# Research articles for the 2020-12-02

A New Approach to Measurement of Errors from Trade Discrepancies: The Duty-free Zero Incentive Approach (DFZI)
Masiya, Michael
SSRN
The Duty-Free Zero Incentive Approach (DFZI) for measuring errors in trade discrepancies draws from the assumption that in the absence of taxes, there should be no incentive to evade taxes. Assuming there were zero taxes on goods, that is, duty-free, then there would be zero-incentive to evade (hence the term â€œduty-free zero incentiveâ€) such that any discrepancy in trade data would solely be on account of errors in measurement only. This approach is useful for ascribing the errors arising from missing imports and is very useful in the estimation of smuggling.

A Study on the Efficiency of the Indian Stock Market
Devansh Jain,Manthan Patel,Aman Narsaria,Siddharth Malik
arXiv

The efficiency of the stock market has a significant impact on the potential return on investment. An efficient market eliminates the possibility of arbitrage and unexploited profit opportunities. This study analyzes the weak form efficiency of the Indian Stock market based on the two major Indian stock exchanges, viz., BSE and NSE. The daily closing values of Sensex and Nifty indices for the period from April 2010 to March 2019 are used to perform the Runs test, the Autocorrelation test, and the Autoregression test. The study confirms that the Indian Stock market is weak form inefficient and can thus be outperformed.

Adaptive Bernstein Copulas and Risk Management
Dietmar Pfeifer,Olena Ragulina
arXiv

We present a constructive approach to Bernstein copulas with an admissible discrete skeleton in arbitrary dimensions when the underlying marginal grid sizes are smaller than the number of observations. This prevents an overfitting of the estimated dependence model and reduces the simulation effort for Bernstein copulas a lot. In a case study, we compare different approaches of Bernstein and Gaussian copulas w.r.t. the estimation of risk measures in risk management.

An Artificial Intelligence Solution for Electricity Procurement in Forward Markets
Thibaut Théate,Sébastien Mathieu,Damien Ernst
arXiv

Retailers and major consumers of electricity generally purchase an important percentage of their estimated electricity needs years ahead in the forward market. This long-term electricity procurement task consists of determining when to buy electricity so that the resulting energy cost is minimised, and the forecast consumption is covered. In this scientific article, the focus is set on a yearly base load product from the Belgian forward market, named calendar (CAL), which is tradable up to three years ahead of the delivery period. This research paper introduces a novel algorithm providing recommendations to either buy electricity now or wait for a future opportunity based on the history of CAL prices. This algorithm relies on deep learning forecasting techniques and on an indicator quantifying the deviation from a perfectly uniform reference procurement policy. On average, the proposed approach surpasses the benchmark procurement policies considered and achieves a reduction in costs of 1.65% with respect to the perfectly uniform reference procurement policy achieving the mean electricity price. Moreover, in addition to automating the complex electricity procurement task, this algorithm demonstrates more consistent results throughout the years. Eventually, the generality of the solution presented makes it well suited for solving other commodity procurement problems.

Artificial Intelligenceâ€™s Role in Finance and How Financial Companies are Leveraging the Technology to Their Advantage
Hunt, Whitney
SSRN
This research paper aims to better define artificial intelligence (AI) and its current role in financial markets. All the while discussing the subgroups of AI, how machines learn, the proâ€™s and conâ€™s, itâ€™s role in financial analytics and the future of the field. This work encompasses research from some of the top minds in the field of artificial intelligence in order to explain the relevance of AI thoroughly and its future.

Automated Creation of a High-Performing Algorithmic Trader via Deep Learning on Level-2 Limit Order Book Data
arXiv

Bank Opacity and Financial Crises
Jungherr, Joachim
SSRN
This paper studies a model of endogenous bank opacity. Why do banks choose to hide their risk exposure from the public? And should policy makers force banks to be more transparent? In the model, bank opacity is costly because it encourages banks to take on too much risk. But opacity also reduces the incidence of bank runs (for a given level of risk taking). Banks choose to be inefficiently opaque if the composition of their asset holdings is proprietary information. In this case, policy makers can improve upon the market outcome by imposing public disclosure requirements (such as Pillar Three of Basel II). However, full transparency maximizes neither efficiency nor stability. The model can explain why empirically a higher degree of bank competition leads to increased transparency.

Basiszinssatzermittlung im Rahmen von Bewertungs- und PrÃ¼fgutachten â€" Kritische Analyse der Vorgehensweise und WidersprÃ¼chlichkeiten zwischen Bewertungs- und PrÃ¼fgutachten (Risk-Free-Rate Determination in the Context of Valuation and Auditing Reports â€" Critical Analysis of the Procedure and Inconsistencies Between Valuation and Auditing Reports)
Helms, Nils
SSRN
German abstract: In diesem Beitrag werden 418 Bewertungs- und PrÃ¼fgutachten von 229 Unternehmen zwischen den Jahren 2000 und 2017 bezÃ¼glich der Basiszinssatzermittlung ausgewertet. Auch wenn Ã¼berwiegend den im Untersuchungszeitraum sich verÃ¤ndernden IDW-Empfehlungen gefolgt wird, konnten in den Gutachten gleichzeitig ErmessensspielrÃ¤ume und subjektive Adjustierungen bei der Basiszinssatzermittlung beobachtet werden. Weiterhin wurden im Rahmen der Analyse verschiedene WidersprÃ¼che zwischen den Bewertungs- und PrÃ¼fgutachten aufgedeckt. Um die Aussagekraft der Gutachten zu erhÃ¶hen, sollte die Basiszinssatzermittlung an verschiedenen Stellen in den Gutachten noch transparenter und mit zusÃ¤tzlichen ErlÃ¤uterungen versehen werdenEnglish abstract: In this paper 418 valuation reports and auditing reports from 229 companies between 2000 and 2017 are discussed according to the calculation of the Risk-Free-Rate. Mainly the evaluators follow the rec-ommendations from the IDW. But in detail some discretions could be identified in the reports. Further-more inconsistences between the valuation report and the auditing are recognized. For future reports more transparency and significance is necessary

Big 4 Office Political Connections and Client Restatements
Elemes, Anastasios,Chen, Jeff Zeyun
SSRN
Extant literature suggests that audit firms establish political connections at the national level to lobby regulators and legislators. In this paper we construct a novel dataset of Big 4 auditorsâ€™ political connections at the audit office level and examine the implications of auditorsâ€™ political connections for their audit quality. We find that client firms of politically connected audit offices are less likely to restate their earnings. However, this relation is weaker for politically connected clients. Further analyses reveal that, during the years that are subsequently restated, connected clients of connected offices were able to contract for less audit effort and pay less audit fees relative to their non-connected counterparts. Our results, robust to alternative audit quality measures and endogeneity controls, suggest that, while connected auditors have incentives to deliver high audit quality, they are likely to compromise their independence for politically connected clients.

