Research articles for the 2020-03-25
SSRN
A long-standing puzzle in international finance is that a positive interest rate differen- tial systematically forecasts an exchange rate appreciation-the Uncovered Interest Parity (UIP) puzzle. Hence, a carry trade portfolio long in high yield currency bonds funded by borrowing in low yield currencies can be expected to yield positive profits. Following the Great Financial Crisis, however, the sign of the puzzle has changed-positive differentials forecast excessive depreciation-and carry trade has withered after the large losses suffered by investors in 2007-2008. In this paper, we use a century-long time series for the GBP/USD exchange rate to show that a sign switch is neither new, nor, arguably, a new puzzle. First, it is not new in the data-by virtue of a long sample featuring infrequent, non-overlapping currency crashes, we document that switches systematically occur in crises such as the Great Depression in the 1930s and the exchange rate turmoil of the 1990s. However, UIP devi- ations, sharp in either direction for short- to medium-horizon portfolios, remain small to almost negligible for long-horizon investment portfolios. Second, we argue that our century- long evidence is consistent with models featuring a time-varying probability of disasters or 'Peso events,' specified so to account for the difference in UIP deviations in crisis and nor- mal times, as well as for a decreasing term structure of carry trade returns that on average characterize the data.
arXiv
The St. Petersburg paradox, an important topic in probability theory, has not been solved last 280 years. Since Nicolaus Bernoulli proposed the St. Petersburg Paradox in 1738, many people had tried to solve it and had proposed various explanations, but all are not satisfactory. In the paper we proposed a new pricing theory with several rules, which incidentally resolves this paradox. The new pricing theory states that so-called fair (reasonable) pricing should be judged by the seller and the buyer independently. Reasonable pricing for the seller may not be appropriate for the buyer. The seller cares about costs, while the buyer is concerned about the realistic prospect of returns.The pricing theory we proposed can be applied to financial market to solve the confusion that financial asset return with fat tails distribution will cause the option pricing formula to fail, thus making up the theoretical defects of quantitative financial pricing theory. We want to pay tribute to Edward O. Thorp with this article, a man for all markets, for the author entered the financial field just because getting read his story.
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Artificial intelligence (AI) has a growing presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and returns forecasts and under more complex constraints. Trading algorithms utilize AI to devise novel trading signals and execute trades with lower transaction costs, and AI improves risk model-ling and forecasting by generating insights from new sources of data. Finally, robo-advisors owe a large part of their success to AI techniques. At the same time, the use of AI can create new risks and challenges, for instance as a result of model opacity, complexity, and reliance on data integrity.
arXiv
This paper studies the equilibrium price of an asset that is traded in continuous time between N agents who have heterogeneous beliefs about the state process underlying the asset's payoff. We propose a tractable model where agents maximize expected returns under quadratic costs on inventories and trading rates. The unique equilibrium price is characterized by a weakly coupled system of linear parabolic equations which shows that holding and liquidity costs play dual roles. We derive the leading-order asymptotics for small transaction and holding costs which give further insight into the equilibrium and the consequences of illiquidity.
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Offshore markets in a non-convertible currency, usually referred to as non-deliverable forward (NDF) markets, enable trading of the non-convertible currency outside the influence of the domestic authorities. These contracts are settled in a convertible currency, usually US Dollars, as the non-convertible currency cannot be delivered offshore. Historically, NDF markets evolved for currencies with foreign exchange convertibility restrictions and controlled access for non-residents, beginning with countries in South America like Mexico and Brazil and thereafter moving on to emerging Asian economies, viz., Taiwan, South Korea, Indonesia, India, China, Philippines, etc. The sharp growth in the offshore trading volumes in the Rupee NDF market in recent years, even beyond the volumes in the onshore markets have raised concerns around the forces that are determining the value of the rupee and the ability of authorities to ensure currency stability. An attempt has been made in this paper to identify the challenges in trading in rupee derivatives which present good opportunities for India to develop this industry. For that, the paper first discusses the global scenario of currency derivatives which is followed by the rupee derivatives trading in India and rupee derivatives in volumes in other global markets. To draw some lessons from the Chinese experience it then covers in brief the Chinese currency trading experience. This is followed by details covering challenges and opportunities for developing rupee trading in International Financial Services Centre (IFSC) in India, as IFSC is like an offshore centre from regulation and tax perspective but is on Indian shore.
arXiv
Distributed ledger technologies replace trusted clearing counterparties and security depositories with time-consuming consensus protocols to record the transfer of ownership. This settlement latency exposes cross-market arbitrageurs to price risk. We theoretically derive arbitrage bounds that increase with expected latency, latency uncertainty, volatility and risk aversion. Using Bitcoin orderbook and network data, we estimate arbitrage bounds of on average 121 basis points, explaining 91% of the observed cross-market price differences. Consistent with our theory, periods of high latency-implied price risk exhibit large price differences, while asset flows chase arbitrage opportunities. Blockchain-based settlement thus introduces a non-trivial friction that impedes arbitrage activity.
