Research articles for the 2020-09-10

A Proposal for a Temporarily Amended Version of Precautionary Recapitalisation Under the Single Resolution Mechanism Regulation involving the European Stability Mechanism
Gortsos, Christos,Siri, Michele,Bodellini, Marco
European credit institutions are expected to pile up a relevant amount of non-performing loans (NPLs) as a consequence of the crisis provoked by the Covid-19 pandemic. Against this backdrop, one of the most critical issues at stake is whether credit institutions currently hold an amount of capital which is sufficient to absorb the losses that they will likely experience in the forthcoming future. If this will not be the case, then they will have to undergo recapitalisations. In a context of global, generalised and prolonged economic crisis, nevertheless, it could turn out to be extremely challenging to find private investors able and willing to significantly invest in their equity. Therefore, a new solution capable to balance conflicting, yet legitimate, needs, such as credit institutions’ recapitalisation without recurring (again) to excessive and generalised public bail-outs, might have to be quickly found.Accordingly, because of the high bar set in the recent past by the Single Resolution Board (SRB) for the submission of failing or likely to fail (FOLF) credit institutions to resolution (unless a different interpretation of the public interest criterion in light of the current crisis is put forward), and with a view to avoiding credit institutions’ liquidation financed through public resources, what we propose hereby is a temporary, revised and standardised form of privately and publicly funded precautionary recapitalisation, designed beforehand and operating on an quasi-automatic basis. Thus, this paper advocates a temporary amendment of the so-called precautionary recapitalisation under the Single Resolution Mechanism Regulation (SRMR) with the major involvement of the European Stability Mechanism (ESM). Such proposal should, of course, build on the regime currently in place also in light of the European Commission’s (Commission) decision to temporarily suspend the application of the state aid prohibitions laid down in the Treaty on the Functioning of the European Union (TFEU).Along with the European Central Bank (ECB), a major role in the process should also be played by the SRB and the ESM, with a view to keeping as much as possible the same level playing field within the Banking Union (BU). The final goal would be to strike a fair balance between the primary need to avoid the collapse of the whole banking system as a consequence of the Covid-19 crisis and the interest to discourage excessive moral hazard and unsound public policies.Accordingly, for a limited period of time, we propose that some of the conditions currently required by the SRMR for the precautionary recapitalisation of credit institutions established in the BU should be amended in line with the recent measures adopted by the Commission to facilitate public intervention to support the economy. This should be combined with an ESM facility allowing it to buy hybrid instruments issued by the credit institutions that would need to be recapitalised. In this regard, the ESM could raise the resources needed by issuing senior bonds on the market to be then used to buy contingent convertibles (CoCos) with characteristics enabling them to be included in the credit institutions’ Common Equity Tier 1 (CET1) capital, as was the case in Greece in 2015, with a view to divesting as soon as the market conditions will allow it. Such an action, in turn, could be placed within a broader framework permitting the ESM to monitor the credit institutions’ activity against some targets designed to allow them, over time, to pay back the issued instruments.

A Review of COVID-19 and Its Waterfall Effect on the Changed World
Kapur, Manoj,Anand, Tirupathi,Banerjee, Arindam
2019 novel coronavirus has affected over 19.3 million people and caused over 718 thousand deaths globally (as at 7 August 2020). The disease was named as “Covid19” and the virus that causes it was Severe Acute Respiratory Syndrome Corona Virus -2 (SARS-COV-2). On the eve of 2020, when the whole world was celebrating the new year, the virus was unleashing and conquering new territories, minute by minute. So, how come a small virus that is said to have originated from Wuhan, China was able to create such a big havoc? How did a flu-like-symptom virus was able to shackle economies and change the world we live in? What caused Governments to announce relief, fiscal and economic packages to prevent the large-scale economic collapse? The response lies in the way the virus made man-kind to live in the new world. Social distancing was the new norm that led to fewer interactions among people. Next, mass scale shut downs announced by the governments led to closure of financial markets, stock exchanges, corporate offices, exchange of trade as well as several events. No country was immune by the shocks caused by the waterfall effect of COVID19. The compounding rate at which the virus spread hinted several sectors were going to be severely disrupted. The current paper will analyze the waterfall effect of COVID19 on several sectors in the first half of 2020 (Jan to June 2020) and ascertain the fiscal, economic and monetary policies announced by governments in the top 5 affected countries and UAE as at 7 August 2020. The study will qualitatively ascertain how lockdowns and social distancing changed the world we live in and provide certain recommendations for future pandemics/ crises as part of research contribution.

Analysts' Weight of Forecasts in Stock Recommendations - from The Recursive Partitioning Approach
Li, Tao
I utilize the recursive partitioning method to extract analysts’ weight of forecasts assigned in their stock recommendation decisions. My findings suggest that in addition to analysts’ earnings forecasts, the non-earnings forecasts, such as sales forecasts and net income forecasts, also play an important role in explaining stock recommendation decisions. The overall weight from six different types of forecasts is positively related to the effectiveness recommendations and the profitability of trading on recommendations. Homogeneity in the styles of using forecasts is a result of analysts’ learning, which leads to variations in analysts’ capability of producing influential recommendations and their career outcomes.

Are Critical Audit Matters Informative?
Klevak, Julia,Livnat, Joshua,Pei, Duo,Suslava, Kate
Breaking from a long stretch of using largely standard language in unqualified audit opinions, the Public Company Accounting Oversight Board (PCAOB) expanded audit reports to disclose Critical Audit Matters (CAMs) and the audit procedures used to address them. The first wave of CAM disclosures began for large accelerated filers after June 2019, with most disclosures occurring in February 2020. Using Natural Language Processing (NLP) techniques, this study examines the types of CAMs disclosed by auditors and the typical audit procedures used to address them. We then explore whether CAMs are informative to investors and security analysts. Our findings are consistent with greater amounts of CAM disclosures as indicators of greater uncertainty. We document that market reactions are more negative for firms with more CAM disclosures; analysts reduce their earnings forecasts to a larger extent for such firms; stock prices become more volatile; and the dispersion of analyst forecasts are greater for firms with more CAM disclosures. We further find that many issues related to CAMs are raised in earnings conference calls with analysts during the immediately subsequent quarter. While these findings indicate that CAMs are informative to investors and analysts, their effects are concentrated around the time of disclosure. We do not find evidence of a drift in returns after the initial disclosures.

