Research articles for the 2020-04-02
arXiv
We study how the quality dimension affects the social optimum in a model of spatial differentiation where two facilities provide a public service. If quality enters linearly in the individuals' utility function, a symmetric configuration, in which both facilities have the same quality and serve groups of individuals of the same size, does not maximize the social welfare. This is a surprising result as all individuals are symmetrically identical having the same quality valuation. We also show that a symmetric configuration of facilities may maximize the social welfare if the individuals' marginal utility of quality is decreasing.
SSRN
The phenomenon of “raiding,†i.e., the unlawful establishment of control over the property or governing boards of an enterprise, as well as the seizure of its shares, has been reported in all countries of the world for many decades. This phenomenon has the most dangerous forms in the states with the underdeveloped economy and legal system, particularly in Ukraine. The paper aims to determine the areas for counteracting and overcoming corporate raiding in Ukraine and to provide proposals for improving the legislative framework for reliable protection against attacks on the enterprises’ property.The information in the paper, including the geography of raider attacks, indicates a greater vulnerability of enterprises in the most economically developed regions, with extensive transport infrastructure and the prospects for various industries and sectors of the economy development. The state should take some steps to increase the level of enterprises protection against raider attacks. Thus, to improve the quality of preventing and combating corporate raiding, this paper argues the need to develop and adopt the Corporate Property Protection Code of Ukraine. The introduction of the raider attacks register will be an effective measure to warn potential investors and counterparties about the dangers of cooperation with certain companies. The state register should be bilingual (Ukrainian and English) and contain information on the attempts and cases of raider attacks on property and corporate business rights. Also for further innovations in starting a business, Ukraine must pay attention to New Zealand’s and Finland’s experience.
SSRN
We study how analysts’ cultural attitudes to time orientation affect their production of long-term earnings forecasts, the profitability of their stock recommendations, and managerial myopia for the firms they cover. We find that analysts from a long-term oriented culture produce more long-term earnings forecasts, issue more timely long-term forecasts and more profitable stock recommendations. These results are more pronounced among firms with more long-term investments, for smaller firms, and during periods of higher economic uncertainty. Exploring the quasi-natural experiments of brokerage houses’ mergers and closures, we find a positive and plausibly causal effect of the coverage by long-term oriented analysts on firm innovation. Contrary to extant research finding that analysts’ coverage in general fosters managerial myopia, our paper shows that the coverage of long-term oriented analysts ameliorates managerial myopia.
SSRN
Policymakers have minimized the role of bankruptcy law in mitigating the financial fallout from COVID-19. Scholars too are unsure about the merits of bankruptcy, especially Chapter 11, in resolving business distress. We argue that Chapter 11 complements current stimulus policies for large corporations, such as the airlines, and that Treasury should consider making it a precondition for receiving government-backed financing. Chapter 11 offers a flexible, speedy, and crisis-tested tool for preserving businesses, financing them with government funds (if necessary), and ensuring that the costs of distress are borne primarily by investors, not taxpayers. Chapter 11 saves businesses and employment, not shareholders. For consumers and small businesses, however, bankruptcy should serve as a backstop to other policies, such as the CARES Act. Consumer bankruptcy law’s primary goal is to discharge debts, but that’s not what most consumers need right now. What they need is bridge financing, and perhaps forbearance, until the crisis ends, they get back to work, and they regain their ability to pay their debts again. These key policy leversâ€"bridge financing and forbearanceâ€"are available in theory to small businesses in Chapter 11, especially if the government supplies the bridge financing when credit markets are dysfunctional. The practical reality is that bankruptcy is expensive for small businesses, which may deter them from using it in the first place. Equally important, our courts will be flooded if Chapter 11 is the primary rescue policy for small businesses.
