Research articles for the 2019-04-22

A Neural Network Boosted Double Over-Dispersed Poisson Claims Reserving Model
Gabrielli, Andrea
We present an actuarial loss reserving technique that takes into account both claim counts and claim amounts. Separate (over-dispersed) Poisson models for the claim counts and the claim amounts are combined by a joint embedding into a neural network architecture. As starting point of the neural network calibration we use exactly these two separate (over-dispersed) Poisson models. Such a nested model can be interpreted as a boosting machine. It allows us for joint modeling and mutual learning of claim counts and claim amounts beyond the two individual (over-dispersed) Poisson models. Moreover, this choice of neural network initialization guarantees stability and accelerates representation learning.

A New Model for Pricing Wind Power Futures
Hess, Markus
We propose a new model for the pricing of wind power futures written on the wind power production index. Our approach is based on an arithmetic multi-factor pure-jump Ornstein-Uhlenbeck setup with time-dependent coefficients. We express the wind power production index and the corresponding futures price in terms of Fourier integrals and derive the related time dynamics. We conclude the paper by an investigation of the so-called risk premium associated with our wind power model.

A Stochastic Partial Differential Equation Model for Limit Order Book Dynamics
Cont, Rama,Mueller, Marvin S.
We propose an analytically tractable class of models for the dynamics of a limit order book, described as the solution of a stochastic partial differential equation (SPDE) with multiplicative noise. We provide conditions under which the model admits a finite dimensional realization driven by a (low-dimensional) Markov process, leading to efficient methods for estimation and computation. We study two examples of parsimonious models in this class: a two-factor model and a model in which the order book depth is mean-reverting. For each model we perform a detailed analysis of the role of different parameters, study the dynamics of the price, order book depth, volume and order imbalance, provide an intuitive financial interpretation of the variables involved and show how the model reproduces statistical properties of price changes, market depth and order flow in limit order markets.

Accounting Conservatism and the Profitability of Corporate Insiders
Khalilov, Akram,Garcia Osma, Beatriz
We predict that accounting conservatism influences insiders' opportunities to speculate on good and bad news, and thus, insider trading profitability. We find that greater conditional (unconditional) conservatism is associated with lower (higher) insiders' profitability from sales. We find limited evidence that conservatism influences profitability from purchases. These findings are consistent with our hypotheses on the different informational roles of conditional and unconditional conservatism, and on the asymmetric influence of conservatism over the opportunities to speculate on good versus bad news. Our research design takes into consideration the endogenous nature of insiders' trading and conservatism. The results are robust to different measures of conservatism and a number of additional analyses.

Beyond the Doomsday Economics of 'Proof-of-Work' in Cryptocurrencies
Auer, Raphael
This paper discusses the economics of how Bitcoin achieves data immutability, and thus payment finality, via costly computations, i.e., "proof-of-work." Further, it explores what the future might hold for cryptocurrencies modelled on this type of consensus algorithm. The conclusions are, first, that Bitcoin counterfeiting via "double-spending" attacks is inherently profitable, making payment finality based on proof-of-work extremely expensive. Second, the transaction market cannot generate an adequate level of "mining" income via fees as users free-ride on the fees of other transactions in a block and in the subsequent blockchain. Instead, newly minted bitcoins, known as block rewards, have made up the bulk of mining income to date. Looking ahead, these two limitations imply that liquidity is set to fall dramatically as these block rewards are phased out. Simple calculations suggest that once block rewards are zero, it could take months before a Bitcoin payment is final, unless new technologies are deployed to speed up payment finality. Second-layer solutions such as the Lightning Network might help, but the only fundamental remedy would be to depart from proof-of-work, which would probably require some form of social coordination or institutionalisation.

Can Mispricing Explain the Value Premium?
Jaffe, Jeffrey F.,Jindra, Jan,Pedersen, David,Voetmann, Torben
A great deal of empirical research finds that stocks with low market-to-book (MTB) ratios have outperformed stocks with high MTB ratios. Rhodes-Kropf, Robinson, and Viswanathan (RKRV) (2005) separate the MTB ratio into a mispricing component and a growth options component. We investigate the asset pricing implications of this decomposition. We report that RKRV’s mispricing component, but not their growth options component, predicts abnormal returns for up to five years. In addition, using spanning regressions, we find that RKRV’s mispricing component, but not their growth options component, provides incremental information relative to existing asset pricing models. Moreover, after controlling for mispricing, value no longer beats growth, suggesting that RKRV’s measure of mispricing can explain the value premium. In total, our evidence is consistent with a behavioral explanation of the value premium.

