Research articles for the 2020-11-25
arXiv
We consider a network of banks that optimally choose a strategy of asset liquidations and borrowing in order to cover short term obligations. The borrowing is done in the form of collateralized repurchase agreements, the haircut level of which depends on the total liquidations of all the banks. Similarly the fire-sale price of the asset obtained by each of the banks depends on the amount of assets liquidated by the bank itself and by other banks. By nature of this setup, banks' behavior is considered as a Nash equilibrium. This paper provides two forms for market clearing to occur: through a common closing price and through an application of the limit order book. The main results of this work are providing sufficient conditions for existence and uniqueness of the clearing solutions (i.e., liquidations, borrowing, fire sale prices, and haircut levels).
arXiv
We construct a two-tailed peak-over-threshold Hawkes model that captures asymmetric self- and cross-excitation in and between left- and right-tail extreme values within a time series. We demonstrate its applicability by investigating extreme gains and losses within the daily log-returns of the S&P 500 equity index. We find that the arrivals of extreme losses and gains are described by a common conditional intensity to which losses contribute twice as much as gains. However, the contribution of the former decays almost five times more quickly than that of the latter. We attribute these asymmetries to the different reactions of market traders to extreme upward and downward movements of asset prices: an example of negativity bias, wherein trauma is more salient than euphoria.
SSRN
We analyze whether institutional investorsâ increasingly extensive corporate bond holdings are associated with how actively institutions vote and monitor their equity investments. We find that institutions conduct more governance research and are less likely to follow proxy advisor vote recommendations for companies whose bonds represent a larger proportion of their overall portfolio. Corporate bonds held in equity-focused funds and shareholder proposals that are more likely to require investorsâ attention drive these findings. There is no evidence that creditor-shareholder conflicts explain these findings. Our results suggest that institutionsâ bond holdings contribute to their overall incentive to be engaged monitors.
SSRN
We investigate whether the index reconstitutions of the China Securities Index (CSI) are suitable as a quasi-natural experiment to investigate the effect of institutional ownership on corporate policies. Using both actual and predicted index constituents, we document a sharp discontinuity in institutional ownership, especially of domestic mutual funds around the CSI 300 and 500 index thresholds, overcoming a key concern of the approach based on the Russell reconstitution. Using inclusion in the CSI 500 index as an instrument, we find that higher institutional ownership increases the likelihood and amount of dividends, improves firm performance, and improves the information environment surrounding firms. These findings inform us of the salience of domestic institutions in emerging markets.
SSRN
Investments in international fixed income securities are exposed to significant currency risks. We document that over 90 percent of U.S. international fixed income mutual funds use currency forwards to manage their foreign exchange exposure and that their strategies differ substantially. In the cross-section, funds' use of currency forwards is largely determined by their exposure to currency risks. Over time, funds strategically vary their forward positions in response to past performance and to take advantage of carry trade, currency momentum, and risk timing strategies. Funds that hedge their currency risk exhibit lower return variability, but do not generate inferior risk-adjusted returns.
arXiv
We introduce a new deep-learning based algorithm to evaluate options in affine rough stochastic volatility models. We show that the pricing function is the solution to a curve-dependent PDE (CPDE), depending on forward curves rather than the whole path of the process, for which we develop a numerical scheme based on deep learning techniques. Numerical simulations suggest that the latter is extremely efficient, and provides a good alternative to classical Monte Carlo simulations.
SSRN
This paper explores the primary role of financial analysts in the context of unionised firms, where investors have greater information demand. Previous literature suggests that labour unions create substantial uncertainty in firms and undermine the information environment, while another strand of literature argues that analysts devote more effort to generating valuable information through original research in the case of heightened uncertainty or information asymmetry. To date, it is unclear whether financial analysts, as professional information intermediaries, are affected by organised labour. Using a large U.S. sample over the period of 1983-2015, we find that the labour unionisation rate is associated with lower forecast accuracy and higher forecast dispersion, suggesting that financial analysts predominantly play a âcomplementary roleâ rather than a âsubstitutive roleâ when firms are facing significant uncertainty in human capital. Overall, our study has important implications for managers, financial analysts and regulators, by highlighting the value and hence the necessity of non-financial information disclosure specific to a key intangible asset of firms, i.e., their employees.
