Research articles for the 2021-04-01

A Critical Perspective on the Conceptualization of Risk in Behavioral and Experimental Finance
Holzmeister, Felix,Huber, Christoph,Palan, Stefan
Risk is one of the key aspects in financial decision-making and therefore an integral part of the behavioral economics and finance literature. Focusing on the conceptualization of the term "risk", which researchers have addressed from numerous angles, this comment aims to offer a critical perspective on the interactions between risk preferences (a latent trait), risk perceptions (how individuals judge whether something is risky), and risk-taking behavior as distinct concepts, and hence to guide future research on (individual-level) decision-making processes in this direction.

A new spin on optimal portfolios and ecological equilibria
Jerome Garnier-Brun,Michael Benzaquen,Stefano Ciliberti,Jean-Philippe Bouchaud

We consider the classical problem of optimal portfolio construction with the constraint that no short position is allowed, or equivalently the valid equilibria of multispecies Lotka-Volterra equations, in the special case where the interaction matrix is of unit rank, corresponding to a single-resource MacArthur model. We compute the average number of solutions and show that its logarithm grows as $N^\alpha$, where $N$ is the number of assets or species and $\alpha \leq 2/3$ depends on the interaction matrix distribution. We conjecture that the most likely number of solutions is much smaller and related to the typical sparsity $m(N)$ of the solutions, which we compute explicitly. We also find that the solution landscape is similar to that of spin-glasses, i.e. very different configurations are quasi-degenerate. Correspondingly, "disorder chaos" is also present in our problem. We discuss the consequence of such a property for portfolio construction and ecologies, and question the meaning of rational decisions when there is a very large number "satisficing" solutions.

Ancestral Connection and Alliances
Pan, Yihui,Peng, Xiaoxia
This paper studies the cultural determinants of firm boundaries. We find that the historicalancestral composition of the area where firms locate plays an important role in their choices ofpartners when forming business alliances and of the location of the new venture. Partnering firmsexperience significantly better performance when the ancestral connection between theirheadquarters states is stronger. Further, using data on ancestral connections between partners’ keyemployees, we find that shared values and better communication between firms’ stakeholders (e.g.,inventors), as opposed to connections between corporate leaders, likely underline the role ofancestral connection. Our results highlight the importance of ancestral connection in shaping firmboundaries, above and beyond geographic and economic determinants, thus the important roleculture plays in inducing cooperation between firms when facing contractual incompleteness inthe real business world.

Big Banks, Household Credit Access, and Intergenerational Economic Mobility
Mayer, Erik J.
Consolidation in the United States banking industry has led to larger banks. I find that low income households face reduced access to credit when local banks are large. This result appears to stem from large banks’ comparative disadvantage using soft information, which is particularly important for lending to low income households. In contrast, the size of local banks has little or no effect on high income households. Consistent with low income parents’ credit constraints limiting investment in their children’s human capital, areas with larger banks exhibit a greater sensitivity of educational attainment to parental income, and less intergenerational economic mobility.

Board Gender Diversity and Investment Inefficiency
Yu, Chang
This paper investigates the impact of board gender diversity on a firm’s investment inefficiency. We document that firms with gender-diverse boards have significantly less investment inefficiency than firms without gender-diverse board and the fraction of female directors on the board is sigificantly negative correlated with investment inefficiency. The instrumental variable approach indicates that the negative relation is robust after addressing endogeneity concerns. Subsample analysis indicates that the effect of board gender diversity on investment inefficiency is focused on firms with CEO- chairman duality and firms with longer CEO tenures. We also document that board independence is a channel for board gender diversity to reduce investment inefficiency.

Bond Implied Risks Around Macroeconomic Announcements
Li, Xinyang
Using a large panel of Treasury futures and options, I construct model-free measures of bond uncertainty and tail risks across different tenors from 2000 to 2020. I find that bond tail risk 1) negatively correlates with stock tail risk in general, but the correlation turns positive prior to and around three financial crises; 2) It increased dramatically before the 2008 Financial Crisis and in March 2020 foreshadowing the extreme challenges in the Treasury bond markets; 3) and has significantly decreased in recent years under zero-lower-bound and forward guidance. I then study the behavior of bond tail and uncertainty risk measures around FOMC announcements and document three novel findings: First, bond uncertainty increases three to two days prior to the announcements and reverts back upon release, due to an increase in call option prices rather than puts. Second, yields of 5, 10, and 30 year Treasuries decline by 1bps on the day before the announcement. Third, uncertainty risk cannot help explain the pre-FOMC announcement drift.

Characterizing Life-Cycle Dynamics of Annual Days of Work,Wages, and Cross-Covariances
Aktas, Koray
This paper investigates the dispersions in days worked and wages by adapting a novel semi-parametric specification that minimizes assumptions about life-cycle labor income dynamics. Data for Italy shows a substantial increase in income inequality after age 50 for males over the time span from 1985 to 2012, which is remarkably driven by the variations in days worked rather than wages. Results show that this increase is determined by permanent changes in the number of days worked. I also introduce an empirical strategy to decompose the cross-covariances of wages and working days to quantify the permanent and transitory responses of days worked to wage shocks. A one-percent increase in permanent wages increases the permanent days worked by 0.8% at the age of 28, while this increase is about 0.3% at the age of 55. Despite the strong reaction of days of work to wage shocks early in careers, the correlation coefficients are small, indicating that only a small share of variation in permanent days worked â€" which shapes the permanent income inequality â€" is explained by the changes in wages.

Chasing the Beta, Losing the Alpha
Hamaui, Andrea,Jaffard, Pierre
In this paper, we tackle the Beta anomaly, namely the fact that high-Beta assets tend to be associated with lower risk-adjusted returns than low-Beta assets, and connect it to mutual funds’ expectations. We present a model with two types of investors, mutual funds and hedge funds, with heterogeneous market expectations and margin constraints. We show that the Beta anomaly is especially present for stocks purchased by over-optimistic mutual funds. On the empirical side, we first introduce a mutual fund-level measure of market expectations. Then, portfolio analyses and regressions confirm the model’s prediction. The results are robust to alternative definitions of the mutual funds’ market beliefs variable that correct for stock picking, and carry predictive power for mutual funds’ returns.