Capacity Expansion Options and Optimal Performance-Sensitive Debt
Bensoussan, Alain,Chevalier-Roignant, Benoit,Rivera, Alejandro
We study the optimal exercise of real expansion options of a firm financed with performance-sensitive debt (PSD). The main insights are the following. The investment decision of a firm financed with straight debt is distorted in both timing and scale: it invests less and later than its all-equity financed counterpart. Yet, the inclusion of a performance sensitive clause mitigates such distortions, which provides a rationale for the widespread use of such clauses. Importantly, solving this problem represents a technical contribution because the payoff upon exercise is not necessarily smooth, precluding direct application of the smooth-fit principle.

Capital-Market Consequences of Asymmetric Output-Price Rigidities
Xie, Jin
Firms adjust output prices to cost decreases with a delay relative to cost increases. I document firms' operating income becomes less persistent when their input costs decrease than when their costs increase. The stocks of firms slowly cutting output prices due to asymmetric output-price rigidities also experience high stock return volatility, and their CEOs more frequently manage expectations of financial analysts. I show these results are consistent with a New Keynesian model with trend inflation.

Certainty Equivalent and Utility Indifference Pricing for Incomplete Preferences via Convex Vector Optimization
Birgit Rudloff,Firdevs Ulus

For incomplete preference relations that are represented by multiple priors and/or multiple -- possibly multivariate -- utility functions, we define a certainty equivalent as well as the utility buy and sell prices and indifference price bounds as set-valued functions of the claim. Furthermore, we motivate and introduce the notion of a weak and a strong certainty equivalent. We will show that our definitions contain as special cases some definitions found in the literature so far on complete or special incomplete preferences. We prove monotonicity and convexity properties of utility buy and sell prices that hold in total analogy to the properties of the scalar indifference prices for complete preferences. We show how the (weak and strong) set-valued certainty equivalent as well as the indifference price bounds can be computed or approximated by solving convex vector optimization problems. Numerical examples and their economic interpretations are given for the univariate as well as for the multivariate case.

Debt Covenant Violation, Competition and Cost of New Debt
Butt, Umar
This article empirically shows that the cost of new debt is higher for firms that commit covenant violations. Using a proxy for product market competition to capture exogenous changes to a firm’s competitive environment, I find that the cost is systematically higher for firms that operate in competitive markets. Moreover, I identify channels through which violations can increase the cost of new debt, namely, the incidence, timing and frequency effects, and I document these effects to be more acute for competitive markets. Overall, the study finds that the market prices financial contracts by taking into account the information content of the violation and the risk arising from market competition.

Debt and Profitability: Evidence from Indian Firms
Tripathy, Dr. Sasikanta
Capital structure has been a database issue in financial economics ever since Modigliani and Miller showed in 1958 that given frictionless markets and homogeneous expectations, the capital structure decision of the firm is irrelevant because it does not contribute towards the firm’s growth. The dilemma firms are faced with is making a decision on the capital structure choice to use. The purpose of this paper is to find out the effect of capital structure on financial performance of firms based on ROE, ROA, Tobin’s Q and EPS for the companies listed both at BSE and NSE over the period 2011-2016, measured through a simple regression model. Results indicate that Capital Structure is significantly and positively associated with firm Performance when measured by Tobin s Q, however they report a negative relationship between capital structure with firms’ performance when measured by ROA, and no significant relationship when measured by ROE as well as by EPS. Altogether, the study provides evidence which indicates firm performance is positively or even negatively related to capital structure. One important reason for this conflicting result can be the high cost of borrowing in developing countries like India. This study contributes to the empirical literature on the effect of capital structure on financial performance of Indian firms.

Deep-Learning Based Numerical BSDE Method for Barrier Options
Yu, Bing,Xing, Xiaojing,Sudjianto, Agus
As is known, an option price is a solution to a certain partial differential equation (PDE) with terminal conditions (payoff functions). There is a close association between the solution of PDE and the solution of a backward stochastic differential equation (BSDE). We can either solve the PDE to obtain option prices or solve its associated BSDE. Recently a deep learning technique has been applied to solve option prices using the BSDE approach. In this approach, deep learning is used to learn some deterministic functions, which are used in solving the BSDE with terminal conditions. In this paper, we extend the deep-learning technique to solve a PDE with both terminal and boundary conditions. In particular, we will employ the technique to solve barrier options using Brownian motion bridges.

Disastrous Selling Decisions: The Disposition Effect and Natural Disasters
Henriksson, Matthew
Combining county-level natural disaster data with individual investor transactions, I document evidence of an increased disposition effect for investors impacted by a natural disaster. Natural disasters represent negative shocks to an individual, both financially and psychologically. These results are consistent with investors deriving utility from environmental damages and realized gains/losses. That is, when they experience a negative shock outside their portfolio, they increase their relative propensity to realize gains over losses in their portfolio. This effect is increasing in disaster severity and decreasing in the length of time following the disaster event, suggesting that extreme natural disasters can significantly influence investor behavior, especially within one year following the event.