SSRN
This article reviews the theory of imperfectly competitive financial markets with special attention to recent contributions and rapidly growing new areas of research. We survey the literature on advances that have led to a common analytic framework for static, dynamic, centralized, and decentralized markets. This allows us to highlight the results that arise when traders have price impact (but not in competitive markets) and, separately, those that arise with market fragmentation.
arXiv
We show that in a financial market given by semimartingales an arbitrage opportunity, provided it exists, can only be exploited through short selling. This finding provides a theoretical basis for differences in regulation for financial services providers that are allowed to go short and those without short sales. The privilege to be allowed to short sell gives access to potential arbitrage opportunities, which creates by design a bankruptcy risk.
arXiv
In this paper, the technical requirements to perform a cost-benefit analysis of a Demand Responsive Transport (DRT) service with the traffic simulation software MATSim are elaborated in order to achieve the long-term goal of assessing the introduction of a DRT service in G\"ottingen and the surrounding area. The aim was to determine if the software is suitable for a cost-benefit analysis while providing a user manual for building a basic simulation that can be extended with public transport and DRT. The main result is that the software is suitable for a cost-benefit analysis of a DRT service. In particular, the most important internal and external costs, such as usage costs of the various modes of transport and emissions, can be integrated into the simulation scenarios. Thus, the scenarios presented in this paper can be extended by data from a mobility study of G\"ottingen and its surroundings in order to achieve the long-term goal. This paper is aimed at transport economists and researchers who are not familiar with MATSim, to provide them with a guide for the first steps in working with a traffic simulation software.
SSRN
Prior literature recognizes that liquidity is essential in understanding the information content of option trades. In this paper, we model the duration and volume jointly, for the first time, as a natural measure of optionsâ trading intensity and we associate it with differential degrees of information present in option trades. We report a highly significant association between option trading intensity with contemporaneous and future underlying volatility and returns, which is distinct from the effects of option duration and option trading volume and the O/S ratio. Finally, we show that our trading intensity measure and the O/S ratio are complementary in capturing informed trading in the option market.
SSRN
We examine derivatives trading prior to takeover rumors in a sample of 1,638 publicly traded U.S. firms. The volume of options traded is abnormally high over the 5-day pre-rumor period, primarily due to the number of out-of-the-money call options traded. In addition, the direction of option trades (abnormal call volume minus abnormal put volume) prior to takeover rumors predicts forthcoming takeover announcements and rumor date returns. Identifying suspicious trades, we find evidence of individuals trading on knowledge of takeover rumor candidacy in the options market. Our results further indicate that informed traders prefer the options market to the equity market.
SSRN
In the face of lower real interest rates, central bank balance sheets are likely to remain larger relative to pre-crisis levels, resulting in greater banking system liquidity. However, there is little evidence on the impact of higher liquidity on credit supply and the monetary transmission mechanism in the ânew normalâ. We exploit a novel dataset on bank liquidity positions arising from a unique regulatory regime and combine it with a highly-detailed, loan-level administrative dataset on UK mortgages. Using the design of quantitative easing auctions as an instrument for liquidity to address endogeneity, we find that more liquid banks charge slightly higher mortgage interest rates, and pass on significantly less changes in risk-free rates. We explain this through bank behaviour that attempts to preserve net interest margins in the face of holding low-yielding liquidity. Consistent with this, we find excess liquidity leads to reaching-for-yield responses in banksâ mortgage risk-taking. Additionally, the results shed light on the optimal mix between (un)conventional monetary policy tools. Policies that boost bank net interest margins are more likely to help the transmission of risk-free rates to lending rates.
