Research articles for the 2019-10-06

A Dimensionality-Robust Test in Multiple Predictive Regression
Xu, Ke-Li,Guo, Junjie
SSRN
We consider inference of predictive regression with multiple predictors. Extant tests for predictability, including those constructed with robustness to unknown persistence and endogeneity of predictors, may perform unsatisfactorily and tend to discover spurious predictability as the number of predictors increases. We propose a battery of new instrumental-variables based tests which involve enforcement or partial enforcement of the null hypothesis in variance estimation and analyze their asymptotic properties. A test based on the parsimonious system approach is recommended. Empirical Monte Carlos demonstrate the remarkable finite-sample performance regardless of numerosity of predictors. Empirical application to equity premium predictability is also provided.

A Scale of Credit Risk Evaluations Assessed by Ordered Fuzzy Numbers
Wójcicka-Wójtowicz, Aleksandra,Piasecki, Krzysztof Maciej
SSRN
Banks faced many difficulties related to lax credit standards. The effective management of credit risk is a critical component of a comprehensive approach to risk management and it should maintain credit risk exposure within acceptable parameters. However, the problem arises when standards are not strictly quantitative as managers often depend on various approaches â€" also on experts’ techniques. Each bank has the credit assessment department and a specific credit assessment committee. The committee is provided with the analysts’ recommendation based on ratios from financial statements and internal rating system. However, the final decision belongs to the committee members who do not solely rely on financial data and take into consideration factors of a wider spectrum, e.g. the prospects of the line of business or the experience of board members etc. Those factors are often considered on the linguistic scale which includes imprecise and inaccurate quantifiers such as: more/less, better/worse etc. which for the experts are justified and result from their personal experience.The paper presents the approach of the decision-making techniques and scales of imprecise phrases commonly used in the process of credit risk assessment based on experts’ preferences. Due to the imprecision, ordered fuzzy numbers are a useful tool. It also focuses on a question how, a human judgement approach, based on prioritizing and ranking prospect borrowers, affects the decision-making process.

A lending scheme for a system of interconnected banks with probabilistic constraints of failure
Francesco Cordoni,Luca Di Persio,Luca Prezioso
arXiv

We derive a closed form solution for an optimal control problem related to an interbank lending schemes subject to terminal probability constraints on the failure of banks which are interconnected through a financial network. The derived solution applies to a real banks network by obtaining a general solution when the aforementioned probability constraints are assumed for all the banks. We also present a direct method to compute the systemic relevance parameter for each bank within the network.



A memory-based method to select the number of relevant components in Principal Component Analysis
Anshul Verma,Pierpaolo Vivo,Tiziana Di Matteo
arXiv

We propose a new data-driven method to select the optimal number of relevant components in Principal Component Analysis (PCA). This new method applies to correlation matrices whose time autocorrelation function decays more slowly than an exponential, giving rise to long memory effects. In comparison with other available methods present in the literature, our procedure does not rely on subjective evaluations and is computationally inexpensive. The underlying basic idea is to use a suitable factor model to analyse the residual memory after sequentially removing more and more components, and stopping the process when the maximum amount of memory has been accounted for by the retained components. We validate our methodology on both synthetic and real financial data, and find in all cases a clear and computationally superior answer entirely compatible with available heuristic criteria, such as cumulative variance and cross-validation.



Accounting Comparability, Financial Reporting Quality, and the Pricing of Accruals
Chen, Anthony,Gong, James Jianxin
SSRN
This study examines the impact of accounting comparability on financial reporting quality and the extent to which financial statement users understand the implications of firms’ accruals. We predict that comparability improves the information environment, which not only enhances the ability of managers to estimate accruals more accurately and signal their private information, but also improves investors’ comprehension of accruals. Utilizing restatements, the mapping of accruals into cash flows, earnings persistence, and audit fees as measures of financial reporting quality, we find that prior-period comparability is associated with higher financial reporting quality. We also provide evidence that comparability is positively associated with managerial forecast accuracy and precision, consistent with comparability improving the ability of managers to predict future firm performance. Furthermore, we find that when prior-period comparability is higher, current period discretionary accruals are less positively correlated with contemporaneous returns and less negatively correlated with future returns, consistent with our prediction that comparability improves the pricing efficiency of accruals. Our results are robust to controlling for the endogeneity of accounting comparability and several different empirical model specifications. Overall, our findings suggest that enhanced accounting comparability is beneficial to both preparers and users of financial statements.

