Research articles for the 2021-01-12
SSRN
During the last 25 years, the stock market in the US has been strongly pro-cyclical in the presence of a counter-cyclical monetary policy. In this paper, we use an endogenous business cycle model to explore the factors contributing to a pro-cyclical stock market. A dynamic expectation structure in the real sector gives rise to a strong non-linearity and is responsible for the emergence of endogenous business cycles in the model. In the context of this model, we find that a timid or ineffective monetary policy allows the stock market to be dominated by the fluctuations of profits in the real sector. We model the potential ineffectiveness of monetary policy in terms of an endogenous risk premium. The model is calibrated to fit key properties of the data. In particular, it can generate a pro-cyclical stock market in the presence of a counter-cyclical monetary policy.
SSRN
We study a risk-sharing economy where an arbitrary number of heterogenous agents trades an arbitrary number of risky assets subject to quadratic transaction costs. For linear state dynamics, the forward-backward stochastic differential equations characterizing equilibrium asset prices and trading strategies in this context reduce to a system of matrix-valued Riccati equations. We prove the existence of a unique global solution and provide explicit asymptotic expansions that allow us to approximate the corresponding equilibrium for small transaction costs. These tractable approximation formulas make it feasible to calibrate the model to time series of prices and trading volume, and to study the cross-section of liquidity premia earned by assets with higher and lower trading costs. This is illustrated by an empirical case study.
SSRN
We exploit the fact that Israeli pension insurance policies do not take health conditions or smoking status into account in annuity pricing to investigate the potential effect of being a smoker on retirement payout choices. Contrary to the idea that smokers have higher discount rates (and thus should prefer the lump sum option), and even though the insurance pricing mechanism means that smokers would be offered the same annuity as nonsmokers (all else equal), we find that smokers do not prefer the lump sum option. We offer and test several potential explanations for our findings: illusions regarding life expectancy, self-control, and advantageous selection.
SSRN
In the FinTech world, 2020 could be called the year of stablecoins, which are crypto assets with a stable value. Stablecoins were analyzed by various intergovernmental organizations, regulators and scholars. Brightest minds around the world are still trying to understand what the legal nature of various types of stablecoins is and how to regulate stablecoins without hindering innovation. In the UK and EU, regulators are considering whether stablecoins such as LibraCoin are electronic money (e-money) and should be regulated accordingly. In their analysis regulators and scholars concluded that some stablecoins could indeed be considered e-money. The author of this Working Paper found that most legal analyses were done in abstract and were not dedicated to specific stablecoins and the context in which they exist. This Working Paper address this gap by analyzing concrete stablecoins such as LibraCoin, USDT, PAXG, DAI and the context in which they exist. One of the aims of the Working Paper is to create a general framework that can be used to analyse any existing stablecoin project under the UK and EU e-money legislation. This Working Paper defines nine types of stablecoin while explaining and applying the e-money test to these types of stablecoins. Unsurprisingly, this Working Paper reveals that most stablecoins analyzed are not e-money. Some stablecoins such as USDT most likely can be considered as e-money in the EU and UK. However, functions and use cases for USDT are quite different from the use cases of e-money as we know it. USDT and other stablecoins are extensively used in the world of Decentralized Finance (DeFi), and regulators should take into consideration the context surrounding stablecoins when deciding whether to apply the e-money framework to them.
SSRN
After the financial crisis we realised that the balance sheet and going concern statements of many of our major financial institutions proved wrong. The âCredit Scrunchâ of 2007 was a systemic failure. Interactions between elements of the system (banks, rating agencies, regulators, governments, financial instruments, auditors, etc.) mattered more than the specific behaviour of a particular actor. If you believe the crisis was an apocalypse or foreshadows an apocalypse, then you should be considering fundamental redesigns in numerous areas. How might we redesign auditing?
SSRN
This paper proposes a robust framework for disentangling undiversifiable common jumps within the realized covariance matrix. Simultaneous jumps detected in our empirical study are strongly related to major financial and economic news, and their occurrence raises correlation and persistence among assets. Our application to 20 Dow Jones stocks, shows that common jumps and directional common jumps substantially improve the in- and out-of-sample forecasts of the realized covariances at the day-, week- and month-horizon. Applying these new specifications to minimum variance portfolios results in superior positions from reduced turnover. The implication is that investors willingly sacrifice up to 100 annual basis points in switching to those strategies.
SSRN
We examine the impact of COVID-19 (C-19) pandemic on global equity markets by constructing novel infection indices. Our results show that the impact of prompt and large-scale policy interventions is ambiguous yet statistically significant. However, in this equivocality, the impact of global measures of policy interventions is more pronounced than local counterparts. Furthermore, despite the significant connection between variables describing fundamental infection data and equity market changes, we conclude that equity markets have decoupled from adverse impacts of C-19 mortality and morbidity data since the announcement of the pandemic by the WHO. Finally, the most compelling finding of our work is that changes in international equity markets are best predicted by the changes in the sentiment for C-19 infections. This prediction remains significant even if we account for local and global infection data and policy variables as well as control variables that capture changes in the post-pandemic sample.
SSRN
Network models represent a useful tool to describe the complex set of financial relationships among heterogeneous firms in the system. In this paper, we propose a new semiparametric model for temporal multilayer causal networks with both intra- and inter-layer connectivity. A Bayesian model with a hierarchical mixture prior distribution is assumed to capture heterogeneity in the response of the network edges to a set of risk factors including the European COVID-19 cases. We measure the financial connectedness arising from the interactions between two layers defined by stock returns and volatilities. In the empirical analysis, we study the topology of the network before and after the spreading of the COVID-19 disease.
SSRN
We study the effect of civil conflict on investment using detailed microdata from Colombiaâs largest agricultural bank. We use a difference-in-difference design that compares municipalities with varying levels of historical activity by insurgent group FARC before and after the 2016 demobilization agreement between this group and the Colombian government. We show that the monthly number of loans to small farmers in municipalities with historical FARC presence increases disproportionately after the agreement, without changes in average size or interest rate. This increase is driven by a larger number of applications and is concentrated in municipalities with better access to markets. There is no change in default rates and reports from randomized audits reveal no difference in misuse of funds. Effects are much weaker during the negotiation phase that preceded the agreement, despite a reduction in violence, suggesting that armed group presence and the threat of continued conflict disincentivize the pursuit of profitable investments.