SSRN
We propose the bear beta, i.e. the sensitivity of hedge funds to a bear spread portfolio orthogonalized to the market, as a novel way of classifying funds as insurance buyers or sellers. We find that low bear beta funds (insurance sellers) outperform high bear beta funds (insurance buyers) by 0.58% per month on average. The negative relation between bear beta and future hedge fund returns is not subsumed by a large set of fund characteristics and risk exposures. Consistent with a risk-based explanation, this relation remains negative during market crashes but turns positive during periods of increasing bear market concerns.
SSRN
Relative to mutual funds, the innovative features of ETFs attract high liquidity demand investors who engage in positive feedback strategies and transmit selling pressure to the underlying via near proportional trading. In a turmoil period we find evidence that ETFs destabilize the systemically important corporate bond market, but no such evidence is found for mutual funds. Comparing two bonds from the same issuer, we find that the yield spread of bonds with greater ETF selling pressure increases temporarily. Arbitrage activity through in-kind redemptions in the largest most liquid ETFs propagates ETF selling pressure from the exchange to the underlying bonds.
SSRN
This paper examines cyclical behavior of banks’ systemic risk contribution and exposure. Using an unbalanced panel of 787 banks from countries members of the Organisation for Economic Co-operation and Development and the European Union covering the period 2000:Q1-2017:Q4, we document that both systemic risk contribution and exposure are positively related to business cycle. That is, systemic risk starts to accumulate in the financial sector during periods of boom, i.e., when the output gap is positive. Furthermore, during periods of robust economic growth, the level of credit tends to increase dramatically, going hand in hand with asset and property prices developments. We also find that contribution and exposure to system-wide distress move procyclically during credit and house cycles, meaning that during upturns in credit and house cycles bank interconnectedness increases, but tend to fall during downturns. However, individual risk of the banks, proxied by Value at Risk, evolves countercyclically during business and financial cycles, i.e., decreasing in upturns and raising in downturns. Thus, Value at Risk is not a good proxy for signalling the buit-up of financial imbalances. Dynamic conditional beta, however, is a more appropriate measure to quantify individual risk of the banks in relation with the market, being procyclical during the financial cycle. Additionally, the empirical analysis shows that both bank-specific and macroeconomic factors influence banks’ systemic distress. Particularly, size, credit risk and inflation boost systemic risk contribution and exposure of the banks, whereas capitalization, the share of loans in total assets, the share of non-interest income in total revenue and economic freedom help banks in reducing their systemic importance. The findings remain robust after controlling for nesting, cross-sectional dependence and reverse causality issues.
SSRN
Harvey (2017) and The American Statistical Association (2016) point out that business decisions should not be based only on whether the p-value of an empirical model passes a specific threshold and that statistical significance (p-value) cannot measure the size of an effect or the importance of a result. In other words, for economic problems economic significance is required and an economic model evaluation criterion is desirable.This paper derives a criterion for economic significance of valuation differences between empirical models and shows empirically that nearly all empirical models applied in business valuation are dis-similar, i.e., result in economically significant valuation differences. Motivated by the degree of dis-similarity between empirical models, an economic model evaluation criterion is developed. It judges the implicit economic assumptions revealed by computing the dual program of empirical models with the help of compliance with the economic principle and fit to institutional circumstances. Based on this economic model evaluation criterion our paper elaborates that within the group of cross-sectional price models quantile regression proves to be the best model because it is able to offer a good approximation to the economic principle and mimics best the institutional circumstances, in particular, if the regression is run without a constant. On the other hand, statistically more advanced models like generalized least squares regression deteriorates the implied economic content of models.
SSRN
Using data of households approaching retirement in the U.S., I perform quantile decompositions of the Whites’ differences in saving rates with Mexican Americans (ethnic gap) and with African Americans (racial gap). The gaps are small at the bottom half of the distribution and widen at the top, especially those resulting from changes in asset prices (passive savings). Differences in observable factors account for the entire gaps at lower quantiles, but some unexplained racial gap remains at higher quantiles. Thus, racial wealth inequality could be partly attributable to differences in the distributions of saving rates conditional on socio-economic characteristics. Income is the main contributor to the active savings gaps, and education is more important for passive savings. Including retirement assets, the racial but not the ethnic gap in total saving rates disappears. The results suggest that reducing disparities in income, education and pension savings would help to reduce wealth inequality between minorities, particularly Mexican Americans, and Whites.