Construction of Optimal Portfolio using Sharpe Index Model
M, Nagendra,Raveendra, P. V.,Brahmam, U.
SSRN
The investor always likes to have less risk and higher returns. To reduce the risk investors will do diversification. Diversification means combination of securities which provides the highest return and has lowest risk. Combination of securities is called portfolio. Risk and Return are two basic factors for construction of a portfolio. The principle point of every investor in construction of a portfolio is to maximize the return and to minimize the risk. The portfolio which has highest return and lowest risk is termed as Optimal Portfolio. Sharpe Index Model is adequate and conceptually sound in construction of optimal portfolio. This paper makes an attempt to construct optimal portfolio using Sharpe Optimization Model from NSE NIFTY Stocks.

Crowdfunding's Culture of Noncompliance: An Empirical Analysis
Bullard, Mercer
SSRN
The JOBS Act of 2012 launched a number of experiments in the regulation of securities offerings. The exemption it created that allows online equity crowdfunding offerings to retail investors garnered the most attention, in part due to widespread concerns regarding the potential for fraud and abuse. More than three years after the first crowdfunding offering, no empirical analysis of compliance has been conducted that would debunk or confirm critics’ concerns. This Article plugs that gap by analyzing a sample of 362 crowdfunding offerings and evaluating compliance with some of crowdfunding regulation’s simplest, most fundamental regulatory requirements. During the first 13 months of crowdfunding, almost half of issuers failed to file complete financial statements that met the applicable standard of review, barely one-quarter of issuers that were required to file two annual reports did so, less than 15 percent of issuers timely filed the final amount raised in their offering, and the only data point on Form C that was reviewed was, far more often than not, substantially inaccurate. Finally, the third largest crowdfunding funding portal may be violating the prohibition against a funding portal’s giving advice. In short, these findings reveal a deeply embedded culture of noncompliance. This Article is timely in light of the issuance of a concept release by the Securities and Exchange Commission that is intended to set the table for further liberalization of exempt offerings. Rather than supporting such changes, the findings set forth in this Article create doubt as to whether the crowdfunding experiment will even survive. This Article proposes a series of reforms that would address some of the above-mentioned noncompliance problems while both benefiting investors and reducing costs and burdens for issuers.

Directorâ€"Liabilityâ€"Reduction Laws and Conditional Conservatism
Basu, Sudipta,Liang, Yi
SSRN
We study nonofficer directors’ influence on the accounting conservatism of U.S. public firms. Between 1986 and 2002, all 50 U.S. states enacted laws that limited nonofficer directors’ litigation risk but often left officer directors’ litigation risk unchanged. We find that conditional conservatism decreased after the staggered enactments of the laws, which we attribute to less nonofficer director monitoring of financial reporting in affected firms. Conservatism fell less when shareholder or debtholder power was high, consistent with major stakeholders moderating the influence of nonofficer directors. We verify that our results stem from reductions in the asymmetric timeliness of accruals and, specifically, its current assets components. We also show that affected firms switched away from Big N auditors more often, which reduced these firms’ commitment to conservative financial reports.

Distracted Institutional Investors and Audit Risk
Wu, Hai,Yang , Jingyu,Yu, Yangxin
SSRN
We use a newly developed institutional investor distraction measure (Kempf, Manconi, & Spalt, 2016) to examine whether auditors charge higher audit fees and exert higher efforts when their clients’ institutional investors temporarily reduce their monitoring activities. We find that audit fees and audit report lags increase significantly during periods when institutional investors are distracted. This effect is stronger when dedicated institutional investors are distracted. We further show that the positive association between the investor distraction measure and audit risk measures declines in the post-Sarbanesâ€"Oxley Act period. Collectively, our results suggest that institutional shareholders monitoring activities benefits auditors by reducing audit risks. This paper also shows that the negative effect of investors’ limited attentions on corporate monitoring can to some extent be mitigated by auditors.

