Research articles for the 2019-09-11

'Continuous' Time Random Walk in Continuous Time Random Walk.The crucial role of inter-event times in volatility clustering
Jarosław Klamut,Tomasz Gubiec

We are introducing the new family of the Continuous Time Random Walks (CTRW) with long-term memory within consecutive waiting times. This memory is introduced to the model by the assumption that consecutive waiting times are the analog of CTRW themselves. This way, we obtain the 'Continuous' Time Random Walk in Continuous Time Random Walk. Surprisingly, this type of process, only with the long-term memory within waiting times, can successfully describe slowly decaying nonlinear autocorrelation function of the stock market return. The model achieves this result without any dependence between consecutive price changes. It proves the crucial role of inter-event times in volatility clustering phenomenon.

A Legal Perspective on Technology and the Capital Markets: Social Media, Short Activism and the Algorithmic Revolution
Mitts, Joshua
In this essay, I examine the technological revolution in the capital markets through the normative lenses of law, policy and regulation. Do new media platforms necessarily enhance market efficiency? Or do they facilitate fraud and manipulation of stock prices? I focus on the rise of short activism on Twitter, Seeking Alpha and similar forms of social media: much like a stock promoter induces others to buy so he or she can sell at a profit, so a short activist might dupe others into selling so he or she can lock in profits before the stock rises again.Second, I examine the ways in which the rise of algorithmic trading shapes the emergence of accurate prices in the capital markets, from cybersecurity risk to limit order cancellations. There is growing evidence that prosecutors are taking technologically induced price distortions quite seriously. Finally, I consider emerging frontiers of technological innovation in the capital markets. The jury is still out on whether the benefits of digital ledger technology exceed the costs of the rampant investor deception which has led to a steady stream of crypto prosecutions and enforcement actions.

Asset correlation estimation for inhomogeneous exposure pools
Christoph Wunderer

A possible data source for the estimation of asset correlations is default time series. This study investigates the systematic error that is made if the exposure pool underlying a default time series is assumed to be homogeneous when in reality it is not. We find that the asset correlation will always be underestimated if homogeneity with respect to the probability of default (PD) is wrongly assumed, and the error is the larger the more spread out the PD is within the exposure pool. If the exposure pool is inhomogeneous with respect to the asset correlation itself then the error may be going in both directions, but for most PD- and asset correlation ranges relevant in practice the asset correlation is systematically underestimated. Both effects stack up and the error tends to become even larger if in addition a negative correlation between asset correlation and PD is assumed, which is plausible in many circumstances and consistent with the Basel RWA formula. It is argued that the generic inhomogeneity effect described is one of the reasons why asset correlations measured from default data tend to be lower than asset correlations derived from asset value data.

Bayesian Inference on Volatility in the Presence of Infinite Jump Activity and Microstructure Noise
Qi Wang,José E. Figueroa-López,Todd Kuffner

Volatility estimation based on high-frequency data is key to accurately measure and control the risk of financial assets. A L\'{e}vy process with infinite jump activity and microstructure noise is considered one of the simplest, yet accurate enough, models for financial data at high-frequency. Utilizing this model, we propose a "purposely misspecified" posterior of the volatility obtained by ignoring the jump-component of the process. The misspecified posterior is further corrected by a simple estimate of the location shift and re-scaling of the log likelihood. Our main result establishes a Bernstein-von Mises (BvM) theorem, which states that the proposed adjusted posterior is asymptotically Gaussian, centered at a consistent estimator, and with variance equal to the inverse of the Fisher information. In the absence of microstructure noise, our approach can be extended to inferences of the integrated variance of a general It\^o semimartingale. Simulations are provided to demonstrate the accuracy of the resulting credible intervals, and the frequentist properties of the approximate Bayesian inference based on the adjusted posterior.

Being Stranded with Fossil Fuel Reserves? Climate Policy Risk and the Pricing of Bank loans
Delis, Manthos D., de Greiff, Kathrin,Ongena, Steven
Do banks price the risk of stranded fossil fuel reserves? To address this question, we hand collect global data on corporate fossil fuel reserves, match it with syndicated loans, and subsequently compare the loan rate charged to fossil fuel firms â€" along their climate policy exposure â€" to non-fossil fuel firms. We find that before 2015 banks did not price climate policy exposure. After 2015, however, our results show an increase in the cost of credit by 16 basis points for a fossil fuel firm with mean proved reserves, implying an increase in the total cost of borrowing for the mean loan by USD 1.5 million. We also provide some evidence that “green banks” charge marginally higher loan rates to fossil fuel firms.

