# Research articles for the 2019-05-02

SSRN

We introduce learning into a banking model to study the dynamics of relationship lending. In our model, an entrepreneur chooses between bank and market financing. Bank lending facilitates learning over time, but it subjects the borrower to the downside of hold-up cost. We construct an equilibrium in which the entrepreneur starts with bank financing and subsequently switches to the market, and we find conditions under which this equilibrium is unique. Our model generates several novel results: 1) Endogenous zombie lending, i.e. the bank is willing to roll over loans known to be bad for the prospect of future loan sales. 2) Short maturity could encourage zombie lending and deteriorate credit quality; and 3) the hold-up cost may increase or decrease with the length of the lending relationship.

SSRN

In this paper, we show empirically that Active Risk Budgeting is a superior portfolio construction methodology to the tangency portfolio method postulated by Mean Variance Optimization. We compare the performance of Active Risk Budgeting and Tangency Portfolio in a series of systematic experiments as we gradually increase the predictive accuracy of the input signal. We find that almost always Active Risk Budgeting has better returns. Only when the signal used for portfolio construction perfectly knows the Sharpe Ratio of the securities in the next five days does the performance of the tangency portfolio catch up to Active Risk Budgeting. Given the results, we would recommend the use of Active Risk Budgeting in portfolio construction for active investment strategies on derivatives.

SSRN

We present a portfolio construction methodology for futures strategies that incorporates active trading and also borrows salient features from the risk-parity methodology. We document the evolution of expected risk and return based portfolio construction methodologies and propose a new methodology which corrects the crucial assumption in risk parity that all investments have similar risk adjusted returns and improves on Grinold and Kahnâ€™s position sizing methodology by using a optimization based framework. We demonstrate a baseline implementation of active risk budgeting that improves upon both mean variance optimization and risk budgeting and document the challenges associated with its implementation for futures trading.

SSRN

We examine the value-enhancing role of unseasoned independent directors nominated through shareholder activism events (Activist UIDs). Firms appointing Activist UIDs experience a larger value increase than those appointing Nonactivist UIDs, particularly when Activist UIDs have relevant experience, when they sit on the monitoring committees, and when their sponsors hold large target ownership. These firms also experience a decrease (increase) in investment (CEO compensation delta and dividends) post-appointment. Supporting the view that Activist UIDs add value to firms, the appointments of Activist UIDs are greeted more positively by the market, and they receive more favorable votes and obtain more additional directorships.

arXiv

We propose a microstructural modeling framework for studying optimal market making policies in a FIFO (first in first out) limit order book (LOB). In this context, the limit orders, market orders, and cancel orders arrivals in the LOB are modeled as Cox point processes with intensities that only depend on the state of the LOB. These are high-dimensional models which are realistic from a micro-structure point of view and have been recently developed in the literature. In this context, we consider a market maker who stands ready to buy and sell stock on a regular and continuous basis at a publicly quoted price, and identifies the strategies that maximize her P\&L penalized by her inventory. We apply the theory of Markov Decision Processes and dynamic programming method to characterize analytically the solutions to our optimal market making problem. The second part of the paper deals with the numerical aspect of the high-dimensional trading problem. We use a control randomization method combined with quantization method to compute the optimal strategies. Several computational tests are performed on simulated data to illustrate the efficiency of the computed optimal strategy. In particular, we simulated an order book with constant/ symmet-ric/ asymmetrical/ state dependent intensities, and compared the computed optimal strategy with naive strategies.

SSRN

This study tests theoretical predictions about capital structure determinants in the rarely explored context of Middle Eastern and North African (MENA) banks. Differences in capital structure decisions between Islamic and conventional banks are also examined. We use a panel 116 banks over the post-crisis period, 2011-2015. The baseline results show that total and short-term debt ratios are positively affected by the bankâ€™s size and growth rate but negatively affected by its profitability and liquidity. Conversely, the long-term debt ratio is negatively affected by the bankâ€™s size and growth rate. However, the dynamic Arellano-Bond estimations suggest that current year debt ratios are mainly explained by their prior year (target) levels, and many traditional capital structure determinants, except growth rate and profitability, are weak. Moreover, Islamic banks seem to maintain similar capital structure as conventional banks but have their financing decisions affected by different determinants.