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Some individuals are more susceptible to overvaluing assets in bubble markets than others. However, the degree to which an individual’s social environment and social cognition affect bubble susceptibility is unclear. We examined the effects of social aptitude and social context on individual investors’ performance in experimental markets. Here we report that participants with lower social aptitude were less susceptible to bubbles in a social financial market. Participants with higher social responsiveness were more likely to buy a stock after seeing another participant buy a stock, and were also more likely to buy in a bubble market compared to a non-bubble market. Our findings suggest that bubbles are perpetuated by the herding behavior of highly social individuals, highlighting the importance of neurodiversity among asset traders.
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Episodes of debt accumulation have been a recurrent feature of the global economy over the past fifty years. Since 2010, emerging and developing economies have experienced another wave of historically large and rapid debt accumulation. Similar past debt buildups have often ended in widespread financial crises in these economies. This paper examines the factors that are likely to determine the outcome of the most recent debt wave, and considers policy options to help reduce the likelihood that it ends again in widespread crises. It reports two main results. First, the rapid increase in debt has made emerging and developing economies more vulnerable to shifts in market sentiment, notwithstanding historically low global interest rates. Second, policy options are available to lower the likelihood of financial crises, and to help manage the adverse impacts of crises when they do occur. These include sound debt management, strong monetary and fiscal frameworks, and robust bank supervision and regulation. The post-crisis debt buildup has coincided with a period of subdued growth as well as the emergence of non-traditional creditors. As a result, policy priorities also need to ensure that debt is spent on productive purposes to improve growth prospects and that all debt-related transactions are transparently reported.
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The Great Depression is infamous for banking panics, which were a symptomatic of a phenomenon that scholars have labeled a contagion of fear. Using geocoded, microdata on bank distress, we develop metrics that illuminate the incidence of these events and how banks that remained in operation after panics responded. We show that between 1929-32 banking panics reduced lending by 13%, relative to its 1929 value, and the money multiplier and money supply by 36%. The banking panics, in other words, caused about 41% of the decline in bank lending and about nine-tenths of the decline in the money multiplier during the Great Depression.
arXiv
Risk measures connect probability theory or statistics to optimization, particularly to convex optimization. They are nowadays standard in applications of finance and in insurance involving risk aversion. This paper investigates a wide class of risk measures on Orlicz spaces. The characterizing function describes the decision maker's risk assessment towards increasing losses. We link the risk measures to a crucial formula developed by Rockafellar for the Average Value-at-Risk based on convex duality, which is fundamental in corresponding optimization problems. We characterize the dual and provide complementary representations.
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In spite of growing interest in Saudi corporate governance systems, there is little literature on the evolution of Saudi corporate governance. This study helps close this gap by investigating and compiling corporate governance development in Saudi Arabia. After providing background information for Saudi Arabia and its corporate governance model, we touch on the Saudi legal system and key external institutions that helped shape its corporate governance. We examine the specific contributions of the accounting and auditing professions, and the roles of the National Anti-Corruption Commission and the Saudi Stock Exchange. We describe key reforms implemented to develop the Saudi economy and evaluate their importance in facilitating change in corporate governance practices. This study contributes as an initial point of reference for future studies on Saudi Arabia, and serves as a one stop resource for both academics and practitioners, while specifically benefiting foreign and domestic investors considering investments in Saudi Arabia.
arXiv
Since the inception of cryptocurrencies, an increasing number of financial institutions are gettinginvolved in cryptocurrency trading. It is therefore important to summarise existing research papersand results on cryptocurrency trading. This paper provides a comprehensive survey of cryptocurrencytrading research, by covering 118 research papers on various aspects of cryptocurrency trading (e.g.,cryptocurrency trading systems, bubble and extreme condition, prediction of volatility and return,crypto-assets portfolio construction and crypto-assets, technical trading and others). This paper alsoanalyses datasets, research trends and distribution among research objects (contents/properties) andtechnologies, concluding with promising opportunities in cryptocurrency trading
arXiv
In an ideal world, individuals are well informed and make rational choices. Regulators can fill in to protect consumers, such as retail investors. Online P2P lending is a rather new form of market-based finance where regulation is still in its infancy. We analyze how retail investors price the credit risk of P2P consumer loans in a reverse auction framework where personal interaction is absent. The explained interest rate variance is considerably larger than in comparable studies using bank loan data. Our results indicate that retail investors act rational in this weakly regulated environment. This seems surprising when considering the limited set of information provided to the investor. Factors representing economic status significantly influence lender evaluations of the borrower's credit risk. The explanatory power of loan-specific factors increase as the market for P2P consumer loans matures. Furthermore, we find statistical evidence of some discrimination by the lenders with respect to nationality and gender.
