# Research articles for the 2019-08-01

A Model of Presidential Debates
Doron Klunover,John Morgan
arXiv

Presidential debates are thought to provide an important public good by revealing information on candidates to voters. However, this may not always be the case. We consider an endogenous model of presidential debates in which an incumbent and a contender (who is privately informed about her own quality) publicly announce whether they are willing to participate in a public debate, after taking into account that a voter's choice of candidate depends on her beliefs regarding the candidates' qualities and on the state of nature. Surprisingly, it is found that in equilibrium a debate occurs or does not occur independently of the contender's quality or the sequence of the candidates' announcements to participate and therefore the announcements are uninformative.

A Test of the Modigliani-Miller Invariance Theorem and Arbitrage in Experimental Asset Markets
Charness, Gary,Neugebauer, Tibor
SSRN
Modigliani and Miller (1958) show that a repackaging of asset return streams to equity and debt has no impact on the total market value of the firm if pricing is arbitrage-free. We test the empirical validity of this invariance theorem in experimental asset markets with simultaneous trading in two shares of perfectly-correlated returns. Our data support value invariance for assets of identical risks when returns are perfectly correlated. However, exploiting price discrepancies has risk when returns have the same expected value but are uncorrelated, and we find that the law of one price is violated in this case. Discrepancies shrink in consecutive markets, but seem to persist even with experienced traders. In markets where overall trader acuity is high, assets trade closer to parity.

A global economic policy uncertainty index from principal component analysis
Peng-Fei Dai,Xiong Xiong,Wei-Xing Zhou
arXiv

This paper constructs a global economic policy uncertainty index through the principal component analysis of the economic policy uncertainty indices for twenty primary economies around the world. We find that the PCA-based global economic policy uncertainty index is a good proxy for the economic policy uncertainty on a global scale, which is quite consistent with the GDP-weighted global economic policy uncertainty index. The PCA-based economic policy uncertainty index is found to be positively related with the volatility and correlation of the global financial market, which indicates that the stocks are more volatile and correlated when the global economic policy uncertainty is higher. The PCA-based global economic policy uncertainty index performs slightly better because the relationship between the PCA-based uncertainty and market volatility and correlation is more significant.

Bolstering Family Control: Evidence from Loyalty Shares
Bajo, Emanuele,Barbi, Massimiliano,Bigelli, Marco,Croci, Ettore
SSRN
In order to favor shareholder investment over a longer time horizon, Italy introduced loyalty shares in late 2014, which allow double voting rights after a two-year continuous holding period. Italian listed firms which adopted loyalty shares (about 20 percent of those listed in the main market segment) are significantly more likely to be controlled by families and have a more concentrated ownership structure. We report no evidence of a negative market reaction at the announcementâ€™s adoption, nor a reduction in holdings by institutional investors, despite institutional investors generally voting against the introduction of loyalty shares. Notwithstanding the short period of analysis, we find some evidence that controlling shareholders reduce their holdings after loyalty shares are adopted.

Can Financial Intermediary Development Improve Financial Literacy? Evidence from China
Xu, Jia,Su, Qin,Zhang, Xiaoyun
SSRN
The lack of financial knowledge and its serious consequences has brought about extensive discussion among academics since the 2008 financial crisis. This study investigates the importance of financial intermediation in financial literacy. Using Consumer Finance and Investment Education Survey data in 24 cities from 2010 to 2012 in China, we find that financial intermediary development helps to improve financial literacy. This positive impact is magnified in central and western China, and to females and to less-educated consumers. The results hold after controlling the problem of endogeneity by constructing regulation of bank cross-city branching as an instrumental variable. We further run a number of estimations to discover the influence mechanism. Our results show that the influence upon individuals occurs not after but before they make financial decisions, and that the precondition is when their current expenditure exceeds current revenues, which requires inter-temporary cash-flow adjustments. That is to say, only when individuals have formed an effective demand for financial knowledge, will financial intermediary development improve their financial literacy. The study sheds some light on the improvement of consumer financial literacy and financial inclusion.