Cbdc: Can Central Banks Succeed in the Marketplace for Digital Monies?
Bofinger, Peter,Haas, Thomas
SSRN
The discussion about central bank digital currencies (CBDC) has gained an impressive momentum. So far, however, the main focus has been on the macroeconomic implications of CBDCs and the narrow perspective of developing a digital substitute for cash. This paper adds a microeconomic dimension of CBDC to the discussion. We provide an overview of the existing payment ecosystem and derive a systemic taxonomy of CBDCs that distinguishes between new payment objects and new payment systems. Using our systemic taxonomy, we are able to categorize different CBDC proposals. In order to discuss and evaluate the different CBDC design options, we develop two criteria: allocative efficiency, i.e. whether a market failure can be diagnosed that justifies a government intervention, and attractiveness for users, i.e. whether CBDC proposals constitute attractive alternatives for users compared to existing payment objects and payment systems. Our analysis shows that there is no justification for digital cash substitutes from the point of view of allocative efficiency and the user perspective. Instead, our analysis opens the perspective for a retail payment system organized or orchestrated by the central bank without a new, independent payment object.

Choosing the Narrative? The Shadow Banking Crisis in Light of Covid
Miller, Marcus H.
SSRN
Using a common two-sector framework, key features of these contrasting accounts of the market for banking services are presented, along with their corresponding diagnoses of what precipitated financial crisis. To see what the experience of Covid might imply about their relative credibility, four aspects of the current pandemic are considered: how it began from a small biological shock; how it gets spread by contagion; the significance of externalities; and how it may end with a vaccine. But the reader is left to form his or her own judgement.

Context information increases revenue in ad auctions: Evidence from a policy change
arXiv

Credit Constraints, Labor Productivity and the Role of Regional Institutions: Evidence from Manufacturing Firms in Europe
SSRN
This paper examines the relationship between credit constraints Ã¢?? proxied by the investment-to-cash flow sensitivity Ã¢?? and firm-level economic performance Ã¢?? defined in terms of labor productivity Ã¢?? during the period 2009-2016, using a sample of 22,380 manufacturing firms from 11 European countries. It also assesses how regional institutional quality affects productivity at the level of the firm both directly and indirectly. The empirical results highlight that credit rationing is rife and represents a serious barrier for improvements in firm-level productivity and that this effect is far greater for micro and small than for larger firms. Moreover, high-quality regional institutions foster productivity and help mitigate the negative credit constraints-labor productivity relationship that limits the economic performance of European firms. Dealing with the European productivity conundrum thus requires greater attention to existing credit constraints for micro and small firms, although in many areas of Europe access to credit will become more effective if institutional quality is improved.

Daily Tracker of Global Economic Activity. A Close-Up of the Covid-19 Pandemic
SSRN
daily evolution of global economic activity during the COVID-19 pandemic.

Decisions and Performance Under Bounded Rationality: A Computational Benchmarking Approach
Dainis Zegners,Uwe Sunde,Anthony Strittmatter
arXiv

This paper presents a novel approach to analyze human decision-making that involves comparing the behavior of professional chess players relative to a computational benchmark of cognitively bounded rationality. This benchmark is constructed using algorithms of modern chess engines and allows investigating behavior at the level of individual move-by-move observations, thus representing a natural benchmark for computationally bounded optimization. The analysis delivers novel insights by isolating deviations from this benchmark of bounded rationality as well as their causes and consequences for performance. The findings document the existence of several distinct dimensions of behavioral deviations, which are related to asymmetric positional evaluation in terms of losses and gains, time pressure, fatigue, and complexity. The results also document that deviations from the benchmark do not necessarily entail worse performance. Faster decisions are associated with more frequent deviations from the benchmark, yet they are also associated with better performance. The findings are consistent with an important influence of intuition and experience, thereby shedding new light on the recent debate about computational rationality in cognitive processes.

Decomposing Cross-Asset Time Series Momentum
PitkÃ¤jÃ¤rvi, Aleksi
SSRN
I decompose the expected return difference between cross-asset time series momentum and time series momentum into market timing and risk premium components, and show that market timing accounts for 71â€"79% of the difference. I thus show that two recent critiques of time series momentum do not apply to cross-asset time series momentum. Instead, the outperformance of cross-asset time series momentum is driven specifically by the strategy's ability to exploit cross-asset time series predictability in global bond and equity markets.

Delegated Career
Liqun Liu
arXiv

I analyze how a careerist delegate carries out reform decisions and implementation under alternative information environments. Regardless of his true policy preference, the delegate seeks retention and tries to signal to a principal that he shares an aligned policy predisposition. Given this pandering incentive, the principal best motivates the delegate's implementation if she can commit to a retention rule that is pivotal on reform outcomes. I characterize an informativeness condition under which this retention rule is endogenous, provided that the principal uses an opaque information policy -- she observes the delegate's policy choice and outcomes, but not the effort. With other information policies, the principal has to reward congruent policy choices rather than good policy outcomes; her policy interest is damaged by failing to sufficiently motivate reform implementation.

Deposit Guarantee Schemes and Bank Crisis Management: Legal Challenges Arising from the Actual EU Legal Framework
Mecatti, Irene
SSRN
The COVID-19 crisis might affect banks too due to, in particular, the problem of npls. In the imminent future it is therefore crucial to maintain banks resolvable. But resolution is for the few, not the many. The so called "middle class" - less significant banks and significant not subject to resolution - will be liquidated under the national insolvency procedure (not-yet-harmonized). As the liquidation, in the lack of a buyer of the bank business, might become a disorderly one, it is crucial to prevent bank insolvency of this kind of banks. In this context, DGSs might play a fundamental role. Then, the paper will analyze the role of DGS in both liquidation and resolution, focusing on the legal constraints arising from the actual legal framework (BRRD; DGSD, Banking Communication 2013) and suggests some proposals to address and overcome them. It also takes into consideration the proposal of a fully harmonized bank insolvency procedure, underlining the need to previously harmonized some key points (ground of insolvency/resolution; creditor hierarchy; public intervention in resolution/liquidation).

