Research articles for the 2021-03-08

Clogged Information Flow and Stock Market Sluggishness
Vora, Premal P.
SSRN
I provide evidence on the trading effects of the 1970 Newspaper and Mail Deliverers’ Union’s strike against The Wall Street Journal. I find that turnover falls significantly on the first few days of the strike, returns to normal, then even exceeds the average as the strike proceeds. The evidence is consistent with the idea that a clogged information flow causes sluggishness in the market but consumers of media substitute one source for another when their preferred source is clogged. The effects are widespread without regard to firm size or other firm characteristics. When information is clogged, I find that return comovement among assets increases. Finally, I also find that turnover is closely related to the publication of an article in the Journal and to positive and negative abnormal returns, but responds more to the latter.

Competitors' Innovation and Informed Trading: Evidence from Weekly Patent Announcements
Gao, Zhenyu,Hsu, Po-Hsuan,Huh, Sahn-Wook
SSRN
By constructing high-frequency measures of informed trading and news about technological competition, we provide evidence that the news about a firm’s disadvantage in competition leads to informed selling. Such a pattern is weaker among firms in the industries with faster technology obsolescence due to lower appropriability of patents. We also find that a firm’s unfavorable status in competition predicts lower subsequent stock returns, and trading on such news is profitable. In particular, institutional investors actively assess the status of firms’ technological competition and capitalize on their informational advantage through trading activities, which are the key channel through which the information about innovation and competition is impounded in stock prices.

Credit Risk and the Transmission of Interest Rate Shocks
Palazzo, Berardino,Yamarthy, Ram
SSRN
Using daily credit default swap (CDS) data, we find a positive relation between corporate credit risk and unexpected monetary policy shocks during FOMC announcement days. Positive shocks to interest rates increase the expected loss component of CDS spreads as well as a risk premium component. However, not all firms respond in the same manner. We show that firm-level credit risk is an important driver of the monetary policy response, both in credit and equity markets, and plays a more prominent role relative to other risk proxies. A stylized corporate model of monetary policy, investment, and financing rationalizes our findings.

Deals in the Time of Pandemic
Subramanian, Guhan,Petrucci, Caley
SSRN
The COVID-19 pandemic has brought new attention to the period between signing and closing in M&A transactions. Transactional planners heavily negotiate the provisions that govern the behavior of the parties during this window, not only to allocate risk between the buyer and seller, but also to manage moral hazard, opportunistic behavior, and other distortions in incentives. Prior literature, both academic and practitioner, has focused virtually exclusively on the material adverse effect (MAE) clause. COVID-19, however, has exposed an important connection between the MAE clause and the obligation for the seller to act “in the ordinary course of business” between signing and closing. This Article is the first to examine the interaction between the MAE clause and the ordinary course covenant in M&A deals. We construct a new database of 1,300 M&A transactions along with their MAE and ordinary course covenantsâ€"by far the most comprehensive, accurate, and detailed database of such deal terms that currently exists. We document how these deal terms currently appear in M&A transactions, including the sharp rise in “pandemic” carveouts from the MAE clause since the COVID-19 pandemic began. We then provide implications for corporate boards, the Delaware courts, and transactional planners. Our empirical findings and recommendations are relevant not just for the next pandemic or “Act of God” event, but also the next (inevitable) downturn in the economy more generally.

Deep Hedging, Generative Adversarial Networks, and Beyond
Hyunsu Kim
arXiv

This paper introduces a potential application of deep learning and artificial intelligence in finance, particularly its application in hedging. The major goal encompasses two objectives. First, we present a framework of a direct policy search reinforcement agent replicating a simple vanilla European call option and use the agent for the model-free delta hedging. Through the first part of this paper, we demonstrate how the RNN-based direct policy search RL agents can perform delta hedging better than the classic Black-Scholes model in Q-world based on parametrically generated underlying scenarios, particularly minimizing tail exposures at higher values of the risk aversion parameter. In the second part of this paper, with the non-parametric paths generated by time-series GANs from multi-variate temporal space, we illustrate its delta hedging performance on various values of the risk aversion parameter via the basic RNN-based RL agent introduced in the first part of the paper, showing that we can potentially achieve higher average profits with a rather evident risk-return trade-off. We believe that this RL-based hedging framework is a more efficient way of performing hedging in practice, addressing some of the inherent issues with the classic models, providing promising/intuitive hedging results, and rendering a flexible framework that can be easily paired with other AI-based models for many other purposes.



Developments in Islamic Finance Literature: Evidence from Specialized Journals
Hanif, Muhammad,Zafar, Kiran
SSRN
This study documents the literary developments and classifies the literature in the area of Islamic Financial Services Industry (IFSI). Our findings are based on articles published in selected Islamic finance specialized journals for six years (2012-2017). Classification is based on multiple factors including subject/specialization areas, country of origin and publications, research methodology, and yearly progress in investigations. Findings suggest that the majority of publications are in the area of general Islamic finance and follow qualitative research methodology. Malaysia and Pakistan were found to be the most significant contributors to the literature. Although the results of empirical studies are mixed, however, the majority favor resilience of IFSI to the global financial crisis (GFC). The potential role of IFSI in poverty alleviation and corporate social responsibility (CSR) has also been highlighted. Demand for IFSI with quality services exists. The literature highlights the lack of Islamic financial literacy and skepticism about SharÄ«Ê¿ah compliance in practice. Need for regulatory framework and application of Islamic accounting is documented. Future research needs to focus on an objective assessment of IFSI in the light of Islamic finance objectives. Also, further investigations are needed to highlight the social role of IFSI â€" with a focus on CSR, zakāh, waqf and microfinance. Additionally, certain specialized areas including accounting, management, and corporate governance need more attention in future researches.

Does automation erode governments' tax basis? An empirical assessment of tax revenues in Europe
Kerstin Hötte,Angelos Theodorakopoulos,Pantelis Koutroumpis
arXiv

Decomposing taxes by source (labor, capital, sales), we analyze the impact of automation (1) on tax revenues, (2) the structure of taxation, and (3) identify channels of impact in 19 EU countries during 1995-2016. Robots and Information and Communication Technologies (ICT) are different technologies designed to automate manual (robots) or cognitive tasks (ICT).