Do Multiple Credit Ratings Reduce Money Left on the Table? Evidence from U.S. IPOs
Goergen, Marc,Gounopoulos, Dimitrios,Koutroumpis, Panagiotis
We examine initial public offerings (IPOs) with single, multiple, and no credit ratings. We document a beneficial effect of credit ratings provided by the three main credit rating agencies on IPO underpricing, which is amplified by the existence of multiple credit ratings. Multiple ratings also reduce the extent of filing price revisions. Credit rating levels matter for IPOs with more than one rating but not for those with a single rating. Firms with multiple credit ratings also have higher probabilities of survival than those with a single or no rating. Finally, IPOs awarded a first credit rating on the borderline between investment and non-investment grade are more likely to seek an additional rating.

Does Corporate Social Responsibility Reduce Information Asymmetry? Empirical Evidence from Australia
Nguyen, Van Ha,Agbola, Frank W.,Choi, Bobae
This study examines whether corporate social responsibility (CSR) reduces information asymmetry (IA). Using a firm-level CSR dataset of Australian publicly listed firms from 2004 to 2014, we estimate IA models using a fixed-effects panel estimator. We find that CSR performance is negatively associated with IA. Moreover, this negative relationship is stronger for larger firms and firms with stronger market power. We also find that the negative association between CSR and IA decreases for firms with a high level of equity risk. Our results are robust to alternative measures of CSR and IA, model specifications and endogeneity controls.

Does the CAPM Predict Returns?
Hasler, Michael,Martineau, Charles
We provide strong empirical evidence that asset returns can be predicted using the dynamic CAPM. Indeed, the predictive power of the market return predictor transmits to the product of the asset's conditional beta and the market expected return. The dynamic CAPM yields a monthly out-of-sample R2 of about 4% across all test assets, which is of the same order of magnitude as the out-of-sample R2 obtained by predicting market returns using the market return predictor. Strategies exploiting the predictive power of the dynamic CAPM have Sharpe ratios up to 100% larger than those of the corresponding buy-and-hold strategies.

Dynamic investment model of the life cycle of a company under the influence of factors in a competitive environment
O. A. Malafeyev,I. I. Pavlov

Modelling all possible life cycles of a company in a highly competitive economic environment gives a significant advantage to the owner in his business investment activities. This article proposes and analyses a dynamic model of a company's life cycle with known action costs and transition probabilities, that can be affected by an outside influence. For this task, the Markov model was utilized. The proposed model is illustrated on a task of determining an advertising policy for a car dealership, that would increase the stock equity of a company. The result demonstrates the usefulness of a model for use in determining future actions of a company. We also review multiple models of the influence of outside factors on a company's total capitalization.

Enterprise Risk Management and Corporate Governance
Sekerci, Naciye,Pagach, Donald P.
The purpose of this paper is to examine the role Enterprise Risk Management (ERM) plays in corporate governance. We provide evidence on the relationship between ERM and corporate governance using data for a survey on how firms organize their risk management programs. Using survey results, we create a measure of ERM process, yielding valuable firm specific information. We argue that ERM best practices are governance tools used to monitor managerial discretion in risk management, ultimately reducing the agency cost of traditional risk management. Accordingly, the existence of an ERM program is more likely in firms with certain corporate governance practices. Specifically, ERM facilitates monitoring in firms that require more monitoring by certain governance bodies (i.e., independent board directors and large boards), or in those situations where there is absence of large monitoring owners. Our findings overall suggest that firms benefit from the monitoring provided by ERM based on the governance setting the firms have.

Event-Driven Strategies in Crypto Assets
Krüger, Samed,Müller, Maximilian,Betzer, André,Rokitta, Christian
Due to structural, regulatory and security-related advantages, crypto assets attract an unparalleled attention all over the world and lead to a heated discussion, whether crypto assets can be considered as a viable option for alternative investments. However, aside from regulatory uncertainty, a lack of profound academic studies and quantitative time series analysis seems to be a vast entry barrier for institutional investors, leading to the fact that the majority share of crypto assets are still being held by young, risk-tolerant retail investors, with high affinity for blockchain technology and innovation. This paper applies important findings of asset pricing theory on the rising academic field of crypto assets and deduces practical implications for retail and institutional investors. Our study includes descriptive statistics and correlation analysis of crypto and capital markets, as well as an event and price impact analysis. Our empirical findings document no evidence for an increase of market efficiency of crypto assets as proxied by bitcoin and reveal significant inefficiencies, leaving valid arguments for either passive or active investment strategies. In addition, our event study findings show significant evidence for insider trading which should call market regulators for actions to fight tax regulations and ensure a fair market environment.