arXiv
We investigate finite population games of optimal execution, taking place at a market with friction. The models over which we develop our results are akin to the standard Almgren-Chriss model with linear price impacts. On the one hand, at a temporary level, our perspective is rather similar to that of the aforementioned model. On the other hand, all players in the model will impact the asset's public price, yielding an aggregate permanent price impact. We propose to analyze two different settings. The first one comprises the case where there is no hierarchy among players, and there is a symmetry of information. In this setting, we obtain closed-form formulas to the Nash equilibrium in the most general setting, i.e., when players' preferences are completely heterogeneous. Particularizing to the case of homogeneous parameters, we show that the average optimal inventory of the finite population converges to its mean-field counterpart, uniformly over a fixed trading horizon, as the population size grows to infinity. In the second framework, we consider a major player, also called a leader, with the first move advantage, and a population of minor players, also known as followers, thought of as high-frequency traders, which trade on informational advantage against the leader. This leads to a model of McKean-Vlasov type for the dynamics of the asset's midprice. We prove the existence and uniqueness of the Stackelberg-Nash equilibrium for a reasonable set of model parameters. We also characterize it as the solution of an abstract vector forward-backward stochastic differential equation system.
SSRN
Using tools described in our earlier work (Hassan et al., 2019, 2020), we develop text-based measures of the costs, beneï¬ts, and risks listed ï¬rms in the US and over 80 other countries associate with the spread of COVID-19 and other epidemic diseases. We identify which ï¬rms expect to gain or lose from an epidemic disease and which are most affected by the associated uncertainty as a disease spreads in a region or around the world. As COVID-19 spreads globally in the ï¬rst quarter of 2020, we ï¬nd that ï¬rms’ primary concerns relate to the collapse of demand, increased uncertainty, and disruption in supply chains. Other important concerns relate to capacity reductions, closures, and employee welfare. By contrast, ï¬nancing concerns are mentioned relatively rarely. We also identify some ï¬rms that foresee opportunities in new or disrupted markets due to the spread of the disease. Finally, we ï¬nd some evidence that ï¬rms that have experience with SARS or H1N1 have more positive expectations about their ability to deal with the coronavirus outbreak.
SSRN
This article examines various conditions for optimality in financial inclusion. The optimal level of financial inclusion is achieved when basic financial services are provided to members of the population at a price that is affordable and that price is also economically sufficient to encourage providers of financial services to provide such financial services on a continual basis. Any level of financial inclusion that does not meet these conditions is sub-optimal. The consequences of sub-optimal levels of financial inclusion are reported and I show that maintaining a sub-optimal level of financial inclusion â€" which is common in many countries â€" is incentive-inefficient both for users and suppliers of basic financial services.
SSRN
We examine how wealth windfalls affect self-employment decisions using data on cash payments from claims on Texas shale drilling to people throughout the United States. Individuals who receive large wealth shocks (greater than $50,000) have 51% higher self-employment rates. The increase in self-employment rates is driven by individuals who lengthen existing self- employment spells, and not by individuals who leave regular employment for self-employment. Moreover, the effect of wealth reverts for individuals whose payments run out. Rather than alleviating a financial constraint, our evidence suggests that unrestricted cash windfalls affect self-employment decisions primarily through self-employment’s non-pecuniary benefits.