Bigger Is Not Always Safer: A Critical Analysis of the Subadditivity Assumption for Coherent Risk Measures
Rau-Bredow, Hans
This paper provides a critical analysis of the subadditivity axiom, which is the key condition for coherent risk measures. Contrary to the subadditivity assumption, bank mergers can create extra risk. We begin with an analysis how a merger affects depositors, junior or senior bank creditors, and bank owners. Next it is shown that bank mergers can result in higher payouts having to be made by the deposit insurance scheme. Finally, we demonstrate that if banks are interconnected via interbank loans, a bank merger could lead to additional contagion risks. We conclude that the subadditivity assumption should be rejected, since a subadditive risk measure, by definition, cannot account for such increased risks.

Cognitive Trading System Model
Martín Parrondo, Ramón
A model captures a community consensus on a coherent field of knowledge, serving as a cumulative benchmark that can guide both research and application design, while also focusing efforts to extend or review it. Here we propose to develop this model for cognitive trading systems, computational entities whose structures and processes are substantially similar to those in human cognition. We hypothesize that cognitive architectures provide an adequate computational abstraction to define a model applicable to the design of trading systems in their entirety, although the model is not in itself such an architecture. The resulting cognitive trading system model encompasses critical aspects of structure and processing, memory and content, learning, perception, and action; highlighting the main architectural aspects while identifying the potential areas of incompleteness which remain undeveloped. We hope to provide to the general community what it is and what we expect of a modern and future trading system, which is currently challenging to find synthesized in one place.

Creditor’s Holdup, Releveraging and the Setting of Private Appropriation in a Control Contract Between Shareholders
de La Bruslerie, Hubert
Debt is analyzed in relation to the conflict between three parties, a controlling shareholder, outside investors and creditors. We follow Jensen and Meckling’s (1976) and Myers’ (1977) intuitions that a leverage may result in excess value appropriation by creditors while at the same time acting to discipline private benefits appropriation. A contingent claim valuation model is used to show that debt releveraging is also a key governance variable when incentivization triggers a transfer of value to creditors. We show that debt is a complex regulation tool in an agency contract approach as it interferes endogenously with private benefits incentivization schemes particularly when value creation events occur.

Demographics, Family/Social Interaction, and Household Finance
Gao, Ming,Fok, Robert (Chi-Wing)
We examine the role of demographics and family/social interaction in Chinese household finance. The impacts of demographic characteristics are not limited to stock market participation, but extend to other financial activities. Households with strong family and social interaction are more likely to save, invest in risky assets and borrow. Family interaction is positively related to informal financing.

Direct and Indirect Effects based on Changes-in-Changes
Martin Huber,Mark Schelker,Anthony Strittmatter

We propose a novel approach for causal mediation analysis based on changes-in-changes assumptions restricting unobserved heterogeneity over time. This allows disentangling the causal effect of a binary treatment on a continuous outcome into an indirect effect operating through a binary intermediate variable (called mediator) and a direct effect running via other causal mechanisms. We identify average and quantile direct and indirect effects for various subgroups under the condition that the outcome is monotonic in the unobserved heterogeneity and that the distribution of the latter does not change over time conditional on the treatment and the mediator. We also provide a simulation study and an empirical application to the Jobs II programme.

Distorted stochastic dominance: a generalized family of stochastic orders
Tommaso Lando,Lucio Bertoli-Barsotti

We study a generalized family of stochastic orders, semiparametrized by a distortion function H, namely H-distorted stochastic dominance, which may determine a continuum of dominance relations from the first- to the second-order stochastic dominance (and beyond). Such a family is especially suitable for representing a decision maker's preferences in terms of risk aversion and may be used in those situations in which a strong order does not have enough discriminative power, whilst a weaker one is poorly representative of some classes of decision makers. In particular, we focus on the class of power distortion functions, yielding power-distorted stochastic dominance, which seems to be particularly appealing owing to its computational simplicity and some interesting statistical interpretations. Finally, we characterize distorted stochastic dominance in terms of distortion functions yielding isotonic classes of distorted expectations.

Earnings Conference Calls and Institutional Monitoring: Evidence from Textual Analysis
Amoozegar, Arash,Berger, Dave,Cao, Xueli,Pukthuanthong, Kuntara
We document the effects of institutional investors on the qualitative information disclosure of firms within earnings conference calls. Utilizing conference call and institutional ownership data between 2005 and 2016, we find that aggregate institutional ownership dampens conference call tone. The effects of institutional investors on tone are causal based on results from indexed firms. Consistent with hypotheses regarding investor’s horizon, short-term institutional investors are associated with greater conference call tone, as well as potentially opportunistic trading, while long-term investors decrease tone. Market participants can generally disentangle the impact of institutional investors on tone based on investor type.