SSRN
A perfectly divisible corporate bond is allocated to a set of bidders characterized by limits both to their budget, but most importantly to the risk entailed in their portfolio. Bidders possess symmetric information concerning the secondary market's yield. We choose to use a uniform pricing mechanism contrary to discriminatory as the former generates more revenues and reduces the winner's curse. As a first step, we prove the existence of symmetric Bayesian Nash equilibrium when risk-neutral bidders respond to an exogenous secondary market providing the necessary comparative statics. In the second stage, we confirm the existence of equilibrium when bidders' types are affiliated with the secondary market by a copula.
SSRN
This paper briefly overviews several challenging dimensions pertaining to cryptocurrencies with respect to their valuation, legitimacy, design, consensual acceptance and market-based stylized facts with a view to understanding whether this new asset class indeed has the potential to become an alternative, or a replacement, to traditional fiat currencies. Our survey indicates that public embrace of cryptocurrencies continues to lag as the masses continue to show reluctance in embracing cryptocurrencies as a complement, let alone a substitute to fiat counterparts. Governments have also successfully defended their sovereignty in preserving legal tender status, structural seigniorage, and exclusivity. Market-based studies hint at consistent inefficiencies across the spectrum. Furthermore, whether fundamental and mining factors determine cryptocurrenciesâ values remain unsettled. The most promising areas of research for crypto-financial intelligentsia would be delving into establishing trial runs for central bank backed cryptocurrencies. In addition, we highlight that several methodological and data-based obstacles remain in assessing the link between cryptocurrencies and their traditional rivals. This avenue remains a fertile ground for potential future research.
SSRN
We introduce elements of Cumulative Prospect Theory into the portfolio selection problem and then compare stock portfolios selected under the behavioral approach with those selected according to classical approaches, such as Mean Variance and Mean Absolute Deviation ones. The mathematical programming problem associated to the behavioral portfolio selection is highly non-linear and non-differentiable; for these reasons it is solved using a Particle Swarm Optimization approach. An application to the STOXX Europe 600 equity market is performed.
arXiv
With the recent advancement in Deep Reinforcement Learning in the gaming industry, we are curious if the same technology would work as well for common quantitative financial problems. In this paper, we will investigate if an off-the-shelf library developed by OpenAI can be easily adapted to mean reversion strategy. Moreover, we will design and test to see if we can get better performance by narrowing the function space that the agent needs to search for. We achieve this through augmenting the reward function by a carefully picked penalty term.
SSRN
This paper provides highly significant evidence that golden parachutes spur innovation in concentrated-ownership corporations and State-Owned-Enterprises (SOEs). Taking advantage of China's institutional features, we find that golden parachutes lead to higher levels of innovation quantity and quality through a risk-taking mechanism. The positive effects of parachutes on innovation are more pronounced when ownership concentration increases for SOEs, as well as when ownership concentration decreases for non-SOEs. We establish causality with two novel instrumental variables â" executive lawyer alumni connection and law firm density around headquarter.
SSRN
Dollar carry trade risk premiums â" unlike dollar-neutral or foreign exchange carry risk premiums â" are positively correlated with firm-level dispersions in investment, profitability, and book-to-market in addition to the Treasury-bill rate, long term bond yield, term spread, and default spread. Several forecasting models pin down the few periods responsible for the entire premium, based on these proxies for the latent risk and price of risk states in the U.S. (and its business cycle). This predictability is also statistically and economically significant out of sample: It generates Sharpe ratios as large as 1.37 (compared to 0.44 unconditionally), for example.
SSRN
The term structure of equity and its cyclicality are key to understand the risks driving equilibrium asset prices. We propose a general equilibrium model that jointly explains four important features of the term structure of equity: (i) a negative unconditional term premium, (ii) countercyclical term premia, (iii) procyclical equity yields, and (iv) premia to value and growth claims respectively increasing and decreasing with the horizon. The economic mechanism hinges on the interaction between heteroskedastic long-run growth â" which helps price long-term cash flows and leads to countercyclical risk premia â" and homoskedastic short-term shocks in the presence of limited market participation â" which produce sizeable risk premia to short-term cash flows. The slope dynamics hold irrespective of the sign of its unconditional average. We provide empirical support to our model assumptions and predictions.
arXiv
In the presence of monotone information, the stochastic Thiele equation describing the dynamics of state-wise prospective reserves is closely related to the classic martingale representation theorem. When the information utilized by the insurer is non-monotone, the classic martingale theory does not apply. By taking an infinitesimal approach, we derive a generalized stochastic Thiele equation that allows for information discarding. En passant, we solve some open problems for the classic case of monotone information. The results and their implication in practice are illustrated via examples where information is discarded upon and after stochastic retirement.
SSRN
This paper contributes to the literature on interlocking directorates (ID) by providing a new solution to the two econometric issues arising in the joint analysis of interlocks and firm performance which are the endogenous nature of ID and sample selection bias due to the exclusion of isolated firms. Some key determinants of ID network formation are identified and used to check for endogeneity. We analyze the impact of the positioning in the network on firmsâ performance and inspect how the impact varies across firms of different sizes drawing on information relating to 37,324 firms in the interlocking network which, to our knowledge, is the widest dataset ever used in approaching the study of ID. Our results, made robust for endogeneity and sample selection bias, suggest that eigenvector centrality and the clustering coefficient have a positive and significant impact on all the performance measures and that this effect is more pronounced for small firms.
SSRN
The application of the scientific paradigm to business operations transformed management thinking in the early part of the 20th century. A plethora of management theorizing since often obscures the simplicity at the core of the scientific paradigm. One approach, Environmental Consistency Confidence, restores statistical correlation to its rightful place at the core of financial risk management. For financial services organisations statistical correlation integrates well with existing Key Risk Indicator (KRI) initiatives. Through Environmental Consistency Confidence, financial organisations understand the limits of their environmental comprehension.
SSRN
Financial derivatives linked to the median, which is the 50%-th percentile of a distribution, have not been extensively studied in realistic models of financial markets, as such derivatives simply did not exist until recently. The Libor reform that brought a seismic change to the interest rate markets - the largest market in the world - linked derivatives worth hundreds of trillions of notional to a median of interest rate spreads, making the median, arguably, the most important "number" to study and understand in all of the financial markets at the moment.Numerically-efficient algorithms for calculating the fair value of the median that incorporate both the historical observations and the future dynamics of the Libor vs. the risk-free rate spreads in a realistic model have already been developed in our previous work on the subject. In this paper, we go significantly deeper than this important special case. Here, we focus on calculating the expected value of the median in a model of a history-less Brownian motion with a time-dependent shift, a model that provides rich mathematical structure to investigate, while also being very relevant to the current financial markets. We combine a newly-established linearization property under the large-volatility limit of the median, a universal white-noise approximation, and novel Machine Learning techniques to derive a general, numerically efficient algorithm for calculating the expected median. Theoretical advances and practical solutions to currently-topical problems are presented.