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We use hand-collected data of 20,460 investment decisions and two distinct portals to analyze whether investors in equity crowdfunding direct their investments to local firms. In line with agency theory, the results suggest that investors exhibit a local bias, even when we control for family and friends. In addition to the regular crowd, our sample includes angel-like investors, who invest considerable amounts and exhibit a larger local bias. Well-diversified investors are less likely to suffer from this behavioral anomaly. The data further show that portal design is important for attracting investors more prone to having a local bias. Overall, we find that investors who direct their investments to local firms more often pick start-ups that run into insolvency or are dissolved, which indicates that local investments in equity crowdfunding constitute a behavioral anomaly rather and a rational preference. Here again, however, portal design plays a crucial role.
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We develop a dynamic model of debt contracts with adverse selection and belief updates. In the model, entrepreneurs borrow investment goods from lenders to run businesses whose returns depend on entrepreneurial productivity and common productivity. The entrepreneurial productivity is the entrepreneur's private information, and the lender constructs beliefs about the entrepreneur's productivity based on the entrepreneur's business operation history, common productivity history, and terms of the contract. The model provides insights on the dynamic and cross-sectional relationship between firm age and credit risk, cyclical asymmetry of the business cycle, slow recovery after a crisis, and the constructive economic downturn.
arXiv
Stock prices are influenced over time by underlying macroeconomic factors. Jumping out of the box of conventional assumptions about the unpredictability of the market noise, we modeled the changes of stock prices over time through the Markov Decision Process, a discrete stochastic control process that aids decision making in a situation that is partly random. We then did a "Region of Interest" (RoI) Pooling of the stock time-series graphs in order to predict future prices with existing ones. Generative Adversarial Network (GAN) is then used based on a competing pair of supervised learning algorithms, to regenerate future stock price projections on a real-time basis. The supervised learning algorithm used in this research, moreover, is original to this study and will have wider uses. With the ensemble of these algorithms, we are able to identify, to what extent, each specific macroeconomic factor influences the change of the Brownian/random market movement. In addition, our model will have a wider influence on the predictions of other Brownian movements.
arXiv
We study risk-sharing economies where heterogenous agents trade subject to quadratic transaction costs. The corresponding equilibrium asset prices and trading strategies are characterised by a system of nonlinear, fully-coupled forward-backward stochastic differential equations. We show that a unique solution generally exists provided that the agents' preferences are sufficiently similar. In a benchmark specification with linear state dynamics, the illiquidity discounts and liquidity premia observed empirically correspond to a positive relationship between transaction costs and volatility.
arXiv
The global spread of 2019-nCoV, a new virus belonging to the coronavirus family, forced national and local governments to apply different sets of measures aimed at containing the outbreak. Los Angeles has been one of the first cities in the United States to declare the state of emergency on March 4th, progressively issuing stronger policies involving (among the others) social distancing, the prohibition of crowded private and public gatherings and closure of leisure premises. These interventions highly disrupt and modify daily activities and habits, urban mobility and micro-level interactions between citizens. One of the many social phenomena that could be influenced by such measures is crime. Exploiting public data on crime in Los Angeles, and relying on routine activity and pattern theories of crime, this work investigates whether and how new coronavirus containment policies have an impact on crime trends in a metropolis. The article specifically focuses on eight urban crime categories, daily monitored from January 1st 2017 to March 16th 2020. The analyses will be updated bi-weekly to dynamically assess the short- and medium-term effects of these interventions to shed light on how crime adapts to such structural modification of the environment. Finally, policy implications are also discussed.
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Low-risk investing within equities and other asset classes has received a lot of attention over the past decade. An intensive academic debate has spurred, and been spurred by, the growing market for low-risk strategies. This article presents five fact and dispels five fictions about low-risk investing. The facts are: Low-risk returns have been 1) strong historically, 2) highly significant out-of-sample, 3) robust across many countries and asset classes, and 4) backed by strong economic theory, but, nevertheless, 5) can be negative when the market is down. The fictions that this article dispels are that low-risk investing 1) delivers weaker returns than other common factor premia, 2) is mostly about betting on bond-like industries, 3) is especially sensitive to transaction costs and only works among small-cap stocks, and 4) have become so expensive that they cannot do well going forward. Lastly, the article dispels the fiction 5) that CAPM is dead and so is low-risk investing â€" this statement is a contradiction; If the CAPM is dead, then low-risk investing is alive.