Estimating the volatility of Bitcoin using GARCH models
Samuel Asante Gyamerah

In this paper, an application of three GARCH-type models (sGARCH, iGARCH, and tGARCH) with Student t-distribution, Generalized Error distribution (GED), and Normal Inverse Gaussian (NIG) distribution are examined. The new development allows for the modeling of volatility clustering effects, the leptokurtic and the skewed distributions in the return series of Bitcoin. Comparative to the two distributions, the normal inverse Gaussian distribution captured adequately the fat tails and skewness in all the GARCH type models. The tGARCH model was the best model as it described the asymmetric occurrence of shocks in the Bitcoin market. That is, the response of investors to the same amount of good and bad news are distinct. From the empirical results, it can be concluded that tGARCH-NIG was the best model to estimate the volatility in the return series of Bitcoin. Generally, it would be optimal to use the NIG distribution in GARCH type models since time series of most cryptocurrency are leptokurtic.

Gender Discrimination in Small Business Lending. Evidence from a Lab in-the-Field Experiment in Turkey
Brock, J. Michelle,De Haas, Ralph
We test for the presence of gender discrimination in small business lending through a lab-in-the-field experiment with 334 Turkish loan officers. Each officer reviews multiple loan applications in which we randomize the applicant’s gender. While unconditional approval rates are the same for male and female applicants, we detect a more subtle form of discrimination. Loan officers are 30 percent more likely to make loan approval conditional on the presence of a guarantor when we present an application as coming from a female instead of a male entrepreneur. This gender discrimination is concentrated among young, inexperienced, and gender-biased loan officers. Discrimination is also most pronounced for loans that perform well in real life, making it costly to the bank. Experimental variation in the available applicant information does not impact lending decisions, suggesting that the nature of discrimination is implicit rather than statistical.

Hacia una central de siniestros: dime qué reclamas y te diré quién eres (Towards a Claims Bureau: Tell Me What Do You Claim and I Will Tell You Who You Are)
Dassatti, Cecilia
Spanish Abstract: En las últimas décadas se han venido desarrollando bases de datos con estadísticas de siniestralidad en algunas ramas de seguros, motivadas tanto por fundamentos teóricos de modelos de diseño de precios de seguros, así también por la búsqueda de mayor transparencia en los mercados de seguros. El presente trabajo analiza ambos tipos de fundamentos con el fin de proponer la implementación de bases de datos de similares características para el caso del mercado de seguros Uruguayo.English Abstract: In recent decades, databases with accident statistics have been developed in some insurance lines of business, both motivated by theoretical foundations of insurance price design models, as well as the search for greater transparency in insurance markets. This paper analyzes both types of fundamentals in order to propose the implementation of databases of similar characteristics in the case of the Uruguayan insurance market.

Income and Social Communication: The Demographics of Stock Market Participation
Gao, Ming,Meng, Juanjuan,Zhao, Longkai
This paper analyses the determinants of stock market participation decisions using officially compiled aggregate stock account opening data in China. Different from the literature that often focuses on one particular dimension, our paper systematically evaluates the relative importance of disposable income, demographic variables, macroeconomic factors, stock market conditions and social communication on both the level and the change of the participation rate. We find that the level of the participation rate is predominately determined by the income factor, followed by various measures of social communication. Social communication plays the most important role in the change of the participation rate, acting as a multiplier to stimulate stock market participation. The effects are more pronounced in high‐income, high‐education, high‐population‐density groups and during the bull market period.

Linear Equilibria for Dynamic LQG Games with Asymmetric Information and Dependent Types
Nasimeh Heydaribeni,Achilleas Anastasopoulos

We consider a non-zero-sum linear quadratic Gaussian (LQG) dynamic game with asymmetric information. Each player observes privately a noisy version of a (hidden) state of the world $V$, resulting in dependent private observations. We study perfect Bayesian equilibria (PBE) for this game with equilibrium strategies that are linear in players' private estimates of $V$. The main difficulty arises from the fact that players need to construct estimates on other players' estimate on $V$, which in turn would imply that an infinite hierarchy of estimates on estimates needs to be constructed, rendering the problem unsolvable. We show that this is not the case: each player's estimate on other players' estimates on $V$ can be summarized into her own estimate on $V$ and some appropriately defined public information. Based on this finding we characterize the PBE through a backward/forward algorithm akin to dynamic programming for the standard LQG control problem. Unlike the standard LQG problem, however, Kalman filter covariance matrices, as well as some other required quantities, are observation-dependent and thus cannot be evaluated off-line through a forward recursion.