Until 2007, robot diffusion led to decreasing factor and tax income, and a shift from taxes on capital to goods. ICTs changed the structure of taxation from capital to labor. We find decreasing employment, but increasing wages and labor income. After 2008, robots have no effect but we find an ICT-induced increase in capital income, a rise of services, but no effect on taxation. Automation goes through different phases with different economic impacts which affect the amount and structure of taxes. Whether automation erodes taxation depends (a) on the technology type, (b) the stage of diffusion and (c) local conditions.



Driver Surge Pricing
Nikhil Garg,Hamid Nazerzadeh
arXiv

Ride-hailing marketplaces like Uber and Lyft use dynamic pricing, often called surge, to balance the supply of available drivers with the demand for rides. We study driver-side payment mechanisms for such marketplaces, presenting the theoretical foundation that has informed the design of Uber's new additive driver surge mechanism. We present a dynamic stochastic model to capture the impact of surge pricing on driver earnings and their strategies to maximize such earnings. In this setting, some time periods (surge) are more valuable than others (non-surge), and so trips of different time lengths vary in the induced driver opportunity cost.

First, we show that multiplicative surge, historically the standard on ride-hailing platforms, is not incentive compatible in a dynamic setting. We then propose a structured, incentive-compatible pricing mechanism. This closed-form mechanism has a simple form and is well-approximated by Uber's new additive surge mechanism. Finally, through both numerical analysis and real data from a ride-hailing marketplace, we show that additive surge is more incentive compatible in practice than is multiplicative surge.



Economic Preferences Over Risk-Taking and Corporate Finance
Delis, Manthos D.,Hasan, Iftekhar,Tsoumas, Chris,Iosifidi, Maria
SSRN
We contend that economic preferences over risk-taking in different subnational regions worldwide affect fundamental aspects of firms’ corporate financing, namely financing costs and capital structure. We study this hypothesis, by hand-matching firms’ regions worldwide with the corresponding regional economic risk-taking preferences. Our baseline results show that credit and bond pricing increase with higher risk-taking preferences, whereas such preferences yield lower ratios of book leverage and short-term debt. We backup our baseline results with an instrumental variables approach, which is based on the premise that high-yield agricultural societies in the pre-industrial era exhibit low risk-taking preferences.

Efficient Variance Reduction with Least-Squares Monte Carlo Pricing
Boire, François-Michel,Reesor, R. Mark,Stentoft, Lars
SSRN
This paper examines the efficiency of standard variance reduction techniques across option characteristics when pricing American-style call and put options with the Least-Squares Monte Carlo algorithm of Longstaff & Schwartz (2001). Our numerical experiments evaluate the efficiency of antithetic sampling, control variates, importance sampling, and combinations thereof. Whereas most of the American option pricing literature has focused on either put or call options individually, we employ the symmetry relation of McDonald & Schroder (1998) to compare performance for pairs of call and put options whose solution coincide. Our results first show that variance reduction is generally more efficient for put than call options and that control variates is the most efficient stand-alone method. We also find that marginal gains in efficiency are typically achieved by combining variance reduction techniques, though some techniques may interact conflictingly. Finally, since valuation of American-style call options can be improved by pricing symmetric put options instead (Stentoft 2019), we demonstrate that drastic reductions in the standard deviation of the call is obtained by combining all three variance reduction techniques in a symmetric pricing approach, which reduces the standard deviation by a factor of over 20 for long maturity call options on highly volatile assets.

Environmental performance of shared micromobility and personal alternatives using integrated modal LCA
Anne de Bortoli
arXiv

The environmental performance of shared micromobility services compared to private alternatives has never been assessed using an integrated modal Life Cycle Assessment (LCA) relying on field data. Such an LCA is conducted on three shared micromobility services in Paris - bikes, second-generation e-scooters, and e-mopeds - and their private alternatives. Global warming potential, primary energy consumption, and the three endpoint damages are calculated. Sensitivity analyses on vehicle lifespan, shipping, servicing distance, and electricity mix are conducted. Electric micromobility ranks between active modes and personal ICE modes. Its impacts are globally driven by vehicle manufacturing. Ownership does not affect directly the environmental performance: the vehicle lifetime mileage does. Assessing the sole carbon footprint leads to biased environmental decision-making, as it is not correlated to the three damages: multicriteria LCA is mandatory to preserve the planet. Finally, a major change of paradigm is needed to eco-design modern transportation policies.



Free-Float Liquidity and Trading Constraints: Increasing Informational Efficiency in Family Firms’ Financing Decisions
Dupuis, Daniel,Bodolica, Virginia,Spraggon, Martin
SSRN
Volume-based liquidity ratios suffer from potential measurement bias due to share restriction and may misrepresent actual liquidity. In this paper, we develop a modified metric, the free-float liquidity ratio. We argue that this measure is better suited to estimate liquidity in the presence of trading constraints as can be found in family-owned businesses or closely-held entities. Empirical testing indicates that the free-float liquidity ratio compares favorably with other volume-based methods. Furthermore, we use family firms as a of restricted share setting to demonstrate the empirical validity of the free-float liquidity ratio. The proposed metric provides potential informational gain for family leaders to aid in their strategic financing decisions and for non-family outsiders to guide their investment choice.

Greening (Runnable) Brown Assets with a Liquidity Backstop
Jondeau, Eric,Mojon, Benoît,Monnet, Cyril
SSRN
The momentum toward greening the economy implies transition risks that are new threats to financial stability. In particular, the expectation that other investors may exclude high carbon corporate emitters from their portfolio creates a risk of runs on brown assets. We show that runs can be contained by a liquidity backstop with an access fee that depends on the firm’s carbon intensity, while the interest rate on the liquidity lent through this facility is independent from its carbon intensity.

Insights on Islamic Finance (Part - One)
Hussain Minhas, Imran
SSRN
Islam prescribes all inclusive blue print for life. It recommends guiding rules for personal, interpersonal, financial, economic, political and religious aspects of life. This article discusses the sources of these rules and goes on to explain the basic prohibitive rule in Islamic finance â€" riba and its exclusion in earlier revealed religions as well, and why. It extents it scope on Fiqh ul Muamulat and discusses Islamic business ethics particularly prohibitions in financial transactions in the modern Islamic Banking.

Insights on Islamic Finance - Part Two
Hussain Minhas, Imran
SSRN
Riba, the major driving force and key element in conventional banking, is one of those items which have been strictly forbidden and declared as Haram in Islam. The convention banking and finance system is not meant for the Muslims and Islamic societies. Practicing riba based banking and financial system is sinful and destructive for the Muslims for which the State and its Organs are primarily responsible. It is true that the modern economies cannot survive without a sound financial system but it is not necessary that it should be based on conventional banking practices and riba. Shariah compliant solution to the riba based conventional or modern financial system is not a dream now.It is second part of the series on Islamic finance and this article particularly discussed history of Islamic Banking and Finance.