Bayesian state-space modeling for analyzing heterogeneous network effects of US monetary policy
Niko Hauzenberger,Michael Pfarrhofer

Understanding disaggregate channels in the transmission of monetary policy is of crucial importance for effectively implementing policy measures. We extend the empirical econometric literature on the role of production networks in the propagation of shocks along two dimensions. First, we allow for industry-specific responses that vary over time, reflecting non-linearities and cross-sectional heterogeneities in direct transmission channels. Second, we allow for time-varying network structures and dependence. This feature captures both variation in the structure of the production network, but also differences in cross-industry demand elasticities. We find that impacts vary substantially over time and the cross-section. Higher-order effects appear to be particularly important in periods of economic and financial uncertainty, often coinciding with tight credit market conditions and financial stress. Differentials in industry-specific responses can be explained by how close the respective industries are to end-consumers.

Big Shoes to Fill: CEO Turnover and Pre-Appointment Firm Performance
Minutti-Meza, Miguel,Nanda, Dhananjay,Xu, Rosy
Bayesian learning implies that corporate owners’ performance expectations for their CEO are affected by their firm’s performance prior to the CEO’s appointment because firm asset quality is persistent. Accordingly, we find that the sensitivity of CEO turnover to performance increases in pre-appointment firm performance; that is, a CEO is more likely to be dismissed for underperformance when appointed at a better-performing firm. Consistent with Bayesian learning, we show that this effect increases with firm uncertainty and declines over CEO tenure. We find no evidence that the effect is due to owners’ biased assessments of CEO ability or corporate governance quality. Collectively, our results suggest that CEOs, indeed, face a “big shoes to fill” effect that affects their performance-related turnover likelihood.

Bribes and Corporate Performance: Evidence from a Quasi-Natural Experiment
Im, Jieun,Kim, Woojin
We examine how bribes may affect corporate performance using a quasi-natural experiment. Specifically, we exploit the 2016 enactment of the Improper Solicitation and Graft Act in Korea which limits provision of gifts and entertainment to public sector employees as an exogenous shock to bribery practices. We find that a firm’s level of bribery activities, instrumented by industry-level government exposure, has a negative impact on its performance. In particular, a reduction in predicted bribery activity results in a significant improvement in operating performance. Overall, our findings provide convincing evidence that bribery may impair corporate performance.

Client Engineering of XVA in Crisis and Normality: Restructuring, Mandatory Breaks and Resets
Kenyon, Chris
Crises challenge client XVA management because the prices of derivatives contain the XVA hedges that the provider requires, as well as the functional hedge the client requires. By functional hedge we mean the hedge linked to the client's business, e.g. FX, inflation, interest rate. By XVA hedge we mean the hedge linked to the client's credit risk and the provider's funding risk. The issue is that a derivative locks in the client credit level and the provider's funding level on the trade date, for the life of the trade. During a crisis both levels may be elevated. The standard methods for separating XVA hedges from the functional hedge is to use a Mandatory Break at inception, limiting the lock in, or to restructure post-trade assuming XVA can be rebated. Alternatively, in normal times resets can be used and are better because the client pays XVA on the continuation after the reset using the provider's view of client survival probability from original trade inception. We quantify these strategies from the client point of view to find where a Mandatory Break, or equivalently restructuring, is a better client strategy and where a reset is better. This quantification combines risk-neutral and risk-neutral conditional on physical measures. We provide numerical examples using Mandatory Breaks/restructuring and resets, informed by credit shocks and recovery from past crises. In normal times a reset can be twice as effective as a Mandatory Break or restructuring, whereas provided there is at least a 1/3 recovery from a CDS shock a Mandatory Break is better in our examples.

Common Fund Flows: Flow Hedging and Factor Pricing
Dou, Winston Wei,Kogan, Leonid,Wu, Wei
We consider a myopic environment, where some investors delegate investments to fund managers. Managers care about fund size, fluctuating due to fund returns and flows, and thus have flow-hedging motives to tilt portfolios toward low-flow-beta stocks, boosting these stocks’ valuations. Fund flows endogenously respond to macroeconomic conditions, and thus a risk premium analogous to the ICAPM’s intertemporal hedging term emerges. Net alphas also fluctuate endogenously. Empirically, fund flows obey a strong factor structure with the common component priced, and fund portfolios are further tilted toward low-flow-beta stocks following increases in flow-hedging motives, instrumented using unexpected trade-war announcements and natural disasters.

Competition Laws, Ownership and Corporate Social Responsibility
Ding, Wenzhi,Levine, Ross,Lin, Chen,Xie, Wensi
Theory offers differing perspectives and predictions about the impact of product market competition on corporate social responsibility (CSR). Using firm-level data on CSR from 2002 through 2015 and panel data on competition laws in 48 countries, we discover that intensifying competition induces firms to increase CSR activities as a strategy for strengthening relationships with workers, suppliers, and customers. The CSR-enhancing effects of competition depend on corporate ownership, with smaller effects among block-holders with shorter horizons (e.g., hedge funds) and among family-controlled firms. Furthermore, the competition-CSR effect is stronger (a) among less financially constrained firms that are better positioned to boost CSR activities and (b) in economies where social norms prioritize CSR activities, as this is where the relationship building effect of CSR are likely to be the greatest.

Correlation Risk, Strings and Asset Prices
Distaso, Walter,Mele, Antonio,Vilkov, Grigory
Many asset pricing theories treat the cross-section of returns volatility and correlations as two intimately related quantities driven by common factors, which hinders achieving a neat definition of a correlation premium. We formulate a model without factors, but with a continuum of securities that have returns driven by a string. In this model, the arbitrage restrictions require that any asset premium links to the granular exposure of the asset returns to shocks in all other asset returns: an average correlation premium. This premium is both statistically and economically significant, and considerably fluctuates, driven by time-varying correlations and global market developments. The model predictions also lead to uncover fresh properties of big stocks. Big stocks display a high degree of market connectivity in bad times, but they are safer than other stocks, thereby providing hedges against times of heightened correlations. Finally, the model also explains the time-series behavior of the premium for the risk of changes in asset correlations (the premium for correlation risk), including its inverse relation with realized correlations.

Deep Replication of a Runoff Portfolio
Thomas Krabichler,Josef Teichmann

To the best of our knowledge, the application of deep learning in the field of quantitative risk management is still a relatively recent phenomenon. This article presents the key notions of Deep Asset Liability Management (Deep~ALM) for a technological transformation in the management of assets and liabilities along a whole term structure. The approach has a profound impact on a wide range of applications such as optimal decision making for treasurers, optimal procurement of commodities or the optimisation of hydroelectric power plants. As a by-product, intriguing aspects of goal-based investing or Asset Liability Management (ALM) in abstract terms concerning urgent challenges of our society are expected alongside. We illustrate the potential of the approach in a stylised case.