Designing a NISQ reservoir with maximal memory capacity for volatility forecasting
Samudra Dasgupta,Kathleen E. Hamilton,Arnab Banerjee

Forecasting the CBOE volatility index (VIX) is a highly non-linear and memory-intensive task. In this paper, we use quantum reservoir computing to forecast the VIX using S&P500 (SPX) time-series. Our reservoir is a hybrid quantum-classical system executed on IBM's 53-qubit Rochester chip. We encode the SPX values in the rotation angles and linearly combine the average spin of the six-qubit register to predict the value of VIX at the next time step. Our results demonstrate a potential application of noisy intermediate scale quantum (NISQ) devices to complex, real world applications.

Detection of False Investment Strategies through FWER and FDR (Seminar Slides)
Lopez de Prado, Marcos
Financial systems rarely allow experimentation. For example, we cannot reproduce the flash crash of 2010 while controlling for environmental conditions. As a result, much financial research relies on the statistical analysis of finite (historical) datasets, where: (a) Time series datasets are limited, and (b) The investment universe is limited.The implication is that a large number of hypotheses are tested on the same observations. In the context of asset management, this situation leads to false investment strategies and losses, particularly among quantitative funds.This seminar explains how to detect false investment strategies by controlling for the familywise error rate (FWER) and the false discovery rate (FDR) of an organization. It is part of Cornell University's ORIE 5256 course.

Do Risk Disclosures Matter When It Counts? Evidence from the Swiss Franc Shock
Hail, Luzi,Muhn, Maximilian,Oesch, David
We examine the relation between disclosure quality and information asymmetry among market participants following an exogenous shock to macroeconomic risk. In 2015, the Swiss National Bank abruptly announced that it would abandon the longstanding minimum euro‐Swiss franc exchange rate. We find evidence suggesting that firms with more transparent disclosures regarding their foreign exchange risk exposure ex ante exhibit significantly lower information asymmetry ex post. The information gap in bid‐ask spreads appears within 30 minutes of the announcement and persists for two weeks, during which new information gradually substitutes for past disclosures. We validate the information dynamics of past risk disclosures with three field surveys: (1) Sell‐side analysts emphasize the importance of existing (risk) disclosures in evaluating the translational and transactional effects of the currency shock. (2) Lending banks’ credit officers rely on past disclosures as the primary information source available for smaller (unlisted) firms in the immediate aftermath of the shock. (3) Investor‐relations managers use existing financial filings as a key resource when communicating with external stakeholders. The results suggest that historical disclosures help investors attenuate information asymmetry in light of unexpected news.

Do women empower other women? Empirical evidence of female pervasiveness and firm risk-taking
CIAPPEI, CAMILLA,Liberatore, Giovanni,Terzani, Simone
This study investigates the effect of gender pay gap, a measure of female pervasiveness, on the volatility of cash flow margin and profitability of UK listed firms. As long as women receive lower compensation than men, ceteris paribus, the gender pay gap explains women’s role in a firm and their power to influence the decision-making process. Our findings show that female pervasiveness reduces firm risk-taking. These results are robust to several additional tests providing evidence that gender-based differences are significant if women hold a higher representation in the entire company and are empowered to make agreements and form coalitions.

Exceptionally Low Interest Rate Policy, Risk-Taking Channel, and Bank Competition: Evidence from Loan-level Data
Shikimi, Masayo
This study investigates how bank competition affects the transmission of monetary policy through risk-taking channel. Using Japanese matched bank-firm loan data from the fiscal year 2005 to 2018, we test whether banks with weak balance-sheet lend to risky firms during low interest rate environment than banks with strong balance-sheet and their degree of risky lending is enhanced by bank competition. We find that transmission of monetary policy through risk taking channel vary according to bank competition. Risky lending by banks with poor capital during the low interest rate period is enhanced by bank competition. After the introduction of negative interest rate policy, the bank competition has a nonlinear effect on risk taking behavior of banks with abundant liquidity. Our findings remain mostly unchanged after conducting several robustness checks. Our results suggest that the effects of monetary policy through the risk-taking channel are asymmetrical and depend on bank competition in lending markets.

Factor-Investing and Asset Allocation Strategies: A Comparison of Factor Versus Sector Optimization
Bessler, Wolfgang,Taushanov, Georgi,Wolff, Dominik
Given the tremendous growth of factor allocation strategies in active and passive fund management, we investigate whether either asset allocation strategies based on factors or sectors provide investors with a superior portfolio performance. Our focus is on comparing factor versus sector allocation as some recent empirical evidence indicates the dominance of sector over country portfolios. We analyze the performance and performance differences of sector and factor portfolios for various weighting and portfolio optimization approaches including ‘equal-weighting’ (1/N), ‘risk-parity’ (RP), minimum-variance (MinVar), mean-variance (MV), Bayes-Stein (BS) and Black-Litterman (BL) by employing a sample-based approach in which the sample moments are the input parameters for the allocation model. For the period from May 2007 to November 2020, our results clearly reveal that, over longer investment horizons, factor portfolios provide relative superior performances. For shorter periods, however, we observe time varying and alternating performance dominances as the relative advantage of one over the other strategy depends on the economic cycle. We find that during “normal” times factor portfolios clearly dominate sector portfolios, whereas during crisis periods sector portfolios are superior offering better diversification opportunities.

Financial Reforms and Innovation: A Micro-Macro Perspective
Boikos, Spiros,Bournakis, Ioannis,Christopoulos, Dimitris,McAdam, Peter
We develop a horizontal R&D growth model that allows us to investigate the different channels through which financial reforms affect R&D investment and patent activity. First, a “micro” reform that abolishes barriers to entry in the banking sector produces a straightforward result: a decrease in lending rates which stimulates R&D investment and economic growth. Second, a “macro” reform that removes restrictions on banks’ reserves and credit controls. While this reform increases liquidity, it also increases the risk of default, potentially raising the cost of borrowing. This we dub the “reserves paradox” â€" this makes banks offset the rise in the default rate with a higher spread between loans and deposit rates. Thus our model suggests that whilst micro reforms boost innovation, macro reforms may appear negative. We test and find empirical support for these propositions using a sample of 21 OECD countries.

