# Research articles for the 2020-09-30

An Artificial Intelligence Approach to the Valuation of American-style Derivatives: A Use of Particle Swarm Optimization
Chen, Ren-Raw
SSRN
In this paper, we evaluate American-style, path-dependent derivatives with an artificial intelligence technique. Specifically we use swarm intelligence to find the optimal exercise boundary for an American-style derivative. Swarm intelligence is particularly efficient (computation and accuracy) in solving high-dimensional optimization problems and hence perfectly suitable for valuing complex American-style derivatives (e.g. multiple-asset, path-dependent) which require a high-dimensional optimal exercise boundary.

An Assessment of the Competitive Effects of the Proposed Merger of the New York Stock Exchange and the Nasdaq Stock Market
Brunell, Robert
SSRN
In March of 2000 the New York Stock Exchange proposed a merger with The Nasdaq Stock Market. Applying a qualitative assessment to the proposed merger from the organizations' perspective it is argued that the merger would be favorable for both organizations. Applying a quantitative assessment to the proposed merger from an antitrust perspective it is shown that the merger should be disallowed by federal antitrust regulators if the industry is to be treated as any ordinary industry.

Analysis of the Global Energy Industry, Climate Change and Financial Matters: The Need for Effective Corporate Governance
Broker, Todd,Durr, David,Smith, Murphy
SSRN
Energy companies provide critical economic resources for advanced societies. Yet, critics complain about climate change and excess profits. A plethora of research offers ample evidence, from scientific and policy experts, that climate change is not a significant problem, whether human-caused or otherwise. For example, Richard Lindzen, the Alfred P. Sloan Professor of Meteorology at MIT from 1983 to 2013, called â€œglobal warmingâ€ proponents discredited alarmists. Financial analysis shows energy companies are less profitable than those in other industries. Findings of this study are meaningful to academic researchers and corporate leaders, particularly if concerned with corporate governance of energy companies. Energy company managers would do well to inform the public, government leaders, and policy makers about the unfair charges of environmental harm and excess profitability, and assert the positive contributions of energy companies to the world economy.

Are cryptocurrencies becoming more interconnected?
Nektarios Aslanidis,Aurelio F. Bariviera,Alejandro Perez-Laborda
arXiv

This paper studies the dynamic market linkages among cryptocurrencies during August 2015 - July 2020 and finds a substantial increase in market linkages for both returns and volatilities. We use different methodologies to check the different aspects of market linkages. Financial and regulatory implications are discussed.

Artificial Intelligence and High-Skilled Work: Evidence from Analysts
Grennan, Jillian,Michaely, Roni
SSRN
Policymakers fear artificial intelligence (AI) will disrupt labor markets, especially for high-skilled workers. We investigate this concern using novel, task-specific data for security analysts. Exploiting variation in AI's power across stocks, we show analysts with portfolios that are more exposed to AI are more likely to reallocate efforts to soft skills, shift coverage towards low AI stocks, and even leave the profession. Analyst departures disproportionately occur among highly accurate analysts, leaving for non-research jobs. Reallocating efforts toward tasks that rely on social skills improve consensus forecasts. However, increased exposure to AI reduces the novelty in analysts' research which reduces compensation.

Bank Stock Performance During the COVID-19 Crisis: Does Efficiency Explain Why Islamic Banks Fared Relatively Better?
SSRN
In this paper, we evaluate stock performance of Islamic banks relative to their conventional counterparts during the initial phase of the COVID-19 crisis (from December 31, 2019 to March 31, 2020). Using a total of 426 banks from 48 countries, we find that stock returns of Islamic banks were about 10% â€" 13 % higher than those of conventional banks, after controlling for a host of bank- and country-level variables. We provide an explanation for the superior stock performance of Islamic banks by assigning a special role for the levels of efficiency. We show that pre-crisis levels of efficiency that are adjusted for bank risk can explain crisis stock returns for Islamic banks, but not for conventional banks. The evidence is robust to alternative measures of stock returns, efficiency models, and other empirical strategies. We finally present some insight on the importance of key bank characteristics in determining the stock returns of conventional banks during the crisis period.

Biased News and Irrational Investors: Evidence from Biased Beliefs about Uncertainty and Information Acquisition
Liu, Jiatao
SSRN
Investors who use biased information from news media subsequently tend to make irrational decisions about acquiring firm-specific information compared to rational expectations. This model of information acquisition yields testable predictions that are verified by using a novel dataset. First, when sentiment in news articles, as a proxy for biased public information, is more optimistic, investors tend to acquire less earnings-relevant information before the earnings announcement and vice versa. Second, the return predictability from firm-specific news sentiment confirms that it contributes to variations in asset information risk due, in a biased belief equilibrium, to the proportion of informed investors deviating from rational expectations. Overall, these findings suggest that biased public information inherent in news sentiment serves to irrationalize investorsâ€™ acquisition of firm-specific information through a biased perception of uncertainties in the risky asset payoff.