Investing in Crises
Baron, Matthew,Laeven, Luc,Penasse, Julien,Usenko, Yevhenii
SSRN
We investigate asset returns around banking crises in 44 advanced and emerging economies from 1960 to 2018. In contrast to the view that buying assets during banking crises is a profitable long-run strategy, we find returns of equity and other asset classes generally underperform after banking crises. While prices are depressed during crises and partially recover after acute stress ends, consistent with theories of fire sales and intermediary-based asset pricing, we argue that investors do not fully anticipate the consequences of debt overhang, which result in lower long-run dividends. Our results on bank stock underperformance suggest that government-funded bank recapitalizations can often lead to substantial taxpayer losses.

Legal Liability for Fraud in the Evolving Architecture of Securities Markets: From Marketplaces to Traders
Dolgopolov, Stanislav
SSRN
This chapter analyses the reach of legal liability for securities fraud in the United States in relation to certain types of abuses often associated with high-frequency trading strategies. The nature of algorithmic and high-frequency trading presents new challenges for establishing legal liability for fraud in securities markets. It specifically examines the reach of legal liability in relation to two, sometimes overlapping, entities: marketplaces and proprietary traders. Through an examination of various informational asymmetries in securities markets, including the order type controversy, this chapter finds that establishing liability for securities fraud is significantly murkier for proprietary traders than for marketplaces. Subsequently, this study addresses potential approaches to the reach of liability to traders and discusses mechanics and proper characterization of the underlying harm.

Levelling Down and the COVID-19 Lockdowns: Uneven Regional Recovery in UK Consumer Spending
Gathergood, John,Gunzinger, Fabian,Guttman-Kenney, Benedict,Quispe-Torreblanca, Edika,Stewart, Neil
SSRN
We show the recovery in consumer spending in the United Kingdom through the second half of 2020 is unevenly distributed across regions. We utilise Fable Data: a real-time source of consumption data that is a highly correlated, leading indicator of Bank of England and Office for National Statistics data. The UK’s recovery is heavily weighted towards the “home counties” around outer London and the South. We observe a stark contrast between strong online spending growth while offline spending contracts. The strongest recovery in spending is seen in online spending in the “commuter belt” areas in outer London and the surrounding localities and also in areas of high second home ownership, where working from home (including working from second homes) has significantly displaced the location of spending. Year-on-year spending growth in November 2020 in localities facing the UK’s new tighter “Tier 3” restrictions (mostly the midlands and northern areas) was 38.4% lower compared with areas facing the less restrictive “Tier 2” (mostly London and the South). These patterns had been further exacerbated during November 2020 when a second national lockdown was imposed. To prevent such COVID-19-driven regional inequalities from becoming persistent we propose governments introduce temporary, regionally-targeted interventions in 2021. The availability of real-time, regional data enables policymakers to efficiently decide when, where and how to implement such regional interventions and to be able to rapidly evaluate their effectiveness to consider whether to expand, modify or remove them.

Measuring Accounting Fraud and Irregularities Using Public and Private Enforcement
Donelson, Dain C.,Kartapanis, Antonis,McInnis, John M.,Yust, Christopher G.
SSRN
Most accounting studies use only public enforcement actions (SEC cases) to measure accounting fraud. However, private cases (securities class actions) also play an important enforcement role. We discuss the legal standards and processes for both public and private enforcement regimes, emphasize the importance of screening cases for credible fraud allegations, and show both yield credible fraud measures. Further, we demonstrate these research design choices affect inferences from prior research and a hypothetical research setting. Finally, we show common measures of accounting irregularities using Audit Analytics to proxy for fraud result in significant false positives and negatives and develop a fraud prediction model for use in future research. We recommend using both public and private enforcement with appropriate screening when examining accounting fraud to reduce Type I and II errors, or reporting the sensitivity of findings across regimes. This is particularly important given the reduction in accounting-related enforcement after 2005.

Mining the Relationship Between COVID-19 Sentiment and Market Performance
Ziyuan Xia,Jeffery Chen
arXiv

At the beginning of the COVID-19 outbreak in March, we observed one of the largest stock market crashes in history. Within the months following this, a volatile bullish climb back to pre-pandemic performances and higher. In this paper, we study the stock market behavior during the initial few months of the COVID-19 pandemic in relation to COVID-19 sentiment. Using text sentiment analysis of Twitter data, we look at tweets that contain key words in relation to the COVID-19 pandemic and the sentiment of the tweet to understand whether sentiment can be used as an indicator for stock market performance. There has been previous research done on applying natural language processing and text sentiment analysis to understand the stock market performance, given how prevalent the impact of COVID-19 is to the economy, we want to further the application of these techniques to understand the relationship that COVID-19 has with stock market performance. Our findings show that there is a strong relationship to COVID-19 sentiment derived from tweets that could be used to predict stock market performance in the future.



Minority Analysts, Diversity, and Market Behavior
Borochin, Paul,Chhaochharia, Vidhi,Kumar, Alok
SSRN
This study examines whether race/ethnicity of financial intermediaries influences the production and dissemination of information in the U.S. capital markets. We find that brokerage diversity influences both the forecasting style and accuracy of analysts. Asian analysts are more likely to issue bold positive forecasts while African American and Hispanic analysts are relatively more pessimistic. Further, White (Asian) analysts are more (less) accurate while African American and Hispanic analysts are as accurate as their peers. These accuracy differences primarily reflect the effects of brokerage diversity. Stock market participants perceive Asian analysts relatively more favorably in spite of their lower accuracy but their career outcomes are adversely affected by increased diversity. In contrast, stock market participants perceive African American and Hispanic analysts relatively less favorably and their career outcomes are minimally affected by brokerage diversity. Taken together, these findings demonstrate that minority analysts do not benefit from increased diversity while White analysts do.