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This paper studies how markets adjust to the sudden emergence of previously neglected risks. It does so by analyzing the stock price effects of the 2019 novel Coronavirus disease (COVID-19) pandemic. The telecom and health care industries did relatively well, while transportation and energy plummeted. Within industries, US firms reliant on Chinese inputs and those with a strong export orientation towards China suffered. Sophisticated investors appear to have started pricing in the effects of the virus already in the first part of January (the "Incubation" phase), that is, before managers or analysts started paying attention; the first earnings conference call that contained a discussion of "Coronavirus" took place on January 22. The "Outbreak" phase followed, during which China-oriented stocks and internationally oriented stocks more generally strongly underperformed. In the last week of February and early March (the "Fever" phase), the aggregate market first fell strongly and then entered a whipsaw pattern. But behind these feverish and seemingly behaviorally-driven price moves, some patterns emerge. In particular, investors became increasingly worried about corporate debt and liquidity, indicating widespread concerns that the health crisis may evolve into a financial crisis.
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We empirically assess the responses of banks in the United States to a regulatory change that influenced the distribution of funding in the banking system. Following the 2011 FDIC change in the assessment base, insured banks found wholesale funding more costly, while uninsured branches of foreign banks enjoyed cheaper access to wholesale liquidity. We use quarterly bank balance sheet data and a rich data set of syndicated loans with borrower and lender characteristics to show that uninsured foreign banks, which faced a relatively positive shock, engaged in liquidity hoarding. Hence, they accumulated more reserves but extended fewer total syndicated loans and became more passive in the syndicated loan deals in which they participated. These results contribute to the discussion on the role of foreign banks in credit creation, especially in a country like the United States where foreign banks also have a crucial role in managing USD money market operations at the group level.
arXiv
Using a survey on wage expectations among students at two Swiss institutions of higher education, we examine the wage expectations of our respondents along two main lines. First, we investigate the rationality of wage expectations by comparing average expected wages from our sample with those of similar graduates; we further examine how our respondents revise their expectations when provided information about actual wages. Second, using causal mediation analysis, we test whether the consideration of a rich set of personal and professional controls, namely concerning family formation and children in addition to professional preferences, accounts for the difference in wage expectations across genders. We find that males and females overestimate their wages compared to actual ones, and that males respond in an overconfident manner to information about outside wages. Despite the attenuation of the gender difference in wage expectations brought about by the comprehensive set of controls, gender generally retains a significant direct, unexplained effect on wage expectations.
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In this paper we analyze the effect of loan officers' gender on the approval of loans and, in particular, on their subsequent performance. Using detailed bank information on a sample of close to half a million loans, we show that female loan officers have, conditional on the risk score, around a 15\% lower delinquency rate than that of male officers. In addition to the original scoring of the loans, we also have the recommendation of the expert system. We find that the risk profile of applicants screened by male and female loan officers is very similar, but conditional on risk score, women follow the recommendations more often than men. Moreover, we find evidence of gender bias in terms of a mistake-punishment trade-off, which could explain, at least in part, women's higher compliance with the recommendations. Indeed, there is a double standard in terms of the consequences for breaking the rules: errors, in the form of delinquent loans as a result of not following the recommendation of the system, are forgiven more often for male than for female loan officers.
arXiv
We define a new family of multivariate stochastic processes over a finite time horizon that we call Generalised Liouville Processes (GLPs). GLPs are Markov processes constructed by splitting L\'evy random bridges (LRBs) into non-overlapping subprocesses via time changes. We show that the terminal values and the increments of GLPs have generalised multivariate Liouville distributions, justifying their name. We provide various other properties of GLPs and some examples.
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Household financial decisions are complex, interdependent, and heterogeneous, and central to the functioning of the financial system. We present an overview of the rapidly expanding literature on household finance (with some important exceptions) and suggest directions for future research. We begin with the theory and empirics of asset market participation and asset allocation over the lifecycle. We then discuss household choices in insurance markets, trading behavior, decisions on retirement saving, and financial choices by retirees. We survey research on liabilities, including mortgage choice, refinancing, and default, and household behavior in unsecured credit markets, including credit cards and payday lending. We then connect the household to its social environment, including peer effects, cultural and hereditary factors, intra-household financial decision making, financial literacy, cognition and educational interventions. We also discuss literature on the provision and consumption of financial advice.
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The paper analyzes the credit supply of commercial banks and universal banks over the 2003-2009 period. Relying on a unique database of credits, banks and firms covering more than 8,000 firms from SMEs to large firms, I show that universal banks and commercial banks had a similar credit supply prior to the crisis. However, during the liquidity crisis, universal banks had a strongly lower credit supply, leading to real effects on firms’ investment. An analysis of transmission channels highlights a specific binding constraint applying to universal banks: their liquidity risk through undrawn commitments. While smallest firms are usually considered more vulnerable, the paper shows that small firms were less impacted by credit rationing than medium and large firms due to their bank-firm relationships prior to the crisis.
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In this paper, we examine the spillover effect of school ties. Analysts who have direct school ties with at least one firm in an industry make more frequent and more accurate forecasts, as well as more profitable recommendations on other firms in the same industry where they do not have direct school ties, suggesting that analysts acquire both firm-specific and industry-wide information through school ties. This spillover effect persists after enactment of Regulation Fair Disclosure. The effect is valuable enough to affect analysts’ coverage assignments and their likelihood to be named all-stars. Thus, benefits from school ties would be understated without considering the spillover effect; furthermore, we would have inferred incorrectly that school-tie analysts no longer enjoy information advantage through private access after Reg FD.