Default or Profit Scoring Credit Systems? Evidence from an Emerging High-Risk P2P Loan Market.
Lyocsa, Stefan,Vašaničová, Petra
For the emerging peer-to-peer (P2P) lending markets to survive, they need to employ credit risk management practices that ensure an investor base that is profitable in the long-term. In this paper, we propose a profit scoring decision support system that is dynamically updated and based on modeling the annualized adjusted internal rate of return of a loan. Our statistical approach is based on logistic and linear regularization methods complemented with Bayesian model averaging and selection techniques. Using data on loans from an emerging European P2P market, we document that in an out-of-sample framework, our approach overwhelmingly dominates standard credit scoring models that are based on labeling loans as either defaulted or not. In fact, even if we take data snooping bias into account, we find that realized returns tend to be significantly--almost 2.5 times--higher when using our profit scoring approach compared to the standard credit-scoring model based on regularized logistic regressions. Finally, as our results are robust across different modeling choices, we conclude that the management of credit risk can be significantly increased by designing systems that model profitability instead of loan (non)failure. Our results thus suggest a paradigm shift in modeling credit risk in the P2P market as modeling loan returns leads to much more accurate decisions than that achieved by more elaborate models that model loan's probability of a default.

Designing All-Weather Overlays â€" A Study on Option-Based Systematic Strategies
Loeper, Gregoire
We perform an empirical analysis of systematic trading strategies on options. Namely, we focus on strategies which sell out of the money (OTM) call options to harvest the premium, and buy downside protection through OTM puts. We compare the risk adjusted performance across different choices of strike, maturity and option notional. In this paper we mostly focus on the S&P 500 index over the period 2007â€"2018. There is also a brief look of the performances of the best strategies during the COVID-19 pandemic in early 2020.

Detecting and Adapting to Crisis Pattern with Context Based Deep Reinforcement Learning
Benhamou, Eric,Saltiel, David,Ohana, Jean-Jacques,Atif, Jamal
Deep reinforcement learning (DRL) has reached super human levels in complex tasks like game solving (Go, StarCraft II, Atari Games), and autonomous driving. However, it remains an open question whether DRL can reach human level in applications to financial problems and in particular in detecting pattern crisis and consequently dis-investing. In this paper, we present an innovative DRL framework consisting in two subnetworks fed respectively with portfolio strategies past performances and standard deviations as well as additional contextual features. The second sub network plays an important role as it captures dependencies with common financial indicators features like risk aversion, economic surprise index and correlations between assets that allows taking into account context based information. We compare different network architectures either using layers of convolutions to reduce network’s complexity or LSTM block to capture time dependency and whether previous allocations is important in the modeling. We also use adversarial training to make the final model more robust. Results on test set show this approach substantially over-performs traditional portfolio optimization methods like Markovitz and is able to detect and anticipate crisis like the current COVID one.

Executive Stock Options and Systemic Risk
Armstrong, Chris,Zhou, Frank,Nicoletti, Allison
We examine whether features of bank executives’ compensation contracts cause them to take actions that contribute to systemic risk. Using multiple return-based measures of systemic risk coupled with an identification strategy that exploits heteroskedasticity to account for endogenous matching of executives and banks, we find that bank executives’ equity portfolio vega leads to greater subsequent systemic risk that manifests during economic downturns, but not during expansions. We also find that vega encourages bank executives to pursue specific activities that contribute to the accretion of systemic risk, including: (i) maintaining lower Tier 1 capital ratios, (ii) investing in commercial and industrial loans, which tend to track the business cycle, and non agency mortgagebacked securities, which are subject to greater default and liquidity risk, and (iii) greater reliance on liabilities subject to runs (i.e., short-term deposits). Collectively, our evidence suggests that bank executives’ incentive-compensation contracts promote systemic risk-taking by encouraging them to adopt lending, investment, and financing policies that are highly procyclical and contagious.

Exploration of Safe Havens for Africa’s Stock Markets: A Test Case under COVID-19 Crisis
Omane-Adjepong, Maurice,Alagidede, Imhotep
The bear markets associated with the ongoing COVID-19 crisis present a test case to examine the traditionally expounded safe haven capabilities of gold and other precious metals, as well as the growing claims that bitcoin is the new “virtual gold” of our time. New evidence from our paper fails to corroborate such claims, however, we find bitcoin as a complementary safe haven asset. Further results show that none of the traditional safe havens and bitcoin could offer refuge for Africa’s emerging equity markets. Instead, gold and palladium outperform the other candidates to provide sanctuary for small-sized equity markets.

Fearing the Fed: How Wall Street Reads Main Street
Yaron, Amir,Law, Tzuo Hann,Song, Dongho
We document a countercyclical sensitivity of the stock market to major macroeconomic news announcements. Stock prices react more to (either good or bad) announcement surprises when the economy is below its potential trend with the expectation of easing policy. Based on comprehensive regression analyses and a no-arbitrage asset pricing model with state-dependent dynamics of cash flows (dividends), interest rates (monetary policy), and risk premium (market price of risk), we argue that this cyclical pattern is driven by the procyclical nature of monetary policy expectation and countercyclical nature of market price of risk.

Financial Development and the Effect of Cross-Border Bank Flows on House Prices
Romero, Nestor,Cho, Sungjun,Hyde, Stuart
We analyse the role of financial development as a buffer to diminish the effect of a cross-border bank flows shock on house prices. From panel vector auto-regressions, we compute impulse-response functions for 38 countries ranked and grouped by financial development. In less financially developed countries, the observed response is positive and significant. As the level of development increases the response is tempered and becomes insignificant. Our findings extend to equity and bond markets. Cross-border bank flows shocks are also more important in explaining the historical dynamics of house prices in comparison to other shocks of a domestic nature in financially less developed countries while monetary policy shocks are key in the most financially developed markets. We explore the heterogeneity in house price response within each level of financial development, differences are associated with the levels of maximum loan-to-value ratios and a ratio of cross-border bank inflows over total liabilities abroad.