Multiscale characteristics of the emerging global cryptocurrency market
Marcin Wątorek,Stanisław Drożdż,Jarosław Kwapień,Ludovico Minati,Paweł Oświęcimka,Marek Stanuszek
arXiv

The review introduces the history of cryptocurrencies, offering a description of the blockchain technology behind them. Differences between cryptocurrencies and the exchanges on which they are traded have been shown. The central part surveys the analysis of cryptocurrency price changes on various platforms. The statistical properties of the fluctuations in the cryptocurrency market have been compared to the traditional markets. With the help of the latest statistical physics methods the non-linear correlations and multiscale characteristics of the cryptocurrency market are analyzed. In the last part the co-evolution of the correlation structure among the 100 cryptocurrencies having the largest capitalization is retraced. The detailed topology of cryptocurrency network on the Binance platform from bitcoin perspective is also considered. Finally, an interesting observation on the Covid-19 pandemic impact on the cryptocurrency market is presented and discussed: recently we have witnessed a "phase transition" of the cryptocurrencies from being a hedge opportunity for the investors fleeing the traditional markets to become a part of the global market that is substantially coupled to the traditional financial instruments like the currencies, stocks, and commodities.

The main contribution is an extensive demonstration that structural self-organization in the cryptocurrency markets has caused the same to attain complexity characteristics that are nearly indistinguishable from the Forex market at the level of individual time-series. However, the cross-correlations between the exchange rates on cryptocurrency platforms differ from it. The cryptocurrency market is less synchronized and the information flows more slowly, which results in more frequent arbitrage opportunities. The methodology used in the review allows the latter to be detected, and lead-lag relationships to be discovered.



Network Structures of Collective Intelligence: The Contingent Benefits of Group Discussion
Joshua Becker,Abdullah Almaatouq,Emőke-Ágnes Horvát
arXiv

Research on belief formation has produced contradictory findings on whether and when communication between group members will improve the accuracy of numeric estimates such as economic forecasts, medical diagnoses, and job candidate assessments. While some evidence suggests that carefully mediated processes such as the "Delphi method" produce more accurate beliefs than unstructured discussion, others argue that unstructured discussion outperforms mediated processes. Still others argue that independent individuals produce the most accurate beliefs. This paper shows how network theories of belief formation can resolve these inconsistencies, even when groups lack apparent structure as in informal conversation. Emergent network structures of influence interact with the pre-discussion belief distribution to moderate the effect of communication on belief formation. As a result, communication sometimes increases and sometimes decreases the accuracy of the average belief in a group. The effects differ for mediated processes and unstructured communication, such that the relative benefit of each communication format depends on both group dynamics as well as the statistical properties of pre-interaction beliefs. These results resolve contradictions in previous research and offer practical recommendations for teams and organizations.



Nonlinearities and Asymmetric Adjustment to PPP in an Exchange Rate Model with Inflation Expectations
Anderl, Christina,Caporale, Guglielmo Maria
SSRN
This paper estimates a model of the real exchange rate including standard fundamentals as well as two alternative measures of inflation expectations for five inflation targeting countries (UK, Canada, Australia, New Zealand, Sweden) over the period January 1993-July 2019. Both a benchmark linear ARDL model and a nonlinear ARDL (NARDL) specification are considered. The results suggest that the nonlinear framework is more appropriate to capture the behaviour of real exchange rates given the presence of asymmetries both in the long- and short-run. In particular, the speed of adjustment towards the PPP-implied long-run equilibrium is three times faster in a nonlinear framework, which provides much stronger evidence in support of PPP. Moreover, inflation expectations play an important role, with survey-based ones having a more sizable effect than market-based ones. Monetary authorities should aim to achieve a high degree of credibility to manage them and thus currency fluctuations effectively. The inflation targeting framework might be especially appropriate for this purpose.

On Asymptotic Log-Optimal Buy-and-Hold Strategy
Chung-Han Hsieh
arXiv

In this paper, we consider a frequency-based portfolio optimization problem with $m \geq 2$ assets when the expected logarithmic growth (ELG) rate of wealth is used as the performance metric. With the aid of the notion called dominant asset, it is known that the optimal ELG level is achieved by investing all available funds on that asset. However, such an "all-in" strategy is arguably too risky to implement in practice. Motivated by this issue, we study the case where the portfolio weights are chosen in a rather ad-hoc manner and a buy-and-hold strategy is subsequently used. Then we show that, if the underlying portfolio contains a dominant asset, buy and hold on that specific asset is asymptotically log-optimal with a sublinear rate of convergence. This result also extends to the scenario where a trader either does not have a probabilistic model for the returns or does not trust a model obtained from historical data. To be more specific, we show that if a market contains a dominant asset, buy and hold a market portfolio involving nonzero weights for each asset is asymptotically log-optimal. Additionally, this paper also includes a conjecture regarding the property called high-frequency maximality. That is, in the absence of transaction costs, high-frequency rebalancing is unbeatable in the ELG sense. Support for the conjecture, involving a lemma for a weak version of the conjecture, is provided. This conjecture, if true, enables us to improve the log-optimality result obtained previously. Finally, a result that indicates a way regarding an issue about when should one to rebalance their portfolio if needed, is also provided. Examples, some involving simulations with historical data, are also provided along the way to illustrate the~theory.



Optimal Bookmaking
Matthew Lorig,Zhou Zhou,Bin Zou
arXiv

We introduce a general framework for continuous-time betting markets, in which a bookmaker can dynamically control the prices of bets on outcomes of random events. In turn, the prices set by the bookmaker affect the rate or intensity of bets placed by gamblers. The bookmaker seeks a price process that maximizes his expected (utility of) terminal wealth. We obtain explicit solutions or characterizations to the bookmaker's optimal bookmaking problem in various interesting models.



Optimal Search and Discovery
Rafael P. Greminger
arXiv

This paper studies a search problem where a consumer is initially aware of only a few products. At every point in time, the consumer then decides between searching among alternatives he is already aware of and discovering more products. I show that the optimal policy for this search and discovery problem is fully characterized by tractable reservation values. Moreover, I prove that a predetermined index fully specifies the purchase decision of a consumer following the optimal search policy. Finally, a comparison highlights differences to classical random and directed search.



Optimal Transport of Information
Semyon Malamud,Anna Cieslak,Andreas Schrimpf
arXiv

We study the general problem of Bayesian persuasion (optimal information design) with continuous actions and continuous state space in arbitrary dimensions. First, we show that with a finite signal space, the optimal information design is always given by a partition. Second, we take the limit of an infinite signal space and characterize the solution in terms of a Monge-Kantorovich optimal transport problem with an endogenous information transport cost. We use our novel approach to: 1. Derive necessary and sufficient conditions for optimality based on Bregman divergences for non-convex functions. 2. Compute exact bounds for the Hausdorff dimension of the support of an optimal policy. 3. Derive a non-linear, second-order partial differential equation whose solutions correspond to regular optimal policies. We illustrate the power of our approach by providing explicit solutions to several non-linear, multidimensional Bayesian persuasion problems.