Decomposition formula for rough Volterra stochastic volatility models
Raul Merino,Jan Pospíšil,Tomáš Sobotka,Tommi Sottinen,Josep Vives
arXiv

The research presented in this article provides an alternative option pricing approach for a class of rough fractional stochastic volatility models. These models are increasingly popular between academics and practitioners due to their surprising consistency with financial markets. However, they bring several challenges alongside. Most noticeably, even simple non-linear financial derivatives as vanilla European options are typically priced by means of Monte-Carlo (MC) simulations which are more computationally demanding than similar MC schemes for standard stochastic volatility models.

In this paper, we provide a proof of the prediction law for general Gaussian Volterra processes. The prediction law is then utilized to obtain an adapted projection of the future squared volatility -- a cornerstone of the proposed pricing approximation. Firstly, a decomposition formula for European option prices under general Volterra volatility models is introduced. Then we focus on particular models with rough fractional volatility and we derive an explicit semi-closed approximation formula. Numerical properties of the approximation for a popular model -- the rBergomi model -- are studied and we propose a hybrid calibration scheme which combines the approximation formula alongside MC simulations. This scheme can significantly speed up the calibration to financial markets as illustrated on a set of AAPL options.

Employer Losses and Deferred Compensation
Walker, David I.
SSRN
Most large public companies offer their executives the opportunity to defer the receipt and taxation of their salary or other current compensation until retirement or some other future date, and equity compensation, which also entails deferral of pay and taxation, constitutes a large fraction of the typical executive pay package. Conventional wisdom holds that employer net operating losses (NOLs) improve the joint economics of deferred and equity compensation (henceforth together "deferred compensation") for the parties. However, empirical studies provide little evidence of an association between employer NOLs and deferred compensation use. This paper focuses on two potential explanations for this apparent disconnect. First, this paper shows that the relationship between employer NOLs and the attractiveness of deferred compensation is more complex and less predictable than is generally recognized, that a large NOL position does not necessarily produce a larger driving force for use of deferred compensation, and that in some cases employer NOLs can actually result in poorer deferred compensation economics. As a result, some employers and executives may rationally choose to ignore employer NOLs when making compensation decisions. Second, even if companies are sensitive to the existence of employer NOLs when making compensation decisions, it is not clear that research methods currently in use would detect the sensitivity. The commonly used proxies and simulations of employer effective marginal tax rates that have been employed in these studies may not adequately capture the complexity of the relationship between NOLs and the economics of deferred compensation.

European ETF Factor Exposures: Evidence from a Regression- and Holdings-Based Analysis
Dirkx, Philipp
SSRN
The article analyzes factor exposures of European equity exchange-traded funds (ETFs) according to 10-year regressions and a holdings-based analysis. While smart beta ETFs target certain factors explicitly, they and conventional market-capitalization-weighted ETFs (conventional ETFs) both can carry implicit exposures, too. The analysis shows that especially various sector ETFs carry strong regression-based factor exposures, which are only partially mirrored from a holdings-based view. Collectively, the conventional and smart beta ETFs show various significant factor loadings, which are mostly backed by the holdings-based analysis. Translating the flows in smart beta ETFs into a form of factor timing of market participants, the asset-weighted smart beta aggregate outperformed the market on an absolute and risk-adjusted basis.

Experimental Stock Market Dynamics: Excess Bids, Directional Learning, and Adaptive Style Investing in a Call-Auction with Multiple Multiperiod Lived Assets
Selten, Reinhard,Neugebauer, Tibor
SSRN
We study the behavioral dynamics of limit orders in simultaneous experimental call-auction markets with multiple multiperiod lived securities. As analytical decision variable we use excess bids; the number of submitted bids minus the number of offers. The feedback variable is (excess) return. Our results suggest that excess bids are predictive of qualitative asset returns, and that excess bids are formed in an adaptive way. We conclude that the price trend or reversal is reinforced by rejected excess bids and the fundamental laws of demand and supply instigate a regression to the mean. Our analysis of portfolio adjustment dynamics which is based on learning direction theory shows that adaptive value-style investing and path-dependence explain a significant share of individual behavior.