Fair Value Accounting and Financial Contagion: An Analysis of Marking Up
Tang, Chao
This paper examines how fair value accounting can create financial contagion among banks and therefore increase bank regulators' costs of protecting insured depositors. Prior research mainly focuses on the economic consequences of marking down, whereas I contribute to the literature by providing a novel trade-off of marking up. On the one hand, by marking its assets up, a healthy bank obtains additional regulatory capital to absorb a failing bank, which would otherwise be liquidated in a less efficient secondary market, thereby saving regulators' costs. On the other hand, the otherwise healthy bank becomes more leveraged and thus may face excessive default risk after this acquisition, leading to financial contagion and increased overall costs for bank regulators.

Family Comes First: Reproductive Rights and the Gender Gap in Entrepreneurship
Bulka, Jordan,Zandberg, Jonathan
The gender gap in entrepreneurship is a well-documented puzzle. It refers to the persistent gap between the number of male and female entrepreneurs. We analyze four different data sets that cover six different decades and find strong evidence that better access to reproductive health care increases a woman's propensity to become an entrepreneur. First, we document that access to reproductive health care correlates positively with female entrepreneurial activity. This correlation is driven by women who own large firms, and by women in the middle tercile of wealth. In addition, we find that access to reproductive health care is negatively correlated with the age of female entrepreneurs, suggesting that women with better control over their reproduction can become entrepreneurs at a younger age. For empirical identification, we exploit the 1973 Roe v. Wade Supreme Court ruling and the staggered enactment of state-level Targeted Regulation of Abortion Providers (TRAP) Laws and show that better access to reproductive health services causes higher levels of female entrepreneurship. None of the empirical results hold when tested on men, women above 40, or when examining other placebo professions. Our results suggest that changes in policies securing better reproductive rights can help close this gender gap and empower women who seek to become entrepreneurs.

Grasping asymmetric information in market impacts
Shanshan Wang,Sebastian Neusüß,Thomas Guhr

The price impact for a single trade is estimated by the immediate response on an event time scale, i.e., the immediate change of midpoint prices before and after a trade. We work out the price impacts across a correlated financial market. We quantify the asymmetries of the distributions and of the market structures of cross-impacts, and find that the impacts across the market are asymmetric and non-random. Using spectral statistics and Shannon entropy, we visualize the asymmetric information in price impacts. Also, we introduce an entropy of impacts to estimate the randomness between stocks. We show that the useful information is encoded in the impacts corresponding to small entropy. The stocks with large number of trades are more likely to impact others, while the less traded stocks have higher probability to be impacted by others.

Horizon-unbiased Investment with Ambiguity
Qian Lin,Xianming Sun,Chao Zhou

In the presence of ambiguity on the driving force of market randomness, we consider the dynamic portfolio choice without any predetermined investment horizon. The investment criteria is formulated as a robust forward performance process, reflecting an investor's dynamic preference. We show that the market risk premium and the utility risk premium jointly determine the investors' trading direction and the worst-case scenarios of the risky asset's mean return and volatility. The closed-form formulas for the optimal investment strategies are given in the special settings of the CRRA preference.

How Cognitive Ability and Financial Literacy Shape the Demand for Financial Advice at Older Ages
Kim, Hugh Hoikwang,Maurer, Raimond,Mitchell, Olivia S.
We investigate how cognitive ability and financial literacy shape older Americans’ demand for financial advice using an experimental module in the 2016 Health and Retirement Study. We show that cognitive ability and financial literacy strongly improve the quality, but not the quantity, of financial advice sought. Most importantly, the financially literate and more cognitively able tend to seek financial help from professionals rather than family members, and they are less likely to accept so-called ‘free’ financial advice that may entail conflicts of interest. Nevertheless, those with higher cognitive function also tend to distrust financial advisors, leading them to eschew their services.

How Time Constraint Affects the Disposition Effect?
Niu, Xiaofei,Li, Jianbiao
Time constraint is a central aspect of financial decision making. This paper experimentally examines the effect of time constraint on the disposition effect, which refers to the empirical fact that investors have a higher propensity to sell stocks with capital gains compared to stocks with capital losses. We distinguish time pressure from time constraint by implementing three treatments: no time constraint (NTC), 20 seconds time constraint (20TC), and 10 seconds time constraint (10TC). The experimental results show that time constraint affects the disposition effect at some conditions, i.e. the 10TC treatment, in which subjects perceive more time pressure, significantly reduces the disposition effect; this treatment effect, however, vanishes in 20TC treatment, where feelings of stress do not differ from the NTC treatment. Self-control is one of the psychological mechanisms that explains why time pressure reduces the disposition effect.

ICT Capital-Skill Complementarity and Wage Inequality: Evidence from Fourteen OECD Countries
Hiroya Taniguchi,Ken Yamada

Abstract Although it is well known that wage inequality has evolved over recent decades, it is not known the extent to which the evolution of wage inequality is attributed to observed factors such as capital and labor quantities or unobserved factors such as labor-augmenting technology in many countries. To examine this issue, we use cross-country panel data from 14 OECD countries for the years 1970 to 2005 and estimate the aggregate production function extended to allow for capital-skill complementarity and skill-biased technological change. Our results point to a strong influence of the observed expansion of ICT capital equipment around the world.