SSRN
Existing studies have addressed the significance of social influence and private communication in decision making in stock markets. However, the estimation of investor information networks remains an important and challenging task because the existing network inference methodologies lack the ability to explicitly account for the impact of public information on investor trading decisions. We address this gap by proposing a new framework to estimate private information channels in stock markets. In our approach, the impact of public information on investors' trading events is filtered out from investors' transactions. This allows us to reveal their co-behavior driven by the transfer of private information. Our results show that taking public information into account when inferring investor networks significantly changes their topology and strengthens the relationship between investor's network centrality and returns. Therefore, we believe that our approach leads to a more precise representation of the information network. Moreover, we find that the association between centrality and returns becomes statistically insignificant when network links are validated. The latter observation provides evidence of the importance of weak ties in information diffusion.
RePEC
This study examines the impact of information security breaches on the stock returns on French companies. Using the event study methodology, we provide insights on the effect of cyberattack announcements on the market value of French companies from 2009 to 2019. We show that following cyberattack announcements, stock returns significantly decrease. We find that financial companies are more negatively impacted than other industries. Our results lead conclude that cybersecurity is now fully integrated into risk management and the overall strategy of companies. Cyber resilience appears to be the essential element to face current threats and reassure investors.
SSRN
Shares sold through Initial Public Offerings (IPOs) are often underpriced and therefore very popular investment objects. Fjesme (2016) documents that the allocating investment bank requires certain larger investors in popular IPOs to also purchase more shares after the stock exchange listing. This additional buying supports prices and attracts more attention to the companies in the short term. Wilhelm (1999) explains how non-professional investors are likely to misunderstand this price support as positive information and thereby increase their investment. Obtaining data to investigate the implications of price support on investor holdings has proven difficult in the past. In this paper, I investigate actual IPO allocations combined with trading after the listing on the Oslo Stock Exchange (OSE). I document that increased price support generates a large influx of domestic and retail ownership as opposed to foreign institutional ownership. I conclude that price support reduces international institutional ownership on the OSE.
SSRN
We analyze the ESG rating criteria used by prominent agencies and show that there is a lack of a commonality in the definition of ESG (i) characteristics, (ii) attributes and (iii) standards in defining E, S and G components. We provide evidence that heterogeneity in rating criteria can lead agencies to have opposite opinions on the same evaluated companies and that agreement across those providers is substantially low. Those alternative definitions of ESG also affect sustainable investments leading to the identification of different investment universes and consequently to the creation of different benchmarks. This implies that in the asset management industry it is extremely difficult to measure the ability of a fund manager if financial performances are strongly conditioned by the chosen ESG benchmark. Finally, we find that the disagreement in the scores provided by the rating agencies disperses the effect of preferences of ESG investors on asset prices, to the point that even when there is agreement, it has no impact on financial performances.
SSRN
This paper addresses whether institutional investors drive the innovation direction of corporates toward environmentally friendly technologies. Using environmental patents filed by Chinese publicly-listed firms in the manufacturing and public utility sectors during the 2003-2010 period, we seek to quantify the relationship between shareholding ratios of institutional investors and corporate environmental innovation. Some novel findings are obtained. Firstly, institutional investors lead to a higher ratio of environmental patents in total patents for corporates in the pollution-intensive sectors than those in the non-pollution-intensive sectors. Secondly, institutional investors exert the roles of financial support and corporate governance in pursuit of monitoring corporateâs long-term innovation. Lastly, institutional investors could experience gains in a rise in corporate market value from accumulative environmental innovation.
SSRN
Regulators, investors, and the financial media argue that underwriters tie Initial Public Offering (IPO) allocations to investor post-listing purchases in the issuer shares. Using unique data from the Oslo Stock Exchange (OSE) I investigate if these tie-in agreements are driven by price stabilization (reducing price falls below the offer price) or laddering (inflating prices above the offer price). I find that both stabilizing and laddering investors are rewarded with increased allocations for their service. However, only laddering investors increase allocations in very oversubscribed future issues. Secondary investors also lose from falling returns following laddering. I conclude that underwriters use both price stabilization and laddering across different IPOs. However, the rewards for cooperating investors and the economic consequences for secondary investors are much greater following laddering.
arXiv
The topic of my research is "Learning and Upgrading in Global Value Chains: An Analysis of India's Manufacturing Sector". To analyse India's learning and upgrading through position, functions, specialisation & value addition of manufacturing GVCs, it is required to quantify the extent, drivers, and impacts of India's Manufacturing links in GVCs. I have transformed this overall broad objective into three fundamental questions: (1) What is the extent of India's Manufacturing Links in GVCs? (2) What are the determinants of India's Manufacturing Links in GVCs? (3) What are the impacts of India's Manufacturing Links in GVCs? These three objectives represent my three chapters in my PhD thesis.
SSRN
The market for auction rate securities collapsed following a series of failed auctions in February 2008, significantly constraining some closed-end fundsâ access to leverage. We use this exogenous shock to study empirically how leverage constraints affect investorsâ portfolio choice. Our main finding is that tightened leverage constraints result in an increased appetite for systematic risk: in the months following the shock, the affected funds bought significantly more high-beta stocks, and sold significantly more low-beta stocks, than their unaffected peers. Our results are consistent with the theoretical predictions of Black (1972) and Frazzini and Pedersen (2014), and provide causal evidence of the central mechanism underlying asset pricing under leverage constraints.
arXiv
The aim of this paper is to quantify and manage systemic risk caused by default contagion in the interbank market. We model the market as a random directed network, where the vertices represent financial institutions and the weighted edges monetary exposures between them. Our model captures the strong degree of heterogeneity observed in empirical data and the parameters can easily be fitted to real data sets. One of our main results allows us to determine the impact of local shocks, where initially some banks default, to the entire system and the wider economy. Here the impact is measured by some index of total systemic importance of all eventually defaulted institutions. As a central application, we characterize resilient and non-resilient cases. In particular, for the prominent case where the network has a degree sequence without second moment, we show that a small number of initially defaulted banks can trigger a substantial default cascade. Our results complement and extend significantly earlier findings derived in the configuration model where the existence of a second moment of the degree distribution is assumed. As a second main contribution, paralleling regulatory discussions, we determine minimal capital requirements for financial institutions sufficient to make the network resilient to small shocks. An appealing feature of these capital requirements is that they can be determined locally by each institution without knowing the complete network structure as they basically only depend on the institution's exposures to its counterparties.
arXiv
An approach to the modelling of volatile time series using a class of uniformity-preserving transforms for uniform random variables is proposed. V-transforms describe the relationship between quantiles of the stationary distribution of the time series and quantiles of the distribution of a predictable volatility proxy variable. They can be represented as copulas and permit the formulation and estimation of models that combine arbitrary marginal distributions with copula processes for the dynamics of the volatility proxy. The idea is illustrated using a Gaussian ARMA copula process and the resulting model is shown to replicate many of the stylized facts of financial return series and to facilitate the calculation of marginal and conditional characteristics of the model including quantile measures of risk. Estimation is carried out by adapting the exact maximum likelihood approach to the estimation of ARMA processes and the model is shown to be competitive with standard GARCH in an empirical application to Bitcoin return data.