Explanations of Cycles in Seasoned Equity Offerings: An Examination of the Choice between Rights Issues and Private Placements
SSRN
A feature of the Australian equity market is that, unlike all other equity markets, private placements and rights issues are used more frequently than public offerings. This study examines time-variation in these types of seasoned equity offerings (SEOs), to examine choice between them, and to enhance our understanding of the reasons for time-variation in SEOs. Time-variation in information asymmetry, the demand for capital, and investment sentiment, together with market timing, are explanations for this cyclicality in SEO issuance; although the drivers of time-variation differ across SEO types. Time-variation in the demand for capital has a statistically and economically significant impact on time-variation in private placements, while time-variation in investor sentiment has a statistically and economically significant impact on the prevalence of rights issues. Market timing and information asymmetry do not have explanatory power for variation in SEO activity.

Fooling Actively: Factor Exposure Analysis of Active ESG Managers
Kumar, Dr. Rajnish
SSRN
The article examines the factor return attribution of active managers with exposure to Environment, Social and Governance (ESG). The analyses have been done using CAPM, Fama- French three factors, Fama-French-Carhart four factors, Fama-French five factors and Fama- French-Carhart six factors asset pricing models since the inception of each of active ESG funds using Fama-French factor library as well as AQR factor library data. We find that returns of most of the active ESG funds are explained by CAPM market factor as adjusted R2 varies from 70% to 98%. The analyses show that only 10% of the active ESG managers are able to generate positive alpha after controlling for all the factors. Further, for all the active ESG funds for which alpha is positive and significant, factors other than market are both negatively and positively associated with ESG fundsâ€™ return. This implies that not all active ESG managers are correctly incorporating ESG metric in their portfolio construction. Active ESG managers can generate alpha either by including other performance metric in constructing their ESG portfolio or creating portfolio based on materiality mapped ESG score or incorporating the information available in basic components of ESG which is still not priced in the already established factors.

Hamilton's Law and Finance - Borrowing from the Brits (And the Dutch)
Day, Christian C.
SSRN
We live in an era when Modern Monetary Theory has gained purchase. Deficits do not seem to matter to nations or their finance ministers. States believe the can print their way to utopia without a reckoning; this is a scheme freighted with disaster. This article centers on the achievements of Americaâ€™s greatest finance minister whose grasp of political economy was without equal. Hamilton charted the course for American economic power. His work is timely and worthy of study.Late-18th century America sought commercial growth and new manufacturers yet feared monopolistic economic power. Hamiltonâ€™s economic program, centered on a national bank and program for manufacturing, provided the framework for the finance-led transformation of America. In a short time, Hamiltonâ€™s elegant solutions (based upon the English financial model) transformed America from a defaulting debtor to a magnet that attracted immense amounts of capital in the 19th century. The burden of the Revolutionary War debt needed to be resolved. Hamiltonâ€™s program: the assumption of the states and Confederation debt, its monetization, the establishment of the Bank of the United States, and Report on Manufactures laid the foundation for a vibrant economy. The article demonstrates how Hamiltonâ€™s prudent program strengthened the new federal government while providing the blueprint for the commercial society that emerged in the 19th century.

Hedging Non-Tradable Risks with Transaction Costs and Price Impact
Alvaro Cartea,Ryan Donnelly,Sebastian Jaimungal
arXiv

A risk-averse agent hedges her exposure to a non-tradable risk factor $U$ using a correlated traded asset $S$ and accounts for the impact of her trades on both factors. The effect of the agent's trades on $U$ is referred to as cross-impact. By solving the agent's stochastic control problem, we obtain a closed-form expression for the optimal strategy when the agent holds a linear position in $U$. When the exposure to the non-tradable risk factor $\psi(U_T)$ is non-linear, we provide an approximation to the optimal strategy in closed-form, and prove that the value function is correctly approximated by this strategy when cross-impact and risk-aversion are small. We further prove that when $\psi(U_T)$ is non-linear, the approximate optimal strategy can be written in terms of the optimal strategy for a linear exposure with the size of the position changing dynamically according to the exposure's "Delta" under a particular probability measure.