Innovation in Newly Public Firms: The Influence of Government Grants, Venture Capital, and Private Equity
Shinkle, George A.,Suchard, Jo-Ann
We investigate the influence of government grants, venture capital (VC), and private equity (PE) funding on innovation in newly public firms. We examine innovation inputs (R&D), innovation outputs (patents), and the quality thereof (patent citations). We contribute to understanding of the mechanisms between government grants and subsequent VC and PE funding and innovation. We find that grants encourage VC funding but not PE funding. Grants and VC/PE funding are generally complements regarding innovation except grants substitute for VC funding on innovation inputs. Furthermore, we observe that the firm-level heterogeneity of VC/PEs significantly influences innovation in portfolio companies.

Intermediated Implementation
Anqi Li,Yiqing Xing

We examine problems of "intermediated implementation." An example is sales, whereby retailers compete through offering consumption bundles to consumers with hidden tastes, whereas a manufacturer with a potentially different goal than retailers' can regulate only the sold goods but not the charged prices by legal barriers. We study how the manufacturer can implement through retailers any incentive compatible and individually rational social choice rule for consumers. We demonstrate the effectiveness of per-unit fee schedules and distribution regulations, which hinges on whether retailers have private or interdependent values. We formulate problems of this kind and give applications to taxation and healthcare.

Investment in EV charging spots for parking
Brendan Badia,Randall Berry,Ermin Wei

As demand for electric vehicles (EVs) is expanding, meeting the need for charging infrastructure, especially in urban areas, has become a critical issue. One method of adding charging stations is to install them at parking spots. This increases the value of these spots to EV drivers needing to charge their vehicles. However, there is a cost to constructing these spots and such spots may preclude drivers not needing to charge from using them, reducing the parking options for such drivers\color{black}. We look at two models for how decisions surrounding investment in charging stations on existing parking spots may be undertaken. First, we analyze two firms who compete over installing stations under government set mandates or subsidies. Given the cost of constructing spots and the competitiveness of the markets, we find it is ambiguous whether setting higher mandates or higher subsidies for spot construction leads to better aggregate outcomes. Second, we look at a system operator who faces uncertainty on the size of the EV market. If they are risk neutral, we find a relatively small change in the uncertainty of the EV market can lead to large changes in the optimal charging capacity.

Next-Gen Financial Advice: Digital Innovation and Canada’s Policymakers
Grace, Chuck
While the financial services industry wrestles with the challenges of change, our policymakers have an opportunity to take a lead role in defining Canada’s place within the global digital advice landscape. There are numerous creative and exciting solutions being discussed. What we haven’t seen a lot of are clientfacing holistic solutions â€" and what we don’t have is much time. This paper provides a series of steps for regulators and policymakers to follow that will improve innovation for incumbents and start-ups alike, all while providing an enhanced customer experience in financial advice. Firms are dealing with a looming perfect storm â€" fee compression, shifting demographics, unrelenting regulatory changes and an erosion in the number of human advisors as advisors who are part of the baby boom look to their own retirement. In this context, technology should be viewed as a savior, rather than a threat. We define a five-year aspiration for the application of digital technology to prudent and valued financial advice. There are several myths we were able to dispel as a result of our research, which we hope will form the basis for a discussion about what’s needed to facilitate a higher level of digital adoption. We nickname it “Next Generation Digital Advice.” The guiding principles and best practices encompass a holistic view of the client, objective data-driven recommendations, full transparency and ease of use. At a high level, the next generation of digital advice offers an opportunity for stronger client impact. It will see human advisors complemented by digital collaboration through technology that is not disruptive but generally proven, likely economical and widely available. Our current regulations per se are not a barrier to this next generation of advice â€" but our regulatory practices are. And just how much the industry will be disrupted matters because wholesale disruption of our financial services comes with wholesale economic risk. Policymakers play an important role in this transformation starting with a need to take the lead and get in front of the innovations in order to understand their full implications. We need to move swiftly towards open banking and improving on the benchmark set in Europe, break down regulatory silos to allow data mobility in furtherance of stronger client outcomes, update advisor proficiencies for a new normal where technical skills are automated and behavioural skills are required and de-risk the decision to innovate â€" for start-ups and incumbents alike.