Forecasting financial markets with semantic network analysis in the COVID-19 crisis
A. Fronzetti Colladon,S. Grassi,F. Ravazzolo,F. Violante

This paper uses a new textual data index for predicting stock market data. The index is applied to a large set of news to evaluate the importance of one or more general economic related keywords appearing in the text. The index assesses the importance of the economic related keywords, based on their frequency of use and semantic network position. We apply it to the Italian press and construct indices to predict Italian stock and bond market returns and volatilities in a recent sample period, including the COVID-19 crisis. The evidence shows that the index captures well the different phases of financial time series. Moreover, results indicate strong evidence of predictability for bond market data, both returns and volatilities, short and long maturities, and stock market volatility.

Framing Effects in the Chinese Stock Market: A Test of New Measurement to Firm-Special Behavioral Characteristic
Xie, Jun,Hu, Nan,Gao, Bin,Tan, ChunZhi
This paper provides a measurement of framing effects in the stock market by using actual market open trading data, and provide a test of this new firm-special behavioral characteristic. We adopt univariate and bivariate portfolio-level analyses with seminal rational and behavioral factors, to demonstrate that framing effects which we defined is indeed a new firm-special behavioral characteristic. Additionally, we find that there is a strong negative relation between framing effects and one-month-ahead excess returns. Framing effects is stochastic with no persistence feature. Stocks with higher framing effects are more likely to be held by retail investors, and the role of framing effects is more important in the boom macroeconomic conditions than in the recessions. And the investment strategy based on framing effects can achieve an excellent performance.

Improving Investment Suggestions for Peer-to-Peer (P2P) Lending via Integrating Credit Scoring into Profit Scoring
Yan Wang,Xuelei Sherry Ni

In the peer-to-peer (P2P) lending market, lenders lend the money to the borrowers through a virtual platform and earn the possible profit generated by the interest rate. From the perspective of lenders, they want to maximize the profit while minimizing the risk. Therefore, many studies have used machine learning algorithms to help the lenders identify the "best" loans for making investments. The studies have mainly focused on two categories to guide the lenders' investments: one aims at minimizing the risk of investment (i.e., the credit scoring perspective) while the other aims at maximizing the profit (i.e., the profit scoring perspective). However, they have all focused on one category only and there is seldom research trying to integrate the two categories together. Motivated by this, we propose a two-stage framework that incorporates the credit information into a profit scoring modeling. We conducted the empirical experiment on a real-world P2P lending data from the US P2P market and used the Light Gradient Boosting Machine (lightGBM) algorithm in the two-stage framework. Results show that the proposed two-stage method could identify more profitable loans and thereby provide better investment guidance to the investors compared to the existing one-stage profit scoring alone approach. Therefore, the proposed framework serves as an innovative perspective for making investment decisions in P2P lending.

Investing with Cryptocurrencies -- evaluating their potential for portfolio allocation strategies
Alla Petukhina,Simon Trimborn,Wolfgang Karl Härdle,Hermann Elendner

Cryptocurrencies (CCs) have risen rapidly in market capitalization over the last years. Despite striking price volatility, their high average returns have drawn attention to CCs as alternative investment assets for portfolio and risk management. We investigate the utility gains for different types of investors when they consider cryptocurrencies as an addition to their portfolio of traditional assets. We consider risk-averse, return-seeking as well as diversificationpreferring investors who trade along different allocation frequencies, namely daily, weekly or monthly. Out-of-sample performance and diversification benefits are studied for the most popular portfolio-construction rules, including mean-variance optimization, risk-parity, and maximum-diversification strategies, as well as combined strategies. To account for low liquidity in CC markets, we incorporate liquidity constraints via the LIBRO method. Our results show that CCs can improve the risk-return profile of portfolios. In particular, a maximum-diversification strategy (maximizing the Portfolio Diversification Index, PDI) draws appreciably on CCs, and spanning tests clearly indicate that CC returns are non-redundant additions to the investment universe. Though our analysis also shows that illiquidity of CCs potentially reverses the results.

Is Factor Momentum More than Stock Momentum?
Antoine Falck,Adam Rej,David Thesmar

Yes, but only at short lags. In this paper we investigate the relationship between factor momentum and stock momentum. Using a sample of 72 factors documented in the literature, we first replicate earlier findings that factor momentum exists and works both directionally and cross-sectionally. We then ask if factor momentum is spanned by stock momentum. A simple spanning test reveals that after controlling for stock momentum and factor exposure, statistically significant Sharpe ratios only belong to implementations which include the last month of returns. We conclude this study with a simple theoretical model that captures these forces: (1) there is stock-level mean reversion at short lags and momentum at longer lags, (2) there is stock and factor momentum at all lags and (3) there is natural comovement between the PNLs of stock and factor momentums at all horizons.

Leave-One-Out Least Square Monte Carlo Algorithm for Pricing American Options
Jeechul Woo,Chenru Liu,Jaehyuk Choi

The least square Monte Carlo (LSM) algorithm proposed by Longstaff and Schwartz (2001) is widely used for pricing American options. The LSM estimator contains undesirable look-ahead bias, and the conventional technique of removing it necessitates doubling simulations. We present the leave-one-out LSM (LOOLSM) algorithm for efficiently eliminating look-ahead bias. We also show that look-ahead bias is asymptotically proportional to the regressors-to-simulation paths ratio. Our findings are demonstrated with several option examples, including the multi-asset cases that the LSM algorithm significantly overvalues. The LOOLSM method can be extended to other regression-based algorithms improving the LSM method.

Linking Risk Management Under Expected Shortfall to Loss-Averse Behavior
Chen, An,Nguyen, Thai
We introduce and solve an optimal asset allocation problem under a weighted expected shortfall (WES) constraint, which contains the risk management problem under an expected shortfall constraint of Basak and Shapiro (2001) as a special case. Furthermore, we link our risk management problem under the WES constraint with an optimal asset allocation with a multiple-reference-based preference (MRBP) and find that the optimal wealth with MRBP owns the same form as the optimal solution under the WES constraint. For the degenerate case with a fixed reference level, we are able to determine the critical maximal allowed expected shortfall constraint as a function of the loss aversion parameters to achieve equivalence. It is interesting to observe that, while no equivalence can be in general obtained between the WESand the MRBP solution, the optimal terminal wealth of the WES can be made to coincide with theMRBP terminal wealth in the most favorable and in the worst market states. In addition, we carry out a general equilibrium analysis in the presence of a WES/MRBP risk manager.