Optimal make take fees in a multi market maker environment
Bastien Baldacci,Dylan Possamaï,Mathieu Rosenbaum
arXiv

Following the recent literature on make take fees policies, we consider an exchange wishing to set a suitable contract with several market makers in order to improve trading quality on its platform. To do so, we use a principal-agent approach, where the agents (the market makers) optimise their quotes in a Nash equilibrium fashion, providing best response to the contract proposed by the principal (the exchange). This contract aims at attracting liquidity on the platform. This is because the wealth of the exchange depends on the arrival of market orders, which is driven by the spread of market makers. We compute the optimal contract in quasi explicit form and also derive the optimal spread policies for the market makers. Several new phenomena appears in this multi market maker setting. In particular we show that it is not necessarily optimal to have a large number of market makers in the presence of a contracting scheme.



Optimal management of DC pension fund under relative performance ratio and VaR constraint
Guohui Guan,Zongxia Liang,Yi xia
arXiv

In this paper, we investigate the optimal management of defined contribution (abbr. DC) pension plan under relative performance ratio and Value-at-Risk (abbr. VaR) constraint. Inflation risk is introduced in this paper and the financial market consists of cash, inflation-indexed zero coupon bond and a stock. The goal of the pension manager is to maximize the performance ratio of the real terminal wealth under VaR constraint. An auxiliary process is introduced to transform the original problem into a self-financing problem first. Combining linearization method, Lagrange dual method, martingale method and concavification method, we obtain the optimal terminal wealth under different cases. For convex penalty function, there are fourteen cases while for concave penalty function, there are six cases. Besides, when the penalty function and reward function are both power functions, the explicit forms of the optimal investment strategies are obtained. Numerical examples are shown in the end of this paper to illustrate the impacts of the performance ratio and VaR constraint.



Optimizing Expected Shortfall under an $\ell_1$ constraint -- an analytic approach
Gábor Papp,Imre Kondor,Fabio Caccioli
arXiv

Expected Shortfall (ES), the average loss above a high quantile, is the current financial regulatory market risk measure. Its estimation and optimization are highly unstable against sample fluctuations and become impossible above a critical ratio $r=N/T$, where $N$ is the number of different assets in the portfolio, and $T$ is the length of the available time series. The critical ratio depends on the confidence level $\alpha$, which means we have a line of critical points on the $\alpha-r$ plane. The large fluctuations in the estimation of ES can be attenuated by the application of regularizers. In this paper, we calculate ES analytically under an $\ell_1$ regularizer by the method of replicas borrowed from the statistical physics of random systems. The ban on short selling, i.e. a constraint rendering all the portfolio weights non-negative, is a special case of an asymmetric $\ell_1$ regularizer. Results are presented for the out-of-sample and the in-sample estimator of the regularized ES, the estimation error, the distribution of the optimal portfolio weights and the density of the assets eliminated from the portfolio by the regularizer. It is shown that the no-short constraint acts as a high volatility cutoff, in the sense that it sets the weights of the high volatility elements to zero with higher probability than those of the low volatility items. This cutoff renormalizes the aspect ratio $r=N/T$, thereby extending the range of the feasibility of optimization. We find that there is a nontrivial mapping between the regularized and unregularized problems, corresponding to a renormalization of the order parameters.



Phase Transitions in Kyle's Model with Market Maker Profit Incentives
Charles-Albert Lehalle,Eyal Neuman,Segev Shlomov
arXiv

We consider a stochastic game between three types of players: an inside trader, noise traders and a market maker. In a similar fashion to Kyle's model, we assume that the insider first chooses the size of her market-order and then the market maker determines the price by observing the total order-flow resulting from the insider and the noise traders transactions. In addition to the classical framework, a revenue term is added to the market maker's performance function, which is proportional to the order flow and to the size of the bid-ask spread. We derive the maximizer for the insider's revenue function and prove sufficient conditions for an equilibrium in the game. Then, we use neural networks methods to verify that this equilibrium holds. We show that the equilibrium state in this model experience interesting phase transitions, as the weight of the revenue term in the market maker's performance function changes. Specifically, the asset price in equilibrium experience three different phases: a linear pricing rule without a spread, a pricing rule that includes a linear mid-price and a bid-ask spread, and a metastable state with a zero mid-price and a large spread.



Portfolio Optimization Constrained by Performance Attribution
Yuan Hu,W. Brent Lindquist
arXiv

This paper investigates performance attribution measures as a basis for constraining portfolio optimization. We employ optimizations that minimize expected tail loss and investigate both asset allocation (AA) and the selection effect (SE) as hard constraints on asset weights. The test portfolio consists of stocks from the Dow Jones Industrial Average index; the benchmark is an equi-weighted portfolio of the same stocks. Performance of the optimized portfolios is judged using comparisons of cumulative price and the risk-measures maximum drawdown, Sharpe ratio, and Rachev ratio. The results suggest a positive role in price and risk-measure performance for the imposition of constraints on AA and SE, with SE constraints producing the larger performance enhancement.



Precision of Public Information Disclosures, Banks’ Stability and Welfare
Takalo, Tuomas,Moreno, Diego
SSRN
We study the optimal precision of public information disclosures about banks assets quality. In our model the precision of information affects banks' cost of raising funding and asset profile riskiness. In an imperfectly competitive banking sector, banks'stability and social surplus are non-monotonic functions of precision: an intermediate precision (or low-to-intermediate precision if banks contract their repayment promises on public information) maximizes stability, and also yields the maximum surplus when the social cost of bank failure c is large. When c is small and the banks' asset risk taking is not too sensitive to changes in the precision, the maximum surplus (and maximum risk) are reached at maximal precision. In a perfectly competitive banking sector in which banks' asset risk taking is not too sensitive to the precision of information, the maximum surplus (and maximum risk) are reached at maximal precision, while maximum stability is reached at minimal precision.

Pricing high-dimensional Bermudan options with hierarchical tensor formats
Christian Bayer,Martin Eigel,Leon Sallandt,Philipp Trunschke
arXiv

An efficient compression technique based on hierarchical tensors for popular option pricing methods is presented. It is shown that the "curse of dimensionality" can be alleviated for the computation of Bermudan option prices with the Monte Carlo least-squares approach as well as the dual martingale method, both using high-dimensional tensorized polynomial expansions. This discretization allows for a simple and computationally cheap evaluation of conditional expectations. Complexity estimates are provided as well as a description of the optimization procedures in the tensor train format. Numerical experiments illustrate the favourable accuracy of the proposed methods. The dynamical programming method yields results comparable to recent Neural Network based methods.



