# Research articles for the 2019-10-21

A Theory of Socially Responsible Investment
Oehmke, Martin,Opp, Marcus M.
SSRN
Based on a canonical model of corporate financing under agency frictions, we characterize how and when socially responsible investors can affect firm behavior and derive an investment criterion, the social profitability index (SPI), to guide scarce socially responsible capital. The SPI highlights the importance of counterfactual social costs that would arise in the absence of socially responsible investors. Accordingly, most existing ESG metrics are not suited to guide investment decisions. Our model also uncovers a complementarity between financial capital and socially responsible capital: The presence of financial investors without regard for externalities can raise welfare relative to a setting with only socially responsible investors.

Alpha, Beta and the Endowment Model
Karris, Michael
SSRN
Alpha, or outperformance of a benchmark, can be generated in many ways within a portfolio. It can be created by picking the top hedge fund managers, or by capturing the illiquidity premium via alternative assets. Venture capital is a major source of alpha for long-term investors. Alpha can also be achieved by active asset allocation using both tactical and strategic beta tilts.For the top endowments, these and other innovative portfolio decisions have created great, long-term alpha versus a global balanced benchmark with 70% stocks / 30% bonds. Since asset allocation plays a large role in determining portfolio returns, it is interesting to compare how beta (or index fund) portfolios have compared historically versus sophisticated institutional portfolios. We compare 3 decades of performance: the 10 year period before the Internet Bubbleâ€™s peak (FY1988-1998), the 10 years including fiscal year 2000â€™s spectacular gains (FY1998-2008), and a more recent period (FY2008-2018).The Endowment Model will no doubt continue to help colleges to fulfill their missions, and enable public pensions to meet their retirement obligations. However, for some investors, over-diversification can dilute manager alpha and lead to performance that is similar to beta portfolios. Given its complexity, the Endowment Model is not a one-size-fits-all strategy, and is best suited for larger investment teams with considerable resources. For those institutions constrained by limited resources, using a balance of alternative assets and beta could achieve the best of both worlds. For instance, mid-sized investors might be better served by streamlining their portfolios with a liquid beta core, coupled with satellite alternative assets. And smaller investors could only use index fund portfolios and still achieve alpha. An index fund portfolio may be no substitute for a world-class endowment fund, but it could be an ideal investment solution for some long-term investors.

Beating the House: Identifying Inefficiencies in Sports Betting Markets
Sathya Ramesh,Ragib Mostofa,Marco Bornstein,John Dobelman
arXiv

Inefficient markets allow investors to consistently outperform the market. To demonstrate that inefficiencies exist in sports betting markets, we created a betting algorithm that generates above market returns for the NFL, NBA, NCAAF, NCAAB, and WNBA betting markets. To formulate our betting strategy, we collected and examined a novel dataset of bets, and created a non-parametric win probability model to find positive expected value situations. As the United States Supreme Court has recently repealed the federal ban on sports betting, research on sports betting markets is increasingly relevant for the growing sports betting industry.

Chinaâ€™s Rise as a Global Power
Peetz, Dietmar
SSRN
China has created an economic miracle since its economic reforms began in the late 1970s, becoming the fastest growing economy in the world. The tremendous success of Chinaâ€™s economy has attracted worldwide attention. But at the same time, it has raised concerns as the countryâ€™s enormous debt overhand and outsized shadow banking system is weighing on its economy. Could the end of the China miracle be near or is China on track to become the dominating global superpower? This paper explores from a historical perspective the success factors of the Chinese miracle since the communist revolution and examines the economic and geopolitical implications that would be triggered by the elimination of the factors. We conclude that despite all current economic and social problems, China has all the prerequisites to become the new world hegemon in the coming years.

Consensus Analyst Target Prices: Information Content and Implications for Investors
Palley, Asa,Steffen, Thomas D.,Zhang, Frank
SSRN
Consensus analyst target prices are widely available online at no cost to investors. In this paper we consider whether these consensus target prices are informative for predicting future returns. We find that when considered in isolation, consensus target prices are not generally informative about future returns. However, we find that the dispersion of individual analystsâ€™ target prices that comprise the consensus is an important moderating factor. When dispersion is low (high), there is a strong positive (negative) correlation between predicted returns based on the consensus target price and future realized returns. Further analyses suggest that this phenomenon is partially due to consensus target prices being slow to reflect bad news. In addition, we show that the negative correlation between consensus-based predicted returns and future realized returns for high-dispersion stocks exists only for stocks with high short interest or low institutional ownership, suggesting that limits to arbitrage play a role in the observed mispricing and that unsophisticated investors are negatively impacted by high consensus target prices.