Machine Learning Classification Methods and Portfolio Allocation: An Examination of Market Efficiency
Bai, Yang,Pukthuanthong, Kuntara
Richard Thaler proposes two questions to test efficient market hypothesis: (1) can we beat the market, and (2) are the prices correct? We introduce a novel methodology, machine learning classification methods, and apply them to answer these questions. First, our classification portfolios beat the market in time series and cross-sections. Our models capture the information about return state transition and have time invariant applicability. Second, the performance is attributed to the prediction accuracy both in sample (IS) and out of sample (OOS). The accuracy implies that our classification models can generate information about future return states with historical observations. Our study suggests the current prices may not fully reflect all historical information.

Modelling uncertainty in coupled electricity and gas systems -- is it worth the effort?
Iegor Riepin,Thomas Möbius,Felix Müsgens

The interdependence of electricity and natural gas markets is becoming a major topic in energy research. Integrated energy models are used to assist decision-making for businesses and policymakers addressing challenges of energy transition and climate change. The analysis of complex energy systems requires large-scale models, which are based on extensive databases, intertemporal dynamics and a multitude of decision variables. Integrating such energy system models results in increased system complexity. This complexity poses a challenge for energy modellers to address multiple uncertainties that affect both markets. Stochastic optimisation approaches enable an adequate consideration of uncertainties in investment and operation planning; however, stochastic modelling of integrated large-scale energy systems further scales the level of complexity. In this paper, we combine integrated and stochastic optimisation problems and parametrise our model for European electricity and gas markets. We analyse and compare the impact of uncertain input parameters, such as gas and electricity demand, renewable energy capacities and fuel and CO2 prices, on the quality of the solution obtained in the integrated optimisation problem. Our results quantify the value of encoding uncertainty as a part of a model. While the methodological contribution should be of interest for energy modellers, our findings are relevant for industry experts and stakeholders with an empirical interest in the European energy system.

On the Effectiveness of Minisum Approval Voting in an Open Strategy Setting: An Agent-Based Approach
Joop van de Heijning,Stephan Leitner,Alexandra Rausch

This work researches the impact of including a wider range of participants in the strategy-making process on the performance of organizations which operate in either moderately or highly complex environments. Agent-based simulation demonstrates that the increased number of ideas generated from larger and diverse crowds and subsequent preference aggregation lead to rapid discovery of higher peaks in the organization's performance landscape. However, this is not the case when the expansion in the number of participants is small. The results confirm the most frequently mentioned benefit in the Open Strategy literature: the discovery of better performing strategies.

Price formation and optimal trading in intraday electricity markets
Olivier Féron,Peter Tankov,Laura Tinsi

We develop a tractable equilibrium model for price formation in intraday electricity markets in the presence of intermittent renewable generation. Using stochastic control theory we identify the optimal strategies of agents with market impact and exhibit the Nash equilibrium in closed form for a finite number of agents as well as in the asymptotic framework of mean field games. Our model reproduces the empirical features of intraday market prices, such as increasing price volatility at the approach of the delivery date and the correlation between price and renewable infeed forecasts, and relates these features with market characteristics like liquidity, number of agents, and imbalance penalty.

Price, Volatility and the Second-Order Economic Theory
Olkhov, Victor
This paper considers price volatility as the reason for description of the second-degree economic variables, trades and expectations aggregated during certain time interval Î". We call it - the second-order economic theory. The n-th degree products of costs and volumes of trades, performed by economic agents during interval Î" determine price n-th statistical moments. First two price statistical moments define volatility. To model volatility one needs description of the squares of trades aggregated during interval Î". To describe price probability one needs all n-th statistical moments of price but that is almost impossible. We define squares of agent’s trades and macro expectations those approve the second-degree trades aggregated during interval Î". We believe that agents perform trades under action of multiple expectations. We derive equations on the second-degree trades and expectations in economic space. As economic space we regard numerical continuous risk grades. Numerical risk grades are discussed at least for 80 years. We propose that econometrics permit accomplish risk assessment for almost all economic agents. Agents risk ratings distribute agents by economic space and define densities of macro second-degree trades and expectations. In the linear approximation we derive mean square price and volatility disturbances as functions of the first and second-degree trades disturbances. In simple approximation numerous expectations and their perturbations can cause small harmonic oscillations of the second-degree trades disturbances and induce harmonic oscillations of price and volatility perturbations.

Primary Corporate Bond Markets and Social Responsibility
Halling, Michael,Yu, Jin,Zechner, Josef
We document that good ES-performance is rewarded in primary bond markets by lower credit spreads. This effect is strongest for low-rated bonds and for firms in manufacturing, agriculture, mining and construction. However, not all ES-dimensions are equally important. The above results are driven mostly by the product-related dimension and to a lesser extent by the employee-related dimension. Environment-related aspects only seem to matter for those industries with largest exposure to environmental risks. Finally, we neither find that the above results are driven by crisis periods nor pronounced dynamics reflecting the growing interest in ESG. Overall, our evidence suggests that some ES-dimensions capture information that is relevant for default risk.

Quantitative Easing and the Cost of Issuing UK Government Debt during SARS-CoV-2, Brexit and the Financial Crisis
Steeley, James
I estimate the costs of issuing UK government debt by auction from the inception of the market in 1987 through the financial crisis and the phases of QE and into the current period of policy responses to SARS-CoV-2. Issuance costs decreased from the start of QE and have remained stable since, improving slightly in 2020. Variation in issuance costs is mostly explained by benchmark status, volatility and pent-up demand. Cost estimates do not show a strong relation to maturity suggesting that no one set of gilt market investors is attracting habitat rents.

Regtech Adoption and the Cost of Capital
Lai, Sandy,Lin, Chen,Ma, Xiaorong
This paper studies the real effect of a major RegTech event - the staggered implementation of the SEC’s EDGAR system in 1993-1996. This event represents an exogenous shock to corporate information dissemination technologies, which leads to a considerable reduction in information acquisition costs for investors. We find evidence that firms’ cost of equity capital declines substantially after they switch from paper filing to mandatory electronic filing in EDGAR. The effect is stronger for small firms and firms with low institutional ownership. We identify three channels via which the EDGAR implementation affects firms’ capital cost: liquidity, risk-taking, and corporate governance channels. EDGAR filing firms experience a significant drop in firm risk and an improvement in stock liquidity and corporate governance.