COVID-19 Pandemic and its Impact on Labor Force: A New Model Based on Social Stress Theory and Prospect Theory
C. G., Manojkrishnan,M, Aravind
SSRN
Human beings across the globe irrespective of caste and creed, culture, economic and geographic distances, are facing a very strange time, struggling and fighting against a pandemic COVID-19. On analyzing the literature, it is understood that most of the research scholars have confined their study to the clinical and therapeutic aspects of COVID-19 and there are a lesser number of studies related to the impact of COVID-19 on economic, psychological, social and behavioral perspective. This study is carried out to propose a new theory that can integrate the social and financial stress of the labor force during the pandemic situation. For this purpose, we have taken lessons from the social stress theory and prospect theory. The research extensively covers 420 samples duly collected from the labor force working across Kerala State, India. In this study, we have identified three major social stress constructs viz., Governance, Personal and Societal among the labor force through the Common Factor Analysis (CFA) method. We have also observed three major stressors using Cohenâ€™s effect size; they are difficulty in diagnosing the disease, worry of the disease that it will get affected to the dear ones, and the fear of using public utilities. The general presumption of our theoretical model was identified stress constructs can create social stress among labor force, which was reconfirmed through the Covariance Based Structural Equation Modeling Approach (CB-SEM). The risk and benefit of the pandemic situation were further examined mathematically. It is interestingly observed that during COVID-19 pandemic the labor force across Kerala will value health and wellness as the most important gain than financial benefits.

Calibrating Local Volatility Models with Stochastic Drift and Diffusion
Orcan Ogetbil,Narayan Ganesan,Bernhard Hientzsch
arXiv

We propose Monte Carlo calibration algorithms for three models: local volatility with stochastic interest rates, stochastic local volatility with deterministic interest rates, and finally stochastic local volatility with stochastic interest rates. For each model, we include detailed derivations of the corresponding SDE systems, and list the required input data and steps for calibration. We give conditions under which a local volatility can exist given European option prices, stochastic interest rate model parameters, and correlations. The models are posed in a foreign exchange setting. The drift term for the exchange rate is given as a difference of two stochastic short rates, domestic and foreign, each modeled by a G1++ process. For stochastic volatility, we model the variance for the exchange rate by a CIR process. We include tests to show the convergence and the accuracy of the proposed algorithms.

Capital and Labor Income Pareto Exponents across Time and Space
Tjeerd de Vries,Alexis Akira Toda
arXiv

We estimate capital and labor income Pareto exponents across 428 country-year observations that span 54 countries over half a century. We document two stylized facts: (i) capital income is more unequally distributed than labor income; namely, the capital exponent (1-3) is smaller than labor (2-5), and (ii) capital and labor exponents are nearly uncorrelated. To explain these findings, we build an incomplete market model with job ladders and capital income risk that gives rise to a capital income Pareto exponent smaller than but nearly unrelated to the labor exponent. Our results suggest the importance of distinguishing income and wealth inequality.

CombinaÃ§Ã£o da ProjeÃ§Ã£o da Volatilidade Percebida Por Redes Neurais E Har (Combination of the Projection of Volatility Perceived by Neural Networks and Har)
AraÃºjo, Alcides,Montini, Alessandra,Sampaio, Joelson Oliveira
SSRN

Differential Machine Learning
Brian Huge,Antoine Savine
arXiv

Differential machine learning combines automatic adjoint differentiation (AAD) with modern machine learning (ML) in the context of risk management of financial Derivatives. We introduce novel algorithms for training fast, accurate pricing and risk approximations, online, in real-time, with convergence guarantees. Our machinery is applicable to arbitrary Derivatives instruments or trading books, under arbitrary stochastic models of the underlying market variables. It effectively resolves computational bottlenecks of Derivatives risk reports and capital calculations.

Differential ML is a general extension of supervised learning, where ML models are trained on examples of not only inputs and labels but also differentials of labels wrt inputs. It is also applicable in many situations outside finance, where high quality first-order derivatives wrt training inputs are available. Applications in Physics, for example, may leverage differentials known from first principles to learn function approximations more effectively.

In finance, AAD computes pathwise differentials with remarkable efficacy so differential ML algorithms provide extremely effective pricing and risk approximations. We can produce fast analytics in models too complex for closed form solutions, extract the risk factors of complex transactions and trading books, and effectively compute risk management metrics like reports across a large number of scenarios, backtesting and simulation of hedge strategies, or regulations like XVA, CCR, FRTB or SIMM-MVA.

TensorFlow implementation is available on https://github.com/differential-machine-learning

Disclosure and Investor Inattention
Bertomeu, Jeremy,Hu, Keri Peicong,Liu, Yibin
SSRN
Investors have a finite capacity to organize all information they receive from financial disclosures. In a model of rational inattention, we show that investor attention capacity affects the probability of disclosure. In the model, an informed firm makes a strategic voluntary disclosure subject to proprietary costs (Verrecchia 1983) or uncertainty about information endowment (Dye 1985), investors optimally allocate their attention as a function of their conjectures about the disclosure strategy. Our main result is that the probability of disclosure is inverse U-shaped in investor attention: for low levels of attention, more attention facilitates communication and increases disclosure; for high levels of attention, more attention better identifies, and therefore deters, unfavorable voluntary disclosure. We provide preliminary empirical evidence that the relationship between investor attention and management forecast is concave and inverse U-shaped, using institutional ownership as a proxy for investor attention.