Distributionally Robust XVA via Wasserstein Distance Part 1: Wrong Way Counterparty Credit Risk
Derek Singh,Shuzhong Zhang
arXiv

This paper investigates calculations of robust CVA for OTC derivatives under distributional uncertainty using Wasserstein distance as the ambiguity measure. Wrong way counterparty credit risk can be characterized (and indeed quantified) via the robust CVA formulation. The simpler dual formulation of the robust CVA optimization is derived. Next, some computational experiments are conducted to measure the additional CVA charge due to distributional uncertainty under a variety of portfolio and market configurations. Finally some suggestions for future work, such as robust FVA, are discussed.



Employment, Corporate Investment and Cash Flow Risk
Alnahedh, Saad,Bhagat, Sanjai,Obreja, Iulian
SSRN
We highlight the role of cash flow uncertainty on corporate employment and investment. We find that a 1% increase in cash flow uncertainty leads to a 0.62% decrease in tangible investment, a 1.39% decrease in intangible investment, and a 3.67% decrease in corporate employment. Our results are statistically and economically significant. We further find that these relationships are stronger during economic recessions. Our findings have significant policy implications. To wit, if policy makers would like corporations to increase their employment and investment, they should focus on policies that decrease corporate cash flow uncertainty.

Hedge Fund Regulation and Fund Governance: Evidence on the Effects of Mandatory Disclosure Rules
Honigsberg, Colleen
SSRN
This paper uses three alternating changes in hedge fund regulation to study whether regulation reduces hedge funds’ misreporting, and, if so, why regulation is effective. Relative to public companies, hedge fund regulation is relatively light. Much of the regime is a “comply‐or‐explain” framework that allows funds to forego compliance with governance rules, providing that they disclose their lack of compliance. The results show that regulation reduces misreporting at hedge funds. Further analysis suggests that the disclosure requirements led funds to make changes in their internal governance, such as hiring or switching the fund's auditor, and that these changes induced funds to report their financial performance more accurately.

Information Intermediary or De Facto Standard Setter? Field Evidence on the Indirect and Direct Influence of Proxy Advisors
Hayne, Christie,Vance, Marshall D.
SSRN
We examine whether proxy advisory firms (PAs) serve primarily an information intermediary role by providing research and voting recommendations to shareholders, or directly influence executive compensation by exerting pressure on firms to adopt preferred pay practices. Through a field study, we find that PAs are perceived as both information intermediaries and agenda setters and that these roles provide leverage to enable PAs to exercise significant influence over executive pay practices. Boards feel, and sometimes yield to, pressure to conform to PA “best” practices despite their own preferred compensation philosophies, even in the absence of overt PA scrutiny or negative shareholder votes. We also find that PAs are susceptible to conflicts of interest and generally use a “one‐size‐fits‐all” approach to voting recommendations. Overall, however, PAs are viewed as improving compensation practices by increasing transparency and accountability and fostering dialogue between firms and their shareholders.

Made in the U.S.A.? A Study of Firm Responses to Domestic Production Incentives
Lester, Rebecca
SSRN
How do U.S. companies respond to incentives intended to encourage domestic manufacturing? I study the Domestic Production Activities Deduction (DPAD), which was enacted in the American Jobs Creation Act (AJCA) of 2004 and was the third largest U.S. corporate tax expenditure as of 2017. Using confidential data from the U.S. Bureau of Economic Analysis, I find greater average domestic investment spending of $95.5â€"$143.6 million, but only within the sample of domestic‐only firms and not until 2010, when the greatest statutory DPAD benefits were available. Additional evidence suggests that U.S. multinational claimants invest abroad rather than in the United States and that the increased investment by DPAD firms is accompanied by a reduction in the domestic workforce, consistent with a substitution of capital for labor. I also show that the delayed investment response is due to firms engaging in other responses first, such as changing corporate reporting to shift income across time and borders. Quantifying the extent of these effects contributes to the literature that studies this tax deduction and informs policy makers as to the effectiveness of both manufacturing incentives and U.S. corporate income tax rate reductions in stimulating real domestic activity.