Conservation Laws in a Limit Order Book
Jan Rosenzweig
arXiv

We present a class of macroscopic models of the Limit Order Book to simulate the aggregate behaviour of market makers in response to trading flows. The resulting models are solved numerically and asymptotically, and a class of similarity solutions linked to order book formation and recovery is explored. The main result is that order book recovery from aggressive liquidity taking follows a simple $t^{1/3}$ scaling law.

Consumption in the Great Recession: The Financial Distress Channel
Athreya, Kartik,Mather, Ryan,Mustre-del-Rio, Jose,M. SÃ¡nchez CÃ©spedes, Juan
SSRN
During the Great Recession, the collapse of consumption across the U.S. varied greatly but systematically with house-price declines. We find that financial distress among U.S. households amplified the sensitivity of consumption to house-price shocks. We uncover two essential facts: (1) the decline in house prices led to an increase in household financial distress prior to the decline in income during the recession, and (2) at the zip-code level, the prevalence of financial distress prior to the recession was positively correlated with house-price declines at the onset of the recession. Using a rich-estimated-dynamic model to measure the financial distress channel, we find that these two facts amplify the aggregate drop in consumption by 7 percent and 45 percent respectively.

CorrGAN: Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks
Gautier Marti
arXiv

We propose a novel approach for sampling realistic financial correlation matrices. This approach is based on generative adversarial networks. Experiments demonstrate that generative adversarial networks are able to recover most of the known stylized facts about empirical correlation matrices estimated on asset returns. This is the first time such results are documented in the literature. Practical financial applications range from trading strategies enhancement to risk and portfolio stress testing. Such generative models can also help ground empirical finance deeper into science by allowing for falsifiability of statements and more objective comparison of empirical methods.

Earnings Quality and Book-to-Market in the Cross Section of Expected Returns
Athanasakou, Vasiliki E.,Athanassakos, George
SSRN
The purpose of this paper is to examine whether earnings quality contributes to the book-to- marketâ€™s predictive power in the cross section of stock returns. Earnings quality is embedded in the value-growth effect given that retained earnings is a key part of the book value of equity. Earnings quality reflects the effects of managerial discretion on reported earnings, which has been shown to be associated with both risk and behavioral biases in asset pricing. Our results affirm the existence of a value premium and show that the value premium is more pronounced within poor earnings quality stocks. Moreover, we find that poor earnings quality contributes to the value premium mainly through the pricing of growth stocks. Our results suggest that the quality of reported earnings has an incremental role in shaping expected returns of value versus growth stocks.

Econoquantumphysics and econonetwork: do correlations and eigenstates shape the taxonomy of the cryptocurrency market?
Carlo Requião da Cunha,Roberto da Silva
arXiv

We investigate 17 digital currencies making an analogy with quantum systems and develop the concept of eigenportfolios. We show that the density of states of the correlation matrix of these assets shows a behavior between that of the Wishart ensemble and one whose elements are Cauchy distributed. A metric for the participation matrix based on superposition of Gaussian functions is proposed and we show that small eigenvalues correspond to localized states. Nonetheless, some level of localization is also present for bigger eigenvalues probably caused by the fat tails of the distribution of returns of these assets. We also show through a clustering study that the digital currencies tend to stagger together. We conclude the paper showing that this correlation structure leads to an Epps effect.

Eignung von Varianz-Kovarianz-AnsÃ¤tzen und Copula-Modellen zur Risikoaggregation in bankaufsichtlichen RisikotragfÃ¤higkeitskonzepten (How Adequate Are Covariance and Copula Based Approaches of Risk Aggregation?)
Graalmann, Marc-Philip,Lehrbass, Frank
SSRN
German Abstract: Mit einer Simulationsstudie zeigen wir, dass die Skepsis der Aufsicht hinsichtlich der Anerkennung von Diversifikationseffekten berechtigt scheint.English Abstract: We run a simulation study to check whether the scepticism of regulators to accept diversification benefits is well-founded. Our findings are confirmatory.