SSRN
The empirical finding that market movements in stock prices may be correlated with the order flow of other stocks has led to the notion of "cross-impact" and has prompted the development of multivariate models of market impact. These models are parametrized by a matrix of impact coefficients whose off-diagonal elements are meant to capture how trades in one asset influence the price of other assets, leading to a large number of 'cross-impact' parameters which may not be identified solely based on the covariance of returns with order flow. Moreover, empirical evidence suggests that these cross-impact terms are unstable and change sign randomly over time, which poses a problem for their interpretation and use. We reexamine this empirical evidence from a causal standpoint and offer a simpler explanation for the observed correlation between the returns of an asset and the order flow imbalance of other assets, in terms of common components in order flow across stocks which may naturally arise from multi-asset trading strategies.We provide empirical evidence from order flow and price changes of NASDAQ-100 stocks to support this explanation. Our results show the main determinants of impact to be idiosyncratic order flow imbalance as well as a market order flow factor common across stocks. Additional âcross-impactâ terms account for less than 1% of market impact. This leads to a parsimonious approach for causal modelling of multi-asset impact, which does not require introducing any concept of "cross-impact".
arXiv
Many important economic outcomes result from cumulative effects of smaller choices, so the best outcomes require accounting for other choices at each decision point. We document narrow bracketing -- the neglect of such accounting -- in work choices in a pre-registered experiment on MTurk: bracketing changes average willingness to work by 13-28%. In our experiment, broad bracketing is so simple to implement that narrow bracketing cannot possibly be due to optimal conservation of cognitive resources, so it must be suboptimal. We jointly estimate disutility of work and bracketing, finding gender differences in convexity of disutility, but not in bracketing.
SSRN
In this study, we propose an implied forward-looking measure for systemic risk that employs the information from put option prices, the Systemic Options Value-at-Risk (SOVaR). This new measure can capture the buildup stage of systemic risk in the financial sector earlier than the standard stock market-based systemic risk measures (SRMs). Non-parametric tests show that our measure exhibits more timely early warning signals (up to one month earlier) regarding the main turbulent events around the global financial crisis of 2007-2009 than the three main stock market-based SRMs. Moreover, this new measure also shows significant predictive power with respect to macroeconomic downturns as well as future recessions. Our results are robust to various specifications, breakdowns of financial sectors, and controlling for the other mainrisk measures proposed in the literature.
arXiv
In this paper we develop models of asset return mean and covariance that depend on some observable market conditions, and use these to construct a trading policy that depends on these conditions, and the current portfolio holdings. After discretizing the market conditions, we fit Laplacian regularized stratified models for the return mean and covariance. These models have a different mean and covariance for each market condition, but are regularized so that nearby market conditions have similar models. This technique allows us to fit models for market conditions that have not occurred in the training data, by borrowing strength from nearby market conditions for which we do have data. These models are combined with a Markowitz-inspired optimization method to yield a trading policy that is based on market conditions. We illustrate our method on a small universe of 18 ETFs, using four well known and publicly available market variables to construct 10000 market conditions, and show that it performs well out of sample. The method, however, is general, and scales to much larger problems, that presumably would use proprietary data sources and forecasts along with publicly available data.
arXiv
In this paper we reformulate the problem of pricing options in a quantum setting. Our proposed algorithm involves preparing an initial state, representing the option price, and then evolving it using existing imaginary time simulation algorithms. This way of pricing options boils down to mapping an initial option price to a quantum state and then simulating the time dependence in Wick's imaginary time space. We numerically verify our algorithm for European options using a particular imaginary time evolution algorithm as proof of concept and show how it can be extended to path dependent options like Asian options. As the proposed method uses a hybrid variational algorithm, it is bound to be relevant for near-term quantum computers.
SSRN
As an alternative to bookbuilding, auctions are also used in IPO pricing and allocation in the U.S. and elsewhere. Is there quid pro quo in auctioned IPOs? We study this using a large proprietary IPO bidding dataset for auctions from China in which uniform price applies and the underwriter has pricing but not allocation discretion (and these features resemble the auctions adopted by WR Hambrecht in the U.S.). Exploiting the regulatory regime shift from pro-rata share allocation to lottery-draw allocation as an event, we examine whether there is quid pro quo between underwriters and their favored mutual fund families. We predict and find that when the share allocation rule changed from pro-rata to lottery-draw (that increases the participating costs and risk to bidders and thereby their incentives to seek favoritism), fund families having pre-event stronger commission ties with the underwriter tend to submit bids later, place more strategic and accurate bids, have a higher fraction of bids qualified for the allocation round, and a higher chance of receiving share allocation than fund families that have weaker commission ties with the underwriter. The evidence is consistent with the existence of quid pro quo facilitated the underwriterâs leakage of privileged bidding information and choosing an offering price below the market clearing price. Our novel evidence on quid pro quo in auctioned IPO extends the evidence of quid pro quo in U.S. book-building IPOs.
SSRN
This paper studies the link between bank recapitalization and welfare in a dynamic production economy. The model features financial frictions because banks benefit of a cost advantage at monitoring firms and face costly equity issuance. The competitive equilibrium outcome is inefficient because agents do not internalize the effects banksâ capitalization over the allocation of capital, its price and, in turn, firmsâ investments. It follows, individual recapitalizations are sub-optimal and bailout policies may benefit social welfare in the long run. Bailouts improve capital allocation in states where aggregate banks are poorly capitalized, therefore enhancing their market valuation, fostering investments, and stabilizing the economy recovery path.