On the Dependence between Quantiles and Dispersion Estimators
Bräutigam, Marcel,Kratz, Marie
SSRN
In this study, we derive the joint asymptotic distributions of functionals of quantile estimators (the non-parametric sample quantile and the parametric location-scale quantile) and functionals of measure of dispersion estimators (the sample standard deviation, sample mean absolute deviation, sample median absolute deviation) - assuming an underlying identically and independently distributed sample. Additionally, for location-scale distributions, we show that asymptotic correlations of such functionals do not depend on the mean and variance parameter of the distribution. Further, we compare the impact of the choice of the quantile estimator (sample quantile vs. parametric location-scale quantile) in terms of speed of convergence of the asymptotic covariance and correlations respectively. As application, we show in simulations a good finite sample performance of the asymptotics. Further, we show how the theoretical dependence results can be applied to the most well-known risk measures (Value-at-Risk, Expected Shortfall, expectile). Finally, we relate the theoretical results to empirical findings in the literature of the dependence between risk measure prediction (on historical samples) and the estimated volatility.

Option pricing under normal dynamics with stochastic volatility
Matta Uma Maheswara Reddy
arXiv

In this paper, we derive the price of a European call option of an asset following a normal process assuming stochastic volatility. The volatility is assumed to follow the Cox Ingersoll Ross (CIR) process. We then use the fast Fourier transform (FFT) to evaluate the option price given we know the characteristic function of the return analytically. We compare the results of fast Fourier transform with the Monte Carlo simulation results of our process. Further, we present a numerical example to understand the normal implied volatility of the model.



Predicting Consumer Default: A Deep Learning Approach
Stefania Albanesi,Domonkos F. Vamossy
arXiv

We develop a model to predict consumer default based on deep learning. We show that the model consistently outperforms standard credit scoring models, even though it uses the same data. Our model is interpretable and is able to provide a score to a larger class of borrowers relative to standard credit scoring models while accurately tracking variations in systemic risk. We argue that these properties can provide valuable insights for the design of policies targeted at reducing consumer default and alleviating its burden on borrowers and lenders, as well as macroprudential regulation.



Sensitivity of Collective Outcomes Identifies Pivotal Components
Lee, Edward,Katz, Daniel Martin,Bommarito, Michael James,Ginsparg, Paul
SSRN
A social system is susceptible to perturbation when its collective properties depend sensitively on a few, pivotal components. Using the information geometry of minimal models from statistical physics, we develop an approach to identify pivotal components to which coarse-grained, or aggregate, properties are sensitive. As an example we introduce our approach on a reduced toy model with a median voter who always votes in the majority. With this example, we construct the Fisher information matrix with respect to the distribution of majority-minority divisions and study features of the matrix that pinpoint the unique role of the median. More generally, these features identify pivotal blocs that precisely determine collective outcomes generated by a complex network of interactions. Applying our approach to data sets from political voting, finance, and Twitter, we find remarkable variety from systems dominated by a median-like component (e.g., California State Assembly) to those without any single special component (e.g., Alaskan Supreme Court). Other systems (e.g., S&P sector indices) show varying levels of heterogeneity in between these extremes. By providing insight into such sensitivity, our information-geometric approach presents a quantitative framework for considering how nominees might change a judicial bench, serve as a measure of notable temporal variation in financial indices, or help analyze the robustness of institutions to targeted perturbation.