arXiv

Since the money is of time value, we will study a new class of risk statistics, named cash sub-additive risk statistics in this paper. This new class of risk statistics can be considered as a kind of risk extension of risk statistics introduced by Kou, Peng and Heyde (2013), and also data-based versions of cash sub-additive risk measures introduced by El Karoui and Ravanelli (2009) and Sun and Hu (2019).

arXiv

Research in operations management has traditionally focused on models for understanding, mostly at a strategic level, how firms should operate. Spurred by the growing availability of data and recent advances in machine learning and optimization methodologies, there has been an increasing application of data analytics to problems in operations management. In this paper, we review recent applications of data analytics to operations management, in three major areas -- supply chain management, revenue management and healthcare operations -- and highlight some exciting directions for the future.

arXiv

We determine the number of statistically significant factors in a forecast model using a random matrices test. The applied forecast model is of the type of Reduced Rank Regression (RRR), in particular, we chose a flavor which can be seen as the Canonical Correlation Analysis (CCA). As empirical data, we use cryptocurrencies at hour frequency, where the variable selection was made by a criterion from information theory. The results are consistent with the usual visual inspection, with the advantage that the subjective element is avoided. Furthermore, the computational cost is minimal compared to the cross-validation approach.

SSRN

Both a healthy lifestyle and financially responsible behavior contribute to individual wellbeing and benefit society. Motivated by the fact that both types of behavior involve short-term sacrifices in exchange for uncertain long-term benefits and require self-control, we examine individualsâ€™ consistency in behavior across the health and financial domains. Using a nationally representative dataset of 3,752 employed Australians, we find that the majority of individuals behave in a consistently beneficial or detrimental way across both domains. This behavioral consistency relates to fundamental life outcomes, including physical and mental health, financial prosperity, and life satisfaction. In a new contribution to the literature, we show how personality traits â€" Locus of Control, the Big Five, Achievement Motivation â€" have a meaningful role in explaining the simultaneous pursuit of a healthy lifestyle and financially responsible behavior. These behavioral insights can guide policymakers in developing more effective strategies to steer individuals towards beneficial health and financial outcomes.

SSRN

We examine whether risk factor disclosures in 10-K filings change the third moment of stock returns â€" skewness or stock price crash risk. We use textual analysis to measure risk factor disclosure and find that risk factor disclosure is negatively associated with crash risk. This effect is further identified through a difference-in-differences analysis and the regression discontinuity design approach. The channels for this effect appear to mitigate the effects of information asymmetry and the impact of hoarding negative news on crash risk â€" the effect is stronger in firms with higher information asymmetry, litigation risk, and short interest. Overall, our findings provide evidence that additional disclosure can have positive effects on firm outcomes such as stock price crash risk.

SSRN

We use random decision forests, a statistical machine learning technique, to classify firmsâ€™ equity and debt constraints using only firm-level financial information. We train our model on the Hoberg and Maksimovic (2015) text-based measures, which are informative, but lack coverage. By mapping to financial variables we are able to extend the coverage of the text-based measures both in the cross-section and the time series, increasing the number of classified firm-years by 245%. Our method captures important non-linearities and interactions between financial variables and constraints and exhibits significant out-of-sample performance. We assess the informativeness of our constraint classifications using multiple tests â€" tests that commonly-used indices have previously been shown to fail. Our classifications perform well. They even outperform the Hoberg and Maksimovic (2015) measures over a similar sample period likely due to the increased coverage.

SSRN

This paper examines empirically the value of early exercise by testing the ability of two American put valuation models to predict the early exercise premium for the S&P 100 American put options. An accuracy test and a quality test are performed on (1) the MacMillan, Barone-Adesi and Whaley model, and (2) the Carr, Jarrow and Myneni model. The test results show that early exercise premium is significant regardless of moneyness. Moreover, consistent with the theory, the value of early exercise is significantly negatively related to moneyness and interest rates and significantly positively related to time to maturity and to the volatility of the underlying index. Both American put valuation models examined do not fully capture the value of early exercise embedded in American put prices.