Error estimates for discrete approximations of game options with multivariate diffusion asset prices
Yuri Kifer
arXiv

We obtain error estimates for strong approximations of a diffusion with a diffusion matrix $\sigma$ and a drift b by the discrete time process defined recursively X_N((n+1)/N) = X_N(n/N)+N^{1/2}\sigma(X_N(n/N))\xi(n+1)+N^{-1}b(XN(n/N)); where \xi(n); n\geq 1 are i.i.d. random vectors, and apply this in order to approximate the fair price of a game option with a diffusion asset price evolution by values of Dynkin's games with payoffs based on the above discrete time processes. This provides an effective tool for computations of fair prices of game options with path dependent payoffs in a multi asset market with diffusion evolution.

Ethnicity and gender influence the decision making in a multinational state: The case of Russia
Tatiana Kozitsina,Anna Mikhaylova,Anna Komkova,Anastasia Peshkovskaya,Anna Sedush,Olga Menshikova,Mikhail Myagkov,Ivan Menshikov
arXiv

Individuals' behavior in economic decisions depends on such factors as ethnicity, gender, social environment, personal traits. However, the distinctive features of decision making have not been studied properly so far between indigenous populations from different ethnicities in a modern and multinational state like the Russian Federation. Addressing this issue, we conducted a series of experiments between the Russians in Moscow (the capital of Russia) and the Yakuts in Yakutsk (the capital of Russian region with the mostly non-Russian residents). We investigated the effect of socialization on participants' strategies in the Prisoner's Dilemma game, Ultimatum game, and Trust game. At the baseline stage, before socialization, the rates of cooperation, egalitarianism, and trust for the Yakuts are higher than for the Russians in groups composed of unfamiliar people. After socialization, for the Russians all these indicators increase considerably; whereas, for the Yakuts only the rate of cooperation demonstrates a rising trend. The Yakuts are characterized by relatively unchanged indicators regardless of the socialization stage. Furthermore, the Yakutsk females have higher rates of cooperation and trust than the Yakuts males before socialization. After socialization, we observed the alignment in indicators for males and females both for the Russians and for the Yakuts. Hence, we concluded that cultural differences can exist inside one country despite the equal economic, politic, and social conditions.

Fat Tailed Factors
Jan Rosenzweig
arXiv

Standard, PCA-based factor analysis suffers from a number of well known problems due to the random nature of pairwise correlations of asset returns. We analyse an alternative based on ICA, where factors are identified based on their non-Gaussianity, instead of their variance. Generalizations of portfolio construction to the ICA framework leads to two semi-optimal portfolio construction methods: a fat-tailed portfolio, which maximises return per unit of non-Gaussianity, and the hybrid portfolio, which asymptotically reduces variance and non-Gaussianity in parallel. For fat-tailed portfolios, the portfolio weights scale like performance to the power of $1/3$, as opposed to linear scaling of Kelly portfolios; such portfolio construction significantly reduces portfolio concentration, and the winner-takes-all problem inherent in Kelly portfolios. For hybrid portfolios, the variance is diversified at the same rate as Kelly PCA-based portfolios, but excess kurtosis is diversified much faster than in Kelly, at the rate of $n^{-2}$ compared to Kelly portfolios' $n^{-1}$ for increasing number of components $n$.

Fifty Shades of QE: Conflicts of Interest in Economic Research
Fabo, Brian,Jancokova, Martina,Kempf, Elisabeth,Pastor, Lubos
SSRN
Central banks sometimes evaluate their own policies. To assess the inherent conflict of interest, we compare the research findings of central bank researchers and academic economists regarding the macroeconomic effects of quantitative easing (QE). We find that central bank papers report larger effects of QE on output and inflation. Central bankers are also more likely to report significant effects of QE on output and to use more positive language in the abstract. Central bankers who report larger QE effects on output experience more favorable career outcomes. A survey of central banks reveals substantial involvement of bank management in research production.

Financing the Rebuilding of the City of London after the Great Fire of 1666
Coffman, D'Maris,Sussman, Nathan,Stephenson, Judy Z.
SSRN
This paper presents new archival data to analyse how, in the absence of banking or capital market finance, the London Corporation funded the rebuilding of London after the Great Fire of 1666. The City borrowed at rates much lower than previously thought from its citizens and outside investors to replace vital services and to support large improvement works. Borrowing was partly secured on its' reputation and partly secured by future coal tax receipts. Although records show that the funding from these sources was forthcoming and would have covered costs, and most of the rebuilding project was completed in less than a decade, having invested in public goods without generating the expected fiscal flows, the City defaulted in 1683.

Foreign Currency Borrowing of Corporations as Carry Trades: Evidence from India
Acharya, Viral V.,Vij, Siddharth
SSRN
during the market stress due to the COVID-19 pandemic.

Forward utility and market adjustments in relative investment-consumption games of many players
arXiv

We study a portfolio management problem featuring many-player and mean-field competition, investment and consumption, and relative performance concerns under the forward performance processes (FPP) framework. We focus on agents using power (CRRA) type FPPs for their investment-consumption optimization problem an under common noise Merton market model and we solve both the many-player and mean-field game providing closed-form expressions for the solutions where the limit of the former yields the latter.

In our case, the FPP framework yields a continuum of solutions for the consumption component as indexed to a market parameter we coin "market consumption intensity". The parameter permits the agent to set a preference for their consumption going forward in time that, in the competition case, reflects a common market behaviour. We show the FPP framework, under both competition and no-competition, allows the agent to disentangle his risk-tolerance and elasticity of intertemporal substitution (EIS) just like Epstein-Zin preferences under recursive utility framework and unlike the classical utility theory one. This, in turn, allows a finer analysis on the agent's consumption "income" and "substitution" regimes, and, of independent interest, motivates a new strand of economics research on EIS under the FPP framework.