Risk Managers in Banks
Efing, Matthias,Kampkötter, Patrick
How do banks remunerate risk managers and what are the implications for risk-taking? Studying 127 German banks during the years 2003 to 2007, we show that risk managers' remuneration is positively aligned with performance-linked pay in front offices (FOs). When bonuses in FOs increase by one Euro, the bonus of a risk manager increases by 13.6 to 33.5 Cents, depending on the risk manager’s seniority. Risk-sharing among employees or labor market competition do not explain this finding. Banks with more aligned incentive pay between risk management and FOs during the years before the crisis of 2008-2009 performed better in the crisis.

Risk Prediction of Peer-to-Peer Lending Market by a LSTM Model with Macroeconomic Factor
Yan Wang,Xuelei Sherry Ni

In the peer to peer (P2P) lending platform, investors hope to maximize their return while minimizing the risk through a comprehensive understanding of the P2P market. A low and stable average default rate across all the borrowers denotes a healthy P2P market and provides investors more confidence in a promising investment. Therefore, having a powerful model to describe the trend of the default rate in the P2P market is crucial. Different from previous studies that focus on modeling the default rate at the individual level, in this paper, we are the first to comprehensively explore the monthly trend of the default rate at the aggregative level for the P2P data from October 2007 to January 2016 in the US. We use the long short term memory (LSTM) approach to sequentially predict the default risk of the borrowers in Lending Club, which is the largest P2P lending platform in the US. Although being first applied in modeling the P2P sequential data, the LSTM approach shows its great potential by outperforming traditionally utilized time series models in our experiments. Furthermore, incorporating the macroeconomic feature \textit{unemp\_rate} (i.e., unemployment rate) can improve the LSTM performance by decreasing RMSE on both the training and the testing datasets. Our study can broaden the applications of the LSTM algorithm by using it on the sequential P2P data and guide the investors in making investment strategies.

Shadow Trading
Mehta, Mihir N.,Reeb, David M.,Zhao, Wanli
We investigate whether corporate insiders attempt to circumvent insider trading restrictions by using their private information to facilitate trading in economically-linked firms, a phenomenon we call “shadow trading.” Using measures of informed trading to proxy for shadow trading, we find increased levels of informed trading among business partners and competitors before a firm releases private information. To rule out alternative explanations, we examine two shocks to insiders’ incentives to engage in shadow trading: high-profile regulatory enforcement against conventional insider trading and staggered changes to their outside employment opportunities. Finally, we document attenuated levels of informed trading among business partners and competitors when firms prohibit shadow trading. Overall, we provide evidence that shadow trading is an undocumented and widespread mechanism that insiders use to avoid regulatory scrutiny.

Shareholder Voting: A Complementary Mechanism to Mandatory Disclosure Regulation
Mukhopadhyay, Tathagat,Shivakumar, Lakshmanan
We offer that, when regulators require firms to obtain stakeholder approval of a corporate decision through voting on a resolution, firms disclose additional information that is needed for stakeholders to understand the optimal nature of the proposal and to vote in favor of it. We suggest that this indirect regulatory approach to disclosure can improve transparency over and beyond that achieved through mandated disclosures alone. The study documents the effectiveness of this indirect regulatory mechanism in the context of Say-on-Pay rules relating to executive compensation. The analyses reveal that, even though firms were previously required to provide detailed compensation-related disclosures, the passage of the SoP rule increased disclosures further, especially among firms that had seemingly excessive pay packages. Also, firms that had previously failed their SoP voting or had received an ‘Against’ recommendation from a proxy advisor increase their compensation-related disclosures disproportionately. These additional disclosures also help the firms achieve better subsequent SoP voting outcomes. We conclude that stakeholder-voting regulations can be an effective tool to improve corporate transparency.

Someone Else’s Problem? The IFRS Enforcement Field in Europe
Quagli, Alberto,Avallone, Francesco,Ramassa, Paola,Di Fabio, Costanza
This study adopts an institutional lens to explore enforcement as a complex and nuanced phenomenon shaped by the dynamics of its social context. It examines an IFRS regulatory incident that fails to conclude with any decision or resolving action in the context of the European Union, and as such invites serious questioning of enforcement functions. From our analysis accounting enforcement emerges as an interacting issue-based field in which auditors and the national enforcement agency adhere narrowly to their tasks, ensuring formal but not substantive IFRS compliance. Field participants are seen to respond to institutional pressures strategically by avoiding public positions and delegating choices to other actors, substantially accepting earnings manipulation. Our study shows that the national enforcer increased its interactions with other regulatory actors (i.e. agencies concerned with the setting and interpretation of standards) in the case of controversial issues and their responses can heavily influence overall enforcement effectiveness. Furthermore, its findings contribute to debates on the need for a pan-European enforcement agency and shed light on the importance of IFRS interpretation for the enforce-ability of international accounting standards.

Strategic Deviance and Cash Holdings
Dong, Xueyan,Chan, Kam C.,Cui, Yujia,Guan, Jenny Xinjiao
We examine the impact of strategic deviance on corporate cash holdings and find that firms with strategies that deviate from their industry peers hold more cash. This pattern can be consistent with an agency motive, a precautionary motive, or both. We show that the value of cash holdings decreases with strategic deviance and that the cash effect of strategic deviance increases with agency costs but not with financial constraints, consistent with an agency motive. Finally, we find that strategically deviant firms pay lower dividends and avoid more taxes, both of which can potentially contribute to cash holdings. We conclude that strategically deviant firms hold more cash due to an agency motive.

The 2020 Sturgis Motorcycle Rally and COVID-19
Yong Cai,Grant Goehring

The Sturgis Motorcycle Rally that took place from August 7-16 was one of the largest public gatherings since the start of the COVID-19 outbreak. Over 460,000 visitors from across the United States travelled to Sturgis, South Dakota to attend the ten day event. Using anonymous cell phone tracking data we identify the home counties of visitors to the rally and examine the impact of the rally on the spread of COVID-19. Our baseline estimate suggests a one standard deviation increase in Sturgis attendance increased COVID-19 case growth by 1.1pp in the weeks after the rally.