SSRN
In response to discussions about large multinational enterprisesâ tax planning activities, legislators around the world have adopted numerous regulations to increase corporate tax transparency. New settings and datasets have spurred empirical research in recent years. Our paper presents a review of this emerging literature on corporate tax transparency. To this end, we first propose a framework to structure the diverse landscape of tax-related disclosures. Second, we elaborate on the conceptual underpinnings of tax transparency by drawing on established theories from financial accounting and CSR reporting research. Third, we survey empirical evidence on corporate tax transparency. We classify the findings into (i) determinants of firmsâ tax disclosure decisions, (ii) informativeness of different kinds of tax-related disclosure, and (iii) effects of increased tax transparency on firms and their stakeholders. Finally, we synthesize the main inferences and offer suggestions for future research.
arXiv
Index insurance has been promoted as a promising solution for reducing agricultural risk compared to traditional farm-based insurance. By linking payouts to a regional factor instead of individual loss, index insurance reduces monitoring costs, and alleviates the problems of moral hazard and adverse selection. Despite its theoretical appeal, demand for index insurance has remained low in many developing countries, triggering a debate on the causes of the low uptake. Surprisingly, there has been little discussion in this debate about the experience in the United States. The US is an unique case as both farm-based and index-based products have been available for more than two decades. Furthermore, the number of insurance zones is very large, allowing interesting comparisons over space. As in developing countries, the adoption of index insurance is rather low -- less than than 5\% of insured acreage. Does this mean that we should give up on index insurance?
In this paper, we investigate the low take-up of index insurance in the US leveraging a field-level dataset for corn and soybean obtained from satellite predictions. While previous studies were based either on county aggregates or on relatively small farm-level dataset, our satellite-derived data gives us a very large number of fields (close to 1.8 million) comprised within a large number of index zones (600) observed over 20 years. To evaluate the suitability of index insurance, we run a large-scale simulation comparing the benefits of both insurance schemes using a new measure of farm-equivalent risk coverage of index insurance. We make two main contributions. First, we show that in our simulations, demand for index insurance is unexpectedly high, at about 30\% to 40\% of total demand. This result is robust to relaxing several assumptions of the model and to using prospect theory instead of expected utility.
SSRN
We reconsider the design of welfare-optimal monetary policy when financing frictions impair the supply of bank credit, and when the objectives set for monetary policy must be simple enough to be implementable and allow for effective accountability. We show that a flexible inflation targeting approach that places weight on stabilising inflation, a measure of resource utilisation, and a financial variable produces welfare benefits that are almost indistinguishable from fully-optimal Ramsey policy. The macro-financial trade-off in our estimated model of the euro area turns out to be modest, implying that the effects of financial frictions can be ameliorated at little cost in terms of inflation. A range of different financial objectives and policy preferences lead to similar conclusions.
SSRN
This paper analyses theperformance ofmaturity transformation strategiesduring a period of high and low interest rates. Based on German government bond yieldsfrom September 1972 to May 2019,we construct a rolling window of bond ladders where long-term assets are financed by short-term liabilities. Risk and return increase significantly with maturity gaps for both sample periods. During theperiod of low interest rates,dominant strategies can be observed for short-term and medium-term gaps.With respect to different financial reporting standards,weaddress maturity transformation results froman earnings-based perspective as well as froma market value-based perspective.
SSRN
Banks are not immune from COVID-19. The economic downturn may drive some banks to the point of non-viability (PONV). If so, is the resolution regime in the Euro-area ready to respond?No, for banks may not have the right amount of the right kind of liabilities to make bail-in work. That could lead to a banking crisis.The Euro area can avoid this risk, by arranging now for a recap later. This would plug the gap between what the failing bank has and what it would need to make bail-in work. To do so, banks would pay â" possibly via the contributions they make to the Single Resolution Fund â" a commitment fee to a European backstop authority for a mandatory, system-wide note issuance facility. This would compel each bank, as it reached the PONV, to issue to the backstop, and the backstop to purchase from the bank, the obligations the failing bank needs in order to make bail-in work. Such obligations would take the form of âsenior-mostâ non-preferred debt, and bail-in would stop with such debt. That would allow the SRB to use the bail-in tool to resolve the failed bank, reopen it and run it under a solvent wind down strategy. That protects counterparties and customers and ensures the continuity of critical economic functions. It also keeps investors at risk and promotes market discipline. Above all, it preserves financial stability.