We find that competition rescales the agent's perception of consumption in a non-trivial manner in addition to a time-dependent "elasticity of conformity" of the agent to the market's consumption intensity.

Generating unfavourable VaR scenarios with patchwork copulas
Dietmar Pfeifer,Olena Ragulina
arXiv

The central idea of the paper is to present a general simple patchwork construction principle for multivariate copulas that create unfavourable VaR (i.e. Value at Risk) scenarios while maintaining given marginal distributions. This is of particular interest for the construction of Internal Models in the insurance industry under Solvency II in the European Union.

Incorporating Financial News for Forecasting Bitcoin Prices Based on Long Short-Term Memory Networks
Nazemi, Abdolreza,Jakubik, Johannes,Geyer-Schulz, Andreas,Fabozzi, Frank J.
SSRN
In recent years, most of the collected data are untapped unstructured data that have a high potential for further research developments in finance. In this paper, we assess this potential in the context of Bitcoin price forecasting. We compare the prediction accuracies of long short-term memory (LSTM) networks and random forests for forecasting out-of-time Bitcoin prices. Notably, this paper studies the value added to machine learning models for Bitcoin price forecasting and trading by incorporating unstructured information from financial news. We find that the proposed LSTM network with input from financial news outperforms other machine learning models significantly. Moreover, the out-of-time rate of return attained with the suggested deep learning model is 2,520 basis points higher than for a buy-andhold strategy. Our study highlights the importance of the combined application of deep learning and financial news for practitioners and traders and gives a concrete suggestion on the monetization of unstructured data in finance.

Sy, Oumar,Zaman, Ashraf Al
SSRN
A hotly debated question in finance is whether the higher stock returns under Democratic presidencies relative to Republican presidencies represent abnormal return, risk premium, or mere statistical fluke. This paper investigates whether this presidential premium is due to spurious-regression bias, data mining, or economic policy uncertainty. Decomposing the presidential premium into expected and unexpected components, we find that over two-thirds of the premium is unexpected, which is inconsistent with the spurious regression bias explanation. The presidential premium is not explained by data mining given that it persists in the post-publication period, and remains robust even if we purge returns of their covariation with economic policy uncertainty.

It&Apos;S What You Say and What You Buy: A Holistic Evaluation of the Corporate Credit Facilities
Boyarchenko, Nina,Kovner, Anna,Shachar, Or
SSRN
We evaluate the impact of the Federal Reserve corporate credit facilities (PMCCF and SMCCF). A third of the positive effect on prices and liquidity occurred on the announcement date. We document immediate pass through into primary markets, particularly for eligible issuers. Improvements continue as additional information is shared and purchases begin, with the impact of bond purchases larger than the impact of purchases of ETFs. Exploiting cross-sectional evidence, we see the greatest impact on investment grade bonds and in industries less affected by COVID, concluding that the improvement in corporate credit markets can be attributed both to announcement effects of Federal Reserve interventions on the economy and to the specific differential impact of the facilities on eligible issues.

Labor Reforms in Rajasthan: A boon or a bane?
Diti Goswami,Sourabh Bikas Paul
arXiv

We examine the impact of labour law deregulations in the Indian state of Rajasthan on plant employment and productivity. In 2014, after a long time, Rajasthan was the first Indian state that introduced labour reforms in the Industrial Disputes Act (1947), the Factories Act (1948), the Contract Labour (Regulation and Abolition) Act (1970), and the Apprentices Act (1961). Exploiting this unique quasi-natural experiment, we apply a difference-in-difference framework using the Annual Survey of Industries panel data of manufacturing plants. Our results show that reforms had an unintended consequence of the decline in labour use. Also, worryingly, the flexibility resulted in the disproportionate decline in the directly employed worker. Evidence suggests that the reforms positively impacted the plants' value-added and productivity. The strength of these effects varies depending on the underlying industry and reform structure. These findings prove robust to a set of specifications.

Leasing as a Mitigation Channel of Capital Misallocation
Li, Kai,Xu, Yiming
SSRN
We document that leased capital accounts for about 20% of the total productive physical assets used by U.S. public listed firms, and this proportion is even higher among small and financially constrained firms - over 40%. However, operating lease has been recorded as an off-balance-sheet item until the recent IFRS 16 lease accounting rule change (effective from 1 January 2019). Therefore, leased capital is an important ''unmeasured'' capital which leads to a significant mis-measurement in firms' capital productivity, and in quantifying capital misallocation (Hsieh and Klenow, 2009). In this paper, we argue that leasing is an important mitigation channel of credit-constraint-induced capital misallocation. First, we develop a general equilibrium model with heterogeneous firms, collateral constraint and an explicit buy versus lease decision to demonstrate a novel economic mechanism: the possibility for firms to rent capital when they are financially constrained mitigates capital misallocation. Second, we empirically show that ignoring leased capital and its mitigation effect leads to a significant overestimate of capital misallocation.

Maximum Spectral Measures of Risk with Given Risk Factor Marginal Distributions
Ghossoub, Mario,Hall, Jesse,Saunders, David
SSRN
We consider the problem of determining an upper bound for the value of a spectral risk measure of a loss that is a general nonlinear function of two factors whose marginal distributions are known, but whose joint distribution is unknown. The factors may take values in complete separable metric spaces. We introduce the notion of Maximum Spectral Measure (MSP), as a worst-case spectral risk measure of the loss with respect to the dependence between the factors. The MSP admits a formulation as a solution to an optimization problem that has the same constraint set as the optimal transport problem, but with a more general objective function. We present results analogous to the Kantorovich duality, and we investigate the continuity properties of the optimal value function and optimal solution set with respect to perturbation of the marginal distributions. Additionally, we provide an asymptotic result characterizing the limiting distribution of the optimal value function when the factor distributions are simulated from finite sample spaces. The special case of Expected Shortfall and the resulting Maximum Expected Shortfall is also examined.