SSRN
On October 6, 2020, the UK Financial Conduct Authority (âFCAâ) prohibited the sale of cryptocurrency-related derivatives (âcryptoderivativesâ) to retail investors on the ground that cryptocurrency as a reference asset for is an unreliable basis for valuation for these derivatives products. The FCA concluded that cryptoderivatives, especially in the form of contract for difference (âCFDâ) and exchange-traded notes (âETNsâ), are ill-suited for retail consumers due to the harm they pose. In Europe, the European Securities and Markets Authority (âESMAâ) has also been looking to curb cryptoderivatives trading as these products are risky, speculative, and expose consumers to potentially huge losses. Both regulators seem to have three main reasons for banning the sale of cryptoderivatives to retail investors: first, cryptocurrenciesâ extremely volatility as a reference asset; second, the prevalence of rampant market abuse, price manipulation, and security breaches in the cryptocurrency spot market; and third, investorsâ significant lack of understanding of these complex derivatives products. While regulators have initiated a broader crackdown in the UK and the EU to protect retail investors from the cryptoderivatives marketsâ abuse and manipulation, US regulators chose to go in the opposite direction. In 2014, the Commodity Futures Trading Commission (âCFTCâ) approved TeraExchange, a bitcoin derivatives exchange, to self-certify bitcoin swaps allowing investors to trade dollar-dominated bitcoin currency swaps. The following year, the CFTC classified bitcoin as a commodity in its order against Coinflip, Inc.â"a bitcoin trading platform, and thus ensured its entrance into the traditional derivatives market just like other commodities. Since then, several cryptoderivatives have proliferated in the marketâ"the Chicago Mercantile Exchange (âCMEâ) and Chicago Board Options Exchange (âCBOEâ) first launched cash-settled bitcoin futures in December 2017. The Intercontinental Exchange (âICEâ) introduced physically-settled bitcoin futures and bitcoin options in September and October 2019, respectively. With the CFTCâs announcement that the cryptocurrency âEthereumâ is a commodity, Eris Exchange (âErisXâ) launched Ethereum-based physically settled futures contracts on May 11, 2020. As of today, the US cryptoderivatives and perpetual swap market cap stands at $48.58 billion. As the market grows, the cryptoderivatives marketâs concerns are also emerging as unregulated online exchanges and brokerage firms offering cryptocurrency trading products are susceptible to spot market manipulation and cyber-attacks. To support the cryptoderivatives market, many argue that cryptoderivatives give institutional investors an efficient and confident way to hedge risk. However, this claim could be far from reality as two major global regulatorsâ"the FCA and the ESMA view cryptoderivatives as harmful to retail investors due to its opaque and uncertain nature. From a regulatory standpoint, the CFTCâs approach to regulating cryptoderivatives through self-certification (like traditional derivatives products) inadequately encapsulates the cryptocurrency spot marketâs inherent risks of opacity, price volatility, and its exposure to market manipulation. Such inadequacy is embedded in the CFTCâs two opposite positions. In a traditional commodity derivatives market, the CFTC has the power and capacity to oversee the commodity spot markets and, therefore, to take enforcement actions against any abusive and manipulative behavior that is detrimental to the investorsâ interests. However, concerning cryptoderivatives, the CFTCâs oversight mechanism over the cryptocurrency spot market is debatable as the CFTC, on repeated occasions, has appeared to have conflicting opinions regarding such power. Further, market participants in the spot market operate, assuming that the spot market is beyond the CFTCâs regulatory perimeter. Hence, in the absence of any regulatory clarity and the CFTCâs questionable oversight mechanism, the spot market could be a means to incentivize a bad actor to jeopardize cryptoderivatives marketsâ integrity and thereby undermine retail investorsâ confidence.In addition, investor protection is a grey area in the US cryptocurrency regulatory regime. As an example, although an Initial Coin Offering (âICOâ) is a security, it is uncertain that all investments are protected under the Security Investment Protection Act (âSIPAâ) given that the SEC has also determined that not all digital tokens are securities as depending on the degree of decentralization, a coin or token may fall outside the definition of a security. Similarly, investor protection in the cryptoderivatives market also remains vague as the answer to the question lies in the effectiveness of the CFTCâs regulatory and oversight mechanisms in preventing manipulation in the cryptocurrency spot market. Most investors, especially retail investors, lack an understanding of the complexity of cryptocurrency pricing and thus tend to treat cryptocurrency trading like gambling. Further, the complex pricing combined with extreme price volatility gives main-street investors an incentive to speculate the cryptocurrency price. Against this background, this paper puts forth a comparative analysis of the US regulatory responses to cryptoderivatives with specific references to the UKâs and the EUâs approaches and motives towards cryptoderivatives regulations in their respective regions. It discusses that the UK and the EU regulators primarily focus on protecting the retail investors from monetary losses arising from investment in cryptoderivatives products. In contrast, the US regulatory efforts are limited to interpreting cryptocurrency in light of the existing legal and regulatory framework, despite cryptocurrencyâs novel risks of price volatility and susceptibility to spot market manipulation, and the CFTCâs lack of oversight over the cryptocurrency spot market. It explores the possibility of imposing an outright ban on cryptoderivatives like the UK but concludes that an outright ban on the cryptoderivatives market is likely to jeopardize financial innovation growth in the US. Furthermore, some cryptocurrency trading platforms are already complying with the existing laws and regulations, and an outright ban will put set them back. Therefore, to protect market integrity and safeguard retail investorsâ interest, the paper proposes that Congress enact a comprehensive cryptocurrency regulation (âcryptoregulationâ) recognizing the novelty of the cryptocurrenciesâ market risks and introducing effective regulatory treatments to curb market manipulation in the cryptocurrency spot market vis-Ã -vis cryptoderivatives market. This paper envisions a comprehensive cryptoregulation, which would include (1) centralization of cryptocurrency trading platforms, (2) a mandatory registration requirement for all cryptocurrency exchanges, and (3) a federal cryptocurrency agency, having exclusive jurisdiction over cryptocurrencies and oversight authority on the cryptocurrency spot markets.
SSRN
Using a sample of commercial aircraft transactions, the paper decomposes the raw fire sale discount on sales of aircraft by distressed airlines into three components: (i) quality impairment due to under-maintenance, (ii) misallocation to lower productivity users, and (iii) a liquidity component due to the immediacy of the sale. Results indicate that financially distressed airlines sell aircraft that have a lower life expectancy and lower productivity. We combine the two effects into a quality impairment adjustment that explains around one half of the raw liquidation discount. For the remaining discount of around 9%, we find no direct evidence of misallocation to lower productivity users and industry outsiders. Rather, the post-sale users of distressed aircraft have significantly higher productivity than the distressed sellers, while their productivity is similar to that of other (non-distressed) users. In summary, our results indicate that the inefficiencies associated with fire sales are likely to be lower than have been previously documented.