Diversidade De GÃªnero Nos Conselhos Administrativos E Sua RelaÃ§Ã£o Com Desempenho E Risco Financeiro Nas Empresas Familiares (Gender Diversity on Administrative Boards and Their Relationship With Performance and Financial Risk in Family Businesses)
Costa, Lilian,Sampaio, Joelson Oliveira,Flores, Eduardo
SSRN

Do Corporate Insiders Take Advantage of Their Political Connections? Evidence from Insider Trading
Liu, Xia (Summer)
SSRN
Using corporate insidersâ€™ employment data, I study the impact of political connections on corporate insidersâ€™ trading behavior. I find that purchases (sales) by politically connected corporate insiders are associated with lower (higher) abnormal returns compared with non-politically connected insiders, indicating that politically connected insiders in general are sophisticated and cautious about potential legal risk. This effect is more significant among purchases. I also find that politically connected insiders are more likely to have longer trading horizons, and more likely to make routine trades. The Stop Trading on Congressional Knowledge (STOCK) Act passed in April 2012 effectively decreases (increases) the abnormal returns associated with insider purchases (sales) made by Congress members and staff in short horizons.

Does Executive Compensation Reflect Corporate Productivity?
Choi, Yoon K.
SSRN
Recent literature has given attention to the effect of CEO‐specific productivity on the structure of CEO compensation. Our paper instead focuses on the effect of a different productivity factor—which we call "corporate productivity"—on CEO compensation. In particular, we show that corporate productivity affects the trade‐off between incentive and risk in a non‐monotonic fashion, which the literature has not yet recognized. Using various empirical proxies for corporate productivity, we show that our results are consistent with the non‐monotonic relation and thus contribute to the debates in the incentive‐risk trade‐off literature. Second, our findings also contribute to the internal capital market literature by exploring the relation between the structure of CEO compensation and excess value.

Economic Policy Uncertainty, Interest Rates and the Co-Movement of Sovereign-Bank Default Risk
Bales, Stephan
SSRN
The present study examines political roots of bank and sovereign default risk co-movements for banks in Europe and the United States. A flattening of the yield curve, lower bank interest margins, higher interbank market rates and increasing levels of Economic Policy Uncertainty are found to intensify the dynamic correlation of sovereign and bank default risk. Utilizing the 2018's parliament election in Italy as a specific policy uncertainty shock, correlation increases of 25%-35% are observable within the government formation process. The connection is significantly weaker in the United States, which can be attributed to a different interest rate policy of the central bank and the absence of default risk commonality as embedded in the eurozone.

Equilibrium Asset Pricing with Transaction Costs
Martin Herdegen,Johannes Muhle-Karbe,Dylan Possamaï
arXiv

We study risk-sharing economies where heterogenous agents trade subject to quadratic transaction costs. The corresponding equilibrium asset prices and trading strategies are characterised by a system of nonlinear, fully-coupled forward-backward stochastic differential equations. We show that a unique solution generally exists provided that the agents' preferences are sufficiently similar. In a benchmark specification with linear state dynamics, the illiquidity discounts and liquidity premia observed empirically correspond to a positive relationship between transaction costs and volatility.

Exploring How Independent Directors View CSR Inequality Using A Quasi-Natural Experiment
Ongsakul, Viput,Jiraporn, Napatsorn (Pom),Jiraporn, Pornsit
SSRN
Purpose: Our purpose is to explore CSR inequality, which is the inequality across different CSR categories. Higher inequality suggests a less balanced CSR policy. To determine if CSR inequality is beneficial or harmful, we investigate how independent directors view CSR inequality, using an exogenous regulatory shock introduced by the passage of the Sarbanes-Oxley Act. Design: To draw causality, we rely on a quasi-natural experiment based on an exogenous regulatory shock that forced certain firms to raise board independence. This approach is significantly less vulnerable to endogeneity and is much more likely to show a causal effect. We also confirm our results using propensity score matching, principal component analysis, and instrumental-variable analysis.Findings: Our difference-in-difference estimates show that independent directors view CSR inequality unfavorably. Specifically, board independence diminishes CSR inequality by approximately 34-43%. Because our empirical strategy is based on a quasi-natural experiment, our results are more likely to show causality. Our results also imply that CSR inequality is a crucially important aspect of CSR. Originality: Although a substantial volume of research has examined CSR, one vital aspect of CSR has been largely unexplored. Filling this void in the literature, we investigate CSR inequality. Our study is the first to explore how independent directors view CSR inequality using a quasi-natural experiment.

