other lottery-like stocks by increasing the accessibility of tail events. By exploiting the randomized distribution of IPO shares in China as a natural experiment, we find that, compared with matched control investors, the investors who were allocated IPO shares (lottery winners) substantially shift their non-IPO portfolios toward lottery-like stocks over the three months subsequent to the distribution. This effect is more pronounced for investors winning IPO lotteries with lower winning rates or larger issue-price discounts. Moreover, lottery winners experience a decrease in their overall portfolio return by more than 1% within the three months subsequent to the distribution relative to matched control investors, which is largely in proportion to the increases in their subsequent demand for lottery-like stocks. Our findings are not explained by the house money effect or the wealth effect. Overall, our study suggests that lottery-like cues play a critical role in shaping investors’ gambling preferences in stock markets, providing field-based evidence for the long-term priming effect.
Protecting Investors From Themselves: Evidence From a Regulatory Intervention
SSRN
Retail investors in securities suffer from biases and consequent investment under-performance. A plausible approach to improving this is to restrict the least skilful investors. I investigate an intervention which includes a mandatory assessment of investment knowledge and experience. I study the empirical relationship between investors’ actual investment portfolio outcomes, and their assessment results. Those assessed as “competent†made fewer mistakes, as benchmarked by a range of normative models. I show that the assessment is able to weakly screen out unskilled investors. However, the intervention’s high misclassification rate, under an analysis favorable to the scheme, highlights the challenges of this approach.
SSRN
Retail investors in securities suffer from biases and consequent investment under-performance. A plausible approach to improving this is to restrict the least skilful investors. I investigate an intervention which includes a mandatory assessment of investment knowledge and experience. I study the empirical relationship between investors’ actual investment portfolio outcomes, and their assessment results. Those assessed as “competent†made fewer mistakes, as benchmarked by a range of normative models. I show that the assessment is able to weakly screen out unskilled investors. However, the intervention’s high misclassification rate, under an analysis favorable to the scheme, highlights the challenges of this approach.
Quantifying Risks to Sovereign Market Access: Methods and Challenges
SSRN
In this paper we use data from the euro area to study episodes when sovereigns lose market access. We construct a detailed dataset with potential indicators of market access tensions, and evaluate their ability to forecast episodes when market access is lost, using various econometric approaches. We find that factors associated with high market access tensions are not limited to financial markets, but also encompass developments in global demand, macroeconomic conditions and the fiscal stance. Using the top-performing indicators, we construct a number of market tension indices and use them as single predictors of market access tensions. While such indices are helpful in capturing worsening conditions, they do not yield satisfactory out-of-sample results. On the other hand, using the same top- performing indicators in various multivariate models generates good forecasts of upcoming difficulties in accessing sovereign bond markets. Our results thus point to a trade-off between communicability and accuracy that policymakers face in the search for tools to evaluate risks to market access.
SSRN
In this paper we use data from the euro area to study episodes when sovereigns lose market access. We construct a detailed dataset with potential indicators of market access tensions, and evaluate their ability to forecast episodes when market access is lost, using various econometric approaches. We find that factors associated with high market access tensions are not limited to financial markets, but also encompass developments in global demand, macroeconomic conditions and the fiscal stance. Using the top-performing indicators, we construct a number of market tension indices and use them as single predictors of market access tensions. While such indices are helpful in capturing worsening conditions, they do not yield satisfactory out-of-sample results. On the other hand, using the same top- performing indicators in various multivariate models generates good forecasts of upcoming difficulties in accessing sovereign bond markets. Our results thus point to a trade-off between communicability and accuracy that policymakers face in the search for tools to evaluate risks to market access.
Rational Kernel on Pricing Models of Inflation Derivatives
arXiv
arXiv
The aim of this thesis is to analyze and renovate few main-stream models on inflation derivatives. In the first chapter of the thesis, concepts of financial instruments and fundamental terms are introduced, such as coupon bond, inflation-indexed bond, swap.
In the second chapter of the thesis, classic models along the history of developing quantified interest rate models are introduced and analyzed. Moreover, the classification of interest rate models is introduced to help audiences understand the intrinsic ideology behind each type of models.
In the third chapter of the thesis, the related mathematical knowledge is introduced. This part has the contribution on understanding the terms and relation among terms in each model introduced previously.
In the fourth part of the thesis, the renovation of HJM frame work is introduced and analysis has been initiated.