SSRN

We argue that the analysis of multiple political connections in an event study framework can improve the study of institutional change. Based on a unique dataset of multiple political relationships of 4,936 South Korean board of director members, we show that the large business conglomerates, the chaebol, did not benefit from the unexpected conservative election victories in the 2012 South Korean parliamentary and presidential elections. By contrast, personal connections to candidates and to the opposition party were still considered to matter for small firms. Our findings suggest that Koreaâ€™s political economy has evolved into a hybrid regime in which the political power of large multinational corporations is limited, but the influence of political connections is still relevant for smaller firms. The corruption scandal that led to the impeachment of President Park in 2017 and the long-term development of market capitalization appear to be congruent with the results of our study.

SSRN

This paper develops composite indicators of financial integration within the euro area for both price-based and quantity-based indicators covering money, bond, equity and banking markets. Prior to aggregation, individual integration indicators are harmonised by applying the probability integral transform. We find that financial integration in Europe increased steadily between 1995 and 2007. The subprime mortgage crisis marked a turning point, bringing about a marked drop in both composite indicators. This fragmentation trend reversed when the European banking union and the ECB's Outright Monetary Transactions Programme were announced in 2012, with financial integration recovering more strongly when measured by price-based indicators. In a growth regression framework, we find that higher financial integration can be associated with an increase in per capita real GDP growth in euro area countries. In times of high financial stress, however, such a positive correlation between financial integration and growth seems to break down.

SSRN

We introduce the concept of forward rank-dependent performance processes, extending the original notion to forward criteria that incorporate probability distortions. A fundamental challenge is how to reconcile the time-consistent nature of forward performance criteria with the time-inconsistency stemming from probability distortions. For this, we first propose two distinct definitions, one based on the preservation of performance value and the other on the time-consistency of policies and, in turn, establish their equivalence. We then fully characterize the viable class of probability distortion processes, providing a bifurcation-type result. Specifically, it is either the case that the probability distortions are degenerate in the sense that the investor would never invest in the risky assets, or the marginal probability distortion equals to a normalized power of the quantile function of the pricing kernel. We also characterize the optimal wealth process, whose structure motivates the introduction of a new, distorted measure and a related market. We then build a striking correspondence between the forward rank-dependent criteria in the original market and forward criteria without probability distortions in the auxiliary market. This connection also provides a direct construction method for forward rank-dependent criteria. A byproduct of our work are some new results on the so-called dynamic utilities and on time-inconsistent problems in the classical (backward) setting.

RePEC

We study how asset quality deterioration influences the way Euro area banks adjust their balance sheets over 2010-2015. Findings from the fixed effect analysis report strong evidence of a negative correlation between asset quality and asset and lending growth. To explore the causality of the nexus, we exploit the 2014 ECB Asset Quality Review exercise in a diff-in-diff framework. We uncover a direct and negative effect of higher NPLs on banks' credit supply. Results are stronger for AQR banks plagued by high level of problem loans located in High-NPLs countries.

SSRN

This internet appendix provides supplemental results as described in our paper "Stakeholder Orientation and Firm Value", available at https://ssrn.com/abstract=3299889

SSRN

The estimation of risk factors and their replication through mimicking portfolios are of critical importance for academics and practitioners in finance. We propose a general optimization framework to construct macro factor mimicking portfolios that encompasses existing portfolio mimicking approaches such as two-pass cross-sectional regression models (Fama and MacBeth, 1973) and maximal correlation approaches (Huberman et al., 1987, Lamont, 2001). We also incorporate potential empirical estimation improvements through machine learning methodologies. We provide an application to the construction of tradable portfolios mimicking three global macro factors such as growth, inflation surprises, and financial stress indicators.

arXiv

A new approach to obtaining market--directional information, based on a non-stationary solution to the dynamic equation "future price tends to the value that maximizes the number of shares traded per unit time" [1] is presented. In our previous work[2], we established that it is the share execution flow ($I=dV/dt$) and not the share trading volume ($V$) that is the driving force of the market, and that asset prices are much more sensitive to the execution flow $I$ (the dynamic impact) than to the traded volume $V$ (the regular impact). In this paper, an important advancement is achieved: we define the "scalp-price" ${\cal P}$ as the sum of only those price moves that are relevant to market dynamics; the criterion of relevance is a high $I$. Thus, only "follow the market" (and not "little bounce") events are included in ${\cal P}$. Changes in the scalp-price defined this way indicate a market trend change - not a bear market rally or a bull market sell-off; the approach can be further extended to non-local price change. The software calculating the scalp--price given market observations triples (time, execution price, shares traded) is available from the authors.