The Bank Insolvency: From Lehman Brothers to COVID-19 (International Remarks and National Peculiarities)
Zahariev, Andrey,Prodanov, Stoyan,Radulova, Aneliya,Zaharieva, Galina,Pavlova, Mariyana,Angelov, Petko,Ismailov, Taner,Aleksandrova, Aleksandrina,Marinova, Kristi
A study of the international experience of applicable policies for crisis management in the credit system in bank insolvency, identifies three types of solutions, including: elimination of the "toxic element" in the banking system following the example of "Lehman Brothers" in the US from 15.09. 2008 through a voluntary insolvency procedure declared by the bank's management before the respective regulatory body; support for the financially troubled institution through nationalization and a reform plan following the example of Northern Rock in the UK from 2007-2008 and Greek banks from the Greek debt crisis after 2010; liquidation of the "toxic element" in the banking system, following the example of CCB in Bulgaria (2014-2020), through a regulatory insolvency procedure. Each of the three policies has its pros and cons, but it definitely has a "stressful" impact on banking systems and economic agents with long-term consequences, incl. in the context of the TBTF doctrine. On this basis, international regulators are introducing the methodology of bank stress tests for early warning of bank insolvency. The study of the experience of the central banks, BIS and ECB for conducting stress tests brings to the fore their grouping by three criteria: first criteria - Type of stress test, which distinguishes stress tests conducted by macroprudential authorities for the purpose of assessing broad systemic risks, stress tests conducted by microprudential authorities for supervisory purposes and stress tests by the internal bank risk management for the purposes of assessing capital adequacy policies; second criteria - Focus of the stress test, which distinguishes systematic assessments at the institutional level, measuring mainly solvency or liquidity, assessments on the first and second pillars of Basel II, as well as assessments of financial instruments, investment portfolios, business sectors from institutional positions to prepare models for decision-making by the central banking management regarding the response to the various risks; and third criteria - Approach to conducting the stress test, which is grouped into two categories, top - down and vice versa, bottom - up. These approaches must be tested with the new environment for COVID-19 as a global systemic risk generator. Its impact on the creditworthiness of companies, households and the state can be assessed as extremely negative and testing the capital adequacy of commercial banks under BASEL III framework.

The Brokerage Insurance Companies Under COVID-19 Framework (The Bulgarian Experience)
Zahariev, Andrey,Prodanov, Stoyan,Zaharieva, Galina,Krastev, Lyudmil,Kostov, Dimitar,Pavlov, Tsvetan ,Stanimirov, Stefan,Zarkova, Silvia,Zdravkov, Nikolay
The history of insurance and insurance mediation in Bulgaria can be divided into four periods - from 1878 to 1946; from 1946 to 1989; from 1989 to 2007; and after the accession of Bulgaria to the EU in 2007. The most significant regulatory at the end of the penultimate period and the last period are related to the establishment of the Financial Supervision Commission (2003), the adoption of the first Insurance Code (2005) of the second, still valid new Insurance Code. The analysis shows that the legislation of insurance intermediation in Bulgaria is undergoing significant development in the direction of improvement and adaptation to evolving and complicating modern market conditions. The most significant trends that are observed are in the direction of explicitly differentiating the functions of brokers and agents; strengthening the requirements for education and qualification of the persons managing and the persons directly carrying out the activity of insurance mediation; development of the licensing and registration regime; subordination of the requirements for brokers and agents and to other categories of persons engaged in mediation (employees of the insurers themselves in direct sales, as well as intermediaries developing insurance mediation as an additional activity). After 2007, all changes are in the direction of synchronization with EU legislation and protection of consumers of insurance products. The most significant features and current challenges of the global and Bulgarian insurance market and in particular of the intermediaries working on it are related to changes in the general economic conditions. Here are added changes in the financial system, regulations, the emergence of new types of risk, changes in the insurance business (digitalization), and the cycle of the insurance market. Among the changes with the most significant impact since 2020 is COVID-19 as a new, global systemic risk with a huge impact on all economic agents and on the value of insurance estimates.

The Great Pandemic of the 21st Century: The Stolen Lives
Taskinsoy, John
One microscopic coronavirus has done what US sanctions, tariffs, embargoes, trade war, and the use of dollar as a weapon of economic destruction have failed to accomplish. The COVID-19 pandemic shock has caused unconceivable damage; 200,000 stolen lives in the U.S. (and close to 1 million in the world) and trillions of dollars globally. The farfetched impacts of coronavirus pandemic, the costliest in history (i.e. Great Lockdown), put many economies including the world’s biggest economy on a ventilator. Important signs provided by the coronavirus health crisis must not be ignored as previous signs were in the past. Tens of thousands of lives could have been saved if the White House (US President Donald Trump in particular) did not choose to downplay significant impacts of COVID-19; moreover, despite clear warnings by senior officials in late January 2020, not only Mr. Trump delayed taking aggressive actions to curb the spread of the virus to the United States (i.e. closing schools, locking down cities/states, imposing a travel ban, enforcing face masks, and social distancing), but he focused instead on protecting his re-election campaign; he also took the easy way out and blamed Beijing for misleading governments and not sharing the genome sequence of the coronavirus.

The Seven-League Scheme: Deep learning for large time step Monte Carlo simulations of stochastic differential equations
Shuaiqiang Liu,Lech A. Grzelak,Cornelis W. Oosterlee

We propose an accurate data-driven numerical scheme to solve Stochastic Differential Equations (SDEs), by taking large time steps. The SDE discretization is built up by means of a polynomial chaos expansion method, on the basis of accurately determined stochastic collocation (SC) points. By employing an artificial neural network to learn these SC points, we can perform Monte Carlo simulations with large time steps. Error analysis confirms that this data-driven scheme results in accurate SDE solutions in the sense of strong convergence, provided the learning methodology is robust and accurate. With a variant method called the compression-decompression collocation and interpolation technique, we can drastically reduce the number of neural network functions that have to be learned, so that computational speed is enhanced. Numerical results shows the high quality strong convergence error results, when using large time steps, and the novel scheme outperforms some classical numerical SDE discretizations. Some applications, here in financial option valuation, are also presented.

The Term Structure of Equity Risk Premia
Bansal, Ravi,Yaron, Amir,Miller, Shane,Song, Dongho
We show that the term structure of dividend risk premia and discount rates implied by equity strip yields are downward sloping in recessions and upward sloping in expansions, a finding which is statistically significant and robust across the U.S., Europe, and Japan. Our results are based on the estimation of a regimeswitching dividend growth model, which allows us to characterize not just the conditional but also unconditional moments. Our evidence suggests that the claim about downward sloping equity term structure is rejected from the data. This is an important finding as the standard asset pricing models are not in conflict with the new data on dividend strips. In fact, we show that the standard asset pricing models extended with regime-switching dynamics are able to reconcile these facts.