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We analyze contract-level data on approved and rejected microloans to assess the impact of a new credit registry in Bosnia and Herzegovina, a country with a competitive microcredit market. Our findings are threefold. First, information sharing reduces defaults, especially among new borrowers, and increases the return on lending. Second, lending tightens at the extensive margin as loan officers, using the new registry, reject more applications. Third, lending also tightens at the intensive margin: microloans become smaller, shorter and more expensive. This affects both new borrowers and lending relationships established before the registry. In contrast, repeat borrowers whose lending relationship started after the registry introduction begin to benefit from larger loans at lower interest rates.
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Share repurchase announcements create an asymmetric information environment for institutional investors. The firm and its insiders know the announcement’s timing and enjoy regulatory exemptions from securities law violations for the timing and pricing of share repurchase implementation or lack thereof. Institutions do not have this information ex-ante, unlike insiders. We find that institutions, with the exception of mutual funds, are not profitable in aggregate around the announcement of firms that do not follow through with actual repurchases. Contrastingly, institutions are profitable when firms actually repurchase shares. The difference between the two groups appears to be the varying degrees of mispricing. Firms with a larger degree of mispricing have less information production and create a difficult trading environment for institutions.
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This study aims to investigate the effects of crude oil price (COP) and base rate (BR) on the strength of the Ringgit (RM) against the US Dollar (USD). Within the framework of the international Fisher effect theory, the study employs yearly data from the Bloomberg Database over an observed period from 1984 through 2017. Using bivariate Engle-Granger cointegration test as an estimation tool, the study reveals the presence of a long-term relationship between the RM and COP. However, the results of the Granger Causality test show an absence of a dynamic relationship between them. From the second analysis between the RM and BR, the study finds the presence of both long-term and short-term relationships between them. Interestingly, the relationship is somewhat bidirectional. Overall, the study has suggested the relevance of the international Fisher effect in explaining how variations in the RM exchange rate are elucidated by the bank lending market. In addition, it is worth noting that both BR and COP exert a significant influence on the strength of the RM against USD over time.
arXiv
Natural and social multivariate systems are commonly studied through sets of simultaneous and time-spaced measurements of the observables that drive their dynamics, i.e., through sets of time series. Typically, this is done via hypothesis testing: the statistical properties of the empirical time series are tested against those expected under a suitable null hypothesis. This is a very challenging task in complex interacting systems, where statistical stability is often poor due to lack of stationarity and ergodicity. Here, we describe an unsupervised, data-driven framework to perform hypothesis testing in such situations. This consists of a statistical mechanical approach - analogous to the configuration model for networked systems - for ensembles of time series designed to preserve, on average, some of the statistical properties observed on an empirical set of time series. We showcase its possible applications on a set of stock market returns from the NYSE.
SSRN
We develop a novel theory of mis-allocation within firms (rather than between firms) due to managers' empire building. We introduce an internal capital market into a two-factor model of multi-segment firms. We show that more open markets impose discipline on competition for capital within firms, which explains why exporters exhibit a lower conglomerate discount than non-exporters (a fact that we establish). Testing our model with data on US companies, we establish that import competition reduces mis-allocation within firms. A one standard deviation increase in Chinese imports lowers the conglomerate discount by 32% and over-reporting of costs by up to 15%.
arXiv
In stochastic control problems delicate issues arise when the controlled system can jump due to both exogenous shocks and endogenous controls. Here one has to specify what the controller knows when about the exogenous shocks and how and when she can act on this information. We propose to use Meyer-$\sigma$-fields as a flexible tool to model information flow in such situations. The possibilities of this approach are illustrated first in a very simple linear stochastic control problem and then in a fairly general formulation for the singular stochastic control problem of irreversible investment with inventory risk. For the latter, we illustrate in a first case study how different signals on exogenous jumps lead to different optimal controls, interpolating between the predictable and the optional case in a systematic manner.
arXiv
We present a parsimonious stochastic model for valuation of options on the fraction of infected individuals during an epidemic. The underlying stochastic dynamical system is a stochastic differential version of the SIR model of mathematical epidemiology.
SSRN
Dividends are taxed at the investor level, but injecting funds into firms does not offer investors the symmetric tax benefit. Hence, there is a tax saving incentive to retain cash in the firm. We theoretically and empirically show that this tax saving motive is important for corporate cash holdings. We develop a dynamic corporate finance model of liquidity management, in which the firm's liquidity policy trades off precaution and saved personal taxes against agency and corporate tax costs. The model implies that corporate cash holdings are substantial and increasing with the dividend tax rate. To identify the empirical relation between dividend taxes and corporate cash accumulation, we use the 2003 dividend tax cut. Consistent with a reduction of the tax saving motive owing to lower dividend taxes, treated firms reduce their cash accumulation after the cut.
arXiv
Answers to interview questions sent to a selected group of former physicists working in finance. The interview will be published as part of a Special Issue on Physics and Derivatives by The Journal of Derivatives in the second half of 2020.