SSRN

This paper contributes to the revived Delaware incorporation debate, focusing on the causal effects of the long-term financial value of incorporation. We find that the Delaware-incorporated firms are still valued higher than firms incorporated elsewhere, but this Delaware premium has dwindled over the years. To address the identification challenge that higher-valued firms tend to incorporate in Delaware, we examine exogenous shocks to the sources of the Delaware premium (or discount) with regard to three aspects of the legal structure governing corporations: statutory corporation laws, judge-made laws, and the court system. Our results are consistent with a causal relationship from Delaware only incorporation to firm value, mainly driven by the judge-made laws and the premier court system. Our results also indicate that the Delaware advantage sourced from the statutory laws has shrunk over the years with the federal intervention of the Sarbanes-Oxley Act and the Dodd-Frank Act.

arXiv

In the spirit of Arrow-Debreu, we introduce a family of financial derivatives that act as primitive securities in that exotic derivatives can be approximated by their linear combinations. We call these financial derivatives signature payoffs. We show that signature payoffs can be used to nonparametrically price and hedge exotic derivatives in the scenario where one has access to price data for other exotic payoffs. The methodology leads to a computationally tractable and accurate algorithm for pricing and hedging using market prices of a basket of exotic derivatives that has been tested on real and simulated market prices, obtaining good results.

SSRN

We provide a closed-form solution to an optimal investment and consumption problem for a constant absolute risk aversion (CARA) agent, who faces execution costs when trading risky assets with return predictability. The optimal investment strategy indicates that the agent should trade gradually toward a dynamic aim portfolio, which is an adjusted Merton portfolio with modifications to account for the persistence of the return-predicting signals and the execution costs. The optimal consumption strategy is quadratic in the return-predicting signals and linear in the agentâ€™s wealth. Our numerical studies show that the execution costs diminish the importance of asset return predictability on the agentâ€™s optimal investment strategy, thereby confirming the conjecture raised by Liu (2004). In addition, the presence of intermediate consumption leads to a more aggressive aim portfolio than the case without consumption.

arXiv

We present a method for obtaining approximate solutions to the problem of optimal execution, based on a signature method. The framework is general, only requiring that the price process is a geometric rough path and the price impact function is a continuous function of the trading speed. Following an approximation of the optimisation problem, we are able to calculate an optimal solution for the trading speed in the space of linear functions on a truncation of the signature of the price process. We provide strong numerical evidence illustrating the accuracy and flexibility of the approach. Our numerical investigation both examines cases where exact solutions are known, demonstrating that the method accurately approximates these solutions, and models where exact solutions are not known. In the latter case, we obtain favourable comparisons with standard execution strategies.

SSRN

We use a combination of financial risk factors and sparse hedging portfolios to allocate a large number of assets into a minimum variance portfolio. Regularized hedging portfolios can be formed using the graphical lasso but relies on statistical sparsity assumptions. To motivate these assumptions we make use of common financial risk factors. The estimated hedging portfolios are formed to complement the risk factors by allowing for deviations from the strict factor structure. Empirically we find that our method reduces portfolio volatility more than competing methods, especially when the number of assets far exceed the amount of historical returns. The strong performance stems from three related sources: (1) the power of parsimonious factor models to explain common risk; (2) the ability of the graphical lasso to perform effective model selection; (3) the benefits of avoiding high-dimensional matrix inversion in the portfolio allocation.

SSRN

We provide evidence on how statutory corporate tax rate changes affect income-shifting behavior. Our difference-in-differences identification strategy exploits the 112 staggered changes in corporate income tax rates across the 33 U.S. states during the period 1989-2012. We find that accounting earnings are more likely to be managed upward in response to state tax cuts and more significantly among firms with higher prior-year return on assets. Most firms do not manage earnings downward in response to tax increases, probably because significant tax increases usually occur when states are fiscally constrained and downward smoothing of reported earnings can certainly draw scrutiny from cash-strapped state governments. More importantly, firms had higher ROA but experienced lower stock returns prior to tax cuts do use discretionary accruals to increase earnings in the year of the tax cut and reduce earnings in the year of the tax rise, a strategy that improves returns to shareholders. This evidence suggests that firms often trade off the tax benefits of earnings management to maximize firm value for a lower risk of being detected by the regulators and other market participants.