Statistical analysis and stochastic interest rate modelling for valuing the future with implications in climate change mitigation
Josep Perelló,Miquel Montero,Jaume Masoliver,J. Doyne Farmer,John Geanakoplos
arXiv

High future discounting rates favor inaction on present expending while lower rates advise for a more immediate political action. A possible approach to this key issue in global economy is to take historical time series for nominal interest rates and inflation, and to construct then real interest rates and finally obtaining the resulting discount rate according to a specific stochastic model. Extended periods of negative real interest rates, in which inflation dominates over nominal rates, are commonly observed, occurring in many epochs and in all countries. This feature leads us to choose a well-known model in statistical physics, the Ornstein-Uhlenbeck model, as a basic dynamical tool in which real interest rates randomly fluctuate and can become negative, even if they tend to revert to a positive mean value. By covering 14 countries over hundreds of years we suggest different scenarios. We find that only 4 of the countries have positive long run discount rates while the other ten countries have negative rates. Even if one rejects the countries where hyperinflation has occurred, our results support the need to consider low discounting rates. The results provided by these fourteen countries significantly increase the priority of confronting global actions such as climate change mitigation.



The End of Bank Branching
Keil, Jan
SSRN
The U.S. banking industry is in the early stage of an epic transformation: banks are closing their branches in all states across the country. Branch numbers declined in every single year since 2009, amounting to a total net loss of 11,244 by 2018, or 11.4%. If Europe is any guidance, more than 8 out of 10 branches will be closed in the near future. I describe this de-branching of banks and explore differences between regions, banks, and branches. The financial crisis’ adverse shock to bank health is one driver explaining the timing of the de-branching trend’s start.

The Index Effect Minute by Minute: Intraday Returns at NASDAQ-100 and MSCI U.S. Rebalancings
Franz, Friedrich-Carl
SSRN
I use intraday data from 2013 to 2017 and a dataset of NASDAQ-100, MSCI USA and MSCI USA Small Cap Index constituent changes to investigate abnormal returns and trading volume around index rebalancings. The results show no pre-announcement speculation but a significantly positive (negative) post-announcement jump followed by an intraday drift for promotions (demotions). For small-cap changes, the post-announcement jump is smaller but abnormal returns with the same sign are also found on the rebalancing date and especially during the last 30 minutes of trading. Large-cap index changes have higher abnormal trading volume but much smaller abnormal returns on the rebalancing date. Consistent with the price pressure hypothesis, I find a reversal during the early trading hours on the day following the rebalancing date.

The Performance of Exchange-Traded Funds
Blitz, David,Vidojevic, Milan
SSRN
Exchange-traded funds (ETFs) are commonly regarded as an efficient, low-cost alternative to actively managed mutual funds, yet their perceived superiority is largely anecdotal. We evaluate the performance of a comprehensive, survivorship bias-free sample of US equity ETFs following the same approach that has been commonly used to evaluate the performance of actively managed mutual funds. We find that ETFs have collectively lagged the market by an amount that appears similar to the widely documented underperformance of active mutual funds. We perform textual and regression-based analysis to identify factor ETFs and show that most of these have also failed to beat the market. We conclude that, from a pure performance perspective, the allure of ETFs finds little support in the data.

Utility-based pricing and hedging of contingent claims in Almgren-Chriss model with temporary price impact
Ibrahim Ekren,Sergey Nadtochiy
arXiv

In this paper, we construct the utility-based optimal hedging strategy for a European-type option in the Almgren-Chriss model with temporary price impact. The main mathematical challenge of this work stems from the degeneracy of the second order terms and the quadratic growth of the first order terms in the associated HJB equation, which makes it difficult to establish sufficient regularity of the value function needed to construct the optimal strategy in a feedback form. By combining the analytic and probabilistic tools for describing the value function and the optimal strategy, we establish the feedback representation of the latter. We use this representation to derive an explicit asymptotic expansion of the utility indifference price of the option, which allows us to quantify the price impact in options' market via the price impact coefficient in the underlying market. Finally, we describe a game between competing market makers for the option and construct an equilibrium in which the option is traded at the utility indifference price.