Financial Risk Meter Based on Expectiles
Ren, Rui,Lu, Meng-Jou,Li, Yingxing,Härdle, Wolfgang K.
The Financial Risk Meter (FRM) is an established mechanism that, based on conditional Value at Risk (VaR) ideas, yields insight into the dynamics of network risk. Originally, the FRM has been composed via Lasso based quantile regression, but we here extend it by incorporating the idea of expectiles, thus indicating not only the tail probability but rather the actual tail loss given a stress situation in the network. The expectile variant of the FRM enjoys several advantages: Firstly, the coherent and multivariate tail risk indicator conditional expectile-based VaR (CoEVaR) can be derived, which is sensitive to the magnitude of extreme losses. Next, FRM index is not restricted to an index compared to the quantile based FRM mechanisms, but can be expanded to a set of systemic tail risk indicators, which provide investors with numerous tools in terms of diverse risk preferences. The power of FRM also lies in displaying FRM distribution across various entities every day. Two distinct patterns can be discovered under high stress and during stable periods from the empirical results in the United States stock market. Furthermore, the framework is able to identify individual risk characteristics and capture spillover effects in a network.

Going Private Transactions and Firm Innovation: Evidence from Japanese Management Buy-outs
Kawanishi, Takuya
This paper empirically examines the impact of exiting the stock market on corporate innovation activities using Japanese going private type MBO data. Difference-in-differences analysis in regression framework is implemented on panel data consisting of firms that conducted public-to-private MBO and matched firms. Also, hypotheses regarding ex-post firm innovation activities are tested using difference-in-difference-in-differences analysis. The results do not show significant effects of going private transactions on firm innovation activities among the whole MBO firms. However, I find that firms with low ex-ante debt ratios are suppressed in their ex-post innovation activities, which suggests the existence of debt overhang, where the increased debt caused by MBO inhibits innovation activities.

Has the Strengthening of Appraisal Rights Led to an Increase in Takeover Premiums?
Huang, Yuxiao,Jetley, Gaurav,Ji, Xinyu
Two Delaware appraisal related developments occurred in the summer of 2007. These developments have made it easier for target shareholders to seek appraisal, thus strengthening Delaware appraisal rights. Recent studies have documented empirical patterns that associate stronger appraisal rights with higher overall takeover premiums for all appraisal eligible deals. Meanwhile, the finance literature has long discussed the competitive nature of the market for corporate control. If buyers have already been paying competitive prices, the deal prices are unlikely to experience an overall increase in response to stronger appraisal rights, which protect minority target shareholders when they are under-paid at sub-market rates in M&A transactions. In this paper, we revisit the empirical patterns documented by recent studies and find that, consistent with the finance literature, there is no evidence that the strengthening of appraisal rights has led to an overall increase in takeover premiums across all appraisal eligible deals.

Inventory Management with Trade Policy Uncertainty: Evidence from Chinese Exporters
Zhao, Xiaotao
This paper empirically investigates how exporting firms manage their inventorystocks in response to an exogenous trade policy uncertainty shock. Using firm-leveldata on inventory and exports over the period around China’s WTO accession, weshow that a reduction in trade policy uncertainty significantly increases exportingfirms’ inventory holdings. We also find that the reduction in trade policy uncertaintyincreases the frequency and the average volume of export transactions.

JDOI Variance Reduction Method and the Pricing of American-Style Options
Auster, Johan,Mathys, Ludovic,Mäder, Fabio
The present article revisits the Diffusion Operator Integral (DOI) variance reduction technique originally proposed in [HP02] and extends its theoretical concept to the pricing of American-style options under (time-homogeneous) Lévy stochastic differential equations. The resulting Jump Diffusion Operator Integral (JDOI) method can be combined with numerous Monte Carlo based stopping-time algorithms, including the ubiquitous least-squares Monte Carlo (LSMC) algorithm of Longstaff and Schwartz (cf. [Car96], [LS01]). We exemplify the usefulness of our theoretical derivations under a concrete, though very general jump-diffusion stochastic volatility dynamics and test the resulting LSMC based version of the JDOI method. The results provide evidence of a strong variance reduction when compared with a simple application of the LSMC algorithm and proves that applying our technique on top of Monte Carlo based pricing schemes provides a powerful way to speed-up these methods.

Limit Theorems for Default Contagion and Systemic Risk
Hamed Amini,Zhongyuan Cao,Agnes Sulem

We consider a general tractable model for default contagion and systemic risk in a heterogeneous financial network, subject to an exogenous macroeconomic shock. We show that, under some regularity assumptions, the default cascade model could be transferred to a death process problem represented by balls-and-bins model. We also reduce the dimension of the problem by classifying banks according to different types, in an appropriate type space. These types may be calibrated to real-world data by using machine learning techniques. We then state various limit theorems regarding the final size of default cascade over different types. In particular, under suitable assumptions on the degree and threshold distributions, we show that the final size of default cascade has asymptotically Gaussian fluctuations. We next state limit theorems for different system-wide wealth aggregation functions and show how the systemic risk measure, in a given stress test scenario, could be related to the structure and heterogeneity of financial networks. We finally show how these results could be used by a social planner to optimally target interventions during a financial crisis, with a budget constraint and under partial information of the financial network.

Macroprudential Regulation and Financial System (In)Stability â€" Regulatory Banking (Basel) & Insurance (Solvency) Capital Standards and Endogenous Destabilising Effects
Thivaios, Periklis,Núñez-Letamendia, Laura
The objective of this paper is to evaluate the extent to which the design of regulatory banking and insurance capital standards (Basel II/III and Solvency II) provide incentives for endogenously‐generated destabilising effects to the financial system. The literature has identified three areas whereby capital standards can be the source of endogenous financial instability, namely increased asset concentration, regulatory arbitraging, and capital standards procyclicality. We developed an empirical model that calculates regulatory capital requirements and associated metrics for a stylised balance sheet across banking and insurance regulatory frameworks and evaluated the three aforementioned areas in the context of financial system‐wide financial stability, rather than in each sector individually. We find that the design of regulatory capital standards can be the source of endogenous destabilising effects due to incentives for increased asset concentration and capital standard procyclicality. The support for the capital arbitraging hypothesis was weaker. We have concluded that the design of the Basel and Solvency regulatory capital frameworks, while designed to strengthen the stability of each sector individually, may ultimately incentivise behaviours across the banking and insurance industries that give rise to endogenously‐generated financial system‐wide instability, even though they are intended to reduce it.