SSRN
Investorâs returns are enhanced by predictive equity analytics ability to avoid drawdowns and capture gains in bull or bear markets. Predictive equity analytics enables optimal stock selection, timing and bid price with accuracy and reliability. Portfolio value behavior over time is positive and generally a non-decreasing step function. Next trade day predictive equity filtering significantly reduces left tail risk enabling positive returns with high probability. Hedging (crisis proofing) of equity portfolios is a natural artifact of predictive equity analytics with no additional cost and no additional financial instruments required. Portfolios are dynamically constructed using dynamic diversification with higher Sharpe ratios and maximal investment efficiency. Predictive equity analytics enables mean-variance return dominance.
arXiv
Life expectancy have been increasing over the past years due to better health care, feeding and conducive environment. To manage future uncertainty related to life expectancy, various insurance institutions have resolved to come up with financial instruments that are indexed-linked to the longevity of the population. These new instrument is known as longevity bonds. In this article, we present a novel classical Vasicek one factor affine model in modelling zero coupon longevity bond price (ZCLBP) with financial and mortality risk. The interest rate r(t) and the stochastic mortality of the constructed model are dependent but with uncorrelated driving noises. The model is presented in a linear state-space representation of the contiuous-time infinite horizon and used Kalman filter for its estimation. The appropriate state equation and measurement equation derived from our model is used as a method of pricing a longevity bond in a financial market. The empirical analysis results show that the unobserved instantaneous interest rate shows a mean reverting behaviour in the U.S. term structure. The zero-coupon bonds yields are used as inputs for the estimation process. The results of the analysis are gotten from the monthly observations of U.S. Treasury zero coupon bonds from December, 1992 to January, 1993. The empirical evidence indicates that to model properly the historical mortality trends at different ages, both the survival rate and the yield data are needed to achieve a satisfactory empirical fit over the zero coupon longevity bond term structure. The dynamics of the resulting model allowed us to perform simulation on the survival rates, which enables us to model longevity risk.
SSRN
Recent studies show evidence that investors learn about their trading abilities. This paper focuses on understanding how investors learn about their talent and propose a unifying framework that explains many puzzling facts about individual equity investors. In my model, the investor forms subjective beliefs both about the expected return of the current stock-in-holding and about her trading talent represented by the expected return of the next replacement stock, and updates beliefs through learning with fading memory. I calibrate the memory decay parameters to individual trading records, and show that talent learning is about 7 times more sensitive to return signals than stock-in-holding learning. Consequently, the model indicates that stock switching always happens following good performance of the current stock because switching requires a sufficiently large wedge between expected returns of the replacement stock and the current stock to cover the fixed cost, which strongly predicts disposition effect in a learning perspective. This framework also accounts for the performance-contingent trading intensity and attrition, and explains why a negative shock would lead to attrition when an investor has several years of experience, which is inconsistent with the decreasing-gain updating under standard Bayesian learning.
arXiv
Traditional statistical and measurements are unable to solve all industrial data in the right way and appropriate time. Open markets mean the customers are increased, and production must increase to provide all customer requirements. Nowadays, large data generated daily from different production processes and traditional statistical or limited measurements are not enough to handle all daily data. Improve production and quality need to analyze data and extract the important information about the process how to improve. Data mining applied successfully in the industrial processes and some algorithms such as mining association rules, and decision tree recorded high professional results in different industrial and production fields. The study applied seven algorithms to analyze production data and extract the best result and algorithm in the industry field. KNN, Tree, SVM, Random Forests, ANN, Na\"ive Bayes, and AdaBoost applied to classify data based on three attributes without neglect any variables whether this variable is numerical or categorical. The best results of accuracy and area under the curve (ROC) obtained from Decision tree and its ensemble algorithms (Random Forest and AdaBoost). Thus, a decision tree is an appropriate algorithm to handle manufacturing and production data especially this algorithm can handle numerical and categorical data.