SSRN
We investigate whether CEOs' political preferences are associated with the prevalence and compensation of women among non-CEO top executives at U.S. public companies. We find that "Democratic" CEOs are associated with more women in the executive suite. To explore causality, we use an event study approach to show that replacing a Republican with a Democratic CEO increases female representation. Additionally, we discuss how the lack of an association between CEO political preferences and gender diversity in the boardroom influences our interpretation of these results. Finally, gender gaps in the level and performance-sensitivity of compensation diminish, or disappear, under Democratic CEOs.
arXiv
This paper proposes a theory of pricing based on two facts: customers care about the fairness of prices, and firms take these concerns into account when setting prices. The theory assumes that customers dislike unfair prices, namely those marked up steeply over cost. Since costs are unobservable, customers must extract them from prices. The theory assumes that customers infer less than rationally: when a price rises after a cost increase, customers partially misattribute the higher price to a higher markup---which they find unfair. Firms anticipate this response and trim their price increases, which drives the passthrough of costs into prices below one: prices are somewhat rigid. Embedded in a New Keynesian model as a replacement for the usual pricing frictions, our theory produces monetary-policy nonneutrality: when monetary policy loosens and inflation rises, customers misperceive markups as higher and feel unfairly treated; firms mitigate this perceived unfairness by reducing their markups; in general equilibrium, employment rises. The New Keynesian model also features a hybrid short-run Phillips curve, realistic impulse responses of output and employment to monetary and technology shocks, and an upward-sloping long-run Phillips curve.
SSRN
This paper identifies credit booms in 11 Euro Area countries by tracking private loans from the banking sector. The events are associated with both financial crises and specific macro fluctuations, but the standard identification through threshold methods does not allow to catch credit booms in real-time data. Thus, an early warning model is employed to predict the explosive dynamics of credit through several macro-financial indicators. The model catches a large part of the in-sample events and signals correctly both the global financial crisis and the sovereign debt crisis in an out-of-sample setting by issuing signals in real-time data. Moreover, while tranquil booms are driven by global dynamics, crisis-booms are related to the resilience of domestic banking systems to adverse financial shocks. The results suggest an ex-ante policy intervention can avoid dangerous credit booms by focusing on the solvency of the domestic banking system and financial market's overheating.
arXiv
A commonly used stochastic model for derivative and commodity market analysis is the Barndorff-Nielsen and Shephard (BN-S) model. Though this model is very efficient and analytically tractable, it suffers from the absence of long range dependence and many other issues. For this paper, the analysis is restricted to crude oil price dynamics. A simple way of improving the BN-S model with the implementation of various machine learning algorithms is proposed. This refined BN-S model is more efficient and has fewer parameters than other models which are used in practice as improvements of the BN-S model. The procedure and the model show the application of data science for extracting a "deterministic component" out of processes that are usually considered to be completely stochastic. Empirical applications validate the efficacy of the proposed model for long range dependence.
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Why GAO Did This Study: Over the course of individuals’ careers, their retirement savings can be spread across multiple retirement accounts and they can change jobs, both of which can cause their savings to become unclaimed and even lost. Prior GAO work has found that unclaimed retirement savings are sometimes transferred to the states. GAO was asked to review such transfers.This report examines (1) how much in retirement savings is transferred to states as unclaimed property and what happens to those savings once transferred and (2) the steps IRS and DOL have taken to oversee these transfers and what improvements are needed. GAO interviewed federal and state officials, industry representatives, and other stakeholders, and surveyed all 50 states and the District of Columbia (and received 22 responses). GAO also surveyed 401(k) plan service providers and IRA trustees regarding the volume of retirement savings transferred to states and their federal tax reporting and withholding practices for those transfers.What GAO Found: Millions of dollars in retirement savings are transferred to states as unclaimed property, only some of which is later claimed by owners. Of the 22 states responding to GAO’s survey, 17 states provided data indicating that $35 million in unclaimed retirement savings was transferred to them from employer plans and individual retirement accounts (IRAs) in 2016. When account owners do not claim money from retirement savings accounts or cash checks from their plans, the funds may be transferred to state unclaimed property offices (see fig.). Assets and uncashed checks from employer plans (such as 401(k) plans), were the most common form of retirement savings transferred to states. After funds are transferred, owners can claim their savings from the state. According to the 15 states providing data on this, owners claimed about $25 million in retirement savings in 2016: $601, on average, from 401(k) plan checks, and $5,817, on average, from traditional lRAs. States reported using a range of strategies to maintain the value of retirement savings while holding these funds, such as applying interest. States also reported various efforts to locate