On the Cyclical Properties of Hamilton's Regression Filter and Refinements
Schüler, Yves Stephan
Hamilton (2017) criticises the HP filter because of three drawbacks (i. spurious cycles, ii. end-of-sample bias, iii. ad hoc assumptions regarding the smoothing parameter) and proposes a regression filter as an alternative. I demonstrate that Hamilton's regression filter is partially subject to the same drawbacks. For example, Hamilton's ad hoc formulation of a 2-year regression filter implies a cancellation of two-year cycles and an amplification of cycles longer than typical business cycles, leading to inconsistencies with the NBER business cycle chronology. Furthermore, I illustrate that Hamilton's regression filter does not fulfil established criteria on the desired properties of filters. For example, Hamilton's filter does not approximate the ideal band pass filter, does not have constant cyclical properties across time series, and it induces phase shifts into stationary data. I discuss two refinements to bridge Hamilton's and the established view. I find that an asymmetric HP filter and a 1-quarter regression filter can best reconcile both perspectives.

On the Time-Varying Efficiency of Cryptocurrency Markets
Akihiko Noda

This study examines whether the market efficiencies of major cryptocurrencies (e.g., Bitcoin, Ethereum, and Ripple) change over time based on the adaptive market hypothesis (AMH) of Lo (2004). In particular, we measure the degree of market efficiency using Ito et al.'s (2014, 2016, 2017) generalized least squares-based time-varying model. The empirical results show that (1) the degree of market efficiency varies with time in cryptocurrency markets, (2) the market efficiency level of Bitcoin is higher than that of the other markets over most periods, and (3) the market efficiency of cryptocurrencies has evolved. We conclude that the results support the AMH for the established cryptocurrency market.

Policy Uncertainty, Financial Stability, and Stress Testing
Kupiec, Paul
Since the 2009 Supervisory Capital Assessment Program (SCAP), US regulators have employed a representative bank model as the benchmark of comparison in mandatory stress test exercises. For risk management functions, a bank’s own stress model must be calibrated to reflect the bank’s historical performance. I analyze stress test forecasts produced by individual bank and a representative bank stress test models. Each model is calibrated using different data, but an identical statistical approach similar to the Fed’s 2009 SCAP CLASS model. I compare stress test forecasts to actual institution performance over the first 3 years of the financial crisis. Forecasts from the representative bank model differ dramatically from those produced by bank-specific models and actual outcomes. The results highlight the policy uncertainty inherent in using stress tests, both to set minimum bank capital requirements and to assess the capital adequacy needed to maintain banking system stability.

Political Corruption and Household Finance
Bu, Di,Hanspal, Tobin,Liao, Yin
We study the effect of political corruption on household financial well-being using microdata from the United States and China. Our identification strategy exploits recent anti-corruption campaigns in China as exogenous shocks to the perceived level of corruption held by individuals. Households respond to reduced corruption by increasing stock market participation, financial risk taking, and overall financial development. These results can be explained partially by the direct costs of corruption on household societal wealth, and predominantly by the non-pecuniary effect on households' trust and perceptions of institutional quality. Our findings suggest that political corruption largely impedes household financial development.

Prediction Law of Mixed Gaussian Volterra Processes
Tommi Sottinen,Lauri Viitasaari

We study the regular conditional law of mixed Gaussian Volterra processes under the influence of model disturbances. More precisely, we study prediction of Gaussian Volterra processes driven by a Brownian motion in a case where the Brownian motion is not observable, but only a noisy version is observed. As an application, we discuss how our result can be applied to variance reduction in the presence of measurement errors.

Private Information Index and Proprietary Costs
Floros, Ioannis V.,Sivaramakrishnan, Shiva,Zufarov, Rustam
Disclosure theory suggests that firms have incentives to avoid dissemination of proprietary information. We develop a firm-level private information index with three unique features. First, the index is a direct measure of the nature and magnitude of private information that is proprietary. We construct it based on the premise that private information at any given point in time will be realized in measurable terms in future financial statements. Second, our measure is multi-dimensional in nature, which allows us to capture variations in proprietary information across firms. Third, as a measure of proprietary information, it is not specific to any one setting. We use this index to test the proprietary cost hypothesis by examining a firm’s equity financing choice between private investments in public equity and seasoned equity offerings. Our tests provide strong support for the hypothesis. The results are robust to alternate index specifications and other factors that influence a firm's choice between private and public equity markets.

Public Disclosures and Information Asymmetry: A Theory of the Mosaic
Cheynel, Edwige,Levine, Carolyn
We model an information mosaic in which multiple signals, one gathered by an informed trader and the other publicly disclosed by the manager of the firm, are combined to estimate firm value. Under testable conditions, voluntary disclosures lead to higher ex-ante information asymmetry and expected profits for the informed trader by allowing him to refine his trading strategy and complete his information mosaic. The informed trader’s ability to combine information and enhance his advantage is more prevalent when there is more uncertainty about whether the news is favorable or unfavorable, the manager is more likely to be informed, and the manager’s information is precise (i.e., disclosure quality is high).