SSRN

Using a sample of 188 European listed banks covering 2004 to 2016, we conduct textual analysis on banks' Pillar 3 reports and annual reports to showcase how banks formulate their regulatory reports. We first develop dictionaries relying on machine learning tools and its subfield of textual analysis. In addition, we construct measures of text complexity (FOG), text detail (Named Entity Recognition), and boilerplate. We validate our dictionaries by extracting numerous textual indices consisting of (1) sentiment scores, (2) measures of tone, (3) similarity of reports over time, and (4) similarity across banks. As an additional validation test, we examine how markets react to the textual difference in the Pillar 3 disclosure of riskiness and uncertainty, proxied by sense, tone, and preciseness.

SSRN

A conventional wisdom is that ratings exist to solve adverse selection and moral hazard problems. Raters often collect payments from their ratees. It is unclear whether rating schemes tailored to maximize ratees' payments solve adverse selection and moral hazard problems. I prove that ratings which fully extract the ratee's net surplus entirely solve moral hazard by leveraging the presence of adverse selection over time. I find a tension between rating transparency and economic efficiency - ratings that maximize the ratee's and the market's surplus are opaque. I illustrate the relationship between rating coarseness and moral hazard, as well as the implications of fully-extracting ratings for market beliefs and behaviors. I reconcile the conventional wisdom with critiques that ratings add little information to the markets.

SSRN

The present paper applies the financial instability hypothesis in order to explain the financial crises of 2008-2010 in eleven emerging Eastern European economies Also, it seeks to map if institutional frameworks of these countries enabled them to stand against the factors leading into the financial crisis.The paper maps cycles of three macroeconomic indicators representing the real economy, and four indicators representing financial markets. A cycle analysis is conducted with the help of a Hoderick-Prescott filter, made to isolate cycles from trends in time series. The paper concludes that there were substantial positive financial cycles previous to the financial crisis mirrored by similar cycles in the real economy. Similarly, the results show negative cycles in the same parameters during the years of crisis. It seems as an uncontrolled increase in money and credit caused the economy to overheat and thereafter contract in both substantial financial and real economy crises.Also, the paper compiles twelve different indices of institutional development. These are standardized and presented in an institutional development matrix, showing that the institutional framework for the eleven economies was weak previous to and under the melt down of the economy. The construction of an integrated institutional development index on the basis of the same twelve parameters confirm institutional shortcomings, which may have made the economies less able to guard themselves from a crisis initiated by both domestically and internationally financial instability.

SSRN

We investigate the impact of independent valuation specialists on the downward bias of pre-initial public offering (IPO) employee stock option valuations. Undervalued estimates of a firmâ€™s stock price underlying option grants result in stock option valuations that overstate earnings and provide employees with deep in the money options. For a sample of firms that completed IPOs between 2006 and 2016, we find that the decision to obtain an independent stock price valuation is more likely for firms with a Big 4 auditor and an audit committee accounting expert. We also find that valuations prepared by independent valuation specialists are less downward biased than those prepared by internal parties. Cross-sectional results suggest the following. First, independent valuations have a stronger effect on reducing downward valuation bias when the board is more independent, suggesting that independent boards facilitate independent valuations. Second, independent valuations have a weaker effect on reducing downward valuation bias when there is an accounting expert on the audit committee and when CEO equity ownership is greater, suggesting that audit committee accounting experts and greater CEO equity ownership offset the need for an independent valuation to reduce downward valuation bias.

SSRN

Corporate diversification is one of the most debated topics in finance over the past two decades. While it is widely believed that there exists a discount in the stock market valuation of conglomerate firms, the extant research based on least squares methods points to different directions. We argue that the existing empirical analyses ignore some important data features, especially cross sectional heterogeneity, predicted by both theories and casual observations on corporate diversification, and thus cannot provide a complete picture of the diversification discount. Using a quantile regression analysis on U.S. public firms, we investigate the importance of heterogeneity of diversification as well as other firm characteristics. Estimated quantile treatment effects exhibit substantial heterogeneity as predicted. Thus mean impacts miss a great deal. We also tie back differences in the effect of diversification in high-valued and low-valued firms to observable agency characteristics; the most interesting finding is that CEOs seem to play vastly different roles in high-valued and low-valued firms. We conclude that the effect of diversification is likely more varied and more extensive than has been recognized.