Heterogeneous Effects of Job Displacement on Earnings
arXiv

This paper considers how the effect of job displacement varies across different individuals. In particular, our interest centers on features of the distribution of the individual-level effect of job displacement. Identifying features of this distribution is particularly challenging -- e.g., even if we could randomly assign workers to be displaced or not, many of the parameters that we consider would not be point identified. We exploit our access to panel data, and our approach relies on comparing outcomes of displaced workers to outcomes the same workers would have experienced if they had not been displaced and if they maintained the same rank in the distribution of earnings as they had before they were displaced. Using data from the Displaced Workers Survey, we find that displaced workers earn about $157 per week less, on average, than they would have earned if they had not been displaced. We also find that there is substantial heterogeneity. We estimate that 42% of workers have higher earnings than they would have had if they had not been displaced and that a large fraction of workers have experienced substantially more negative effects than the average effect of displacement. Finally, we also document major differences in the distribution of the effect of job displacement across education levels, sex, age, and counterfactual earnings levels. Throughout the paper, we rely heavily on quantile regression. First, we use quantile regression as a flexible (yet feasible) first step estimator of conditional distributions and quantile functions that our main results build on. We also use quantile regression to study how covariates affect the distribution of the individual-level effect of job displacement. Investment Differences Between Public and Private Firms: Evidence From U.S. Tax Returns Feldman, Naomi E.,Kawano, Laura,Patel, Elena,Rao, Nirupama,Stevens, Michael,Edgerton, Jesse SSRN We develop a method for identifying public firms in tax records in order to compare the investments of public and private firms using a representative sample of all US corporations. Despite private firms being significantly smaller than public firms on average, in aggregate, they account for an economically meaningful share of total corporate investment. Nevertheless, while both types of firms invest similar amounts in physical capital, public firms out-invest observationally-similar private firms in R\&D. This greater R\&D investment by public firms is muted when shareholder earnings pressures are heightened, but not so much as to overcome the baseline investment advantage. It Ainâ€™t Just What Funds Disclose (It's The Way That They Do It) Tucker, Anne M.,Xia, Yusen,Smelcer, Susan SSRN The finance and accounting literature document how operating company disclosure tone and textual attributes affect firm performance, earnings persistence, stock volatility, capital costs, and retail investor behavior. In this Article, we explore the applicability of these theories to mutual fund disclosure, examining the extent to which disclosure tone influences fund risk and performance. Following (Loughran and McDonald 2011), we first develop customized dictionaries (word lists) specific to mutual fund disclosure language. We also introduce a novel sentiment scoring framework that generates a transparent sentence and disclosure-level score for our sample of 132,000 mutual fund summary prospectuses (497k) from 2010-2018. Our results demonstrate that investment strategy (IS) sections differ in tone and function from principal risk (PR) sections, results that we explore in conjunction with Tucker and Xia (2020) examination of disclosure readability. In particular, we find IS sections are more negative than PR sectionsâ€"a trend that only increases over time. We also note differences in sentiment scores among CRSP categories, suggesting that asset class drives disclosure tone. A fixed effect regression analysis explores the effect of disclosure tone on fund performance and risk. Levels of structural change: An analysis of China's development push 1998-2014 Torsten Heinrich,Jangho Yang,Shuanping Dai arXiv We investigate structural change in the PR China during a period of particularly rapid growth 1998-2014. For this, we utilize sectoral data from the World Input-Output Database and firm-level data from the Chinese Industrial Enterprise Database. Starting with correlation laws known from the literature (Fabricant's laws), we investigate which empirical regularities hold at the sectoral level and show that many of these correlations cannot be recovered at the firm level. For a more detailed analysis, we propose a multi-level framework, which is validated with empirically. For this, we perform a robust regression, since various input variables at the firm-level as well as the residuals of exploratory OLS regressions are found to be heavy-tailed. We conclude that Fabricant's laws and other regularities are primarily characteristics of the sectoral level which rely on aspects like infrastructure, technology level, innovation capabilities, and the knowledge base of the relevant labor force. We illustrate our analysis by showing the development of some of the larger sectors in detail and offer some policy implications in the context of development economics, evolutionary economics, and industrial organization. Money Market Segmentation and the Transmission of Post-crisis Monetary Policy Han, Yangjue SSRN This paper studies the transmission mechanism of the post-crisis interest rate policy. In particular, we are interested in explaining an upward regime shift in the spreads between interest on reserves (IOR) and overnight funding rates in Jan 2018. While traditional theories would understand such a regime shift through the lens of balance sheet constraints or convenience yield, we propose a theory that builds around the segmentation of U.S. money markets. By assuming that investors face short-sale constraints and have heterogeneous access to the Fed's interest rate policy instruments, we show that the equilibrium interest rate is a non-linear function of the debt-to-reserve ratio due to limited participation. When the debt-to-reserve ratio is low, local debt supply shocks can be absorbed by investors at the corresponding policy rate. But when the debt-to-reserve ratio is high, a small debt supply shock can generate a large spike in the equilibrium rate. Using data on repo transactions collected from SEC filings, we find that the FICC's sponsored repo reform in Jan 2018 significantly increased the repo volume inter-mediated by large banks and drained out the residual cash supply in the RRP facility. Consistent with our predictions, the increased repo volume and the Fed's balance sheet normalization jointly created an environment where window-dressing shocks can generate large rate spikes. Our results suggest that keeping an abundance of reserves is essential for implementing the interest rate policy and building a resilient funding market. Moving Forward: Management Guidance and Earnings Announcement Returns Lu, Yao,Skinner, Douglas J. SSRN We provide new evidence on the role of management guidance in explaining earnings announcement-period returns. We show that guidance practices changed around the financial crisis in ways likely to affect the information content of guidance bundled with earnings. Managers provide guidance for a number of metrics and have moved towards annual and away from quarterly guidance, perhaps because of concerns about the managerial â€œmyopiaâ€ some associate with quarterly EPS guidance. EPS and/or sales guidance news is incrementally informative and explains returns to about the same extent as earnings news, more so when earnings disappoint or firms report large beats. Specifications that capture the sign and