Reforming SOEs in Asia: Lessons from Competition Law and Policy in India
SSRN
India is one of the most significant countries of Asia, particularly in terms of its population and growing economy and markets. India has rapidly moved from a ‘command and control’ economy to free-market principles, and in this regard, one of the major reforms revamped the competition law. The new competition law introduced the principle of ‘competitive neutrality’ by bringing ‘state-owned enterprises’ (SOEs) under the purview of competition law regulation by virtue of defining ‘enterprise’ to include government departments engaged in economic activity. The Competition Commission of India (CCI) has penalized big SOEs like Coal India for violation of the Competition Act. However, looking from a reform perspective, generally there has been a bias toward state-owned enterprises by Governments in giving concessions, relaxing norms, and promoting finances. The biggest example is Air India â€" the national carrier. Other sectors would be railways, including container transport, state-owned banks, the health sector, and the energy sector. The objective of this paper is to examine the impact of competition law and policy on reforming SOEs in India. This will be done through looking at cases against SOEs in India and their impact on changing the behavior of SOEs vis-à -vis competition specifically and reforms generally.
SSRN
India is one of the most significant countries of Asia, particularly in terms of its population and growing economy and markets. India has rapidly moved from a ‘command and control’ economy to free-market principles, and in this regard, one of the major reforms revamped the competition law. The new competition law introduced the principle of ‘competitive neutrality’ by bringing ‘state-owned enterprises’ (SOEs) under the purview of competition law regulation by virtue of defining ‘enterprise’ to include government departments engaged in economic activity. The Competition Commission of India (CCI) has penalized big SOEs like Coal India for violation of the Competition Act. However, looking from a reform perspective, generally there has been a bias toward state-owned enterprises by Governments in giving concessions, relaxing norms, and promoting finances. The biggest example is Air India â€" the national carrier. Other sectors would be railways, including container transport, state-owned banks, the health sector, and the energy sector. The objective of this paper is to examine the impact of competition law and policy on reforming SOEs in India. This will be done through looking at cases against SOEs in India and their impact on changing the behavior of SOEs vis-à -vis competition specifically and reforms generally.
Shocked by Bank Funding Shocks: Evidence from 500 Million Consumer Credit Cards
SSRN
Using approximately 500 million credit card â€" borrower â€" bank matched data, we analyze how a sharp unexpected decline in banks' short-term wholesale funding in 2008 affected their consumers. For the same consumer, card issuers with a 10% greater dependence on wholesale funding reduced credit limits by 3% more relative to other issuers. Consumers' aggregate card balances decreased by 0.32% for a 1% reduction in aggregate limits, with the effects more pronounced and longer-lasting for credit-constrained consumers. Our results suggest a persistent negative impact on the aggregate consumption of some consumers who could not hedge the shock to their banks' funding structure.
SSRN
Using approximately 500 million credit card â€" borrower â€" bank matched data, we analyze how a sharp unexpected decline in banks' short-term wholesale funding in 2008 affected their consumers. For the same consumer, card issuers with a 10% greater dependence on wholesale funding reduced credit limits by 3% more relative to other issuers. Consumers' aggregate card balances decreased by 0.32% for a 1% reduction in aggregate limits, with the effects more pronounced and longer-lasting for credit-constrained consumers. Our results suggest a persistent negative impact on the aggregate consumption of some consumers who could not hedge the shock to their banks' funding structure.
Stock Markets and Female Participation in the Labor Force
SSRN
This paper examines the relation between female participation in the labor force and stock market trading volume. We focus on the first teaching day of the year at kindergartens and primary schools, treating it as an event with characteristics that resemble an exogenous event, and verify this using a web-based survey. We find that the first day of school has lower trading volume than the average daily trading volume during the rest of the year. Moreover, we document that female workforce participation is negatively associated with the trading volume on this day, and that in societies which have legislated gender nondiscrimination laws that govern hiring, this negative effect is even more pronounced. Our main findings document a significant societal phenomenon with a profound impact on stock markets, and specifically on the quality of information environment, and therefore merits further attention.
SSRN
This paper examines the relation between female participation in the labor force and stock market trading volume. We focus on the first teaching day of the year at kindergartens and primary schools, treating it as an event with characteristics that resemble an exogenous event, and verify this using a web-based survey. We find that the first day of school has lower trading volume than the average daily trading volume during the rest of the year. Moreover, we document that female workforce participation is negatively associated with the trading volume on this day, and that in societies which have legislated gender nondiscrimination laws that govern hiring, this negative effect is even more pronounced. Our main findings document a significant societal phenomenon with a profound impact on stock markets, and specifically on the quality of information environment, and therefore merits further attention.