owners. However, not all savings will be claimed because, among other reasons, owner information is not always associated with transferred savings when the amount is small, which complicates state efforts to locate some owners.The Internal Revenue Service (IRS) and the Department of Labor (DOL) have issued guidance on transferring retirement savings to states; however, IRS has not clarified certain responsibilities or ensured that the retirement savings that owners claim from states can be rolled over into other tax-deferred retirement accounts. IRS is responsible for communicating and enforcing tax responsibilities, but has not specified whether 401(k) plan providers should report state transfers to IRS as distributions and withhold federal income taxes. IRS officials said the agency has not issued guidance to clarify this issue because of competing priorities. As a result, 401(k) plan provider practices varyâ€"some providers withhold taxes when transferring savings to states while others do not. This makes the IRS less likely to collect federal income taxes that may be due if transfers are taxable events. IRS also has not taken action to ensure that individuals who claim 401(k) savings from a state can roll over these savings to other tax-deferred retirement accounts after IRS’s 60-day deadline. IRS allows individuals to roll over savings after 60 days for several reasons, none of which include claiming 401(k) savings from a state. Federal law seeks to protect the interests of participants in retirement plans. Account owners who are unable to roll over their reclaimed savings forgo the opportunity to continue investing the funds on a tax-deferred basis.GAO made three recommendations, including that IRS should consider clarifying whether transfers from employer-based plans (such as 401(k) plans) to states constitute reportable and taxable distributions and consider modifying its list of permitted reasons for rolling over savings after the 60-day rollover deadline. IRS agreed with our recommendations and noted that it will work with the Department of the Treasury to address them.
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This paper studies the impact of financial sector size and leverage on business cycles and risk-free rates dynamics. We model a general equilibrium productive economy where financial intermediaries provide costly risk mitigation to households by pooling the idiosyncratic risks of their investment activities. We find that leverage amplifies variations of intermediaries’ relative size, but may also mitigate the business cycle. Moreover, it makes risk-free rates pro-cyclical. Households benefit the most when the financial sector is neither too small, thus avoiding high consumption fluctuations and costly mitigation, nor too big, so that fewer resources are lost after intermediation costs.
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This paper contains the statistics of a survey about the Risk-Free Rate (RF) and the Market Risk Premium (MRP) used in 2020 for 81 countries. We got answers for 87 countries, but we only report the results for 81 countries with more than 6 answers.Many respondents use for European countries a RF higher than the yield of the 10-year Government bonds. The coefficient of variation (standard deviation/average) of RF is higher than the coefficient of variation of MRP for the Euro countries.The paper also contains the links to previous years surveys, from 2008 to 2019. More than fifty respondents provided answers at the beginning of March and later, considering the coronavirus. Most of them increased MRP by 2%.
arXiv
I estimate the Susceptible-Infected-Recovered (SIR) epidemic model using cross-country daily data on Coronavirus Disease 2019 (COVID-19) cases. The transmission rate is heterogeneous across countries and far exceeds the recovery rate, which enables a fast spread. The model suggests that around 30 percent of the population may be simultaneously infected in many countries at the peak, potentially overwhelming the healthcare system. Temporary measures aiming to reduce transmission are likely ineffective to mitigate the peak. An application to a stylized asset pricing model suggests that the stock price may decrease by 25-50% during the epidemic, although the stock market crash is short-lived.
SSRN
We propose a novel conceptual approach to transparently characterizing credit market outcomes in economies with multi-dimensional borrower heterogeneity. Based on characterizations of securities' implicit demand for bank equity capital, we obtain closed-form expressions for the composition of credit, including a sufficient statistic for the provision of bank loans, and a novel cross-sectional asset pricing relation for securities held by regulated levered institutions. Our framework sheds light on the compositional shifts in credit prior to the 07/08 financial crisis and the European debt crisis, and can provide guidance on the allocative effects of shocks affecting both banks and the cross-sectional distribution of borrowers.
SSRN
This paper studies long-run trends in stock market capitalization and their drivers. New annual data for 17 advanced economies reveal a striking time series pattern: the ratio of stock market capitalization to GDP was roughly constant between 1870 and 1980, tripled with a historically unprecedented "big bang" in the 1980s and 1990s, and remains high to this day. We use data on equity returns, yields and cashflows to explore the underlying forces behind this structural shift. We show that the big bang is driven by two factors: a secular decline in the equity discount rate from 1980 onwards, and an upward shift in cashflows paid by listed firms. Equity issuance and new listings make next to no contribution to the structural increase in market cap. We also show that high market capitalization forecasts low equity returns, low dividend growth and a high risk of a stock market crash. This suggests that the currently high valuations and capitalization are a sign of high, rather than low risk in equity markets.