consistency of signals are about as informative as those that use magnitudes. Similar to previous evidence, the response is asymmetric, with a stronger response to adverse earnings news accompanied by downgrades. On Detecting Spoofing Strategies in High Frequency Trading Xuan Tao,Andrew Day,Lan Ling,Samuel Drapeau arXiv Spoofing is an illegal act of artificially modifying the supply to drive temporarily prices in a given direction for profit. In practice, detection of such an act is challenging due to the complexity of modern electronic platforms and the high frequency at which orders are channeled. We present a micro-structural study of spoofing in a simple static setting. A multilevel imbalance which influences the resulting price movement is introduced upon which we describe the optimization strategy of a potential spoofer. We provide conditions under which a market is more likely to admit spoofing behavior as a function of the characteristics of the market. We describe the optimal spoofing strategy after optimization which allows us to quantify the resulting impact on the imbalance after spoofing. Based on these results we calibrate the model to real Level 2 datasets from TMX, and provide some monitoring procedures based on the Wasserstein distance to detect spoofing strategies in real time. On The Quest For Economic Prosperity: A Higher Education Strategic Perspective For The Mena Region Amr A. Adly arXiv In a fast-changing technology-driven era, drafting an implementable strategic roadmap to achieve economic prosperity becomes a real challenge. Although the national and international strategic development plans may vary, they usually target the improvement of the quality of living standards through boosting the national GDP per capita and the creation of decent jobs. There is no doubt that human capacity building, through higher education, is vital to the availability of highly qualified workforce supporting the implementation of the aforementioned strategies. In other words, fulfillment of most strategic development plan goals becomes dependent on the drafting and implementation of successful higher education strategies. For MENA region countries, this is particularly crucial due to many specific challenges, some of which are different from those facing developed nations. More details on the MENA region higher education strategic planning challenges as well as the proposed higher education strategic requirements to support national economic prosperity and fulfill the 2030 UN SDGs are given in the paper. Pareto's 80/20 Rule and the Gaussian Distribution Katsuaki Tanabe arXiv The statistical state for the empirical Pareto's 80/20 rule has been found to correspond to a normal or Gaussian distribution with a standard deviation that is twice the mean. This finding represents large characteristic variations in our society and nature. In this distribution, the rule can be also referred to as, for example, the 25/5, 45/10, 60/15, or 90/25 rule. In addition, our result suggests the existence of implicit negative contributors. Peer effects in R&D investment policy: Evidence from China Peng, Zhen,Lian, Yujun,Forson, Joseph Ato SSRN Using a typical linear model on a sample of listed firms in China over a period of 10 years (2006â€"2016), this study empirically attempts proving how peer effects influence corporate research and development (R&D) investment decision. The study goes further to demonstrate that peer effects play a significant and critical role in determining corporate R&D investment policies, and by extension the more important determinant than most traditional firm-specific factors. After dealing with endogeneity bias and conducting further robustness checks, the above conclusions were valid in this study. It has been theorized in contemporary research that both information and market competition are the main channels through which one can best appreciate peer effects and that firms with weak information acquisition ability and in highly uncertain or competitive environment are more likely to be affected by peer groups. We also find evidence that a firm's R&D investment status relative to its peer firms will affect its R&D investment decision. Moreover, the direction of peer effects follows the law of imitation. Thus, firms are more likely to imitate those peers who share similar characteristics. Yet, leading firms and state-owned enterprises (SOEs) are exceptionally different as their R&D decisions are sensitive to both peer-followers and non-SOEs respectively. Power in Networks: The Medici* Holler, Manfred SSRN We use the Public Good (Power) Index and the Public Value to rank the marriages of business relations of 16 elite families in 15th century Florence â€" with a focus on the networks of the Medici and the taking of power by Cosimo deâ€™ Medici. Theoretical analysis supports the outstanding position of the Medici family and explains much of its historical success. The paper offers material for the more general discussion of network rigidity versus social embeddedness, which concludes the paper. Predicting Non Farm Employment Tarun Bhatia arXiv U.S. Nonfarm employment is considered one of the key indicators for assessing the state of the labor market. Considerable deviations from the expectations can cause market moving impacts. In this paper, the total U.S. nonfarm payroll employment is predicted before the release of the BLS employment report. The content herein outlines the process for extracting predictive features from the aggregated payroll data and training machine learning models to make accurate predictions. Publically available revised employment report by BLS is used as a benchmark. Trained models show excellent behaviour with R2 of 0.9985 and 99.99% directional accuracy on out of sample periods from January 2012 to March 2020. Keywords Machine Learning; Economic Indicators; Ensembling; Regression, Total Nonfarm Payroll Price of Regulations: Regulatory Costs and the Cross-section of Stock Returns Ince, Baris,Ozsoylev, Han N. SSRN Regulations introduce significant fixed costs and add to operating leverage. Fixed regulatory costs that contribute to operating leverage should generate a risk premium. To explore whether such a premium exists, we introduce a measure of "regulatory operating leverage" that reflects the importance of fixed regulatory costs in a firm's cost structure. Regulatory operating leverage predicts stock returns in the cross-section, and a zero-cost high-low equal (value)-weighted regulatory operating leverage strategy generates 5.64% (5.28%) annualized risk-adjusted return. Finally, the impact of regulatory operating leverage on returns is due to the (systematic) risk contribution of fixed regulatory costs. Price, Volatility and the Second-Order Economic Theory Victor Olkhov arXiv This paper considers price volatility as the reason for description of the second-degree economic variables, trades and expectations aggregated during certain time interval {\Delta}. We call it - the second-order economic theory. The n-th degree products of costs and volumes of trades, performed by economic agents during interval {\Delta} determine price n-th statistical moments. First two price statistical moments define volatility. To model volatility one needs description of the squares of trades aggregated during interval {\Delta}. To describe price probability one needs all n-th statistical moments of price but that is almost impossible. We define squares of agent's trades and macro expectations those approve the second-degree trades aggregated during interval {\Delta}. We believe that agents perform trades under action of multiple expectations. We derive equations on the second-degree trades and expectations in economic space. As economic space we regard numerical continuous risk grades. Numerical risk grades are discussed at