The Cost of Steering in Financial Markets: Evidence from the Mortgage Market
SSRN
We build a model of the mortgage market where banks attain their optimal mortgage portfolio by setting rates and "steering" customers. "Sophisticated" households know which mortgage type is best for them, while "naïve" ones are susceptible to steering by their banks. Using data on the universe of Italian mortgages, we estimate the model and quantify the welfare implications of steering. The analysis shows that banks' steering activity could generate distortions, with welfare effects that vary between households depending on their degree of sophistication. However, the introduction of measures to restrict the scope for banks to steer their customers would not necessarily increase household welfare, because such activities, even if potentially distortive, may also contain useful information. By contrast, a financial literacy campaign always has a beneficial effect on the welfare of naïve households, which are proportionately more exposed to the risk of taking inappropriate financial decisions.
SSRN
We build a model of the mortgage market where banks attain their optimal mortgage portfolio by setting rates and "steering" customers. "Sophisticated" households know which mortgage type is best for them, while "naïve" ones are susceptible to steering by their banks. Using data on the universe of Italian mortgages, we estimate the model and quantify the welfare implications of steering. The analysis shows that banks' steering activity could generate distortions, with welfare effects that vary between households depending on their degree of sophistication. However, the introduction of measures to restrict the scope for banks to steer their customers would not necessarily increase household welfare, because such activities, even if potentially distortive, may also contain useful information. By contrast, a financial literacy campaign always has a beneficial effect on the welfare of naïve households, which are proportionately more exposed to the risk of taking inappropriate financial decisions.
The Devil is in the Deceit: Religion and Mortgage Misrepresentation
SSRN
We investigate whether religion acts as a deterrent to the types of mortgage misrepresentation that played a significant role in the recent housing boom and bust. Using a large sample of mortgages originated from 2000 to 2007, we provide evidence that local religious adherence (religiosity) is associated with a lower likelihood of appraisal overstatement, owner occupancy misreporting, and income misrepresentation. We find no evidence that local religious adherence is related to a type of mortgage fraud -- unreported second liens -- that is unlikely to occur at the local level. Our results are consistent with the hypothesis that religion, as a set of social norms, influences risk-aversion and ethics.
SSRN
We investigate whether religion acts as a deterrent to the types of mortgage misrepresentation that played a significant role in the recent housing boom and bust. Using a large sample of mortgages originated from 2000 to 2007, we provide evidence that local religious adherence (religiosity) is associated with a lower likelihood of appraisal overstatement, owner occupancy misreporting, and income misrepresentation. We find no evidence that local religious adherence is related to a type of mortgage fraud -- unreported second liens -- that is unlikely to occur at the local level. Our results are consistent with the hypothesis that religion, as a set of social norms, influences risk-aversion and ethics.
The Impact of Bank's Asset and Liability Structure on their Profitability Regardless of Monetary Policy and Size: A Panel Analysis
SSRN
The study examines the impact of bank's asset and liability structure on their profitability without monetary policy and size; the study utilizes panel data with cross section analysis on data of 10 unit banks according to the annual balance sheet & performance. The populations of the study are bank units listed on Egyptian Exchange (EGX), the study’s data collection covered the duration from 2008 till 2016. Eventually, the study ascertained that there is an impact of the bank's asset and liability structure on their profitability according to "Return on Asset" and "Return on Equity"; however, the interprets of bank's asset and liability structure for "Return on Equity" more that to "Return on Asset". Therefore, the banking units should work to maintain the optimal rate of the structure of the bank's assets and liabilities; this may be a potential research scope in banks.
SSRN
The study examines the impact of bank's asset and liability structure on their profitability without monetary policy and size; the study utilizes panel data with cross section analysis on data of 10 unit banks according to the annual balance sheet & performance. The populations of the study are bank units listed on Egyptian Exchange (EGX), the study’s data collection covered the duration from 2008 till 2016. Eventually, the study ascertained that there is an impact of the bank's asset and liability structure on their profitability according to "Return on Asset" and "Return on Equity"; however, the interprets of bank's asset and liability structure for "Return on Equity" more that to "Return on Asset". Therefore, the banking units should work to maintain the optimal rate of the structure of the bank's assets and liabilities; this may be a potential research scope in banks.
Volatility Dynamics and Liquidity (Presentation Slides)
SSRN
Presentation on the ambivalent role of liquidity in economic stability. A model of speculation, volatility dynamics and liquidity is developed. A natural explanation of extreme randomness is offered. It is shown that news driven expectations imply clustered volatility.
SSRN
Presentation on the ambivalent role of liquidity in economic stability. A model of speculation, volatility dynamics and liquidity is developed. A natural explanation of extreme randomness is offered. It is shown that news driven expectations imply clustered volatility.