Modelos de Score Crediticio: revisión metodológica y análisis a partir de datos de encuesta (Credit Score Models: Methodological Review and Analysis Based on Survey Data)
Dassatti, Cecilia
Spanish Abstract: Las instituciones financieras enfocadas en la concesión de préstamos al consumo se enfrentan a dos tipos de decisiones: por un lado, deben decidir si conceder un préstamo a un cliente nuevo y, por otro, deben decidir cómo gestionar los préstamos que ya concedieron. Los modelos de score crediticio son técnicas muy utilizadas por las instituciones financieras a la hora de tomar este tipo de decisiones. El objetivo del presente trabajo es analizar los modelos de score crediticio y las herramientas de validación de los mismos. Adicionalmente, se evalúa el grado de implementación de score crediticios en Uruguay a partir de datos de una encuesta realizada en 2014.English Abstract: Financial institutions focused on granting consumer loans face two types of decisions: on the one hand, they must decide whether to grant a loan to a new customer and, on the other, they must decide how to manage the loans they have already granted. Credit score models are techniques widely used by financial institutions when making these types of decisions. The objective of this work is to analyze the credit score models and their validation tools. Additionally, the degree of credit score implementation in Uruguay is evaluated based on data from a 2014 survey.

Naming and Shaming: Evidence from Event Studies
Armour, John,Mayer, Colin,Polo, Andrea
A firm’s ‘reputation’ reflects the expectations of its partners of the benefits of trading with it in the future. An announcement by a regulator that a firm has engaged in misconduct may be expected to impact negatively on trading parties’ (i.e. consumers or investors) expectations for a firm’s future performance, and hence on its market value. How can we identify reputational losses from share price reactions? How large are these losses for different type of misconducts? The chapter seeks to answer the above questions in the light of recent empirical evidence and draws implications for regulatory enforcement policy.

Optimal Iterative Threshold-Kernel Estimation of Jump Diffusion Processes
José E. Figueroa-López,Cheng Li,Jeffrey Nisen

In this paper, we propose a new threshold-kernel jump-detection method for jump-diffusion processes, which iteratively applies thresholding and kernel methods in an approximately optimal way to achieve improved finite-sample performance. We use the expected number of jump misclassifications as the objective function to optimally select the threshold parameter of the jump detection scheme. We prove that the objective function is quasi-convex and obtain a new second-order infill approximation of the optimal threshold in closed form. The approximate optimal threshold depends not only on the spot volatility, but also the jump intensity and the value of the jump density at the origin. Estimation methods for these quantities are then developed, where the spot volatility is estimated by a kernel estimator with thresholding and the value of the jump density at the origin is estimated by a density kernel estimator applied to those increments deemed to contains jumps by the chosen thresholding criterion. Due to the interdependency between the model parameters and the approximate optimal estimators built to estimate them, a type of iterative fixed-point algorithm is developed to implement them. Simulation studies for a prototypical stochastic volatility model show that it is not only feasible to implement the higher-order local optimal threshold scheme but also that this is superior to those based only on the first order approximation and/or on average values of the parameters over the estimation time period.

Pay to Play in Investment Management
Beggs, William,Harvison, Thuong
From 2001 to 2016, using the population of all investment advisory firms registered with the U.S. Securities and Exchange Commission (SEC), we document that the presence of government clients (e.g., public pension plans) for an investment advisory firm is strongly associated with past owner and officer contributions to state government officials. To help establish a causal link, we use the adoption of the SEC’s pay to play rules for investment advisors in 2011. Post implementation of the SEC’s pay to play rules, we find that this relationship weakens considerably. Further consistent with a pay to play explanation, the results are driven by advisors whose political contributions are made by senior officers likely to be involved in capital raising for the firm including CEOs, owners/partners, and sales executives. The results are most pronounced for advisors offering pension consulting services, advisors catering to institutional accounts (e.g., institutional asset managers), and advisory firms headquartered in states with a high concentration of public pension plans and a culture of political corruption.

Pricing Poseidon: Extreme Weather Uncertainty and Firm Return Dynamics
Kruttli, Mathias S.,Roth Tran, Brigitte,Watugala, Sumudu W.
We investigate the uncertainty dynamics surrounding extreme weather events through the lens of option and stock markets by identifying market responses to both the uncertainty regarding potential hurricane landfall and subsequent economic impact. Stock options on firms with establishments exposed to the landfall region exhibit increases in implied volatility of 5-10 percent, reflecting impact uncertainty. Using hurricane forecasts, we show that landfall uncertainty and potential impact uncertainty are reflected in prices before landfall. We find no evidence that markets incorporate better hurricane forecasts than those from NOAA. Improvements to hurricane forecasts could have economically significant effects in financial markets.