Risk Transmission from the COVID-19 to Metals and Energy Markets
Yousaf, Imran
SSRN
We examine the risk transmission from the COVID-19 to metal (precious and industrial) and energy markets using the BEKK-MGARCH model. The findings reveal the significant and negative volatility transmission from the COVID-19 to gold, palladium, and brent oil markets, suggesting the safe-haven properties of these markets. The COVID-19 risk is not transmitted to the industrial metal market, whereas the rise in COVID-19 volatility leads to an increase in WTI oil market volatility. These results provide useful insights to investors and policymakers regarding risk management, asset pricing, and financial market stability during the COVID-19 pandemic.

Signaling and Employer Learning with Instruments
Gaurab Aryal,Manudeep Bhuller,Fabian Lange
arXiv

This paper considers the use of instruments to identify and estimate private and social returns to education within a model of employer learning. What an instrument identifies depends on whether it is hidden from, or transparent (i.e., observed) to, the employers. A hidden instrument identifies private returns to education, and a transparent instrument identifies social returns to education. We use variation in compulsory schooling laws across non-central and central municipalities in Norway to construct hidden and transparent instruments. We estimate a private return of 7.9%, of which 70% is due to increased productivity and the remaining 30% is due to signaling.



Softening the Blow: U.S. State-Level Banking Deregulation and Sectoral Reallocation after the China Trade Shock
Ruslanova, Lilia,Hoffmann, Mathias
SSRN
U.S. state-level banking deregulation during the 1980’s mitigated the impact of the China trade shock (CTS) on local economies (states and commuting zones) a decade later, in the 1990s. Local economies, where local banking markets opened up earlier, were also effectively financially more integrated by the 1990’s and saw smaller declines in house prices, wages, and income following the CTS. We explain this pattern in a theoretical model that emphasizes the stabilizing effect of financial integration on demand for housing and on housing prices: faced with an adverse shock to their region’s terms-of-trade (i.e. the CTS), households in more open states can more easily access credit to smooth consumption. This stabilizes consumer demand for housing, keeps the relative price of housing up, stabilizes wages in the non-tradable sector and thus facilitates the sectoral reallocation of labor away from import-exposed manufacturing towards the housing sector. This in turn stabilizes income and consumption. We corroborate these predictions of our model in state- and commuting zone level data. Then, using granular bank-county-level data, we show that household consumption smoothing in response to the CTS was easier in financially open areas, because geographically diversified banks were more elastic in their lending response to household’s increased demand for credit. Our findings highlight that household access to finance is important to ease adjustment after asymmetric terms-of-trade shocks in monetary unions, in particular when the geographical mobility of labor is limited.

Stochastic leverage effect in high-frequency data: a Fourier based analysis
Imma Valentina Curato,Simona Sanfelici
arXiv

The stochastic leverage effect, defined as the standardized covariation between the returns and their related volatility, is analyzed in a stochastic volatility model set-up. A novel estimator of the effect is defined using a pre-estimation of the Fourier coefficients of the return and the volatility processes. The consistency of the estimator is proven. Moreover, its finite sample properties are studied in the presence of microstructure noise effects. The Fourier methodology is applied to S\&P500 futures prices to investigate the magnitude of the stochastic leverage effect detectable at high-frequency.



Stock Option Predictability for the Cross-Section
Neuhierl, Andreas,Tang, Xiaoxiao,Varneskov, Rasmus Tangsgaard,Zhou, Guofu
SSRN
We provide the first comprehensive analysis of the information content from options markets for predicting the cross-section of stock returns. We jointly examine an extensive set of firm characteristics and an exhaustive set of option predictors, filling the void between two largely disjoint literatures. Using both portfolio sorts and machine learning methods, we find that options have strong predictive power for the cross-section of returns after controlling for firm characteristics. A structural analysis shows that the strongest predictors are associated with tail risk premia and leverage. Our findings imply that these risks are estimated more accurately from options data, providing annualized Sharpe ratios in excess 1.5.

Supervision of Financial Institutions Revisited: The Transition From Basel I to Basel III. A Critical Appraisal of the Newly Established Regulatory Framework in Response to the Credit Crunch
Vousinas, Georgios
SSRN
In order to address the weaknesses of the financial system revealed by the recent financial crisis, Basel Committee introduced a series of changes in the international regulatory framework. Basel III is a set of proposed modifications to international rules on capital adequacy and liquidity of banks as well as any other issues relating to banking supervision. This paper is an attempt to identify the provisions of Basel III rules, applicable since 2013 and gradually to a depth of six years. This is probably the most significant initiative of the Commission following the recent credit crunch. In particular, a thorough reference is made to the factors affecting capital adequacy and other regulations of the financial system, as set by the supervising authorities, and also to matters of compliance of all involved institutions. The aim of this paper is to provide a critical evaluation of the new regulatory framework, known as Basel III, with emphasis on the new capital adequacy factors and shed light on its impact on global banking system.

Take-Up of Joint and Individual Liability Loans: An Analysis With Laboratory Experiment
Baulia, Susmita
SSRN
This paper reports a study on decision-making by borrowers regarding take-up of different loan types in a laboratory microfinance experiment. I show that when prospective borrowers are offered a flexible choice of different loan types (here, individual liability (IL) and joint liability (JL)), take-up increases. This is due to heterogeneous borrowers self-selecting into different loan types. Results suggest that more risk averse borrowers are less willing to take up IL loan and less selfish borrowers show signs of higher inclination to take up JL loan. The results collectively imply that microloan offers need to be customized according to the heterogeneous preferences of borrowers; also, there needs to be enough flexibility in the offered choice-set for better self-selection. This would result in a substantial increase in the take-up rate of microloans by the borrowers.