Markov risk mappings and risk-sensitive optimal stopping
Tomasz Kosmala,Randall Martyr,John Moriarty

In contrast to the analytic approach to risk for Markov chains based on transition risk mappings, we introduce a probabilistic setting based on a novel concept of regular conditional risk mapping with Markov update rule. We confirm that the Markov property holds for the standard measures of risk used in practice such as Value at Risk and Average Value at Risk. We analyse the dual representation for convex Markovian risk mappings and a representation in terms of their acceptance sets. The Markov property is formulated in several equivalent versions including a strong version, opening up additional risk-sensitive optimisation problems such as optimal stopping with exercise lag and optimal prediction. We demonstrate how such problems can be reduced to a risk-sensitive optimal stopping problem with intermediate costs, and derive the dynamic programming equations for the latter. Finally, we show how our results can be extended to partially observable Markov processes.

Mass-Shootings and Peer-to-Peer Lending
García, Raffi E.,Li, Sen,Mahmud, Abdullah
This paper analyzes the effect of mass-shootings on peer-to-peer lending behavior. Using US data from 2014-2018, we implement both an event study and a difference-in-differences methodology to exploit the quasi-experimental nature of mass-shooting incidents on local credit markets. Our findings show that immediately after a mass-shooting event, borrowing costs increase (higher interest rates and lower loan amounts) for individuals in affected communities relative to those in non-affected communities. These findings highlight that online credit marketplaces are reactive to random local shocks of violence at the community level.

Modeling Price Clustering in High-Frequency Prices
Vladimír Holý,Petra Tomanová

The price clustering phenomenon manifesting itself as an increased occurrence of specific prices is widely observed and well-documented for various financial instruments and markets. In the literature, however, it is rarely incorporated into price models. We consider that there are several types of agents trading only in specific multiples of the tick size resulting in an increased occurrence of these multiples in prices. For example, stocks on the NYSE and NASDAQ exchanges are traded with precision to one cent but multiples of five cents and ten cents occur much more often in prices. To capture this behavior, we propose a discrete price model based on a mixture of double Poisson distributions with dynamic volatility and dynamic proportions of agent types. The model is estimated by the maximum likelihood method. In an empirical study of DJIA stocks, we find that higher instantaneous volatility leads to weaker price clustering at the ultra-high frequency. This is in sharp contrast with results at low frequencies which show that daily realized volatility has a positive impact on price clustering.

Models and numbers: Representing the world or imposing order?
Matthias Kaiser,Tatjana Buklijas,Peter Gluckman

We argue for a foundational epistemic claim and a hypothesis about the production and uses of mathematical epidemiological models, exploring the consequences for our political and socio-economic lives. First, in order to make the best use of scientific models, we need to understand why models are not truly representational of our world, but are already pitched towards various uses. Second, we need to understand the implicit power relations in numbers and models in public policy, and, thus, the implications for good governance if numbers and models are used as the exclusive drivers of decision making.

Models, Markets, and the Forecasting of Elections
Rajiv Sethi,Julie Seager,Emily Cai,Daniel M. Benjamin,Fred Morstatter

We examine probabilistic forecasts for battleground states in the 2020 US presidential election, using daily data from two sources over seven months: a model published by The Economist, and prices from the PredictIt exchange. We find systematic differences in accuracy over time, with markets performing better several months before the election, and the model performing better as the election approached. A simple average of the two forecasts performs better than either one of them overall, even though no average can outperform both component forecasts for any given state-date pair. This effect arises because the model and the market make different kinds of errors in different states: the model was confidently wrong in some cases, while the market was excessively uncertain in others. We conclude that there is value in using hybrid forecasting methods, and propose a market design that incorporates model forecasts via a trading bot to generate synthetic predictions. We also propose and conduct a profitability test that can be used as a novel criterion for the evaluation of forecasting performance.

New Determinants of Sovereign Risk Premia: Identification through Asset Price Shocks, Credit Premia, and Financial Cycle Synchronization
Boubaker, Sabri,Nguyen, Duc Khuong,Paltalidis, Nikos
Do asset price shocks and credit premia affect sovereign risk premia? Sovereign credit risk in developed countries was essentially non-existent prior to 2009. We find new factors suggesting that a part of sovereign risk premia is exogenously determined. We capture a novel phase synchronization among asset prices and credit premia that is associated with an increase in the cost of public debt. We start by showing that the financial and economic impact of credit premia, and asset price shocks have changed over time, even though the magnitude of the shocks is similar across different episodes. To explain this change, we suggest that the magnitude of the effect is different in 2008 because there is “phase synchronization” where financial cycles (à la Claessens, Kose, and Terrones, 2012) and credit cycles are synchronized in an unprecedented boom and bust episode. To test this hypothesis, we propose a novel econometric procedure, by introducing a Markov-Switching VAR model, and matching it with estimated asset shock episodes (à la Blanchard and Galí, 2009) and credit booms (Jordà, Schularick, and Taylor, 2013). Once we establish the relationship between the cycles and the financial and economic aggregates, we estimate impulse response functions to find that only during the phase synchronization the magnitude of the effect is strong with a clear sign across the whole time period and transmits to the sovereign credit market.

Normalizations and misspecification in skill formation models
Joachim Freyberger

An important class of structural models investigates the determinants of skill formation and the optimal timing of interventions. To achieve point identification of the parameters, researcher typically normalize the scale and location of the unobserved skills. This paper shows that these seemingly innocuous restrictions can severely impact the interpretation of the parameters and counterfactual predictions. For example, simply changing the units of measurements of observed variables might yield ineffective investment strategies and misleading policy recommendations. To tackle these problems, this paper provides a new identification analysis, which pools all restrictions of the model, characterizes the identified set of all parameters without normalizations, illustrates which features depend on these normalizations, and introduces a new set of important policy-relevant parameters that are identified under weak assumptions and yield robust conclusions. As a byproduct, this paper also presents a general and formal definition of when restrictions are truly normalizations.