SSRN
What are the risks? The community needs to take risks, all forms of human activity carry risks, there is no such thing as "risk-free". If society avoids risk, there would be no investment and no exploration. Is it possible to imagine this world without risk? that the human race would end, because of the unwillingness to accept the dangers of childbirth? On the other hand, we know well the consequences of carrying a lot of risks: asset bubbles, financial crises, and, ultimately, economic stagnation. So, banks, as providers of risk capital to the real economy, need to "risk management" so that they are not destructive to either party. Getting it wrong would damage not only the owners of and investors in the bank, but society as a whole.
SSRN
Are investment bankers valued members of society, or leeches? It all depends on the value they add. In economics, rent seekers are those who compete throughmanipulating the environment rather than adding value. Rent seekers use methods such as encouraging regulation or government protection to extract wealth (rent) without improving productivity. If it sounds like a term of derision, it is, and is frequently associated with other terms such as lobbying, bribing and corruption.Wholesale banking may be at a cross-roads. Down one road lies a free-wheeling,value-adding industry; down the other a shrinking oligopoly of banks share their takings from exploiting customers.
SSRN
While equity crowdfunding has grown in prevalence, investors have had very few opportunities to exit their investments. To address this, several equity crowdfunding platforms have started considering developing secondary markets for buying and selling shares. Using detailed data from the worldâs first secondary market for equity crowdfunding, we investigate whether committing to list on the secondary market after the fundraising campaign leads to greater investor participation and thus helps entrepreneurs to raise more money during the campaign. We find that in the early days of the secondary market, making a pre-commitment to list attracted more investors and larger investment sums. However, this positive effect disappeared after the first 18 months of secondary market operation, most likely because investors realized the lack of liquidity on the secondary market and thus the fact that secondary markets are currently unlikely to constitute a viable exit route. Our findings offer valuable insights to platforms aiming at launching secondary markets and regulators responsible for validating such initiatives. In particular, equity crowdfunding would benefit greatly from liquid secondary markets, which however are difficult to achieve due to high information asymmetries, price formation difficulties, reputational concerns, and competition effects from the primary market.
SSRN
In light of the COVID 19 crisis, the Federal Reserve has carried out stress tests to assess if major banks have sufficient capital to ensure their viability should a new and perhaps unprecedented crisis emerge. The Fed argues that the scenarios underpinning these stress tests are severe but plausible, yet they have not offered any evidence or framework for measuring the plausibility of their scenarios. If the scenarios are indeed plausible, it makes sense for banks to retain enough capital to withstand their occurrence. If, however, the scenarios are not reasonably plausible, banks will have deployed capital less productively than they otherwise could have, thereby impairing credit expansion and economic growth. The authors apply a measure of statistical unusualness, called the Mahalanobis distance, to assess the plausibility of the Fedâs stress scenarios. A first pass of their analysis, based on conventional statistical assumptions, reveals that the Fedâs scenarios are not even remotely plausible. However, the authors offer two modifications to their initial analysis that increase the scenariosâ plausibility. First, they show how the Fed can minimally modify their scenarios to render them marginally plausible in a Gaussian world. And second, they show how to evaluate the plausibility of the Fedâs scenarios by replacing the theoretical world of normality with a distribution that is empirically grounded.
SSRN
The purpose of this editorial is to examine fiat currencies and common tenders (tradeâbased money) from a risk perspective. The editorial encourages risk managers to consider the distributive benefits of a multiplicity of currencies and urges them to examine common tenders both old, such as the Swiss WIR, and novel, such as capacity exchange monies, as risk management tools.Design/methodology/approachThe editorial is based on research conducted for the City of London Corporation in 2011 into capacity, trade and credit which examined new architectures for commerce and money.FindingsThe editorial links Freiwirtschaft movement ideas with some characteristics of common tenders. Further, it considers whether some simple regulatory approaches might make such common tenders more useful.Originality/valueOf note, the author suggests that a modern alternative to government regulation might be an audited ISO accreditation standard for âgood currencyâ or âgood common tenderâ.
arXiv
The Secured Overnight Funding Rate (SOFR) is becoming the main Risk-Free Rate benchmark in US dollars, thus interest rate term structure models need to be updated to reflect the key features exhibited by the dynamics of SOFR and the forward rates implied by SOFR futures. Historically, interest rate term structure modelling has been based on rates of substantially longer time to maturity than overnight, but with SOFR the overnight rate now is the primary market observable. This means that the empirical idiosyncrasies of the overnight rate cannot be ignored when constructing interest rate models in a SOFR-based world.
As a rate reflecting transactions in the Treasury overnight repurchase market, the dynamics of SOFR are closely linked to the dynamics of the Effective Federal Funds Rate (EFFR), which is the interest rate most directly impacted by US monetary policy target rate decisions. Therefore, these rates feature jumps at known times (Federal Open Market Committee meeting dates), and market expectations of these jumps are reflected in prices for futures written on these rates. On the other hand, forward rates implied by Fed Funds and SOFR futures continue to evolve diffusively. The model presented in this paper reflects the key empirical features of SOFR dynamics and is calibrated to futures prices. In particular, the model reconciles diffusive forward rate dynamics with piecewise constant paths of the target short rate.
SSRN
The financial crises since 2007 have inspired many suggestions for reform. In order to evaluate proposed changes to financial markets and their regulation, we need to agree on the goals and properties of the financial system which we are trying to create as much as come up with ideas for reform. This paper looks at how design principles might inform financial systems design. It presents a sample set of principles based on a structure that distinguishes Insured Banks from Other Financial Institutions.
arXiv
This paper develops a theoretical model to study the economic incentives for a social media platform to moderate user-generated content. We show that a self-interested platform can use content moderation as an effective marketing tool to expand its installed user base, to increase the utility of its users, and to achieve its positioning as a moderate or extreme content platform. The optimal content moderation strategy differs for platforms with different revenue models, advertising or subscription. We also show that a platform's content moderation strategy depends on its technical sophistication. Because of imperfect technology, a platform may optimally throw away the moderate content more than the extreme content. Therefore, one cannot judge how extreme a platform is by just looking at its content moderation strategy. Furthermore, we show that a platform under advertising does not necessarily benefit from a better technology for content moderation, but one under subscription does. This means that platforms under different revenue models can have different incentives to improve their content moderation technology. Finally, we draw managerial and policy implications from our insights.