The Anatomy of Collateralized Loan Obligations: On the Origins of Covenants and Contract Design
Kundu, Shohini
SSRN
This paper provides a dissection of the Collateralized Loan Obligation (CLO) market and examines the significance of covenants in facilitating the provision of credit. Since the Great Financial Crisis, the leveraged loan market has witnessed unprecedented growth. CLOs play an increasingly central role in the provision of credit to corporations, holding as much as 75% of all new institutional leveraged loans, as reported in 2019. The rise of the leveraged loan and CLO markets have attracted the attention of central banks which have been concerned with both the growth of the market and the opaque nature of interconnections between intermediaries, leveraged borrowers, and investors. Despite their increasing importance, little is understood about CLO intermediaries. In this paper, I describe the agency frictions inherent in the CLO market, and discuss how optimal contracts are derived with covenants that curtail against such frictions. In addition, I describe the general macroeconomic milieu that has facilitated the rapid growth of the CLO market as well as recent changes that have developed. Understanding the structural aspects and dynamics of CLOs intermediaries, situated between investors and loan syndicates, is paramount for analysis of the innards of the market, the role of covenants, and developing insights into the shadow banking sector as well as other securitizations.

The Determinants of Democracy Revisited: An Instrumental Variable Bayesian Model Averaging Approach
Sajad Rahimian
arXiv

Identifying the real causes of democracy is an ongoing debate. We contribute to the literature by examining the robustness of a comprehensive list of 42 potential determinants of democracy. We take a step forward and employ Instrumental Variable Bayesian Model Averaging (IVBMA) method to tackle endogeneity explicitly. Using the data of 111 countries, our IVBMA results mark arable land as the most persistent predictor of democracy with a posterior inclusion probability (PIP) of 0.961. Youth population (PIP: 0.893), life expectancy (PIP: 0.839), and GDP per capita (PIP: 0.758) are the next critical independent variables. In a subsample of 80 developing countries, in addition to arable land (PIP: 0.919), state fragility proves to be a significant determinant of democracy (PIP: 0.779).



The English Patient: Evaluating Local Lockdowns Using Real-Time COVID-19 & Consumption Data
Gathergood, John,Guttman-Kenney, Benedict
SSRN
We find UK “local lockdowns” of cities and small regions, focused on limiting how many people a household can interact with and in what settings, are effective in turning the tide on rising positive COVID-19 cases. Yet, by focusing on household mixing within the home, these local lockdowns have not inflicted the large declines in consumption observed in March 2020 when the first virus wave and first national lockdown occurred. Our study harnesses a new source of real-time, transaction-level consumption data that we show to be highly correlated with official statistics. The effectiveness of local lockdowns are evaluated applying a difference-in-difference approach which exploits nearby localities not subject to local lockdowns as comparison groups. Our findings indicate that policymakers may be able to contain virus outbreaks without killing local economies. However, the ultimate effectiveness of local lockdowns is expected to be highly dependent on co-ordination between regions and an effective system of testing.

The Impact of Savings on Economic Growth in a Developing Country (the Case of Kosovo)
Ribaj, Artur
SSRN
The correlation between savings and economic growth has been the subject of research for some well-known economists. This study provides further insight on such correlation by examining the case of Kosovo from both a qualitative and quantitative research methodology. The data used was from 2010 to 2017 and has been analyzed using the augmented Dickey-Fuller tests, Johansen cointegration tests, and Ganger causality test. The test of the unit root confirms stationarity, and the regression results showed that deposits have a significant positive impact on Kosovo’s economic growth, because savings stimulate investment, production, and employment and consequently generate greater sustainable economic growth. Furthermore, loans and remittances also help boost the economy of Kosovo through their direct impact on investment. This paper confirms that countries whose national savings rate is high are not dependent on foreign direct investment; consequently, the risk arising from volatile foreign direct investment decreases significantly.

The Political Economy of Securities Industry Bars
Tierney, James Fallows
SSRN
Financial regulators can bar or exclude people from various industries. Yet securities regulators tend to impose too many broker bars, and too few against other financial professionals. While scholars have taken this pattern for granted, it presents a puzzle for securities law: what are these sanctions’ function? They are how securities law implements its distributive commitment to investor protectionâ€"making investors better off at brokers’ expense. Their function is to designate certain securities law rules as giving rise to a property-rule-like entitlement to capital owners not to have their profits from investing involuntarily transferred away from them by market intermediaries.Drawing from law and political economy, this article argues that industry bars' function reflects the particular social and historical context in which the securities laws arose. Despite decades of failed attempts, financial mar-ket reform happened only after a critical mass of modestly wealthy Americans, who had newly began investing in the stock market, found their savings defrauded or manipulated away from them. The early securities laws borrowed industry exclusion from the stock exchanges’ self-regulatory practice, and subsequent amendments have expanded exclusion’s role. Exclusion remains today the doctrinal tool that securities law uses for determining that certain misconduct reflects intolerable risk that a person working in the financial industry will involuntarily redistribute the returns on investors’ capital. This project aims to bring a political-economy approach back in to corporate and securities law scholarshipâ€"identifying hidden ways that doctrine and practice in capital markets regulation reflect and reinforce distributions of power and wealth and society.

The Speed of Adjustment in Net Operating Working Capital: An International Study
Baños-Caballero, Sonia,García-Teruel, Pedro J.,Martínez-Solano, Pedro
SSRN
This paper analyses whether there are differences in the speed of adjustment in net operating working capital (NWC) across countries. Unlike prior research, which reported that the adjustment speed of any current item is always rapid, we find that the speed of adjustment to NWC targets depends on a country’s investor protection and financial development. Specifically, using a sample of firms from 30 countries, we show that NWC adjustment speeds vary across countries, and they are faster for companies that operate in countries with stronger investor protection and greater financial development.

The Tradeoff between Discrete Pricing and Discrete Quantities: Evidence from U.S.-listed Firms
Li, Sida,Ye, Mao
SSRN
Economists usually assume that price and quantity are continuous variables, while most market designs, in reality, impose discrete tick and lot sizes. We study a firm’s trade-off between these two discretenesses in U.S. stock exchanges, which mandate a one-cent minimum tick size and a 100-share minimum lot size. A uniform tick size favors high prices because the bidâ€"ask spread cannot be lower than one cent. A uniform lot size favors low prices because low prices reduce adverse selection costs for market makers when they have to display at least 100 shares. We predict that a firm achieves its optimal price when its bidâ€"ask spread is two ticks wide, when the marginal contribution from discrete prices equals that from discrete lots. Empirically, we find that stock splits improve liquidity when they move the bidâ€"ask spread towards two ticks; otherwise, they reduce liquidity. Liquidity improvements contribute 95 bps to the average total return on a split announcement of 272 bps. Optimal pricing can increase the median U.S. stock value by 69 bps and total U.S. market capitalization by $54.9 billion.