arXiv
Recent proposal of Wasserstein Index Generation model (WIG) has shown a new direction for automatically generating indices. However, it is challenging in practice to fit large datasets for two reasons. First, the Sinkhorn distance is notoriously expensive to compute and suffers from dimensionality severely. Second, it requires to compute a full $N\times N$ matrix to be fit into memory, where $N$ is the dimension of vocabulary. When the dimensionality is too large, it is even impossible to compute at all. I hereby propose a Lasso-based shrinkage method to reduce dimensionality for the vocabulary as a pre-processing step prior to fitting the WIG model. After we get the word embedding from Word2Vec model, we could cluster these high-dimensional vectors by $k$-means clustering, and pick most frequent tokens within each cluster to form the "base vocabulary". Non-base tokens are then regressed on the vectors of base token to get a transformation weight and we could thus represent the whole vocabulary by only the "base tokens". This variant, called pruned WIG (pWIG), will enable us to shrink vocabulary dimension at will but could still achieve high accuracy. I also provide a \textit{wigpy} module in Python to carry out computation in both flavor. Application to Economic Policy Uncertainty (EPU) index is showcased as comparison with existing methods of generating time-series sentiment indices.
SSRN
Research shows that Black, Latinx, and other minorities pay more for credit and banking services, and that wealth accumulation differs starkly between their households and white households. The link between debt inequality and the wealth gap, however, remains less thoroughly explored, particularly in light of new credit products and debt-like banking services, such as early wage access and other fintech innovations. These innovations both hold the promise of reducing racial and ethnic disparities in lending and bring concerns that they may be exploited in ways that perpetuate inequality. They also come at a time when policy makers are considering how to help communities of color rebuild their wealth, presenting an opportunity to critique policy proposals. This Article leverages that opportunity by synthesizing research about the long-term costs of debt inequality on communities of color, adding an in-depth analysis of several new advances in banking and lending, and evaluating proposals aimed at closing the wealth gap through the lens of targeting debt inequality.
arXiv
In most OTC markets, a small number of market makers provide liquidity to other market participants. More precisely, for a list of assets, they set prices at which they agree to buy and sell. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money while mitigating the risk associated with holding inventory in a volatile market. Many market making models have been proposed in the academic literature, most of them dealing with single-asset market making whereas market makers are usually in charge of a long list of assets. The rare models tackling multi-asset market making suffer however from the curse of dimensionality when it comes to the numerical approximation of the optimal quotes. The goal of this paper is to propose a dimensionality reduction technique to address multi-asset market making by using a factor model. Moreover, we generalize existing market making models by the addition of an important feature: the existence of different transaction sizes and the possibility for the market makers in OTC markets to answer different prices to requests with different sizes.
SSRN
We examine how social connections built up via shared past working experience or non-business activities would help formal business relationships in the product market. With a unique and comprehensive dataset incorporating social network and supply chain interactions, we find that social connections, measured by either the presence of (or the number of) manager-to-manager personal connections, predict supply chain network formation and sustainment between firms. The predictive relationship is stronger for connections between executives as well as long-standing connections, and also applies to second-degree indirect connections to a lesser extent. An identification strategy with exogenous deaths shocks to companies’ social network is adopted to establish causality. Two mechanisms, the trustworthiness and information channels, are provided to interpret our results. At last, we provide strong evidence that firms with socially connected supply chains tend to expand their size in asset and risky investment, and more importantly, benefit the focal firm in the long run, albeit a relatively lower short-run performance due to the expansions.
arXiv
Can the status hierarchy facilitate the emergence of group cooperation? In an evolutionary model, Mark (2018) provided a positive answer to the theoretical inquiry. Despite the contribution, we critiqued that there are not only mathematical errors in Mark's model but also limitations in applying it to other hierarchical structures. We present a more generalized model by introducing a novel hierarchy measure to interpolate the cooperativeness of group members in any hierarchy structure of interest. We derive the conditions under which cooperation can emerge and verify our analytical predictions by agent-based computer simulation. In general, our evolutionary model provides stronger evidence than Mark's original model with respect to how status behavior can facilitate the emergence of social cooperation.
SSRN
We describe and briefly examine the standard model for viral infection, the so-called SIR model, and its potential usage in the current situation. We furthermore extend the model to account for government interventions, and for differences in testing approaches in different countries.