least for 80 years. We propose that econometrics permit accomplish risk assessment for almost all economic agents. Agents risk ratings distribute agents by economic space and define densities of macro second-degree trades and expectations. In the linear approximation we derive mean square price and volatility disturbances as functions of the first and second-degree trades disturbances. In simple approximation numerous expectations and their perturbations can cause small harmonic oscillations of the second-degree trades disturbances and induce harmonic oscillations of price and volatility perturbations. Pricing with Variance Gamma Information Lane P. Hughston,Leandro Sánchez-Betancourt arXiv In the information-based pricing framework of Brody, Hughston and Macrina, the market filtration$\{ \mathcal F_t\}_{t\geq 0}$is generated by an information process$\{ \xi_t\}_{t\geq0}$defined in such a way that at some fixed time$T$an$\mathcal F_T$-measurable random variable$X_T$is "revealed". A cash flow$H_T$is taken to depend on the market factor$X_T$, and one considers the valuation of a financial asset that delivers$H_T$at$T$. The value$S_t$of the asset at any time$t\in[0,T)$is the discounted conditional expectation of$H_T$with respect to$\mathcal F_t$, where the expectation is under the risk neutral measure and the interest rate is constant. Then$S_{T^-} = H_T$, and$S_t = 0$for$t\geq T$. In the general situation one has a countable number of cash flows, and each cash flow can depend on a vector of market factors, each associated with an information process. In the present work, we construct a new class of models for the market filtration based on the variance-gamma process. The information process is obtained by subordinating a particular type of Brownian random bridge with a gamma process. The filtration is taken to be generated by the information process together with the gamma bridge associated with the gamma subordinator. We show that the resulting extended information process has the Markov property and hence can be used to price a variety of different financial assets, several examples of which are discussed in detail. Product Market Competition in Accounting, Finance, and Corporate Governance: A Review of the Literature Babar, Md.,Habib, Ahsan SSRN Product market competition has been identified as one of the most powerful corporate governance tools for motivating managers to maximize firm value. Consistent with this view, a large body of theoretical and empirical research over the years has investigated the implications of product market competition. This paper synthesizes and critically evaluates the empirical literature on the consequences of product market competition in the accounting, finance, and corporate governance domains. Our review focuses on issues like financial reporting quality, analyst forecasting activities, asset pricing, investment, and financing decisions, and the substitutive versus complementary relationships between product market competition and other corporate governance tools. Our review suggests that, although market competition has profound implications for these issues, the empirical findings often provide conflicting results. We highlight such contradictory findings and offer suggestions for future research. Our review will help researchers intending to further investigate the implications of product market competition, both in the US and internationally. Quantile Convolutional Neural Networks for Value at Risk Forecasting Gábor Petneházi arXiv This article presents a new method for forecasting Value at Risk. Convolutional neural networks can do time series forecasting, since they can learn local patterns in time. A simple modification enables them to forecast not the mean, but arbitrary quantiles of the distribution, and thus allows them to be applied to VaR-forecasting. The proposed model can learn from the price history of different assets, and it seems to produce fairly accurate forecasts. Rebalance Timing Luck: The (Dumb) Luck of Smart Beta Hoffstein, Corey,Faber, Nathan,Braun, Steven SSRN Prior research and empirical investment results have shown that portfolio construction choices related to rebalance schedules may have non-trivial impacts on realized performance. We construct long-only indices that provide exposures to popular U.S. equity factors (value, size, momentum, quality, and low volatility) and vary their rebalance schedules to isolate the effects of â€œrebalance timing luck.â€ Our constructed indices exhibit high levels of rebalance timing luck, often exceeding 100 basis points annualized, with total impact dependent upon the frequency of rebalancing, portfolio concentration, and the nature of the underlying strategy. As a case study, we replicate popular factor-based index funds and similarly find meaningful performance impacts due to rebalance timing luck. For example, a strategy replicating the S&P Enhanced Value index saw calendar year return differentials above 40% strictly due to the rebalance schedule implemented. Our results suggest substantial problems for analyzing any investment when the strategy, its peer group, or its benchmark is susceptible to performance impacts driven by the choice of rebalance schedule. Recovery Process Optimization Using Survival Regression Witzany, Jiri,Kozina, Anastasiia SSRN The goal of this paper is to propose, empirically test and compare different logistic and survival analysis techniques in order to optimize the debt collection process. This process uses various actions, such as phone calls, mails, visits, or legal steps to recover past due loans. We focus on the soft collection part, where the question is whether and when to call a past-due debtor with regard to the expected financial return of such an action. We propose using the survival analysis technique, in which the phone call can be compared to a medical treatment, and repayment to the recovery of a patient. We show on a real banking dataset that, unlike ordinary logistic regression, this model provides the expected results and can be efficiently used to optimize the soft collection process. Regression to the Tail: Why the Olympics Blow Up Bent Flyvbjerg,Alexander Budzier,Daniel Lunn arXiv The Olympic Games are the largest, highest-profile, and most expensive megaevent hosted by cities and nations. Average sports-related costs of hosting are$12.0 billion. Non-sports-related costs are typically several times that. Every Olympics since 1960 has run over budget, at an average of 172 percent in real terms, the highest overrun on record for any type of megaproject. The paper tests theoretical statistical distributions against empirical data for the costs of the Games, in order to explain the cost risks faced by host cities and nations. It is documented, for the first time, that cost and cost overrun for the Games follow a power-law distribution. Olympic costs are subject to infinite mean and variance, with dire consequences for predictability and planning. We name this phenomenon "regression to the tail": it is only a matter of time until a new extreme event occurs, with an overrun larger than the largest so far, and thus more disruptive and less plannable. The generative mechanism for the Olympic power law is identified as strong convexity prompted by six causal drivers: irreversibility, fixed deadlines, the Blank Check Syndrome, tight coupling, long planning horizons, and an Eternal Beginner Syndrome. The power law explains why the Games are so difficult to plan and manage successfully, and why cities and nations should think twice before bidding to host. Based on the power law, two heuristics are identified for better decision making on hosting. Finally, the paper develops measures for good practice in planning and managing the Games, including how to mitigate the extreme risks of the Olympic power law.