On the Perception of Plagiarism in Academia: Context and Intent
Aaron Gregory,Joshua Leeman

Plagiarism is the representation of another author's language, thoughts, ideas, or expressions as one's own original work. In educational contexts, there are differing definitions of plagiarism depending on the institution. Prominent scholars of plagiarism include Rebecca Moore Howard, Susan Blum, Tracey Bretag, and Sarah Elaine Eaton, among others. Plagiarism is considered a violation of academic integrity and a breach of journalistic ethics. It is subject to sanctions such as penalties, suspension, expulsion from school or work, substantial fines and even incarceration. Recently, cases of "extreme plagiarism" have been identified in academia. The modern concept of plagiarism as immoral and originality as an ideal emerged in Europe in the 18th century, particularly with the Romantic movement. Generally, plagiarism is not in itself a crime, but like counterfeiting fraud can be punished in a court for prejudices caused by copyright infringement, violation of moral rights, or torts. In academia and industry, it is a serious ethical offense. Plagiarism and copyright infringement overlap to a considerable extent, but they are not equivalent concepts, and many types of plagiarism do not constitute copyright infringement, which is defined by copyright law and may be adjudicated by courts. Plagiarism might not be the same in all countries. Some countries, such as India and Poland, consider plagiarism to be a crime, and there have been cases of people being imprisoned for plagiarizing. In other instances plagiarism might be the complete opposite of "academic dishonesty," in fact some countries find the act of plagiarizing a professional's work flattering. Students who move to the United States and other Western countries from countries where plagiarism is not frowned upon often find the transition difficult.

Online Banking Users vs. Branch Visitors: Why Are Their Portfolio Returns Different?
Nagano, Mamoru,Uchida, Yuki
This study investigates why portfolio returns of online banking users are higher than those of non-online users. We first demonstrate that households that are eager to improve their level of financial literacy are more likely to use online banking. Second, a marginal increase in risk appetite increases portfolio returns of online users; however, this is not the case for non-online users. Third, online banking promotes debt repayment, and this further encourages risk tolerant investments. In sum, we conclude that financial literacy efforts moderate a positive relationship between use of online banking, risk appetite, and portfolio returns. The positive relationship between use of online banking and debt repayment further increases risk appetite.

Optimal Fees for Geometric Mean Market Makers
Alex Evans,Guillermo Angeris,Tarun Chitra

Constant Function Market Makers (CFMMs) are a family of automated market makers that enable censorship-resistant decentralized exchange on public blockchains. Arbitrage trades have been shown to align the prices reported by CFMMs with those of external markets. These trades impose costs on Liquidity Providers (LPs) who supply reserves to CFMMs. Trading fees have been proposed as a mechanism for compensating LPs for arbitrage losses. However, large fees reduce the accuracy of the prices reported by CFMMs and can cause reserves to deviate from desirable asset compositions. CFMM designers are therefore faced with the problem of how to optimally select fees to attract liquidity. We develop a framework for determining the value to LPs of supplying liquidity to a CFMM with fees when the underlying process follows a general diffusion. Focusing on a popular class of CFMMs which we call Geometric Mean Market Makers (G3Ms), our approach also allows one to select optimal fees for maximizing LP value. We illustrate our methodology by showing that an LP with mean-variance utility will prefer a G3M over all alternative trading strategies as fees approach zero.

Pricing Exchange Rate Options and Quanto Caps in the Cross-Currency Random Field LIBOR Market Model
Rajinda Wickrama

We develop an arbitrage-free random field LIBOR market model to price cross-currency derivatives. The uncertainty of the forward LIBOR rates of our cross-currency model is driven by a two time parameter random field instead of a finite dimensional Brownian motion. To demonstrate the applications of this model, we develop an approximate closed-form pricing formula for Quanto caps and cross-currency swaps. Further, we derive an exact pricing formula for an exchange rate option in the random field setting.

Productivity development in the construction industry and human capital: a literature review
Matthias Bahr,Leif Laszig

Tis paper is a literature review focusing on human capital, skills of employees, demographic change, management, training and their impact on productivity growth. Intrafirm behaviour has been recognized as a potentially important driver for productivity. Results from surveys show that management practices have become more structured, in the sense of involving more data collection and analysis. Furthermore, a strong positive correlation between the measured management quality and firm performance can be observed. Studies suggest that there is a positive association between management score and productivity growth. The lack or low level of employees' skills and qualifications might be in different ways a possible explanation for the observed slowdown of productivity growth. The main reason for the decline in skilled labor is the demographic change. Construction sectors are increasingly affected by demographic developments. Labour reserves in construction are largely exhausted. Shortage of qualified workforce is impacting project cost, schedules and quality.

Rethinking the Role of the Representativeness Heuristic in Macroeconomics and Finance Theory
Frydman, Roman,Tabor, Morten
We propose a novel interpretation and formalization of Kahneman and Tversky's findings in the Linda experiment which implies that subjects are rational in the sense of Muth's hypothesis and provides an approach to specifying rational assessment of uncertainty in macroeconomic models. Behavioral-finance theorists have appealed to Kahneman and Tversky's findings as an empirical foundation for a general approach replacing rational expectations. We show that behavioral models' specifications of participants' irrational forecasts and predictable errors are incompatible with Kahneman and Tversky's findings. Our interpretation of Kahneman and Tversky's findings is supportive of Lucas's compelling critique of inconsistent macroeconomic models.

Revisit of Limit-Order Executions and Cancellations: A Time-Varying Covariate Approach
Han, Zhaohui
We extend Chakrabarty, Han, Tyurin and Zheng (2006) competing risk model to the framework of time-varying covariates. It is found that the hazard rate of execution risk is more sensitive to market conditions than the hazard rate of cancellation. Order imbalance has a significant effect on execution probability, but it has no sizable effect on cancellation hazard. Larger spreads reduce the execution risk but increase the hazard rate of cancellation. Order aggressiveness has a positive effect on execution risk, but it has no impact on cancellation risk due to the fleeting orders observed in our data if the distance between the limit price and midquote is factored out. In comparison with models with fixed covariates, all time-varying covariates have stronger impact on execution and cancellation hazard rates, except the variable mearsuing the distance between the limit price and midquote.

Rewiring Corporate Law for an Interconnected World
Enriques, Luca,Romano, Alessandro
The traditional focus of corporate law is on aligning managers’ preferences to the interests of shareholders. This view is premised on two assumptions that are no longer true: first, the idea that all shareholders want to maximize the net present value of the firm’s earnings per dollar invested; and, second, the view that microeconomic shocks do not produce macroeconomic consequences. The rise of institutional investors undermines the first assumption, since large asset managers hold the entire market and have been shown to display a preference for maximizing the value of their portfolio as a whole, with limited interest in the performance of specific companies: that is, they are “portfolio value maximizers.” At the same time, the increasingly interconnectedness of the economy, and society more broadly, undermines the second assumption, as there is ample empirical evidence demonstrating that microeconomic shocks can propagate through the existing interconnections and generate catastrophic consequences. We also show how a subset of firms, those “central” to the network of interconnections that comprises the economy, is responsible for those shocks. We argue that corporate law should reflect these features of contemporary economies, and hence change its fundamental purpose. On the one hand, it should aim to ensure that non-central firms maximize their own value, despite the rise of portfolio value maximizers. On the other hand, in central firms it should harness the preferences of portfolio-value-maximizing shareholders with the goal of minimizing the risk of catastrophic externalities like climate change or financial crises. We develop a framework to guide policymakers in the pursuit of this new fundamental conception of corporate law and provide concrete examples of how changes in the rules on dual class shares, tenure voting, and ownership disclosure could account for these changes.