Molehills into mountains: Transitional pressures from household PV-battery adoption under flat retail and feed-in tariffs
Kelvin Say,Michele John
arXiv

With Australia's significant capacity of household PV, decreasing battery costs may lead to widespread use of household PV-battery systems. As the adoption of these systems are heavily influenced by retail tariffs, this paper analyses the effects of flat retail tariffs with households free to invest in PV battery systems. Using Perth, Australia for context, an open-source model is used to simulate household PV battery investments over a 20-year period. We find that flat usage and feed-in tariffs lead to distinct residual demand patterns as households' transition from PV-only to PV-battery systems. Analysing these patterns qualitatively from the bottom-up, we identify tipping point transitions that may challenge future electricity system management, market participation and energy policy. The continued use of flat tariffs incentivises PV-battery households to maximise self-consumption, which reduces annual grid-imports, increases annual grid-exports, and shifts residual demand towards winter. Diurnal and seasonal demand patterns continue to change as PV-battery households eventually become net-generators. Unmanaged, these bottom-up changes may complicate energy decarbonisation efforts within centralised electricity markets and suggests that policymakers should prepare for PV-battery households to play a more active role in the energy system.

Monetary Policy with Reserves and Cbdc: Optimality, Equivalence, and Politics
Niepelt, Dirk
SSRN
We analyze policy in a two-tiered monetary system. Noncompetitive banks issue deposits while the central bank issues reserves and a retail CBDC. Monies differ with respect to operating costs and liquidity. We map the framework into a baseline business cycle model with "pseudo wedges" and derive optimal policy rules: Spreads satisfy modified Friedman rules and deposits must be taxed or subsidized. We generalize the Brunnermeier and Niepelt (2019) result on the macro irrelevance of CBDC but show that a deposit based payment system requires higher taxes. The model implies annual implicit subsidies to U.S. banks of up to 0.8 percent of GDP during the period 1999-2017.

Neural network regression for Bermudan option pricing
Bernard Lapeyre,Jérôme Lelong
arXiv

The pricing of Bermudan options amounts to solving a dynamic programming principle, in which the main difficulty, especially in high dimension, comes from the conditional expectation involved in the computation of the continuation value. These conditional expectations are classically computed by regression techniques on a finite dimensional vector space. In this work, we study neural networks approximations of conditional expectations. We prove the convergence of the well-known Longstaff and Schwartz algorithm when the standard least-square regression is replaced by a neural network approximation. We illustrate the numerical efficiency of neural networks as an alternative to standard regression methods for approximating conditional expectations on several numerical examples.

Opening-up Trajectories and Economic Recovery: Lessons after the First Wave of the COVID-19 Pandemic
DemirgÃ¼Ã§-Kunt, Asli,Lokshin, Michael,Torre, IvÃ¡n
SSRN
This paper analyzes the reopening process of countries in Europe and Central Asia after the first wave of the COVID-19 pandemic and provides evidence on the effects of different reopening trajectories and their timing and speed on economic recovery. The analysis indicates that countries that adopted a gradual, staged reopening experienced stronger economic recovery compared with the countries that rushed into lifting the restrictive measures before the pandemic was under control. Postponing lifting the restrictions until after the pandemicâ€™s peak was reached has a positive impact on economic activity. Governance also matters: a higher level of trust in government is associated with increased economic activity among countries that carried out a gradual reopening process. There is also suggestive evidence that providing people objective data on the progress of the pandemic may speed up the recovery process.

Optimal Debt Maturity and Firm Investment
Jungherr, Joachim,Schott, Immo
SSRN
We introduce long-term debt and a maturity choice into a dynamic model of production, firm financing, and costly default. Long-term debt saves roll-over costs but increases future leverage and default rates because of a commitment problem. The model generates rich distributions of maturity choices, leverage ratios, and credit spreads across firms. It explains why larger and older firms borrow at longer maturities, have higher leverage, and pay lower credit spreads. Firms' maturity choice matters for policy: A financial reform which increases investment and output in a standard model of short-term debt can have the opposite effect in a model with short-term debt and long-term debt.

Optimally Imprecise Memory and Biased Forecasts
Azeredo da Silveira, Rava,Sung, Yeji,Woodford, Michael
SSRN
We propose a model of optimal decision making subject to a memory constraint. The constraint is a limit on the complexity of memory measured using Shannon's mutual information, as in models of rational inattention; but our theory differs from that of Sims (2003) in not assuming costless memory of past cognitive states. We show that the model implies that both forecasts and actions will exhibit idiosyncratic random variation; that average beliefs will also differ from rational-expectations beliefs, with a bias that fluctuates forever with a variance that does not fall to zero even in the long run; and that more recent news will be given disproportionate weight in forecasts. We solve the model under a variety of assumptions about the degree of persistence of the variable to be forecasted and the horizon over which it must be forecasted, and examine how the nature of forecast biases depends on these parameters. The model provides a simple explanation for a number of features of reported expectations in laboratory and field settings, notably the evidence of over-reaction in elicited forecasts documented by Afrouzi et al. (2020) and Bordalo et al. (2020a).

Pension Benefits, Early Retirement and Human Capital Depreciation in Late Adulthood
arXiv

Historically, economists have mainly focused on human capital accumulation and considerably less so on the causes and consequences of human capital depreciation in late adulthood. Studying human capital depreciation over the life cycle has powerful economic consequences for decision-making in old age. Using data from the introduction of a retirement program in China, we examine how the introduction of a retirement program influences individual cognition. We find large negative effects of pension benefits on cognitive functioning among the elderly. We detect the most substantial impact of the program to be on delayed recall, which is a significant predictor of the onset of dementia. We show suggestive evidence that the program leads to larger negative impacts among women. We show that retirement plays a significant role in explaining cognitive decline at older ages.

Mark Whitmeyer
arXiv

This paper extends the sequential search model of Wolinsky (1986) by allowing firms to choose how much match value information to disclose to visiting consumers. This restores the Diamond paradox (Diamond 1971): there exist no symmetric equilibria in which consumers engage in active search, so consumers obtain zero surplus and firms obtain monopoly profits. Modifying the scenario to one in which prices are advertised, we discover that the no-active-search result persists, although the resulting symmetric equilibria are ones in which firms price at marginal cost.