Regulation Spillovers Across Cryptocurrency Markets
Borri, Nicola,Shakhnov, Kirill
Several countries have already introduced restrictions on trading of cryptocurrencies, and many more are evaluating whether to follow suit. We document an unprecedented drop in trading volume on the Chinese cryptocurrency market after a recent regulatory change by the Chinese authorities that severely restricted bitcoin trading. This paper shows how changes in domestic regulation not only have large effects on the domestic cryptocurrency market but also produce large international spillovers. Specifically, we observe a large increase in trading volume and relative bitcoin prices in exchange for Korean won, Japanese yen, and U.S. dollars, and on Chinese peer-to-peer exchanges.

Subjective Models of the Macroeconomy: Evidence from Experts and a Representative Sample
Andre, Peter,Pizzinelli, Carlo,Roth, Christopher,Wohlfart, Johannes
We propose a method to measure people's subjective models of the macroeconomy. Using a representative sample of the US population and a sample of experts we study how expectations about the unemployment rate and the inflation rate change in response to four different hypothetical exogenous shocks: a monetary policy shock, a government spending shock, a tax shock, and an oil price shock. While expert predictions are mostly quantitatively aligned with standard dynamic stochastic general equilibrium models and vector auto-regression evidence, there is strong heterogeneity in the predictions in the representative panel. While households predict changes in unemployment that are qualitatively in line with the experts for all four shocks, their predictions of changes in inflation are at odds with those of experts both for the tax shock and the interest rate shock. People's beliefs about the micro mechanisms through which the different macroeconomic shocks are propagated in the economy strongly affect how aligned their predictions are with those of the experts. More educated and older respondents form their expectations more in line with experts, consistent with roles for cognitive limitations and learning over the life-cycle. Our findings inform the validity of central assumptions about the expectation formation process and have important implications for the optimal design of fiscal and monetary policy.

Ten Applications of Financial Machine Learning
Lopez de Prado, Marcos
This article describes ten notable financial applications where ML has moved beyond hype and proven its usefulness. This success does not mean that the use of ML in finance does not face important challenges. The main conclusion is that there is a strong case for applying ML to current financial problems, and that financial ML has a promising future ahead.

The Economic Gordian Knot of Brexit: An East Asian Perspective
Ruiz Estrada, Mario Arturo,Koutronas, Evangelos,Park, Donghyun
We evaluate the impact of Brexit on Asian economies using a new index - the TIFTEL-Index (The International Financial-Trade Exchange Leaking Index). The index is based on three main variables, namely (1) international trade exchange marginal rate (∆Τ’), (2) international financial exchange marginal rate (∆σ’), and (3) GDP in real prices growth marginal rate (∆γ). The main objective of this paper is to use the index to analyze and compare pre-Brexit versus post-Brexit international trade and international financial transactions between Asia and Europe. The comparative analysis indicates that Brexit will have only a limited negative effect on the world economy. In addition, Brexit will affect East Asia more than ASEAN.

The Leapfrog Model: Venture Capital as a Cure to Africa's Funding Paralysis
Phillips, Olayanju
Based on current trends, Africa’s population is projected to double in size by 2050. Lagos leads this exponential population explosion as the fastest growing city in Africa, growing at 77 people per hour. By 2030, Africa’s middle- and high-income groups are expected to grow by 100 million. Africa’s 1.1 billion population is expected to have doubled in 2050 and quadrupled in 2100. This significantly increases the consumer population and makes Africa a rapidly expanding market that attracts investors. Despite these projections, the African continent is palpably unprepared. This paper argues that the financing of startups in critical sectors of Africa's economy through incentivized venture capital funding can be strategic in developing Africa's economy.

The Role of Boutique Financial Advisors in Mergers and Acquisitions
Loyeung, Anna
This study examines the choice of boutique financial advisors in mergers and acquisitions, and the consequences of this choice on deal outcomes and post-acquisition performance. Boutique advisors often specialize in a particular industry and focus exclusively on providing advice in mergers and acquisitions. The results suggest that boutique financial advisors are preferred when the deal is considered complex and when information asymmetry is high. The study finds that the benefits of hiring a boutique advisor flow to both the acquirers and the target firms. Acquiring firms benefit in terms of improved post-merger performance, while target firms benefit in terms of higher completion of value-enhancing deals and positive cumulative abnormal returns. Overall, these results provide support for the growing popularity of boutique financial advisors in the Australian market.

The Valuation of Equity Options in the Perpetual-Debt Structural Model
Barone, Gaia
We propose some formulas for the valuation of equity options in the Perpetual-Debt Structural Model (PDSM), where stockholders have a perpetual American option to default.Our formulas are expressed in terms of binary barrier options, using the results obtained by Rubinstein and Reiner (1991). We also use the results obtained by Barone (2013), where it is proved that perpetual American options follow a geometric Brownian motion, under the standard Black-Scholes-Merton assumptions.