Shareholder Composition, Corporate Governance and Their Monitoring Effects on Firm Performance
Mantovani, Guido Max,Moscato, Gregory F
The main goal of the paper is to understand if the shareholder composition must be considered as part of the corporate governance framework or as monitoring factor. A related goal of the paper is to investigate if the shareholder composition must be included in the loop among the corporate governance and the corporate performance of the firms. We analyze a sample made of 10,520 firms over the years 2006-2015, in 8 European Countries having very differentiated governance frameworks, shareholder composition and corporate performance. Three variables related to equity-ownership structure were considered: (i) equity ratio; (ii) the percentage of institutional investors inside the ownership structure, and (iii) a C-3 index as a measure of ownership concentration explaining the actual influence of shareholders over the managerial decision. Seven indicators of the adopted corporate governance were sourced from ORBIS database and investigated as well. We find out that the qualitative indicators of shareholder composition have significant impacts on the corporate governance framework. On one side, they do not generate an economic incentive, since they do not reinforce the relationships among corporate governance and corporate performance, still an opaque topic. On the other side, shareholder composition deploys its monitoring capabilities by reinforcing the relationship between corporate governance and capital structure. We conclude that corporate governance should be considered as an element contributing to the monitoring capabilities of the shareholder composition of equity, not vice-versa!

Tax Deductions V. Tax-Free Growth: A Closer Look at 529 College Savings Plans Under the TCJA
Riskin, Ross
Now that investors can receive preferential federal income tax treatment when using 529 college savings plans to pay for qualified K-12 tuition expenses under the Tax Cuts and Jobs Act of 2017 (TCJA), it is important to determine whether the value of receiving and investing state income tax deductions provided for qualifying contributions made to this education savings vehicle is more beneficial than the value associated with tax-free growth, given the potential for shortened education planning time horizons.

The Ideological Use and Abuse of Freiburg’s Ordoliberalism
Dold, Malte F.,Krieger, Tim
In the aftermath of the Eurozone crisis, a ‘battle of ideas’ emerged over whether ordoliberalism is part of the cause or the solution of economic problems in Europe. While German ordoliberals argued that their policy proposals were largely ignored before and during the crisis, implying a too small role of ordoliberalism in European economic policy, critics saw too much ordoliberal influence, especially in form of austerity policies. We argue that neither view is entirely correct. Instead, both camps followed their ideological predispositions and argued strongly in favor of their preconceived Weltanschauung. The ordoliberal Freiburg School ceased being an active research program and instead grew to resemble a ‘tradition’ whose proponents shared a certain mindset of convenience. As a result, ordoliberal thinking was both used and abused by its proponents and critics to emphasize their ideologically framed policy recommendations. The present paper analyzes this ongoing debate and reflects on how the different ideological camps refer to the Freiburg School to push their own agendas. Building on this discussion, we end our paper with some constructive thoughts on how a contemporary ordoliberalism might want to react to some of the challenges of the ongoing Eurozone crisis.

The Past and Future of Quantitative Research (Presentation Slides)
Lopez de Prado, Marcos
Traditionally, the development of investment strategies has required domain-specific knowledge and access to restricted datasets. These two barriers exist by design: (a) Financial knowledge is hoarded by firms, and protected as trade secrets, and (b) Financial data is expensive, making it inaccessible to the broad scientific community.This presentation explores how these two barriers impact the quality of quantitative research, and how investment tournaments can help deliver better investment outcomes by overcoming those two barriers.

Validating Weak-form Market Efficiency in United States Stock Markets with Trend Deterministic Price Data and Machine Learning
Samuel Showalter,Jeffrey Gropp

The Efficient Market Hypothesis has been a staple of economics research for decades. In particular, weak-form market efficiency -- the notion that past prices cannot predict future performance -- is strongly supported by econometric evidence. In contrast, machine learning algorithms implemented to predict stock price have been touted, to varying degrees, as successful. Moreover, some data scientists boast the ability to garner above-market returns using price data alone. This study endeavors to connect existing econometric research on weak-form efficient markets with data science innovations in algorithmic trading. First, a traditional exploration of stationarity in stock index prices over the past decade is conducted with Augmented Dickey-Fuller and Variance Ratio tests. Then, an algorithmic trading platform is implemented with the use of five machine learning algorithms. Econometric findings identify potential stationarity, hinting technical evaluation may be possible, though algorithmic trading results find little predictive power in any machine learning model, even when using trend-specific metrics. Accounting for transaction costs and risk, no system achieved above-market returns consistently. Our findings reinforce the validity of weak-form market efficiency.