Portfolio Optimisation Using the D-Wave Quantum Annealer
Frank Phillipson,Harshil Singh Bhatia
arXiv

The first quantum computers are expected to perform well at quadratic optimisation problems. In this paper a quadratic problem in finance is taken, the Portfolio Optimisation problem. Here, a set of assets is chosen for investment, such that the total risk is minimised, a minimum return is realised and a budget constraint is met. This problem is solved for several instances in two main indices, the Nikkei225 and the S\&P500 index, using the state-of-the-art implementation of D-Wave's quantum annealer and its hybrid solvers. The results are benchmarked against conventional, state-of-the-art, commercially available tooling. Results show that for problems of the size of the used instances, the D-Wave solution, in its current, still limited size, comes already close to the performance of commercial solvers.

Research trends in combinatorial optimisation
Jann Michael Weinand,Kenneth Sörensen,Pablo San Segundo,Max Kleinebrahm,Russell McKenna
arXiv

Real-world problems are becoming highly complex and, therefore, have to be solved with combinatorial optimisation (CO) techniques. Motivated by the strong increase of publications on CO, 8,393 articles from this research field are subjected to a bibliometric analysis. The corpus of literature is examined using mathematical methods and a novel algorithm for keyword analysis. In addition to the most relevant countries, organisations and authors as well as their collaborations, the most relevant CO problems, solution methods and application areas are presented. Publications on CO focus mainly on the development or enhancement of metaheuristics like genetic algorithms. The increasingly problem-oriented studies deal particularly with real-world applications within the energy sector, production sector or data management, which are of increasing relevance due to various global developments. The demonstration of global research trends in CO can support researchers in identifying the relevant issues regarding this expanding and transforming research area.

Risk Mitigating Versus Risk Shifting: Evidence from Banks Security Trading in Crises
SSRN
We show that risk mitigating incentives dominate risk shifting incentives in fragile banks. Risk shifting could be particularly severe in banking since it is the most opaque industry and banks are one of the most leveraged corporations with very low skin in the game. To analyze this question, we exploit security trading by banks during financial crises, as banks can easily and quickly change their risk exposure within their security portfolio. However, in contrast with the risk shifting hypothesis, we find that less capitalized banks take relatively less risk after financial market stress shocks. We show this using the supervisory ISIN-bank-month level dataset from Italy with all securities for each bank. Our results are over and above capital regulation as we show lower reach-for-yield effects by less capitalized banks within government bonds (with zero risk weights) or within securities with the same rating and maturity in the same month (which determines regulatory capital). Effects are robust to controlling for the covariance with the existence portfolio, and less capitalized banks, if anything, reduce concentration risk. Further, effects are stronger when uncertainty is higher, despite that risk shifting motives may be then higher. Moreover, three separate tests Ã¢?? based on different accounting portfolios (trading book versus held to maturity), the distribution of capital and franchise value Ã¢?? suggest that bank own incentives, instead of supervision, are the main drivers. Results are confirmed if we consider other sources of balance sheet fragility and different measures of risk-taking. Finally, evidence from the recent COVID-19 shock corroborates findings from the Global Financial Crisis and the Euro Area Sovereign Crisis.

Safe-Haven Properties of Soft Commodities during Times of COVID-19
Rubbaniy, Ghulame,Cheema, Ali Awais,Siriopoulos, Costas
SSRN
We use wavelet coherence analysis on global COVID-19 fear index and soft commodities spot and futures prices to investigate safe-haven properties of soft commodities during the period of novel Corona virus pandemic. The results show that staple food soft commodities (wheat, corn, and cocoa) and the futures on corn, cotton and cocoa possess strong positive co-movement with global COVID-19 fear index and can be used as safe-haven assets due to their price resilience during the times of COVID-19 pandemic. However, the non-staple soft commodities do not exhibit this behavior as their consumption is not persistent and consumers switch to healthy foods during the Covid-19 outbreak to boost their immunity against the COVID-19.

Screening and Loan Origination Time: Lending Standards, Loan Defaults and Bank Failures
SSRN
We show that loan origination time is key for bank lending standards, cycles, defaults and failures. We exploit the credit register from Spain, with the time of a loan application and its granting. When VIX is lower (booms), banks shorten loan origination time, especially to riskier firms. Bank incentives (capital and competition), capacity constraints, and borrower-lender information asymmetries are key mechanisms driving results. Moreover, shorter (loan-level) origination time is associated with higher ex-post defaults, also using variation from holidays. Finally, shorter precrisis origination time -more than other lending conditions- is associated with more bank-level failures in crises, consistent with lower screening.

Selfish Corporations
Colonnelli, Emanuele,Gormsen, Niels Joachim Christfort
SSRN
We conduct representative large-scale surveys of U.S. citizens aimed at measuring perceptions of large corporationsâ€™ environmental, social, and governance performance and investigate how these perceptions affect the public support for economic policies. The public demands corporations to behave better within society, a sentiment we label â€œbig business discontent.â€ We experimentally vary individual perceptions by showing animated videos that highlight the â€œgoodâ€ and the â€œbadâ€ of corporate behavior in recent years. We show that higher big business discontent lowers support for corporate bailouts. The effects are present across the whole political spectrum, but they are stronger for liberals than for conservatives, and they persist even a week after respondents viewed the videos. A second randomized experiment shows that simply making respondents think about the role of large corporations in society lowers their support for bailouts, highlighting a key mechanism whereby the publicâ€™s pre-existing negative beliefs about big business influence behavior once these beliefs are manipulated or triggered. We conduct an additional experimental survey to show that individualsâ€™ self-reported policy preferences are reflected in costly behavioral actions. A higher big business discontent makes respondents less likely to sign an online petition or contact U.S. senators to support corporate bailouts. Treated respondents are also less likely to donate to a non-profit organization supporting the general interests of top U.S. executives. Together, our findings suggest that the perceived strength of the social contract between big corporations and their stakeholders may impact the public support for important economic policies.

Sequential hypothesis testing in machine learning, and crude oil price jump size detection
Michael Roberts,Indranil SenGupta
arXiv

In this paper we present a sequential hypothesis test for the detection of general jump size distrubution. Infinitesimal generators for the corresponding log-likelihood ratios are presented and analyzed. Bounds for infinitesimal generators in terms of super-solutions and sub-solutions are computed. This is shown to be implementable in relation to various classification problems for a crude oil price data set. Machine and deep learning algorithms are implemented to extract a specific deterministic component from the crude oil data set, and the deterministic component is implemented to improve the Barndorff-Nielsen and Shephard model, a commonly used stochastic model for derivative and commodity market analysis.