Entropic Dynamic Time Warping Kernels for Co-evolving Financial Time Series Analysis
Lu Bai,Lixin Cui,Lixiang Xu,Yue Wang,Zhihong Zhang,Edwin R. Hancock
arXiv

In this work, we develop a novel framework to measure the similarity between dynamic financial networks, i.e., time-varying financial networks. Particularly, we explore whether the proposed similarity measure can be employed to understand the structural evolution of the financial networks with time. For a set of time-varying financial networks with each vertex representing the individual time series of a different stock and each edge between a pair of time series representing the absolute value of their Pearson correlation, our start point is to compute the commute time matrix associated with the weighted adjacency matrix of the network structures, where each element of the matrix can be seen as the enhanced correlation value between pairwise stocks. For each network, we show how the commute time matrix allows us to identify a reliable set of dominant correlated time series as well as an associated dominant probability distribution of the stock belonging to this set. Furthermore, we represent each original network as a discrete dominant Shannon entropy time series computed from the dominant probability distribution. With the dominant entropy time series for each pair of financial networks to hand, we develop a similarity measure based on the classical dynamic time warping framework, for analyzing the financial time-varying networks. We show that the proposed similarity measure is positive definite and thus corresponds to a kernel measure on graphs. The proposed kernel bridges the gap between graph kernels and the classical dynamic time warping framework for multiple financial time series analysis. Experiments on time-varying networks extracted through New York Stock Exchange (NYSE) database demonstrate the effectiveness of the proposed approach.

Hierarchical PCA and Applications to Portfolio Management
Avellaneda, Marco
SSRN
It is widely known that the common risk-factors derived from PCA beyond the first eigenportfolio are generally difficult to interpret and thus to use in practical portfolio management. We explore a alternative approach (HPCA) which makes strong use of the partition of the market into sectors. We show that this approach leads to no loss of information with respect to PCA in the case of equities (constituents of the S&P 500) and also that the associated common factors admit simple interpretations. The model can also be used in markets in which the sectors have asynchronous price information, such as single-name credit default swaps, generalizing the works of Cont and Kan (2011) and Ivanov (2016).

Investmentstrategien im Rahmen von Ãœbernahmen bÃ¶rsennotierter Gesellschaften â€" Merger Arbitrage und Maschinelles Lernen (Merger Arbitrage and Machine Learning)
Lehrbass, Frank,Raasch, Alexander
SSRN
German Abstract: Wir stellen verschiedene Investmentstrategien rund um M&A vor. Cash Merger Arbitrage und Stock Merger Arbitrage werden behandelt als auch die Wette auf Compensation Schemes. Zudem untersuchen wir empirisch, ob der Erfolg von M&A mit Ã¶konometrischen Methoden und maschinellem Lernen vorhergesagt werden kann.English Abstract: We introduce various investment strategies related to M&A situations, explain their risks and returns. Cash Merger Arbitrage and Stock Merger Arbitrage are explored as well as betting on Compensation Schemes. Also, we investigate empirically whether the binary variable success/failure of an attempted M&A deal can be forecasted using classical econometrics and machine learning.

Loss or Lost? Economic Consequences of Internal Capital Markets in Business Groups
Olbert, Marcel
SSRN
Business groups can make use of internal capital markets to support financially distressed member firms. Such resource sharing can circumvent credit-risk spillovers and operational disruptions but may come at the cost of inefficient resource allocation. This paper examines when business groups support distressed member firms and how such group support impacts firm survival and productivity. I exploit plausibly exogenous variation in the value of loss-related tax shields that affect the incentives to support distressed member firms. Evidence from a cross-sectional difference-in-differences design based on a large international sample, as well as a single-country regression discontinuity design, suggests that business groups avoid member firms' defaults if loss-related tax shields are more valuable. Further, I document that such tax-motivated group support leads to lower productivity: business groups keep low-quality member firms alive, plausibly causing inefficient resource allocation at the firm and the market level.