SSRN
In 2017, âThe Big Threeâ institutional investors (BlackRock, State Street, and Vanguard) launched campaigns to increase gender diversity on corporate boards. Using difference-in-differences estimation, we find that their campaigns led firms to add at least 2.5 times as many female directors in 2019 as they had in 2016 and increased a female directorâs likelihood of holding a key position on the board, including chairperson of the nominating and audit committees. Evidence suggests that firms achieved these gains by relying less on their existing networks to identify qualified candidates and by placing less emphasis on candidatesâ executive and board experience. Our results highlight the potential for shareholder advocacy to expand womenâs participation in corporate leadership and the ability of index investors to influence firmsâ governance structures.
SSRN
This paper examines whether institutional investors' portfolio diversification strategies reveals their preferences for a constituent's corporate diversification policies. We estimate investor portfolio diversification using return characteristics of institution's 13F holdings relative to a benchmark asset pricing model and find a negative relationship between portfolio and corporate diversification. This relationship is robust to a quasi-natural experiment, and more pronounced when blockholders are fewer, managers are highly incentivized, and quasi-indexer ownership is higher. Further, diversified owners are associated with a reduced propensity of firms engaging in diversifying acquisitions and having product market similarities to rivals. Our findings illustrate how evolving ownership structures reshape the corporate landscape.
SSRN
This paper revisits Keynesâs writings from Indian Currency and Finance (1913) to The General Theory (1936) with a focus on financial instability. The analysis reveals Keynesâs astute concerns about the stability/fragility of the banking system, especially under deflationary conditions. Keynesâs writings during the Great Depression uncover insights into how the Great Depression may have informed his General Theory. Exploring the connection between the experience of the Great Depression and the theoretical framework Keynes presents in The General Theory, the assumption of a constant money stock featuring in that work is central. The analysis underscores the case that The General Theory is not a special case of the (neo-)classical theory that is relevant only to âdepression economicsâ â" refuting the interpretation offered by J. R. Hicks (1937) in his seminal paper âMr. Keynes and the Classics: A Suggested Interpretation.â As a scholar of the Great Depression and Federal Reserve chairman at the time of the modern crisis, Ben Bernanke provides an important intellectual bridge between the historical crisis of the 1930s and the modern crisis of 2007â"9. The paper concludes that, while policy practice has changed, the âclassicalâ theory Keynes attacked in 1936 remains hegemonic today. The common (mis-)interpretation of The General Theory as depression economics continues to describe the mainstreamâs failure to engage in relevant monetary economics.
arXiv
Many workers at the production department of Libyan Textile Company work with different performances. Plan of company management is paying the money according to the specific performance and quality requirements for each worker. Thus, it is important to predict the accurate evaluation of workers to extract the knowledge for management, how much money it will pay as salary and incentive. For example, if the evaluation is average, then management of the company will pay part of the salary. If the evaluation is good, then it will pay full salary, moreover, if the evaluation is excellent, then it will pay salary plus incentive percentage. Twelve variables with 121 instances for each variable collected to predict the evaluation of the process for each worker. Before starting classification, feature selection used to predict the influential variables which impact the evaluation process. Then, four algorithms of decision trees used to predict the output and extract the influential relationship between inputs and output. To make sure get the highest accuracy, ensemble algorithm (Bagging) used to deploy four algorithms of decision trees and predict the highest prediction result 99.16%. Standard errors for four algorithms were very small; this means that there is a strong relationship between inputs (7 variables) and output (Evaluation). The curve of (Receiver operating characteristics) for algorithms gave a high-level specificity and sensitivity, and Gain charts were very close to together. According to the results, management of the company should take a logic decision about the evaluation of production process and extract the important variables that impact the evaluation.
arXiv
I characterize the consumer-optimal market segmentation in competitive markets where multiple firms selling differentiated products to consumers with unit demand. This segmentation is public---in that each firm observes the same market segments---and takes a simple form: in each market segment, there is a dominant firm favored by all consumers in that segment. By segmenting the market, all but the dominant firm maximally compete to poach the consumer's business, setting price to equal marginal cost. Information, thus, is being used to amplify competition. This segmentation simultaneously generates an efficient allocation and delivers to each firm its minimax profit.