Should Bank Dividends Be Regulated? What Is the Long-Term Historical Evidence?
Saunders, Anthony ,Wilson, Berry K.
SSRN
The issue of bank dividend regulation has become highly controversial as the stress induced on bank capital during the 2008 financial crisis and the covid pandemic created a demand for enhanced regulation and restrictions on bank dividend payments. This paper examines this issue from a historical perspective by analyzing the dividend decisions of a sample of central-reserve-city banks during the Great Depression and its aftermath to 1973, and in particular the active risk management role that dividend policy may have played for study banks. Dividend policy was used to balance the interests of stockholders and depositors, and to preserve the long-term solvency of the bank. Overall our study results show that despite an initial reluctance to cut dividends, banks cut dividend levels by 24% in 1932 and by 12.7% in 1933 (in median terms). Post-Great Depression dividends remained at depressed levels through most of the 1930s and 1940s. Our study results indicate that this period of depressed and relatively constant dividends allowed banks to rebuild capital levels, which had fallen sharply with the Great Depression. Capital rebuilding post-depression represented risk-shifting in favor of depositors and likely contributed to the stability of the U.S. banking system in the post-depression era.

Slow Debt, Deep Recessions
Jungherr, Joachim,Schott, Immo
SSRN
Business credit lags GDP growth by about one year. This contributes to high leverage during recessions and slow deleveraging. We show that a model in which firms use risky long-term debt replicates this slow adjustment of firm debt. In the model, slow-moving debt has important effects for real activity. High levels of firm debt issued during expansions are only gradually reduced during recessions. This generates an adverse feedback loop between high default rates and low investment and thereby amplifies the downturn. Sluggish deleveraging slows down the recovery. The equilibrium is constrained inefficient because firms exert an externality on the holders of previously issued debt. The constrained efficient allocation substantially reduces macroeconomic volatility.

Standard or Sustainable - Which Offers Better Performance for the Passive Investor?
Khajenouri, Daniel C,Schmidt, Jacob H
SSRN
This research report studies the risk-adjusted performance of the major international equity indices against their ESG screened equivalents (MSCI World, MSCI USA, MSCI Emerging Markets, and MSCI Europe). The daily closing prices, returns, standard deviations, and Sharpe ratio characteristics are analyzed from 2013 to 2020. The current literature available from highly rated journals on the subject is also considered, which provided mixed results on the subject matter. We found no academic papers focusing specifically on analyzing the performance of indices and their ESG screened equivalents. With this paper, we intend to fill this gap in the current research available.We conclude that for the passive investor, choosing ESG screened indices over the conventional equivalent has consistently provided better risk-adjusted returns over the long-term period. These findings are robust with the consistently higher Sharpe ratios over the eight-year period for each index. We predict ESG investments may continue to outperform due to changing retail and institutional investor preferences.

Stereotypes in Financial Literacy: Evidence from PISA
Bottazzi, Laura,Lusardi, Annamaria
SSRN
We examine gender differences in financial literacy among high school students in Italy using data from the 2012 Programme for International Student Assessment (PISA). Gender differences in financial literacy are large among the young in Italy. They are present in all regions and are particularly severe in the South and the Islands. Combining the rich PISA data with a variety of other indicators, we provide a thorough analysis of the potential determinants of the gender gap in financial literacy. We find that parental background, in particular the role of mothers, matters for the financial knowledge of girls. Moreover, we show that the social and cultural environment in which girls and boys live plays a crucial role in explaining gender differences. We also show that history matters: Medieval commercial hubs and the nuclear family structure created conditions favorable to the transformation of the role of women in society, and shaped gender differences in financial literacy as well.

Stock Price Reaction to Debt Offerings: The Turkish Evidence
Akdogu, Evrim,Avci, Sureyya,Simsir, Serif Aziz
SSRN
We investigate the valuation effects of debt issues on the issuing firmsâ€™ common stock using a sample of Turkish issuers. For the sample of non-financial firms, we find no significant wealth effects for debt issues around the announcement dates. However, market reactions are more positive when information asymmetry between firm managers and outside investors is low, agency costs are high, and when debt issues are likely to carry positive information about firmsâ€™ prospects. These results support pecking order, signaling and agency theories of capital structure. In additional tests, we find positive market reactions to debt issue announcements of financial firms.

Sustainability or Performance? Ratings and Fund Managersâ€™ Incentives
Gantchev, Nickolay,Giannetti, Mariassunta,Li, Rachel
SSRN
We use the introduction of Morningstarâ€™s sustainability ratings (the â€œglobeâ€ ratings) as an exogenous shock to mutual fundsâ€™ preferences and show that mutual funds initially attempt to improve their globe ratings by increasing their demand for sustainable stocks. This trading behavior creates buying pressure, making stocks with high sustainability ratings overvalued. As a consequence, a tradeoff between sustainability and performance arises and the performance of funds improving their globe ratings deteriorates. Since performance appears to be more important in attracting flows than sustainability, a new equilibrium emerges in which the globe ratings stop affecting fundsâ€™ flows and funds do not trade any longer to improve their globe ratings. Our results highlight the issues arising when funds are evaluated along two different dimensions that create conflicting incentives for fund managers who compete for flows.

Temporal mixture ensemble models for intraday volume forecasting in cryptocurrency exchange markets
Nino Antulov-Fantulin,Tian Guo,Fabrizio Lillo
arXiv

We study the problem of the intraday short-term volume forecasting in cryptocurrency exchange markets. The predictions are built by using transaction and order book data from different markets where the exchange takes place. Methodologically, we propose a temporal mixture ensemble, capable of adaptively exploiting, for the forecasting, different sources of data and providing a volume point estimate, as well as its uncertainty. We provide evidence of the outperformance of our model by comparing its outcomes with those obtained with different time series and machine learning methods. Finally, we discuss the predictions conditional to volume and we find that also in this case machine learning methods outperform econometric models.