SSRN
In this paper we present a general equilibrium model to analyze competition between multiple venues (dealers), endogenous market segmentation, transaction speeds and fees, trading volume, optimal regulator's choice for taxing traders, and welfare in illiquid asset markets. Differences in trading speed between different venues lead to endogenous market segmentation, which in- creases trading volume and thus overall liquidity. Specifically, we find that liquidity increases in trading speeds, while decreasing in transaction fees and regulatory taxes. With competition, the optimal choice of transaction fees are increasing (resp. decreasing) in the trading speed of the faster (resp. slower) venue. When venue entry is sequential, the entrant's optimal choice of trading speed increases with lower entry costs and regulatory taxes. We further consider different notions of welfare: surplus from trade, trading volume, and trading revenue. In each of these cases, we consider the optimal regulator's choice for taxing traders, and the resulting optimal choice of speed for the entrant. Depending on the regulatorâs objective, the optimal trading tax choice can be zero or strictly positive. Finally, we investigate welfare loss due to competition and the speed choice of the entrant.
arXiv
Financial disclosure analysis and Knowledge extraction is an important financial analysis problem. Prevailing methods depend predominantly on quantitative ratios and techniques, which suffer from limitations like window dressing and past focus. Most of the information in a firm's financial disclosures is in unstructured text and contains valuable information about its health. Humans and machines fail to analyze it satisfactorily due to the enormous volume and unstructured nature, respectively. Researchers have started analyzing text content in disclosures recently. This paper covers the previous work in unstructured data analysis in Finance and Accounting. It also explores the state of art methods in computational linguistics and reviews the current methodologies in Natural Language Processing (NLP). Specifically, it focuses on research related to text source, linguistic attributes, firm attributes, and mathematical models employed in the text analysis approach. This work contributes to disclosure analysis methods by highlighting the limitations of the current focus on sentiment metrics and highlighting broader future research areas
SSRN
The moral hazard problem plagues the start-ups and even mature enterprises when they incorporate venture capital to pursue business upgrade or expansion. Especially in the value chain where the venture capitalist can synergize with the entrepreneur to contribute to the firm value. This paper proposes a game theoretic approach to solve the entrepreneur's optimization problem in a venture capital financing scheme and generalizes the formulation without a specific revenue function. Furthermore, this study generates managerial insights for venture capital market and relevant sustainable supply chain management. The key results also show that the complementarity effect can incentivize both the entrepreneur and the venture capitalist to exert more effort, thus achieving larger enterprise value when it is relatively significant, and the inefficiency caused by the allocation of equity share could be mitigated.
SSRN
This work addresses the impact of imperfections, such as information asymmetry and market sentiment, on the performance of option pricing models. More precisely, this work compares the option pricing model of Black and Scholes and the same model in the presence of imperfections. This study is based on S&P 500 options that cover the period between 17/03/2000 and 14/06/2013. The achieved results show that, in general, in the presence of imperfections, the model is more effective than the Black and Scholes model. This research appears to be promising for the incorporation of imperfections into the assessment of options.
SSRN
We estimate a logit mixture vector autoregressive model describing monetary policy transmission in the euro area over the period 2003Q1-2019Q4 with a special emphasis on credit conditions. With the help of this model, monetary policy transmission can be described as mixture of two states (e.g., a normal state and a crisis state), using an underlying logit model determining the relative weight of these states over time. We show that shocks to the credit spread and shocks to credit standards directly lead to a reduction of real GDP growth, whereas shocks to the quantity of credit are less important in explaining growth fluctuations. Credit standards and the credit spread are also the key determinants of the underlying state of the economy in the logit submodel. Together with a more pronounced transmission of monetary policy shocks in the crisis state, this provides further evidence for a financial accelerator in the euro area. Finally, the detrimental effect of credit conditions is also reflected in the labor market.
SSRN
We investigate whether financial contract terms alter individualsâ risk-taking behavior under a moral hazard framework. Exploiting (a) the contractual-level data of automobile insurance, and (b) a unique institutional reform that gives more pricing freedom to insurers, we discover a significant decline in the likelihood of accidents (and those involving injuries or deaths) after the premium becomes more sensitive to past performance. The effects are stronger for riskier drivers, and in regions with a more dangerous road condition. The evidence suggests that contracts with a more flexible premium scheme of rewards and penalties induce less risky behavior, mitigating moral hazard.
SSRN
I develop and estimate, using hand-collected data, a game-theoretic model of strategic corporate fraud, that incorporates and quantifies firms' adjustments in fraud propensities in response to regulators' information processing capacity. The findings are economically significant. A one standard deviation change in different regulatory interventions is associated with an annual increase of 10 to 58 fraudulent cases. I exploit the 2005 option backdating scandal as an exogenous shock to regulatory attention, and find further support for both the opportunism in fraud and the deterrence effect. I document that fraudulent behavior is heterogeneous in executive incentives and firm complexity.
SSRN
Material adverse effect (MAE) provisions have taken center stage in mergers and acquisitions (M&A) in the midst of the COVID-19 pandemic. Like with other crises, as the pandemic unfolds, two questions inevitably arise for dealmakers. First, in the short term, what grounds may parties use to exit pending transactions? And, second, in the long term, what impact will the crisis have on negotiating current and future deals and drafting related contractual provisions? In many M&A transactions, especially those involving publicly traded companies, the answers to both questions almost always involve MAEs. These provisions allow parties, typically the acquirer, to exit a transaction without penalty if the other party has suffered a MAE, as that term is defined in the agreement.This Essay examines MAEs through the lens of transaction cost economics, a theory utilized to determine how to best structure transactions especially amidst uncertainty. Uncertainties are inherent in purchasing a highly specific asset, like a company, which are further compounded by external socioeconomic conditions. This, in turn, gives rise to higher transaction costs, such as due diligence, increased negotiations, and ex post enforcement. MAE provisions are one of the ways in which dealmakers attempt to control the transaction costs of ex post enforcement. As life in a pandemic becomes the new reality, dealmakers are adjusting to ensure that pandemic-related effects do not trigger MAEs. Consequently, this raises transaction costs and has an impact on whether a deal is signed and ultimately consummated, and on what terms. This Essay discusses how dealmakers have dealt with the pandemic in terms of MAEs and argues that while revised MAEs may complicate dealmaking, they will not hinder it. This Essay attempts to look into the dealmakerâs crystal ball to foresee changes both in deal process and deal terms. It argues that in place of the traditional role of a MAE, dealmakers instead will take other steps to compensate for uncertainty, including expanded due diligence, adjusted valuations, provisions to renegotiate terms, or reverse termination fees. If anything is clear as dealmakers look into their crystal ball, it is that hope creates opportunity but so does chaos.