Hedging crop yields against weather uncertainties -- a weather derivative perspective
Samuel Asante Gyamerah,Philip Ngare,Dennis Ikpe
arXiv

The effects of weather on agriculture in recent years have become a major global concern. Hence, the need for an effective weather risk management tool (i.e., weather derivatives) that can hedge crop yields against weather uncertainties. However, most smallholder farmers and agricultural stakeholders are unwilling to pay for the price of weather derivatives (WD) because of the presence of basis risks (product-design and geographical) in the pricing models. To eliminate product-design basis risks, a machine learning ensemble technique was used to determine the relationship between maize yield and weather variables. The results revealed that the most significant weather variable that affected the yield of maize was average temperature. A mean-reverting model with a time-varying speed of mean reversion, seasonal mean, and local volatility that depended on the local average temperature was then proposed. The model was extended to a multi-dimensional model for different but correlated locations. Based on these average temperature models, pricing models for futures, options on futures, and basket futures for cumulative average temperature and growing degree-days are presented. Pricing futures on baskets reduces geographical basis risk, as buyers have the opportunity to select the most appropriate weather stations with their desired weight preference. With these pricing models, farmers and agricultural stakeholders can hedge their crops against the perils of extreme weather.

Hiring in the substance use disorder treatment related sector during the first five years of Medicaid expansion
Olga Scrivner,Thuy Nguyen,Kosali Simon,Esmé Middaugh,Bledi Taska,Katy Börner
arXiv

Effective treatment strategies exist for substance use disorder (SUD), however severe hurdles remain in ensuring adequacy of the SUD treatment (SUDT) workforce as well as improving SUDT affordability, access and stigma. Although evidence shows recent increases in SUD medication access from expanding Medicaid availability under the Affordable Care Act, it is yet unknown whether these policies also led to a growth in the changes in the nature of hiring in SUDT related workforce, partly due to poor data availability. Our study uses novel data to shed light on recent trends in a fast-evolving and policy-relevant labor market, and contributes to understanding the current SUDT related workforce and the effect of Medicaid expansion on hiring attempts in this sector. We examine attempts over 2010-2018 at hiring in the SUDT and related behavioral health sector as background for estimating the causal effect of the 2014-and-beyond state Medicaid expansion on these outcomes through "difference-in-difference" econometric models. We use Burning Glass Technologies (BGT) data covering virtually all U.S. job postings by employers. Nationally, we find little growth in the sector's hiring attempts in 2010-2018 relative to the rest of the economy or to health care as a whole. However, this masks diverging trends in subsectors, which saw reduction in hospital based hiring attempts, increases towards outpatient facilities, and changes in occupational hiring demand shifting from medical personnel towards counselors and social workers. Although Medicaid expansion did not lead to any statistically significant or meaningful change in overall hiring attempts, there was a shift in the hiring landscape.

How Slow is the Recovery of Loans to Firms in Italy?
Eramo, Ginette,Felici, Roberto,Finaldi Russo, Paolo,Signoretti, Federico Maria
SSRN
This paper studies the characteristics of the recent evolution of loans to non-financial firms in Italy from an historical perspective, with the aim of ascertaining whether the ongoing recovery is creditless; the main demand- and supply-side determinants of credit are also discussed. We find the following results. First, bank loan dynamics have been weak compared to the universe of recoveries in 13 euro-area countries since 1980; however, credit has evolved in line with the median pattern in the restricted sample of recoveries following deep and long recessions and/or recessions associated with banking crises. Second, the reduction in loans has been common to firms of all sizes, though it has been more pronounced for smaller ones. Third, based on a review of credit market indicators, survey evidence and econometric studies, the weakness of lending to firms has been in line with subdued dynamics of demand; the stringency of lending criteria has also contributed, in particular for smaller and riskier firms.

Large Scale Continuous-Time Mean-Variance Portfolio Allocation via Reinforcement Learning
Wang, Haoran,Zhou, Xun Yu
SSRN
We propose to solve large scale Markowitz mean-variance (MV) portfolio allocation problem using reinforcement learning (RL). By adopting the recently developed continuous-time exploratory control framework, we formulate the exploratory MV problem in high dimensions. We further show the optimality of a multivariate Gaussian feedback policy, with time-decaying variance, in trading off exploration and exploitation. Based on a provable policy improvement theorem, we devise a scalable and data-efficient RL algorithm and conduct large scale empirical tests using data from the S&P 500 stocks. We found that our method consistently achieves over 10% annualized returns and it outperforms econometric methods and the deep RL method by large margins, for both long and medium terms of investment with monthly and daily trading.