Secrets of 'Dirty Money'
Barik, Tushar Ranjan
This paper presents the different aspect of Dirty Money, it's carriers and methods to convert them into White Money. It is also reflects the status in India as well as in Global. There is no doubt that existence of Dirty Money has a significant impact on social, economic and political level of our lives, which has a significant effect on the institutions of the Government. The word ‘Dirty’ is used to describe money that is used by such extreme anti-social elements as terrorists and even the Mafia. If we allow its use in the mainstream economy, there will be very bad consequences.

Sectoral Slowdowns in the UK: Evidence from Transmission Probabilities and Economic Linkages
, Eva F. Janssens,Lumsdaine, Robin L.
This paper studies shock transmission across macroeconomic sectors in the UK, using data from the Bank of England's Flow of Funds statistics. We combine two different approaches to quantify the spread of shocks to assess whether sectors with large bilateral economic linkages as measured through network data have a greater statistical likelihood of shock transmission between them. The combination of both approaches reveals the Monetary Financial Institutions sector's role as shock absorber, and identifies the most important channels of shock transmission. The inferential discrepancies between network data and the actual spillovers highlight the contribution of the proposed methodology.

Shocks, Stocks and Ratings: The Financial Community Response to Global Environmental and Health Controversies
Scholtens, Bert,Witteveen, Emma
The financial community suggests it increasingly accounts for the environmental and social performance of the companies it invests in. To investigate this claim, we study how stock market participants and credit rating agencies respond to environmental and health controversies with internationally operating companies. Stock returns and rating changes are the most prominent financial signals regarding the appreciation of news by the financial community. The actions of numerous investors who trade on public information determine firm value. Credit rating agencies produce ratings based on private information, in part to support these evaluations. Ratings focus directly on a firm’s default and business risk which itself is increasingly associated with global environmental and health controversies. Financial investors show a timely and significant response to measures of such controversies, but this response is highly generic and is small from an economic point of view. Credit ratings do not immediately respond in a significant way. Thus, markets and raters respond in a different way to the controversies. We conclude that the response of the financial community to global environmental and health controversies is limited. Therefore, the financial community seems unable to discipline the economic agents behind the controversies.

Similar Stocks
He, Wei,Wang, Yuehan,Yu, Jianfeng
Similarity between two stocks is measured by the distance between their characteristics such as price, size, book-to-market, return on assets, and investment-to-assets. We find that after a stock's most similar stocks have experienced high (low) returns in the past month, this focal stock tends to earn an abnormally high (low) return in the current month. The long-short portfolio strategy sorted on similar-stocks' past average return earns a monthly CAPM alpha of 1.25% and a Fama-French six-factor alpha of 0.85%. This similarity effect is robust after controlling for style investing and a wide range of well-known firm-level characteristics that can predict returns in the cross section. Our result is consistent with the increased propensity for investors to buy other stocks with similar characteristics after experiencing positive returns for a currently held stock. We also explore other potential explanations for our findings.

Statistical significance revisited
Maike Tormählen,Galiya Klinkova,Michael Grabinski

Statistical significance measures the reliability of a result obtained from a random experiment. We investigate the number of repetitions needed for a statistical result to have a certain significance. In the first step, we consider binomially distributed variables in the example of medication testing with fixed placebo efficacy, asking how many experiments are needed in order to achieve a significance of 95 %. In the next step, we take the probability distribution of the placebo efficacy into account, which to the best of our knowledge has not been done so far. Depending on the specifics, we show that in order to obtain identical significance, it may be necessary to perform twice as many experiments than in a setting where the placebo distribution is neglected. We proceed by considering more general probability distributions and close with comments on some erroneous assumptions on probability distributions which lead, for instance, to a trivial explanation of the fat tail.

Tokat-Acikel, Yesim,Aiolfi, Marco,Johnson, Lorne D,Hall, John,Jin, Yiwen
This paper reviews the significant progress in academic research on economic impact of climate change and explores the implications for expected returns and strategic portfolio allocation across major public asset classes. There have been numerous efforts to measure the environmental impact within a broader ESG framework with a focus on microeconomic and firm-level implications. In this paper, we assess the impact of climate change on long-term expected returns across asset classes from a top-down macroeconomic perspective. We use well-accepted climate risk scenarios to assess the potential impact of alternative climate scenarios on economic growth, inflation and asset returns for major asset classes. Finally, we design hypothetical portfolios given these top-down assumptions and explore portfolio allocation implications.

The COVID-19 Storm and the Energy Sector: The Impact and Role of Uncertainty
Szczygielski, Jan,Brzeszczynski, Janusz,Charteris, Ailie,Bwanya, Princess
Prior research has shown that energy sector stock prices are impacted by uncertainty. The coronavirus (COVID-19) pandemic has given rise to widespread health and economic-related uncertainty. In this study, we investigate the impact and the timing of the impact of COVID-19 related uncertainty on returns and volatility for 20 national energy indices and a global energy index using ARCH/GARCH models. We propose a novel ‘overall impact of uncertainty’ (OIU) measure, explained using a natural phenomenon analogy of the overall impact of a rainstorm, to gauge the magnitude and intensity of the impact of uncertainty on energy sector returns. Drawing from economic psychology, COVID-19 related uncertainty is measured in terms of searches for information relating to COVID-19 as captured by Google search trends. Our results show that the energy sectors of countries further west from the outbreak of the virus in China are impacted to a greater extent by COVID-19 related uncertainty. A similar observation is made for net energy and oil exporters relative to importers. We also find that the impact of uncertainty on most national energy sectors intensified and then weakened as the pandemic evolved. Additional analysis confirms that COVID-19 uncertainty is part of the composite set of factors that drive energy sector returns over the COVID-19 period although its importance has declined over time.