SSRN
I derive two valid forecasting models of the equity premium in monthly frequency, based on little more than no-arbitrage: A âpredictability timingâ version of partial least squares, given that predictability is theoretically time varying; and a least squares model with realized market premiums in monthly frequency as the regressor, since realized returns are theoretically correlated to risk and to the price of risk. This evidence is consistent with the instability inherent to monthly equity premium forecasts based on standard partial least squares and disaggregated book-to-markets as regressors, and with the fact that taking one extra lag of book-to-markets in predictive return regressions improves the estimates.
SSRN
Valuation issues have long posed challenges for the U.S. federal tax system. This is not just because of questions about what technique will most accurately value particular types of property. A key problem for tax administration is that taxpayers have an incentive to claim erroneous, self-serving valuations. This Essay analyzes tax valuation through this tax compliance lens. In so doing, it highlights the importance that third parties to the taxpayer-government relationship act at armâs-length from the taxpayer. It also explains why penalties are insufficient to deter erroneous self-reported valuations. The Essay also draws on the tax compliance perspective to make some preliminary observations about valuation methodologies.
SSRN
Practitioners, regulators, and the financial media argue that underwriters tie Initial Public Offering (IPO) allocations to investor post-listing buying of the issuer shares in a process labelled price support. Arguably, this excess demand boosts post-listing returns which underwriters trade quid-pro-quo with investor stock-trading-commission payments. In this paper, I investigate unique data from the Oslo Stock Exchange (OSE) including investor stock-trading-commissions, IPO allocations, and post-listing trading. I document that investors who provide high returns to underwriters before IPOs benefit from price support through increased returns in IPOs. I conclude that price support is used when investors share boosted returns with underwriters.
arXiv
The application of the Cauchy distribution has often been discussed as a potential model of the financial markets. In particular the way in which single extreme, or "Black Swan", events can impact long term historical moments, is often cited. In this article we show how one can construct Martingale processes, which have marginal distributions that tend to the Cauchy distribution in the large volatility limit. This provides financial justification to the approach investigated in \cite{Romero}, and highlights an example of how quantum probability can be used to construct non-Gaussian Martingales. We go on to illustrate links with hyperbolic diffusion, and discuss the insight this provides.
SSRN
Russian Abstract: Ð' данной ÑÑаÑÑе делаеÑÑÑ Ð¿Ð¾Ð¿ÑÑка пÑовеÑÑи ÑазлиÑие Ð¼ÐµÐ¶Ð´Ñ Ð¿Ð¾Ð½ÑÑиÑми пÑоизводиÑелÑноÑÑи и ÑÑÑекÑивноÑÑи в Ð±Ð°Ð½ÐºÐ°Ñ . Ð' ÑÑаÑÑе показано, ÑÑо понÑÑие ÑÑÑекÑивноÑÑи ÑвлÑеÑÑÑ Ð¾ÑноÑиÑелÑнÑм понÑÑием, опÑеделÑемÑм ÑаÑÑÑоÑнием Ð¼ÐµÐ¶Ð´Ñ ÑÑÑекÑивноÑÑÑÑ Ð¸ идеалÑнÑми ÑÑовнÑми. ÐÑÑекÑивноÑÑÑ Ð·Ð°ÐºÐ»ÑÑаеÑÑÑ Ð² Ñом, ÑÑÐ¾Ð±Ñ ÑабоÑаÑÑ Ñмнее, ÑÑÐ¾Ð±Ñ Ð¿Ð¾Ð»ÑÑаÑÑ Ð±Ð¾Ð»ÑÑе пÑи менÑÑÐ¸Ñ Ð·Ð°ÑÑаÑÐ°Ñ . но пÑодÑкÑивноÑÑÑ Ð½Ð°Ñелена ÑолÑко на ÑвелиÑение обÑего Ð´Ð¾Ñ Ð¾Ð´Ð°, ÑÑо возможно благодаÑÑ Ð¿Ð¾Ð²ÑÑÐµÐ½Ð¸Ñ Ð¿ÑоизводиÑелÑноÑÑи и повÑÑÐµÐ½Ð¸Ñ ÑезÑлÑÑаÑов. Таким обÑазом, конÑепÑÐ¸Ñ ÑÑÑекÑивноÑÑи ÑвлÑеÑÑÑ Ð±Ð¾Ð»ÐµÐµ вÑеобÑемлÑÑей, Ñем конÑепÑÐ¸Ñ Ð¿ÑоизводиÑелÑноÑÑи. Ð' докÑменÑе Ñакже пÑоводиÑÑÑ ÑазлиÑие Ð¼ÐµÐ¶Ð´Ñ Ð´Ð²ÑÐ¼Ñ Ñипами банковÑкой ÑÑÑекÑивноÑÑи, вопеÑвÑÑ , конÑепÑÐ¸Ñ X-ÑÑÑекÑивноÑÑи, в коÑоÑом пÑедполагаеÑÑÑ, ÑÑо ÑÑÑекÑивноÑÑÑ ÑвÑзана Ñ Ð¿ÑиÑодой ÑеловеÑеÑкой оÑганизаÑии, вÑоÑÐ°Ñ - ÑÑо опеÑаÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÑÑекÑивноÑÑÑ, коÑоÑÐ°Ñ ÑвлÑеÑÑÑ ÑиÑÑо ÑÐµÑ Ð½Ð¸ÑеÑкой конÑепÑией, она ÑказÑваеÑ, иÑполÑзÑÐµÑ Ð»Ð¸ банк минималÑнÑй обÑем ÑеÑÑÑÑов Ð´Ð»Ñ Ð¿ÑоизводÑÑва опÑеделенного обÑÑ'ма пÑодÑкÑии или ÑвелиÑÐ¸Ð²Ð°ÐµÑ Ð¾Ð±Ñем вÑÑ Ð¾Ð´Ð½Ð¾Ð¹ дано Ð·Ð°Ð´Ð°Ð½Ð½Ð¾Ð¼Ñ ÐºÐ¾Ð»Ð¸ÑеÑÑÐ²Ñ Ð²Ð²Ð¾Ð´Ð°.English Abstract: This article attempts to distinguish between the concepts of productivity and efficiency in banks. The article shows that the concept of efficiency is a relative concept defined by the distance between efficiency and ideal levels. Efficiency is to work smarter, to get more at a lower cost. but productivity is only aimed at increasing total income, which is possible due to increased productivity and improved results. Thus, the concept of efficiency is more comprehensive than the concept of performance. The document also makes a distinction between the two types of banking efficiency, firstly, the concept of X-efficiency, which assumes that efficiency is related to the nature of the human organization, the second is operational efficiency, which is a purely technical concept, it indicates whether the bank uses the minimum amount of resources for the production of a certain volume of production or increases the output volume is given to a given amount of input.