Using Nudges to Prevent Student Dropouts in the Pandemic
Guilherme Lichand,Julien Christen

The impacts of COVID-19 reach far beyond the hundreds of lives lost to the disease; in particular, the pre-existing learning crisis is expected to be magnified during school shutdown. Despite efforts to put distance learning strategies in place, the threat of student dropouts, especially among adolescents, looms as a major concern. Are interventions to motivate adolescents to stay in school effective amidst the pandemic? Here we show that, in Brazil, nudges via text messages to high-school students, to motivate them to stay engaged with school activities, substantially reduced dropouts during school shutdown, and greatly increased their motivation to go back to school when classes resume. While such nudges had been shown to decrease dropouts during normal times, it is surprising that those impacts replicate in the absence of regular classes because their effects are typically mediated by teachers (whose effort in the classroom changes in response to the nudges). Results show that insights from the science of adolescent psychology can be leveraged to shift developmental trajectories at a critical juncture. They also qualify those insights: effects increase with exposure and gradually fade out once communication stops, providing novel evidence that motivational interventions work by redirecting adolescents' attention.

When Does Portfolio Compression Reduce Systemic Risk?
Veraart, Luitgard Anna Maria
We analyse the consequences of portfolio compression on systemic risk. Portfolio compression is a post-trading netting mechanism that reduces gross positions while keeping net positions unchanged and it is part of the financial legislation in the US (Dodd-Frank Act) and in Europe (European Market Infrastructure Regulation). We derive necessary structural conditions for portfolio compression to be harmful and discuss policy implications. In particular, we show that the potential danger of portfolio compression comes from defaults of firms that conduct portfolio compression. If no defaults occur among those firms that engage in compression, then portfolio compression always reduces systemic risk.

X-Value adjustments: accounting versus economic management perspectives
Alberto Elices

This paper provides a mathematical framework based on the principle of invariance to classify institutions in two paradigms according to the way in which credit, debit and funding adjustments are calculated: accounting and management perspectives. This conceptual classification helps to answer questions such as: In which paradigm each institution sits (point of situation)? Where is the market consensus and regulation pointing to (target point)? What are the implications, pros and cons of switching perspective to align with future consensus (design of a transition)? An improved solution of the principle of invariance equations is presented to calculate these metrics avoiding approximations and irrespective of the discounting curve used in Front Office systems. The perspective is changed by appropriate selection of inputs always using the same calculation engine. A description of balance sheet financing is presented along with the justification of the funding curves used for both perspectives.

أثر استخدام البنوك العاملة في فلسطين لتطبيق موبايل بنك على عملية الإقراض (The Impact of the Banks Operating in Palestine Using The Mobile Bank Application on The Lending Process)
السقا, أديب
Arabic Abstract: هدفتÙ' هذه الدراسة إلى التعرف على مفهوم وأنواع الخدمات التي تقدمها المصارف الالكترونية، وماهية القروض والسياسة الاقراضية المتبعة في البنوك العاملة في فلسطين، بالإضافة إلى التعرف على تطبيق موبايل بنك المستخدم من قبل البنوك العاملة في فلسطين وعلاقته في السياسة الإقراضية المتبعة، وقد استخدم الباحث أسلوب المنهج الوصفي التحلیلي، كأحد أسالیب البحث العلمي التي تناسب مع هذه الدراسة، واعتمد الباحث الاستبانة كأداة رئيسة لجمع البيانات، فيما تم اختيار دراسة حالة بعض البنوك العاملة في فلسطين â€"قطاع غزة، حيث بلغ حجم مجتمع الدراسة (50) موظفاً، اختارهم الباحث كعينة عشوائية، تم استرداد (41) استبانة صالحة لغاية التحليل الإحصائي بنسبة استجابة (82%)ØŒ باستُخدم برنامج الحزم الإحصائية (SPSS) لتحليل البيانات.توصلتÙ' الدراسة إلى نتائج أهمها: وجود فروق ذات دلالة إحصائية عند مستوى دلالة (α ≤ 0.05) بين استخدام تطبيق موبايل بنك وعملية الإقراض في البنوك العاملة في فلسطين، وكان مجال أثر استخدام تطبيق موبايل بنك على ثبات الودائع بالمرتبة الأولى بنسبة (74%)ØŒ ثم جاءت تقديم ودراسة طلب الإقراض بنسبة (73.43%)ØŒ ثم جاءت التمويل والمتابعة بنسبة (70.48%)ØŒ وجاء مجال منح الائتمان أو القرض بالمرتبة الأخيرة وبنسبة (68.78%).وأوصتÙ' الدراسة بعدة توصيات أهمها: أنه على البنوك تشجيع العملاء على استخدام تطبيق موبايل بنك كما يجب أن تعتمد البنوك العاملة في فلسطين على تطبيق موبايل بنك في عرض وتسويق منتجاتها المالية، والصيانة المستمرة لتطبيق موبايل بنك ليتسنى له مواكبة التطورات التي تحصل على مستوى الصيرفة الإلكترونية، وتوظيف مختصين بمجال تكنولوجيا المعلومات لتحسين تطبيقات الصيرفة الإلكترونية من حين لآخر.English Abstract: This study aimed to identify the concept and types of services provided by electronic banks, what loans and lending policy followed in banks operating in Palestine, in addition to identifying the Mobile Bank application used by banks operating in Palestine and its relationship to the adopted lending policy, and the researcher used the methodology Descriptive and analytical, as one of the scientific research methods that fit with this study, and the researcher adopted the questionnaire as a main tool for data collection, while a case study of some banks operating in Palestine - Gaza Strip was chosen, where the size of the study population reached (50) employees, chosen by the researcher as a random sample. (41) valid questionnaires were retrieved for the purpose of statistical analysis, with a response rate of (82%), using the statistical packages program (SPSS) to analyze the data.The study found the most important results: The presence of statistically significant differences at a significant level (α ≤ 0.05) between the use of a mobile bank application and the lending process in banks operating in Palestine, and the effect of using a mobile bank application on the stability of deposits was in the first rank by (74%). Then came the submission and study of the loan application at a rate of (73.43%), then came financing and follow-up by (70.48%), and the field of granting credit or loans came in last place, at a rate of (68.78%).The study recommended several recommendations, the most important of which are: Banks should encourage customers to use the Mobile Bank application. Banks operating in Palestine should also rely on a mobile bank application to display and market their financial products, and the continuous maintenance of the Mobile Bank application in order for it to keep abreast of developments at the level of electronic banking. And the employment of specialists in the field of information technology to improve electronic banking applications from time to time.