The Case for Risk Managed Gold
McMillan, Ben,Robinson, Donald,Myers, Josh,Kennard, Mark
The strategic case for gold revolves around its long history as a store of value. Humans have been drawn to the yellow metal despite its inability to pay a dividend or provide productive output ownership since somebody first discovered it. From an investment perspective, gold has demonstrated an ability to provide a long-term source of uncorrelated returns while also serving as something of a "flight to safety" hedge during geopolitical or fiat instability periods. While there are plenty of speculators looking to gold as a source of potential outsized return, most of the investing public looks to gold at the intersection of those two objectives: risk management. The authors make the case that there is a risk premium for investing in gold, understanding that even though gold does not provide a stream of future cash flows paid out to investors, it has genuine utility as a store of value. The authors also explore the benefits of managing gold exposure in investment portfolios to manage large drawdowns through systematic momentum measures.

The Decline of EMU Core Countries' Portfolio Equity Investments in the Euro Area: The Role of Stock Return Correlations
Giofré, Maela
While the enlargement of the Euro area to new countries has reduced the average return correlation among member countries, the financial crisis and the sovereign debt crisis have led to an increase in stock return correlation among old members. We find that EMU core countries portfolio allocation has been significantly driven by diversification motives: they have reduced their portfolio equity investment in assets issued by member countries featuring a stronger returns' correlation with domestic assets. This evidence sheds light on the determinants of the sharp decline in bilateral equity investments in the Euro area after 2007, and points to the importance of diversification benefits.

The Economic Effect of Bitcoin Halving Events on the U.S. Capital Market
El Mahdy, Ph.D., CFE, Dina
Bitcoin is a digital asset that was first mined in January 2009 after the global financial crisis of 2007-2008. Over a decade later, there is still no consensus across different market regulations on the classification, use cases, policies, and economic implications of bitcoin. However, there is an increasing demand for digital currency, as an alternative to fiat currency which would spur financial innovation and inclusion. This study reviews regulations on digital assets across countries. It further discusses some use cases for bitcoin to reduce financial risk and facilitate cross border transactions. The study also discusses challenges related to bitcoin such as: cryptocurrencies substitution, cross border financing, cyber risk and security, and benefits in terms of the effect of coronavirus on the speed of capital market innovation and hence bitcoin usage. The study concludes by examining the economic effect of bitcoin halving events on the U.S. capital market to better understand the influence of bitcoin on financial markets and key drivers of its intrinsic value. The empirical evidence from this study suggests that bitcoin halving events are associated with significant negative stock market reaction, signaling a trading tradeoff between cryptocurrencies and U.S. stock markets.

The Effectiveness of White‐Collar Crime Enforcement: Evidence from the War on Terror
Nguyen, Trung
This paper analyzes the impact of changes in regulatory priorities and resource allocation on criminal enforcement of white‐collar criminal activities. Using the 9/11 terrorist attacks as a shock to the FBI's priorities and allocation of investigative resources, as well as variation in the Muslim population in the United States, I examine whether prioritization of counterterrorism investigations after 9/11 is associated with weaker enforcement of laws targeting white‐collar crime. I then use a difference‐in‐differences estimation to study the magnitude of any increase in white‐collar crime resulting from reduced oversight. I find a significantly greater reduction in white‐collar criminal cases referred by FBI field offices that shifted more of their investigative focus away from white‐collar crime to counterterrorism. Further, geographic areas in the jurisdictions of FBI field offices with greater shifts in attention from white‐collar crime to counterterrorism experienced greater increases in wire fraud, illegal insider‐trading activities, and fraud within financial institutions.

The Government Agenda and the Effects of Regulatory Dispersion
Kalmenovitz, Joseph,Lowry, Michelle,Volkova, Ekaterina
The agenda of the U.S. government extends across a myriad of agencies, topics, and regulatory stages. The first objective of this paper is to quantify this entire agenda, through an analysis of documents in the Federal Register. We present novel facts on time trends in the government’s agenda and on major turnaround points. Our second objective is to evaluate how companies respond to regulatory dispersion, which is a function of the set of topics relevant to their business and the number of agencies that regulate each topic. We find that higher regulatory dispersion relates to higher subsequent SG&A costs and to lower productivity, profitability, and growth. Overall, the results highlight the potential impact of the government’s broad agenda on regulated companies.

The Impact of Seller-Buyer Relationship Quality in the Financial Service Industry
Chen, Xianglin
The investigation examined some issues regarding relationship quality between buyer and seller from the perspective of an (a) financial service industry. The aim of the research investigate factors affecting relationship quality between buyer and seller in the financial service industry, and maintain a stronger and long-term relationship include client knowledge, customer orientation, expertise and similarity. The study will apply quantitative analysis which use sample instrument with the multiple regression analysis and employed the SPSS 23.0 version software. The paper has been argued customer relationship quality that will be determined by a few independent variables. Thus, it is timely to test the significance of relationship quality among buyers and sellers in the financial service industry. The research will utilize a questionnaire survey to examine customer relationship quality between buyer and seller perceptions of the influence of the various factors on relationship quality.

The Implementation of US GAAP Update 2016-02
Hill, Paula,Lobo, Gerald J.,Wang, Shuo
We analyze the implementation of Accounting Standards Update (ASU) 2016-02, requiring operating lease assets and liabilities to be recognized in the balance sheet. We find that the standard resulted in large increases in balance sheet derived leverage for some companies, particularly in the Retail sector. It also had an impact on the valuation of operating lease liabilities relative to values derived from pre-ASU 16-02 methods, which on average produced values which were 11% higher. However, we find that the impact on new information has been marginal, even in firms where operating lease liabilities account for a large proportion of total liabilities. The reason for this is that the contribution of operating leases to leverage after implementation of ASU 16-02 can largely be predicted employing the data available prior to the standard.