SSRN
We introduce a model of bank risk-taking in the presence of liquidity risk and liquidity requirements. The model illustrates channels by which liquidity regulations can either increase or decrease a bank's incentive to take risk with its remaining illiquid assets and shows that the risk-motivating channel is more likely to dominate when the price of long-term debt is high. We then empirically estimate the effect of liquidity regulations on risk-taking. Using a regression discontinuity design, we do not find evidence that reserve requirements significantly effect risk-taking. By comparison, the liquidity coverage ratio has been associated with increased risk-taking.
SSRN
We study the impact of corporate taxes on firm-level investments, total output and input usage by exploiting a 4.5 percentage-point corporate tax rate cut in Finland in 2014. We use detailed administrative data and a differences-in-differences method comparing small corporations (tax rate cut) to similar partnerships (no change in tax incentives). We find no significant investment responses. However, we observe an increase in annual sales and variable costs, suggesting that corporate tax rates have an effect on business activity. The effects are driven by entrepreneurs who actively work in their firm, suggesting that the tax cut increased entrepreneurial effort.
SSRN
We show empirically that public credit information increases competition in credit markets. We access data that cover all credit card borrowers in Chile and include details about relationship borrowers have with each lender. We exploit a natural experiment whereby a non-bank lender’s portfolio was sold to a bank. Because of this transaction, the lender’s borrowers, who were previously not identifiable unless in default, become observable by banks through the credit bureau but remain unobservable to other non-bank lenders. Using a difference-in-differences strategy, we find that after the transaction the lender’s borrowers receive higher credit limits from other banks relative to other non-bank borrowers. This result is mediated by individuals whose predicted probability of bank default drops as a result of the change to banks’ information set. After the transaction, the lender shifts originations to safer borrowers with higher initial limits, a result that is consistent with cross-sectional evidence that banks tend to lend to safer borrowers. Our results imply that by increasing competition, public credit information can reduce lenders’ incentive to “learn by lendingâ€, potentially excluding riskier populations from access to credit.
SSRN
We use hand-collected data on corporate filings to understand the rise in corporate "cash" holdings over the past twenty years. A large share of aggregate growth is driven by marketable securities, and in recent years bond portfolios are at least as large as cash-like instruments. In particular, corporate bonds issued by other firms have outgrown sovereign bonds holdings. While not restricted to the outlier Apple, the phenomenon is driven by the largest firms: the top 20 holds 75% of aggregate financial assets in our sample. We document a reversal and portfolio shift following the recent tax reform, driven by some firms running down their bond portfolio.
SSRN
We provide the first comprehensive examination of the impact of the advisory services provided by boutique banks on acquirer returns in U.S. Mergers and Acquisitions (M&As). We show that the autonomy and expertise of boutique banks help acquirers realize significant gains in informationally demanding deals. We find that boutique banks add value to acquirers of large private companies in the short-run. Acquirers of small private companies also benefit from boutique banks, but these wealth effects are only pronounced in the post-announcement period. We attribute the delayed market response to the limited activity of information-driven traders at the time of the announcement of small private deals. We also show that resourceful acquirers recognize the valuable services offered by boutique banks and are more likely to involve them in private target deals. Lastly, we present novel evidence that boutique banks contribute to wealth creation in small public target M&As that are economically consequential for the acquirer. This result emerges only after we address endogeneity concerns by controlling for the acquirer’s quality.
SSRN
This paper adopts a versatile multivariate conditional correlation model to estimate daily seasonality in the returns, the volatility, and the correlations between stocks, bonds, gold and Bitcoin. Besides the well known seasonality in stocks and bonds, the day-of-the-week effect is also present in Bitcoin. Mondays are associated with higher Bitcoin returns, while Wednesdays with higher Bitcoin volatility. As opposed to previous literature, our results indicate strong evidence of Bitcoin’s leverage effect. Moreover, we show that daily correlations between Bitcoin and traditional assets are higher at the beginning of the week, while the volatility of these correlations decreases over the week. Our results offer interesting insights in terms of investment and portfolio diversification, that can be applied to the analysis of systematic risk asset allocation and hedging.