Top performing stocks recommendation strategy for portfolio
Kartikay Gupta,Niladri Chatterjee

Stock return forecasting is of utmost importance in the business world. This has been the favourite topic of research for many academicians since decades. Recently, regularization techniques have reported to tremendously increase the forecast accuracy of the simple regression model. Still, this model cannot incorporate the effect of things like a major natural disaster, large foreign influence, etc. in its prediction. Such things affect the whole stock market and are very unpredictable. Thus, it is more important to recommend top stocks rather than predicting exact stock returns. The present paper modifies the regression task to output value for each stock which is more suitable for ranking the stocks by expected returns. Two large datasets consisting of altogether 1205 companies listed at Indian exchanges were used for experimentation. Five different metrics were used for evaluating the different models. Results were also analysed subjectively through plots. The results showed the superiority of the proposed techniques.

Transaction Costs of Factor Investing Strategies
Li, Feifei,Chow, Tzee-man,Pickard, Alex,Garg, Yadwinder
Although hidden, implicit market impact costs of factor investing strategies may substantially erode the strategies' expected excess returns. The authors explain these market impacts costs and model them using rebalancing data of a suite of large and longstanding factor investing indices. They introduce a framework to assess the costs of rebalancing activities, and attribute these costs to characteristics such as rate of turnover and the concentration of turnover, which intuitively describe the strategies' demands on liquidity. The authors evaluate a number of popular factor-investing strategy implementations and identify how index construction methods, when thoughtfully designed, can reduce market impact costs.

We Three Kings: Disintermediating Voting at the Index Fund Giants
Griffin, Caleb N.
The meteoric rise of passive investing has placed three large index funds in a new and pivotal role as the arbiters of corporate law controversies and the framers of market-wide governance standards. Collectively, the “Big Three” â€" Vanguard, BlackRock, and State Street â€" control a supermajority of index funds assets. The single largest investor in almost 9 out of 10 publicly-traded companies is one of the Big Three. As their growth is projected to continue unabated, it is difficult to overstate the centrality and importance of these institutions for the future of corporate governance.Society is only just beginning to grapple with the implications of this concentrated economic power. On the one hand, there is potential for this power to be used for good. Index fund investors are uniquely concerned with long-term, sustainable economic growth and stability, and they are likely to be more representative of the average American investor than many other financial industry actors. Concentrating the power of many dispersed “human investors” through index fund voting has the potential to better align corporate behaviors with the interests of a broad swath of American society. On the other hand, to the extent that this power is divorced from the actual interests and perspectives of individual investors, index funds’ considerable power may instead be used to advance the interests of index fund agents or other special interests in a way that is harmful to society at large.As it currently stands, individual index fund investors are utterly unable to express their preferences in how voting decisions are made. They cannot rely upon index fund providers to take their unique interests and values into consideration when deciding how to vote (or even to know what these interests and values might be). Further, index fund investors cannot even indirectly express their preferences by selecting a particular fund or a particular index fund provider that is more likely to vote in line with their interest and values, since the shares controlled by different individual funds are nearly always voted in the exact same manner and since the different index fund providers share very similar voting philosophies and priorities. As a result, a small number of individuals at a handful of index fund providers wield increasingly dominant power with only very limited accountability.To address this problem, a number of corporate law scholars have recently proposed solutions that would limit index fund providers’ power in some way, whether by requiring increased transparency, placing caps on index funds’ ownership of a given company or industry, or even going so far as to disenfranchise index funds entirely. Instead of these solutions, which generally rely upon regulators, auditors, or index fund advisers themselves to promote better outcomes, this Article proposes a novel solution that would harness the voice of individual index fund investors in the decision-making process. This approach builds off of the technological innovations that have permitted index funds to streamline the process of deciding how to vote their funds’ shares. It proposes using this infrastructure to overcome individual shareholders’ rational apathy instead of using that infrastructure merely to simplify the work of index fund employees. The involvement of individual investors could take one of three forms: (1) allowing individual investors to elect to have the votes corresponding to their indirect share ownership cast according to the recommendations of a particular agent (such as the index fund provider, portfolio company management, a particular proxy adviser, or another institutional investor), (2) requiring index fund providers to seek more information about the characteristics and values of their investors, which funds would use to better inform their voting decisions, or (3) giving individual investors the opportunity to shape the voting guidelines used by index funds by completing a general, issue-based survey about how they desire to vote on a number of key corporate governance issues, the answers to which will guide fund advisors in voting on company-specific questions. The uniting feature of all three approaches is that they would involve individual investors in the voting process to a greater degree, thereby diminishing the power of index fund agents, mitigating concerns about the concentrated power of index funds, and reducing agency costs. The proposals set forth in this Article set out to re-democratize shareholder democracy and to give voice to individuals typically shut out of the corporate decision-making process. With passively-indexed investments set to overtake active investments in the very near future, now is a crucial time to map the future exercise of funds’ corporate governance power.