The Prior Adaptive Group Lasso with an Application to Risk Factor Selection
Bertelsen, Kristoffer Pons
This paper develops and presents the prior adaptive group lasso for generalized linear models. The prior adaptive group lasso is an extension of the prior lasso developed by Jiang, He, and Zhang (2016), which allows for the use of existing information from previous or similar studies in the estimation of the lasso. We demonstrate that the estimator exhibits consistent variable selection and estimation similarly to those derived in Wang and Tian (2019) under at set of similar conditions. The performance of the prior adaptive group lasso estimator is illustrated in a Monte Carlo study. Finally, the estimator is applied in selecting the set of relevant risk factors in asset pricing models conditioning on the fact that the chosen factors must be able to price the test assets as well as the remaining factors. The empirical study shows that the prior adaptive group lasso yields a set of factors that explain the time variation in the returns while delivering 𝛼 estimates close to zero. We also show how this set of factors has evolved over time. We find that the canonical factor models of Fama and French (1993), (Carhart, 1997), (Fama and French, 2015), and (Hou, Xue, and Zhang, 2015) are insufficient to price the cross section of the test assets together with the remaining traded factors, and we find that the required number of pricing factors to include at any given time is closer to 20.

The Race between Technological Progress and Female Advancement: Changes in Gender and Skill Premia in OECD Countries
Hiroya Taniguchi,Ken Yamada

In recent decades, the male-female wage gap has fallen, while the skilled-unskilled wage gap has risen in advanced countries. The rate of decline in the gender wage gap tends to be greater for unskilled than skilled workers, while the rate of increase in the skill wage gap tends to be greater for male than female workers. To account for these trends, we develop an aggregate production function extended to allow for gender-specific capital-skill complementarity, and estimate it using shift-share instruments and cross-country panel data from OECD countries. We confirm that ICT equipment is more complementary not only to skilled than unskilled workers but also to female than male workers. Our results show that changes in gender and skill premia can be explained in terms of the race between progress in ICT and advances in educational attainment and female employment. In addition, we examine the implications of gender-specific capital-skill complementarity for changes in the labor share of income.

The Voice of Monetary Policy
Gorodnichenko, Yuriy,Pham, Tho,Talavera, Oleksandr
We develop a deep learning model to detect emotions embedded in press conferences after the meetings of the Federal Open Market Committee and examine the influence of the detected emotions on financial markets. We find that, after controlling for the Fed's actions and the sentiment in policy texts, positive tone in the voices of Fed Chairs leads to statistically significant and economically large increases in share prices. In other words, how policy messages are communicated can move the stock market. In contrast, the bond market appears to take few vocal cues from the Chairs. Our results provide implications for improving the effectiveness of central bank communications.

The commodity risk premium and neural networks
Rad, Hossein,Low, Rand Kwong Yew,Miffre, Joëlle,Faff, Robert W.
The paper uses linear and nonlinear predictive models to study the linkage between a set of 128 macroeconomic and financial predictors and subsequent commodity futures returns. The linear models use shrinkage methods based on naive averaging and principal components. The nonlinear models use feedforward deep neural networks either as stand-alone (DNN) or in conjunction with LSTM, a recurrent long short-term memory network. Out of the four specifications considered, the LSTM-DNN architecture is the most successful at transforming the 128 predictive variables into profitable investment strategies. The risk premium then modelled is unrelated to, and exceeds, those earned on previously-published characteristic-sorted portfolios. Our analysis is robust to the presence of transaction costs and illiquidity.

The interaction of forward guidance in a two-country new Keynesian model
Daisuke Ida,Hirokuni Iiboshi

Using the method of Haberis and Lipinska (2020), this paper explores the effect of forward guidance (FG) in a two-country New Keynesian (NK) economy under the zero lower bound (ZLB). We simulate the effect of different lengths of FG or the zero interest rate policy under the circumstance of the global liquidity trap. We show that the size of the intertemporal elasticity of substitution plays an important role in determining the beggar-thy-neighbor effect or the prosper-thy-neighbor effect of home FG policy on the foreign economy. And in the former case, by targeting a minimum welfare loss of the individual country alone but not global welfare loss, two central banks can perform interesting FG bargaining in which they cooperatively adopt the same length of FG or strategically deviate from cooperation.

TradeR: Practical Deep Hierarchical Reinforcement Learning for Trade Execution
Karush Suri,Xiao Qi Shi,Konstantinos Plataniotis,Yuri Lawryshyn

Advances in Reinforcement Learning (RL) span a wide variety of applications which motivate development in this area. While application tasks serve as suitable benchmarks for real world problems, RL is seldomly used in practical scenarios consisting of abrupt dynamics. This allows one to rethink the problem setup in light of practical challenges. We present Trade Execution using Reinforcement Learning (TradeR) which aims to address two such practical challenges of catastrophy and surprise minimization by formulating trading as a real-world hierarchical RL problem. Through this lens, TradeR makes use of hierarchical RL to execute trade bids on high frequency real market experiences comprising of abrupt price variations during the 2019 fiscal year COVID19 stock market crash. The framework utilizes an energy-based scheme in conjunction with surprise value function for estimating and minimizing surprise. In a large-scale study of 35 stock symbols from the S&P500 index, TradeR demonstrates robustness to abrupt price changes and catastrophic losses while maintaining profitable outcomes. We hope that our work serves as a motivating example for application of RL to practical problems.

True Liquidity and Fundamental Prices: US Tick Size Pilot
Allena, Rohit,Chordia, Tarun
We develop a big-data methodology to estimate fundamental prices and true liquidity measures,explicitly considering the rounding specification due to the minimum tick size. Evaluation of the tick size pilot (TSP), which increased the tick size for some randomly chosen stocks, requiresthe impact of rounding. Our true liquidity measures capture the TSP-driven decreased inventory costs of market-makers, whereas traditional measures without the rounding adjustment cannot. We nd that the TSP increases market-maker prots, but does not improve liquidity and price efficiency. This result contrasts existing empirical studies but is consistent with recent theoretical studies that account for rounding.

Uncertainty, sentiments and time-varying risk premia
Berardi, Michele
Why are stock prices much more volatile than the underlying dividends? The excess volatility of prices can in principle be attributed to two different causes: time-varying discount rates for expected future dividends, arising from variation in risk premia; or the irrational exuberance of investors, bidding prices up and down even in the absence of changes in the underlying value of the asset. No consensus has so far emerged among economists as to the prevalence of one or the other source of price variation.I propose in this paper a novel way to approach this problem, by identifying changes in the uncertainty faced by investors regarding the fundamental value of an asset and exploiting the different response in prices that such changes in uncertainty would generate through sentiments or risk premia. I then apply this framework to the S&P 500 index from 1872 till 2019: the positive correlation found between uncertainty and prices (or, equivalently, the negative correlation between uncertainty and implied risk premia) is not compatible with rational investors' behavior and suggests instead the presence of a significant sentiments component in stock prices.