Monetary Policy Shocks and the Health of Banks
Jung, Alexander,Uhlig, Harald
SSRN
Based on high frequency identification and other econometric tools, we find that monetary policy shocks had a significant impact on the health of euro area banks. Information effects, which made the private sector more pessimistic about future prospects of the economy and the profitability of the banking sector, were strongly present in the post-crisis period. We show that ECB communications at the press conference were crucial for the market response and that bank health benefitted from surprises, which steepened the yield curve. We find that the effects of monetary policy shocks on banks displayed some persistence. Other bank characteristics, in particular bank size, leverage and NPL ratios, amplified the impact of monetary policy shocks on banks. After the OMT announcement, we detect that the response of bank stocks to monetary policy shocks normalised. We discover that, in the post-crisis episode, Fed monetary policy shocks influenced euro area bank stock valuations.

Moral Incentives in Credit Card Debt Repayment: Evidence from a Field Experiment
Bursztyn, Leonardo,Fiorin, Stefano,Gottlieb, Daniel,Kanz, Martin
SSRN
We study the role of morality in debt repayment, using an experiment with the credit card customers of a large Islamic bank in Indonesia. In our main treatment, clients receive a text message stating that â€œnon-repayment of debts by someone who is able to repay is an injustice." This moral appeal decreases delinquency by 4.4 percentage points from a baseline of 66 percent and reduces default among customers with the highest ex-ante credit risk. Additional treatments help benchmark the effects against direct financial incentives and rule out competing explanations, such as reminder effects, priming religion, and provision of new information.

Net Share Issues and the Cross-Section of Equity Returns under a Dividend Imputation Tax System
SSRN
Despite considerable empirical evidence reporting a negative relationship between net share issuance and subsequent returns, it remains unresolved whether this anomaly is explained by risk or investor irrationality. This paper examines the net share issuance anomaly using seasoned equity offerings before and after the introduction of an imputation tax system. We report robust evidence of a negative relationship between net share issuance and returns post-imputation, but no relationship pre-imputation. Our results provide evidence to support the international pervasiveness of the net share issuance anomaly, but more importantly suggest that this anomaly may be explained by risk.

On the Relation between Financial Reporting Quality and Country Attributes: Research Challenges and Opportunities
Isidro, Helena,Nanda, Dhananjay,Wysocki, Peter D.
SSRN
We provide new evidence on the co-dependence among the many country attributes previously linked to financial reporting quality. First, we show that the synchronicity of 21 changing country attributes spikes surrounding mandatory IFRS adoption. Thus, while IFRS adoption â€œexplainsâ€ increased reporting quality, this finding disappears after including other changing country determinants of reporting quality. Second, a single underlying factor distills the numerous reporting quality measures used in the international literature. Finally, we document that four underlying country factors largely subsume the individual explanatory power of 72 candidate country attributes in explaining reporting quality levels across countries. We conclude with implications and suggestions for future research on international reporting quality.

Option Pricing in an Investment Risk-Return Setting
Kim, Young Shin,Stoyanov, Stoyan V.,Rachev, Svetlozar,Fabozzi, Frank J.
SSRN
In this paper, we combine modern portfolio theory and option pricing theory so that a trader who takes a position in a European option contract and the underlying assets can construct an optimal portfolio such that at the moment of the contractâ€™s maturity the contract is perfectly hedged. We derive both the optimal holdings in the underlying assets for the traderâ€™s optimal mean-variance portfolio and the amount of unhedged risk prior to maturity. Solutions assuming the cases where the price dynamics in the underlying assets follows discrete binomial price dynamics, continuous diffusions, stochastic volatility, volatility-of-volatility, and Merton-jump diffusion are derived.

Projection pursuit based generalized betas accounting for higher order co-moment effects in financial market analysis
Sven Serneels
arXiv

Betas are possibly the most frequently applied tool to analyze how securities relate to the market. While in very widespread use, betas only express dynamics derived from second moment statistics. Financial returns data often deviate from normal assumptions in the sense that they have significant third and fourth order moments and contain outliers. This paper targets to introduce a way to calculate generalized betas that also account for higher order moment effects, while maintaining the conceptual simplicity and interpretability of betas. Thereunto, the co-moment analysis projection index (CAPI) is introduced. When applied as a projection index in the projection pursuit (PP) framework, generalized betas are obtained as the directions optimizing the CAPI objective. A version of CAPI based on trimmed means is introduced as well, which is more stable in the presence of outliers. Simulation results underpin the statistical properties of all projections and a small, yet highly illustrative example is presented.