The economic impact of weather and climate
Richard S.J. Tol
arXiv

I propose a new conceptual framework to disentangle the impacts of weather and climate on economic activity and growth: A stochastic frontier model with climate in the production frontier and weather shocks as a source of inefficiency. I test it on a sample of 160 countries over the period 1950-2014. Temperature and rainfall determine production possibilities in both rich and poor countries; positively in cold countries and negatively in hot ones. Weather anomalies reduce inefficiency in rich countries but increase inefficiency in poor and hot countries; and more so in countries with low weather variability. The climate effect is larger that the weather effect.



The impact of state capacity on the cross-country variations in COVID-19 vaccination rates
Dragan Tevdovski,Petar Jolakoski,Viktor Stojkoski
arXiv

The initial period of vaccination shows strong heterogeneity between countries' vaccinations rollout, both in the terms of the start of the vaccination process and in the dynamics of the number of people that are vaccinated. A predominant thesis in the ongoing debate on the drivers of this observed heterogeneity is that a key determinant of the swift and extensive vaccine rollout is state capacity. Here, we utilize two measures that quantify different aspects of the state capacity: i) the external capacity (measured through the soft power and the economic power of the country) and ii) the internal capacity (measured via the country's government effectiveness) and investigate their relationship with the coronavirus vaccination outcome in the initial period (up to 30th January 2021). By using data on 189 countries and a two-step Heckman approach, we find that the economic power of the country and its soft power are robust determinants of whether a country has started with the vaccination process. In addition, the government effectiveness is a key factor that determines vaccine roll-out. Altogether, our findings are in line with the hypothesis that state capacity determines the observed heterogeneity between countries in the initial period of COVID-19 vaccines rollout.



Till Death (or Divorce) Do Us Part: Early-Life Family Disruption and Investment Behavior
Betzer, André,Limbach, Peter,Rau, P. Raghavendra,Schürmann, Henrik
SSRN
We document a long-lasting association between a common societal phenomenon, early-life family disruption, and investment behavior. Controlling for socioeconomic status and family background, we find fund managers who experienced the death or divorce of their parents during childhood exhibit a stronger disposition effect, take lower risk, and are more likely to sell their holdings following risk-increasing firm events. The results are consistent with persistent symptoms of post-traumatic stress and strengthen as treatment intensifies. The evidence adds to our understanding of the role of social factors and “nurture” in finance as well as the origin of investment biases.

Trade Finance, Gaps and the COVID-19 Pandemic: A Review of Events and Policy Responses to Date
Auboin, Marc
SSRN
Developments in trade finance in 2020 were largely driven by the impact of the COVID-19 pandemic. Twelve years after the great financial crisis of 2008-09, the issue of trade finance reemerged as a matter of urgency. While the current pandemic-related crisis did not have a financial cause, one of its results has been that many countries are experiencing difficulties in accessing trade credit. This is occurring notably in countries â€" particularly developing countries â€" in which structural trade finance gaps were high even before the pandemic. As the health crisis developed and persisted, banks experienced an increase in failures by traders to fulfil payments, including in industries and sectors beyond those initially impacted by lockdowns, such as airlines, aeronautics and tourism. It quickly became evident that one-off extensions of terms of payment by creditors would be insufficient to alleviate the trade finance crisis. Based on the experience of the 2008-09 crisis, governments, export credit agencies and international financial institutions, including multilateral development banks, rapidly intervened to support private markets. Multilateral development banks have provided record amounts of trade finance guarantees and liquidity in developing countries, while governments have implemented payment deferral schemes. Large central banks have supplied foreign exchange resources to other central banks through swap agreements. Efforts to date have been substantial, but challenges remain in 2021, connected first with how to support the importation and exportation of vaccines against COVID-19, and then with how to encourage the recovery of trade flows. Recent events, policy responses and upcoming challenges are discussed and analysed in this paper.

Trading Signals In VIX Futures
M. Avellaneda,T. N. Li,A. Papanicolaou,G. Wang
arXiv

We propose a new approach for trading VIX futures. We assume that the term structure of VIX futures follows a Markov model. The trading strategy selects a multi-tenor position by maximizing the expected utility for a day-ahead horizon given the current shape and level of the VIX futures term structure. Computationally, we model the functional dependence between the VIX futures curves, the VIX futures positions, and the expected utility as a deep neural network with five hidden layers. Out-of-sample backtests of the VIX futures trading strategy suggest that this approach gives rise to reasonable portfolio performance, and to positions in which the investor can be either long or short VIX futures contracts depending on the market environment.



Показатељи тржишне концентрације и њихова дискриминаторна моћ: пример банковног сектора Србије (Indicators of Market Concentration and Its Discriminatory Power: Example of the Banking Sector of Serbia)
Bukvic, Rajko
SSRN
Serbian Abstract: У раду се приказују и анализирају основни показатељи који се користе у анализама концентрације на тржишту. Приказани су стандардни коефицијенти (CRn и HH), нешто реÑ'е коришћени (Ђинијев, Розенблатов и Тајдман-Холов, те коефицијент ентропије), као и Линда-индекси и приступ заснован на Ð"аусовој кривој распореда удела тржишних учесника. Анализа резултата који се добијају на основу тих индекса извршена је на примеру банковног сектора Србије (без Косова и Метохије), за године 2016â€"2019. Коришћени су подаци из завршних рачуна банака за пет билансних величина (укупна актива, депозити, капитал, кредити и друга потраживања и пословни приход). Ð"обијене вредности показатеља илуструју неједнозначност резултата, и то како кад је реч о примењеним индексима, тако и у односу на примењену билансну величину. Све то указује на потребу да се у будућим анализама користи већи број показатеља и већи број билансних величина, као и да се тумачењу резултата приступа уз неопходну пажњу.English Abstract: The paper shows and analyzes the main indicators that are used in the analyses of of the market concentration. It were demonstrated standard coefficients (CRn and HH), more rarely used (Gini, Rosenbluth and Tideman-Hall, and entropy coefficient), and the Linda indices and approach based on the Gaus’ curve of the distribution of market shares. The analysis of the results was made on the example of banking sector of Serbia (without Kosovo and Metohija), for the years 2016â€"2019. It were used the banks’ balances five aggregates (total assets, deposits and other liabilities, capital, loans and receivables, and operating income). The values of indicators illustrate ambiguity of results, both in the case of used indices, as well as the used balance aggregate. All of these indicate the need of the use in future analyses many indicators and aggregates, and the need to interpret the results with necessary attention.