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This study examines the determinants of IPO withdrawal using a unique sample of Specified Purpose Acquisition Companies (SPACs) in the period 2003-2019. Our results show that both prospectuses' characteristics and market characteristics determine choices of withdrawal. The likelihood of withdrawals is in direct relation with the level of volatility on the day of IPO/withdrawal and if the acquisition target is in the private equity domain. SPACs are less likely to withdraw their IPO if they have a clear focus of acquisition, have a larger number of underwriters in the syndicate, and if their legal counsel is specialized in the SPAC market. We also document that the speed of IPO for SPACs is directly related to the level of the market, size of IPO, and if the CEO was previously manager of other public companies. On the other side, IPO takes longer if two lead underwriters underwrite SPAC.
SSRN
This paper studies the mid-September 2019 stress in US money markets: on September 16 and-17, unsecured and secured funding rates spiked up and, on the 17, the effective federal funds rate broke the ceiling of the FOMC target range. We highlight two factors that may have contributed to these events. First, reserves may have become scarce for at least some depository institutions, in the sense that these institutions' reserve holdings may have been close to, or lower than, their desired level. Moreover frictions in the interbank market may have prevented the efficient allocation of reserves across institutions, so that although aggregate reserves may have been higher than the sum of reserves demanded by each institution, they were still scarce given the market's inability to allocate reserves efficiently. Second, we provide evidence that some large domestic dealers likely experienced an increase in intermediation costs, which lead them to charge higher spreads to ultimate cash borrowers. This increase was due to a temporary reduction in lending from money market mutual funds, including through the Fixed Income Clearing Corporation's (FICC's) sponsored repo program.
SSRN
Since the advent of electronic trading in the mid 1990's, U.S. equities have traded (almost) 24 hours a day through equity index futures. This allows new information to be incorporated continuously into asset prices, yet, we show that almost 100% of the U.S equity premium is earned during a 1-hour window between 2:00 a.m. and 3:00 a.m. (ET) which we dub the "overnight drift". We study explanations for this finding within a framework a la Grossman and Miller (1988) and derive testable predictions linking dealer inventory shocks to high-frequency return predictability. Consistent with the predictions of the model, we document a strong negative relationship between end of day order imbalance, arising from market sell offs, and the overnight drift occurring at the opening of European financial markets. Further, we show that in recent years dealers have increasingly offloaded inventory shocks at the opening of Asian markets and exploit a natural experiment based on daylight savings time to show that Asian offloading shifts by one hour between summer and winter.
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We introduce a new deep learning architecture for predicting price movements from limit order books. This architecture uses a causal convolutional network for feature extraction in combination with masked self-attention to update features based on relevant contextual information. This architecture is shown to significantly outperform existing architectures such as those using convolutional networks (CNN) and Long-Short Term Memory (LSTM) establishing a new state-of-the-art benchmark for the FI-2010 dataset.
arXiv
In this article, we examine whether the gold market returns show abnormally positive or negative returns in some months of the calendar year. The statistical analysis and the decomposition techniques suggest that gold prices show some seasonal behavior during the turn of the year. We observe a strong cyclical behavior in gold markets during the turn-of-the-year period. January is likely to offer the highest return whereas significant negative returns are expected in July.
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Concentration plays a key role in banking efficiency and stability, yet the literature lacks any long-run analysis of U.S. banking industry structure. This paper uses newly-collected archival data to provide the first study of banking concentration from the early years of the republic through 2019. While concentration was declining or stable before the mid-1920s, statistical tests identify a structural break thereafter, as concentration started steadily rising as a result of growth at the nation's largest five banks, particularly those located in New York City. A second structural break in the mid-1990s further accelerated the upward trend in concentration before slowing down during the Great Recession.
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The unexpected and extraordinarily fast outbreak of COVID-19 gives us the opportunity to quantify the exposure of major financial markets to news shocks about global and local viral risk. We use both contagion data and social media activity about COVID-19 to measure news shocks. We provide novel empirical patterns both at a daily frequency and at high-frequency Across several class of assets and currencies, the market price of pandemic-infection risk is very significant. Our results suggest that (i) this source of risk is first-order for global wealth; and (ii) prudential policies aimed at mitigating either global contagion or local diffusion may be extremely valuable.
SSRN
The objective of this article is to identify factors that exert an influence on the problem of unbanking in Poland. The empirical material used for the purposes of the presented study was obtained within the framework of the “Social Diagnosis†research project carried out in 2015 by the Board of Social Monitoring operating at the University of Finance and Management in Warsaw. Factors such as disposable personal income, age, one’s level of education, trust placed in commercial banks, place of residence, population, and their social-occupational status had an influence on the propensity to use banking services. Answering the question put forward in the title of the paper, we found that the factors influencing people to remain unbanked were: young age, a low level of education, low income, living in small towns/cities, and lack of trust in commercial banks. The paper contributes to the advancement of research on financial exclusion by providing knowledge on the factors that seem to have an impact on its acceptance on the market in Poland.