Robust Utility Maximization in a Multivariate Financial Market with Stochastic Drift
Jörn Sass,Dorothee Westphal
arXiv

We study a utility maximization problem in a financial market with a stochastic drift process, combining a worst-case approach with filtering techniques. Drift processes are difficult to estimate from asset prices, and at the same time optimal strategies in portfolio optimization problems depend crucially on the drift. We approach this problem by setting up a worst-case optimization problem with a time-dependent uncertainty set for the drift. Investors assume that the worst possible drift process with values in the uncertainty set will occur. This leads to local optimization problems, and the resulting optimal strategy needs to be updated continuously in time. We prove a minimax theorem for the local optimization problems and derive the optimal strategy. Further, we show how an ellipsoidal uncertainty set can be defined based on filtering techniques and demonstrate that investors need to choose a robust strategy to be able to profit from additional information.

Security Regulations, Access to Capital Markets, and Firm Performance: Evidence from China
Wang, Kun,Wei, Zhe,xiao, xing,Sun, Kunpeng
SSRN
This study explores the cost of security regulations in China, where firms are required to meet a certain profitability benchmark before applying for permission to raise more equity via secondary equity offerings (SEOs). Using a differenceâ€inâ€differences setting, we show that firms affected by the regulation (i.e., firms with high external financing demands (EFD) but profitability lower than the regulatory requirement) significantly underperform their counterparts, while unaffected firms do not. The affected firmsâ€™ performance decline increases (decreases) when the requirement of profitability is more (less) restricted. Consistently, the threeâ€day cumulative abnormal return (CAR) of firms with high EFD is significantly negative (positive) when the regulation is tightened (loosened). Our study provides evidence on how the cost of regulation affects companies that have growth opportunities.

Target Firm Accounting Conservatism and Corporate Acquisitions: Transferring Wealth or Benefiting Both?
Kim, Taewoo,Kross, William,Suk, Inho
SSRN
Because conservative accounting practices induce firms to report bad news earlier and defer good news disclosure, accounting conservatism in target firm accounting can hinder acquirers from identifying a potentially profitable target while it can help acquiring firms mitigate the downside risk stemming from future asset write-downs and investment inefficiency. After accounting for other accounting attributes and governance mechanisms, our analysis reveals that a firm is more likely to receive an acquisition offer when its financial reporting is more conservative. More importantly, while the acquirer pays a larger takeover premium to a more conservative target firm, the acquirerâ€™s acquisition performance turns out to be greater when the target firmâ€™s accounting is more conservative. Overall, our findings suggest that unlike other target firm accounting quality proxies that transfer wealth from the target to the acquirer shareholders, target firm accounting conservatism benefits both the acquirer and target shareholders.

The Capital Market Effects of Centralizing Regulated Financial Information
Sran, Gurpal,Tuijn, Marcel,Vollon, Lauren
SSRN
We study the relation between the centralization of regulated financial information, information asymmetry, and capital market liquidity. Specifically, we exploit the staggered implementation of digital storage and access facilities (called Officially Appointed Mechanisms, or OAMs) for regulated financial information in the European Union. We find that the implementation of OAMs results in significant improvements in capital market liquidity. Improvements in liquidity associated with centralization are especially significant for small firms and firms with low levels of institutional ownership. This evidence is consistent with the hypothesis that lowering information processing costs by centralizing information leads to improved liquidity, especially when information processing costs are high. Further, we provide descriptive evidence on the capital market implications of OAM design and oversight.