Lot Layering: The New Frontier for Hedge Fund Partnership Allocations
Sosner, Nathan,Balzafiore, Philip
SSRN
Lot layering may help hedge funds improve the alignment between tax outcomes and the economic experience of their investors. Although lot layering is considered by most tax experts to be the most precise method of partnership allocations, this commonly understood precision is reduced upon redemptions due to the cumbersome and uneconomic basis adjustment method stipulated by Treasury regulations. We propose that changes be made to the current regulations that could remedy this problem. Despite its unavoidable deficiency caused by the basis adjustment requirements under the current regulations, we believe that lot layering aligns tax and economics more closely than do any of the â€œaggregationâ€ methods presently used by most hedge funds.

Multiscale Analysis of Bayesian Cart
Castillo, Ismael,Rockova, Veronika
SSRN
This paper affords new insights about Bayesian CART in the context of structured wavelet shrinkage. We show that practically used Bayesian CART priors lead to adaptive rate-minimax posterior concentration in the supremum norm in Gaussian white noise, performing optimally up to a logarithmic factor. To further explore the benefits of structured shrinkage, we propose the g-prior for trees, which departs from the typical wavelet product priors by harnessing correlation induced by the tree topology. Building on supremum norm adaptation, an adaptive non-parametric Bernsteinâ€"von Mises theorem for Bayesian CART is derived using multi- scale techniques. For the fundamental goal of uncertainty quantification, we construct adaptive confidence bands with uniform coverage for the regression function under self-similarity.

Nonhedgeable risk and Credit Risk Pricing
Juan Dong,Lyudmila Korobenko,Deniz Sezer
arXiv

We introduce a new model for pricing corporate bonds, which is a modification of the classical model of Merton. In this new model, we drop the liquidity assumption of the firm's asset value process, and assume that there is a liquidly traded asset in the market whose value is correlated with the firm's asset value, and all portfolios can be constructed using solely this asset and the money market account. We formulate the market price of the corporate bond as the product of the price of an optimal replicating portfolio and exp(- kappa x replication error), where kappa is a positive constant. The interpretation is that the representative investor accepts the price of the optimal replicating portfolio as a benchmark, however, requests compensation for the non-hedgeable risk. We show that if the replication error is measured relative to the firm's value, the resulting formula is arbitrage free with mild restrictions on the parameters.

Online Appendix for 'Measuring the 'Dark Matter' in Asset Pricing Models'
Chen, Hui,Dou, Winston,Kogan, Leonid
SSRN
This is the supplemental material to the paper titled "Measuring 'Dark Matter' in Asset Pricing Models." It includes detailed derivations, as well as additional empirical and theoretical results.

PENEGAKAN ATURAN HUKUM (Rule of the Law)
Sujono, Imam
SSRN
Indonesian Abstract: Dalam kehidupan sehari-hari, kita tidak terlepas dari hukum, mulai dari norma, nilai, tata dan krama hingga hukum perundang-undangan dalam peradilan. Sayangnya hukum di Negara Indonesia masih kurang dalam penegakannya, terutama penegakan aturan hukum di kalangan pejabat-pejabat dibandingkandengan penegakan hukum di kalangan menegah ke bawah. Hal ini terjadi karena di Negara kita hukum dapat dibeli dengan uang. Siapa yang memiliki kekuasaan, dia yang memenangkan peradilan. Namun bukan hanya pelaku tindak pidana saja yang melakukan kecurangan demikian, bahkan aparat penegak hukum yang seharusnya mengemban amanah untuk menegakkan hukum dan keadilan melakukan tindakan yang sama.English Abstract: In everyday life, we are inseparable from the law, ranging from norms, values, manners and etiquette to the laws and regulations in the judiciary. Unfortunately the law in the State of Indonesia is still lacking in its enforcement, especially the enforcement of the rule of law among officials compared to law enforcement in the middle and lower classes. This happens because in our country the law can be bought with money. Who has power, he who wins justice. But it is not only the perpetrators of criminal acts who commit such fraud, even law enforcement officials who should carry out the mandate to enforce the law and justice to do the same.