Li, Kai,Tsou, Chi-Yang
SSRN
This paper studies how the durability of assets affects the cross-section of stock returns. More durable assets incur lowers frictionless user costs but are more "expensive", in the sense that they need more down payments making them hard to finance. In recessions, firms become more financially constrained and prefer "cheaper" less durable assets. As a result, the price of less durable assets is less procyclical and therefore less risky than that of durable assets. We provide strong empirical evidence to support this prediction. Among financially constrained stocks, firms with higher asset durability earn average returns about 5% higher than firms with lower asset durability. We develop a general equilibrium model with heterogeneous firms and collateral constraints to quantitatively account for such a positive asset durability premium.

The Choice of Certifier in Endogenous Markets
SSRN
For markets to work, buyers must know when products are of high quality. This paper provides a theoretical framework for studying the consequences of the certifier's identity, the characteristics of the best certifier, and the identity of the equilibrium certifier. A certifier that cares about quality and externalities (such as an NGO) motivates firms to invest in their capacities to provide quality; a certifier concerned with the firms' profits (such as an industry association) motivates more firms to enter the market in the first place. The relative importance of externalities, investments, and entry determines the socially optimal certification authority but also the type of certifier that is most likely to enter in equilibrium. The theory's predictions are empirically testable and shed light on the variety of certifiers across markets and over time.

The Financial (In)Stability Real Interest Rate, R*
Akinci, Ozge,Benigno, Gianluca,Del Negro, Marco,Queralto, Albert
SSRN
constraint being binding. Increasing imbalances in the financial sector measured by an increase in leverage are accompanied by a lower threshold that could trigger financial instability events. We also construct a theoretical implied financial condition index and show how it is related to the gap between the natural and financial stability interest rates.

The Impact of Religiosity on Earnings Quality: International Evidence from the Banking Sector
Abdelsalam, Omneya
SSRN
We examine the impact of religiosity on earnings quality, utilising a global sample of 1,283 listed banks headquartered in 39 countries and covering the period 2002â€"2018. Using instrumental variables two-stage least squares regressions, we demonstrate that religiosity has a significant positive impact on banksâ€™ earnings quality. We further show that the impact of religiosity becomes more pronounced among banks headquartered in countries where religion is an important element of national identity and in countries with weak legal protection. We show that the effects of religiosity are more intense during the global financial crisis period. Overall, these findings support the notion that high religiosity tends to reduce unethical activities by managers and can function as an alternative control mechanism for minimising agency costs. Our empirical investigation is robust to alternative model sample specification.

The Speed of Stock Price Adjustment to Corporate Announcements: Insights from Turkey
Ersan, Oguz,Simsir, Serif Aziz,Simsek, Koray D.,Hasan, Afan
SSRN
The market reaction speeds to the news flow are currently measured at the millisecond level in developed markets. We investigate, using a unique setting from Turkey, whether the market reaction speeds in less sophisticated markets are on par with those of developed markets. We find that market reaction times to corporate announcements are slower than documented in recent studies, although markets react to positive news more quickly than negative news. When high-frequency traders are more active in the market prior to announcements, the speed of price adjustment is slower. Finally, we find sizable profit opportunities for investors following event-driven strategies.

The Stability and Predictive Power of Financial Literacy: Evidence from Longitudinal Data
Angrisani, Marco,Burke, Jeremy,Lusardi, Annamaria,Mottola, Gary R.
SSRN
We administered the FINRA Foundation's National Financial Capability Study questionnaire to members of the RAND American Life Panel (ALP) in 2012 and 2018. Using this unique, longitudinal data set, we investigate the evolution of financial literacy over time and shed light on the causal effect of financial knowledge on financial outcomes. Over a six-year observation period, financial literacy appears to be rather stable, with a slight tendency to decline at older ages. Moreover and importantly, financial literacy has significant predictive power for future financial outcomes, even after controlling for baseline outcomes and a wide set of demographics and individual characteristics that influence financial decision making. This estimated relationship is significantly stronger for older individuals, for women, and for those with lower income than for their counterparts in the study. Altogether, our findings suggest that differences in the stock of financial knowledge may lead to increasing inequality over the life course.

Time for Gift Giving: Abnormal Share Repurchase Returns and Uncertainty
Anolick, Nina,Batten, Jonathan A.,Kinateder, Harald,Wagner, Niklas
SSRN
We study share repurchase announcements for nine European countries between 2000 to 2017. In contrast to previous studies, we address the role of market uncertainty as a market-based determinant of positive average abnormal announcement returns, while including governance, liquidity risk and firm related control variables. Economic policy uncertainty and financial uncertainty, individually as well as jointly, positively affect abnormal returns. We suggest that this relation is due to a stronger signaling effect under increased uncertainty, as both information asymmetry and underpricing tend to increase. Also, a potential hedge against adverse market movements is more valuable. Optimal timing of repurchase announcements should therefore consider market uncertainty conditions.

Unexpected Effects of Bank Bailouts: Depositors Need Not Apply and Need Not Run
Berger, Allen N.,Lamers, Martien,Roman, Raluca A.,Schoors, Koen
SSRN
A key policy issue is whether bank bailouts weaken or strengthen market discipline. We address this by analyzing how bank bailouts influence deposit quantities and prices of recipients versus other banks. Using TARP bailouts, we find both deposit quantities and prices decline, consistent with substantially reduced demand for deposits by bailed-out banks that dominate market discipline supply effects. Main findings are robust to numerous checks and endogeneity tests. However, diving deeper into depositor heterogeneity suggests nuance. Increases in uninsured deposits, transactions deposits, and deposits in banks that repaid bailout funds early suggest some temporary limited support for weakened market discipline.

What Can Commercial Property Performance Reveal about Bank Valuations?
Kohlscheen, Emanuel,TakÃ¡ts, ElÅ'd
SSRN
We test whether commercial property performance, proxied by real estate investment trust (REIT) prices, can inform us about bank equity prices. Using data from the United States, the euro area and Japan, we show that REIT prices can predict bank equity prices. Furthermore, a â€œcommercial property factorâ€ adds significant explanatory power to both the CAPM and the 3-factor Fama-French model. At the same time, quantile regressions show that this factor becomes particularly prominent during downturns. It accounts for around half of the drop in average bank valuations during the great financial crisis and, again, during the COVID-19 pandemic.