Quantifying horizon dependence of asset prices: a cluster entropy approach
L.Ponta,A. Carbone
arXiv

Market dynamic is studied by quantifying the dependence of the entropy $S(\tau,n)$ of the clusters formed by the series of the prices $p_t$ and its moving average $\widetilde{p}_{t,n}$ on temporal horizon $M$. We report results of the analysis performed on high-frequency data of the Nasdaq Composite, Dow Jones Industrial Avg and Standard \& Poor 500 indexes downloaded from the Bloomberg terminal www.bloomberg.com/professional. Both raw and sampled data series have been analysed for a broad range of horizons $M$, varying from one to twelve months over the year 2018. A systematic dependence of the cluster entropy function $S(\tau,n)$ on the horizon $M$ has been evidenced in the analysed assets. Hence, the cluster entropy function is integrated over the cluster $\tau$ to yield a synthetic indicator of price evolution: the \emph{Market Dynamic Index} $I(M,n)$. Moreover, the \emph{Market Horizon Dependence} defined as $H(M,n)=I(M,n)-I(1,n)$ is calculated and compared with the values of the horizon dependence of the pricing kernel with different representative agent models obtained by a Kullback-Leibler entropy approach.

Testing Market Efficiency With the Pricing Kernel
SSRN
Market efficiency and the pricing kernel are closely related. A non-monotonic decreasing pricing kernel implies the existence of a trading strategy in contingent claims that stochastically dominates a direct investment in the market. Moreover, a market is assumed to be efficient only if no dominating strategies exist. Empirically, many studies of the pricing kernel find non-monotonicity, apparently ruling out market efficiency. However, these results are often unreliable, because the pricing measures of the pricing kernel are estimated using differing filtration sets. We show this effect both theoretically and empirically, and we discuss recent approaches in the literature for achieving more reliable estimates of the pricing kernel, potentially leading to better tests of market efficiency.

The Cost-Efficiency and Productivity Growth of Euro Area Banks
Huljak, Ivan,Martin, Reiner,Moccero, Diego
SSRN
We use an industrial organisation approach to quantify the size of Total Factor Productivity Growth (TFPG) for euro area banks after the crisis and decompose it into its main driving factors. In addition, we disentangle permanent and time-varying inefficiency in the banking sector. This is important because lack of distinction may lead to biased estimates of inefficiency and because the set of policies needed in both cases is different. We focus on 17 euro area countries over the period 2006 to 2017. We find that cost efficiency in the euro area banking sector amounted to around 84% on average over the 2006 to 2017 period. In addition, we observe that Total Factor Productivity growth for the median euro area bank decreased from around 2% in 2007 to around 1% in 2017, with technological progress being the largest contributor, followed by technical efficiency. Given the need to boost productivity and enhance profitability in the euro area banking sector, these findings suggests that bankâ€™s efforts in areas such as rationalisation of branches, digitalisation of business processes and possibly mergers and acquisitions should be intensified.

Time-Series and Cross-Sectional Stock Return Forecasting: New Machine Learning Methods
Rapach, David,Zhou, Guofu
SSRN
This paper extends the machine learning methods developed in Han et al. (2019) for forecasting cross-sectional stock returns to a time-series context. The methods use the elastic net to refine the simple combination return forecast from Rapach et al. (2010). In a time-series application focused on forecasting the US market excess return using a large number of potential predictors, we find that the elastic net refinement substantively improves the simple combination forecast, thereby providing one of the best market excess return forecasts to date. We also discuss the cross-sectional return forecasts developed in Han et al. (2019), highlighting how machine learning methods can be used to improve combination forecasts in both the time-series and cross-sectional dimensions. Overall, because many important questions in finance are related to time-series or cross-sectional return forecasts, the machine learning methods discussed in this paper should provide valuable tools to researchers and practitioners alike.

Time-Varying Background Risk Over the Great Recession