Robustness of Delta hedging in a jump-diffusion model
arXiv

Suppose an investor aims at Delta hedging a European contingent claim $h(S(T))$ in a jump-diffusion model, but incorrectly specifies the stock price's volatility and jump sensitivity, so that any hedging strategy is calculated under a misspecified model. When does the erroneously computed strategy super-replicate the true claim in an appropriate sense? If the misspecified volatility and jump sensitivity dominate the true ones, we show that following the misspecified Delta strategy does super-replicate $h(S(T))$ in expectation among a wide collection of models. We also show that if a robust pricing operator with a whole class of models is used, the corresponding hedge is dominating the contingent claim under each model in expectation. Our results rely on proving stochastic flow properties of the jump-diffusion and the convexity of the value function. In the pure Poisson case, we establish that an overestimation of the jump sensitivity results in an almost sure one-sided hedge. Moreover, in general the misspecified price of the option dominates the true one if the volatility and the jump sensitivity are overestimated.

Sector Neutral Portfolios: Long memory motifs persistence in market structure dynamics
Jeremy Turiel,Tomaso Aste
arXiv

We study soft persistence (existence in subsequent temporal layers of motifs from the initial layer) of motif structures in Triangulated Maximally Filtered Graphs (TMFG) generated from time-varying Kendall correlation matrices computed from stock prices log-returns over rolling windows with exponential smoothing. We observe long-memory processes in these structures in the form of power law decays in the number of persistent motifs. The decays then transition to a plateau regime with a power-law decay with smaller exponent. We demonstrate that identifying persistent motifs allows for forecasting and applications to portfolio diversification. Balanced portfolios are often constructed from the analysis of historic correlations, however not all past correlations are persistently reflected into the future. Sector neutrality has also been a central theme in portfolio diversification and systemic risk. We present an unsupervised technique to identify persistently correlated sets of stocks. These are empirically found to identify sectors driven by strong fundamentals. Applications of these findings are tested in two distinct ways on four different markets, resulting in significant reduction in portfolio volatility. A persistence-based measure for portfolio allocation is proposed and shown to outperform volatility weighting when tested out of sample.

Singular Perturbation Expansion for Utility Maximization with Order-$\epsilon$ Quadratic Transaction Costs
Andrew Papanicolaou,Shiva Chandra
arXiv

We present an expansion for portfolio optimization in the presence of small, instantaneous, quadratic transaction costs. Specifically, the magnitude of transaction costs has a coefficient that is of the order $\epsilon$ small, which leads to the optimization problem having an asymptotically-singular Hamilton-Jacobi-Bellman equation whose solution can be expanded in powers of $\sqrt\epsilon$. In this paper we derive explicit formulae for the first two terms of this expansion. Analysis and simulation are provided to show the behavior of this approximating solution.

Solving the Reswitching Paradox in the Sraffian Theory of Capital
Carlo Milana
arXiv

The possibility of re-switching of techniques in Piero Sraffa's intersectoral model, namely the returning capital-intensive techniques with monotonic changes in the profit rate, is traditionally considered as a paradox putting at stake the viability of the neoclassical theory of production. It is argued here that this phenomenon can be rationalized within the neoclassical paradigm. Sectoral interdependencies can give rise to non-monotonic effects of progressive variations in income distribution on relative prices. The re-switching of techniques is, therefore, the result of cost-minimizing technical choices facing returning ranks of relative input prices in full consistency with the neoclassical perspective.

Stock Market Reactions and CSR Disclosure in the Context of Negative CSR Events
Hummel, Katrin,Mittelbach-Hoermanseder, Stephanie,Rammerstorfer, Margarethe,Weinmayer, Karl
SSRN
This paper analyses stock market reactions after the occurrence of major negative corporate social responsibility (CSR) events and the possibility of mitigating these effects through the upfront provision of CSR information in firmsâ€™ annual reports. For this purpose, we follow a three-step procedure. First, we analyse the major concerns gathered from REPRiskÂ® data via event study analysis. Herein, we cover a window of 5 to 20 days. Second, we analyse all annual reports of the firms mentioned in the covered period over the entire time horizon and conduct a textual analysis to examine firmsâ€™ disclosure of CSR information. Finally, we draw conclusions from the two approaches and show that firms with more upfront CSR information suffer from stronger negative market reactions after the occurrence of a negative CSR event. Herein, we show that if the occurrence of a negative CSR event conflicts with investorsâ€™ expectations, then it leads to an important update of investorsâ€™ beliefs about firmsâ€™ prospects. Our results also confirm that such an event leads to an adjustment of the subsequent yearâ€™s CSR disclosure in the annual reports.