The Difficulties with 'Financial Difficulties': The Threshold Conditions for the New Part 26A Process
Mokal, Riz
SSRN

The Nexus between Intellectual Capital and Value of the Firms: A Study on BSE S&P IT Firms in India
Vadivel, Thanikachalam,Selvam, Murugesan,Subramaniam, Assoc.Prof.Dr.Geetha ,Maniam, Balasundram
SSRN
Purpose: This paper examines the nexus between Intellectual Capital and Value of Information Technology Firms in the Indian Information Technology Industry. Forty-five companies, listed on BSE S&P IT Sector, were taken as a sample, for the purpose of this study.Methodology: Value Added Intellectual Co-efficient (VAIC) method, as developed by Pulic (1998) and Granger Causality, was used for the evaluation of intellectual capital and its relationship with the value of sample companies.Findings: The result of the study supports the hypothesis that the value of firms could be explained by the intellectual capital. It is found that there was significant association between intellectual capital and the value of sample firms.Practical Implication: The corporate are to be suggested to concentrate more on human capital efficiency. Besides, the Government officials, policy makers and other stake holders are advised to urge the corporate disclosure practices.

The Three Roles of Finance in the US Economy, 1952-2019
Akan, Taner,Hepsag, Aycan,Bozoklu, Seref,MollaahmetoÄŸlu, EbubekiÌ‡r
SSRN
This paper aimed to illustrate that the role of the finance sector in an economic system can be explained more systemically and systematically in the context of its interaction with macroeconomic governance, based on the case of the United States from 1952 Q1 to 2019 Q2. The paper introduced two modes of economic governance based on negative and positive institutional complementarities, developed its hypotheses built on an exhaustive structural analysis of the long-run relationship between finance sector and macroeconomic governance within the frame of these two modes, and quantitatively tested the hypotheses using a time-series cointegration analysis. The paper concluded that finance sector enhanced and impaired the US economic performance, respectively, in the periods 1952 Q1 - 1972 Q4 and 1980 Q1 â€" 2007 Q4, and that its long-run relationship with the US economic performance disappeared in the period 2008 Q1 â€" 2019 Q2.

The Value of Insider Information for Super--Replication with Quadratic Transaction Costs
Yan Dolinsky,Jonathan Zouari
arXiv

We study super--replication of European contingent claims in an illiquid market with insider information. Illiquidity is captured by quadratic transaction costs and insider information is modeled by an investor who can peek into the future. Our main result describes the scaling limit of the super--replication prices when the number of trading periods increases to infinity. Moreover, the scaling limit gives us the asymptotic value of being an insider.

Why Does the Fed Move Markets so Much? A Model of Monetary Policy and Time-Varying Risk Aversion
Pflueger, Carolin E.,Rinaldi, Gianluca
SSRN
We build a new model integrating a work-horse New Keynesian model with investor risk aversion that moves with the business cycle. We show that the same habit preferences that explain the equity volatility puzzle in quarterly data also naturally explain the large high-frequency stock response to Federal Funds rate surprises. In the model, a surprise increase in the short-term interest rate lowers output and consumption relative to habit, thereby raising risk aversion and amplifying the fall in stocks. The model explains the positive correlation between changes in breakeven inflation and stock returns around monetary policy announcements with long-term inflation news.

Wie Der â€˜Green Dealâ€™ Die Richtigen Anreize Setzen Kann: Ein Vorschlag Zur Ausgestaltung Eines Fonds Zur Staatlichen Finanzierung Nachhaltiger Unternehmen Und Realinvestitionen (How the â€˜Green Dealâ€™ Can Provide the Right Incentives: A Proposal for The Design of a Fund for Public Financing of Sustainable Businesses and Real Investments)
Edenhofer, Ottmar,Klein, Christian,Lessmann, Kai,Wilkens, Marco
SSRN
German abstract: Hinreichend ambitionierte CO2 â€Preise lenken Realinvestitionen grundsÃ¤tzlich in die richtige Richtung. Wenn deren EinfÃ¼hrung der Politik jedoch nicht gelingt, bedarf es anderer Instrumente, um eine Fehlallokation von Kapital zu verhindern. Wir schlagen daher im Zuge des europÃ¤ischen Green Deals einen Investitionsfonds fÃ¼r die EU vor, der sich durch langfristige, staatlich gesicherte Anleihen finanziert, um langfristig (zins)verbilligte Kredite an Unternehmen zu vergeben, die in nachhaltige Projekte mit dem primÃ¤ren Ziel der TreibhausgasneutralitÃ¤t investieren. Diese Subventionierung soll so lange Anreize fÃ¼r CO2 â€vermeidende Investitionen setzen, bis ein ausreichend hoher CO2 â€Preis eingefÃ¼hrt ist. FÃ¼r Unternehmen ergeben sich so Anreize, ihre GeschÃ¤ftsmodelle nachhaltiger zu gestalten und den Transformationsprozess der Wirtschaft umzusetzen.English abstract: Real investments that are in line with the climate policy targets of the European Green Deal require a price on CO2 that is sufficiently high. When policy fails to implement ambitious CO2 prices, other instruments are needed to prevent the mis-allocation of capital. We therefore propose an investment fund for the EU as part of the implementation of the European Green Deal, financed by long-term, government-backed bonds, to provide long-term reduced-interest loans to companies that invest in sustainable projects with the primary goal of greenhouse gas neutrality. This support is intended to provide incentives for emission mitigating investments until a sufficiently high CO2 price is introduced. Companies are thus confronted by incentives to turn their business models more sustainable and implement the transformation process of the economy.

Window Dressing Em Fundos De Investimentos No Brasil (Window Dressing in the Brazilian Investment Funds)
Marques, Matheus,Sampaio, Joelson Oliveira,Brunassi Silva, Vinicius
SSRN