The Cobb-Douglas production function revisited
Roman G. Smirnov,Kunpeng Wang
arXiv

Charles Cobb and Paul Douglas in 1928 used data from the US manufacturing sector for 1899-1922 to introduce what is known today as the Cobb-Douglas production function that has been widely used in economic theory for decades. We employ the R programming language to fit the formulas for the parameters of the Cobb-Douglas production function generated by the authors recently via the bi-Hamiltonian approach to the same data set utilized by Cobb and Douglas. We conclude that the formulas for the output elasticities and total factor productivity are compatible with the original 1928 data.

The FIMA NFIPâ€™s Redacted Policies and Redacted Claims Data Sets
Dombrowski, Timothy,Ratnadiwakara, Dimuthu,Slawson, Jr., V. Carlos
SSRN
The National Flood Insurance Program (NFIP) was created in 1968 and allows homeowners, renters, and businesses to purchase flood insurance from the federal government. During the summer of 2019, without compromising privacy, the Federal Emergency Management Agency (FEMA) released a dataset containing nearly 50 million observations. Researchers can now download and evaluate the 47,271,207 flood policy observations (2009-2018) and the 2,418,007 flood claims observations (1970-2019) in an easily accessible machine-readable format, bypassing the complex request procedures of the past. What exactly is included in this policy and claims data? How can it be used? We provide real estate academics and industry professionals with the details of 43 policy data variables and the 36 claims data variables, which we group into seven categories: Locational, Structural, Occupancy, Policy Terms, Elevation and Ratings, Premiums, and Claims. In an effort to aid researchers with the complexities of working with the data, we provide sample R-code that can be used and altered to analyze NFIP data. Finally, for illustration, we merge the NFIP Data with data from both the American Community Survey and Zillow to study the determinants of flood insurance take-up.

The Stock Market and Discrimination in Mortgage Lending
Chu, Yongqiang,, Flora,Zhang, Tim (Teng)
SSRN
This paper examines how the stock market affects discrimination in mortgage lending. Comparing banks that went public through initial public offering or acquisition with similar banks that failed to go public, we find that mortgage denial rates for minority applicants decrease after a bank goes public. We find that the results are not driven by banks' changing risk preferences. Rather, the results are driven by the attenuation of ideological bias.

Trickle-Down Overconfidence: The Impact of Customer Overconfidence on Supplier Firms
Nelson, Aaron,Schwartz, Andrew
SSRN
Economic research has long focused on how individual behavioral biases can create spillover effects. In this paper, we consider why CEO overconfidence impacts other firms in the supply chain. Using data on supplier-customer relationships, we examine how suppliers respond to overconfident customers. We find that suppliers to overconfident customers increase their relationship-specific investment compared to suppliers paired with non-overconfident customers. The effect, however, is attenuated when the customer firms exhibit high-levels of riskiness. We further find no evidence that suppliers become overconfident themselves in response to overconfident customers. These results suggest that increases in supplier investment are not driven by overconfidence spilling over to suppliers. Instead, it appears that increases in supplier investment are driven by a rational response to an expected increase in demand from overconfident customers.

Venture Capital Investment Cycles: The Impact of Public Markets
Gompers, Paul A.,Kovner, Anna,Lerner, Josh,Scharfstein, David S.
SSRN
It is well documented that the venture capital industry is highly volatile and that much of this volatility is associated with shifting valuations and activity in public equity markets. This paper examines how changes in public market signals affected venture capital investing between 1975 and 1998. We find that venture capitalists with the most industry experience increase their investments the most when public market signals become more favorable. Their reaction to an increase is greater than the reaction of venture capital organizations with relatively little industry experience and those with considerable experience but in other industries. The increase in investment rates does not affect the success of these transactions adversely to a significant extent. These findings are consistent with the view that venture capitalists rationally respond to attractive investment opportunities signaled by public market shifts.