Research articles for the 2021-08-12
arXiv
Financial markets are of much interest to researchers due to their dynamic and stochastic nature. With their relations to world populations, global economies and asset valuations, understanding, identifying and forecasting trends and regimes are highly important. Attempts have been made to forecast market trends by employing machine learning methodologies, while statistical techniques have been the primary methods used in developing market regime switching models used for trading and hedging. In this paper we present a novel framework for the detection of regime switches within the US financial markets. Principal component analysis is applied for dimensionality reduction and the k-means algorithm is used as a clustering technique. Using a combination of cluster analysis and classification, we identify regimes in financial markets based on publicly available economic data. We display the efficacy of the framework by constructing and assessing the performance of two trading strategies based on detected regimes.
arXiv
Every year, natural disasters such as earthquake, flood, hurricane and etc. impose immense financial and humane losses on governments owing to their unpredictable character and arise of emergency situations and consequently the reduction of the abilities due to serious damages to infrastructures, increases demand for logistic services and supplies. First, in this study the necessity of paying attention to locating procedures in emergency situations is pointed out and an outline for the studied case of disaster relief supply chain was discussed and the problem was validated at small scale. On the other hand, to solve this kind of problems involving three objective functions and complicated time calculation, meta-heuristic methods which yield almost optimum solutions in less time are applied. The EC method and NSGA II algorithm are among the evolutionary multi-objective optimization algorithms applied in this case. In this study the aforementioned algorithm is used for solving problems at large scale.
arXiv
We present a general framework for the estimation of corporate default based on a firm's capital structure, when its assets are assumed to follow a pure jump L\'evy processes; this setup provides a natural extension to usual default metrics defined in diffusion (log-normal) models, and allows to capture extreme market events such as sudden drops in asset prices, which are closely linked to default occurrence. Within this framework, we introduce several pure jump processes featuring negative jumps only and derive practical closed formulas for equity prices, which enable us to use a moment-based algorithm to calibrate the parameters from real market data and to estimate the associated default metrics. A notable feature of these models is the redistribution of credit risk towards shorter maturity: this constitutes an interesting improvement to diffusion models, which are known to underestimate short term default probabilities. We also provide extensions to a model featuring both positive and negative jumps and discuss qualitative and quantitative features of the results. For readers convenience, practical tools for model implementation and GitHub links are also included.
arXiv
We study a continuous-time asset-allocation problem for an insurance firm that backs up liabilities from multiple non-life business lines with underwriting profits and investment income. The insurance risks are captured via a multidimensional jump-diffusion process with a multivariate compound Poisson process with dependent components, which allows to model claims that occur in different lines simultaneously. Using Lagrangian convex duality techniques, we provide a general verification-type result for investment-underwriting strategies that maximize expected utility from the dividend payout rate and final wealth over a finite-time horizon. We also study the precautionary effect on earnings retention of risk aversion, prudence, portfolio constraints and multivariate insurance risk. We find an explicit characterization of optimal strategies under CRRA preferences. Numerical results for two-dimensional examples with policy limits illustrate the impact of co-integration for ALM with multiple (dependent and independent) sources of insurance risk.
arXiv
The accumulation of individual fitness or wealth is modelled as a population game in which pairs of individuals are recurrently and randomly matched to play a game over a resource. In addition, all individuals have random access to a constant background resource, and their fitness or wealth depreciates over time. For brevity we focus on the well-known Hawk-Dove game. In the base-line model, the probability of winning a fight (that is, when both play Hawk) is the same for both parties. In an extended version, the individual with higher current fitness or wealth has a higher probability of winning. Analytical results are given for the fitness/wealth distribution at any given time, for the evolution of average fitness/wealth over time, and for the asymptotics with respect to time and population size. Long-run average fitness/wealth is non-monotonic in the value of the resource, thus providing a potential explanation of the curse of the riches.
SSRN
[enter Abstract Body]In the Indian equity market, the Systematic Investment Plan (SIP) is the most popularstrategy due to its convenience for disciplined investing regardless of market conditions. This study analyzes the excess returns of an extensive dataset of listed Indiancompanies from 2010 to 2019, along with a value-based version of the Multi-CriteriaDecision Analysis (MCDA), to identify top performing stocks, based on their sectorsand market capitalization. The findings of the study provide empirical evidence ofValue Averaging (VA) as a viable alternative strategy over SIP (also known as DollarCost Averaging or Rupee Cost Averaging) as 352 out of 359 companies yielded higherreturns under VA. The superiority of the VA strategy over the SIP was particularlymarked in the consumer goods, financial services and industrial manufacturing sectors, with a clear dominance of small cap companies. The results also show that riskfactors for VA strategy play an important role and should be taken into account, ratherthan base investment decisions on excess returns alone. The efficiency scores of individual stocks provide important insights for mutual funds, financial brokers and individual investors in India.
SSRN
Banks can take costly actions (such as higher capitalization, liquidity holding, and advanced risk management) to fend off runs. While such actions directly affect bank risks, they can also serve as signals of the banks’ fundamentals. A separating equilibrium due to such signaling, however, would involve two types of inefficiency: strong banks choose excessively costly signals, whereas weak banks are particularly vulnerable to runs. We show that minimum regulatory requirements can maintain a pooling equilibrium and eliminate the inefficiencies associated with the separation. We support this novel rationale for prudential regulations with evidence from the US liquidity requirement.
SSRN
Banks can take costly actions (such as higher capitalization, liquidity holding, and advanced risk management) to fend off runs. While such actions directly affect bank risks, they can also serve as signals of the banks’ fundamentals. A separating equilibrium due to such signaling, however, would involve two types of inefficiency: strong banks choose excessively costly signals, whereas weak banks are particularly vulnerable to runs. We show that minimum regulatory requirements can maintain a pooling equilibrium and eliminate the inefficiencies associated with the separation. We support this novel rationale for prudential regulations with evidence from the US liquidity requirement.
SSRN
Assuming that a central bank is successful in steering money market interest rates, commercial banks’ loan rate setting behaviour is not expected to change during a transition between liquidity surplus and deficit. However, this logic does not hold if the interest rates for the lending and borrowing activities of an individual bank on the money market do not coincide. In this environment, it may be appropriate to adjust the loan rates when a bank transitions between liquidity surplus and deficit (i.e. switches between the benchmark money market rates). This strategy is fundamentally different from linking the loan rates to the average cost of funding (i.e. the average between retail and wholesale funding rates). The magnitude of such loan rate adjustment is limited by the (usually moderate) spread between the funding and investment money market rates.
RePEC
We study the impact of the COVID-19 crisis on auto loan origination activity during 2020. We focus on the dynamic impact of the crisis across lending channels, Equifax Risk Score (Risk Score) segments, and relevant geographic characteristics such as urbanization rate. We measure a significant drop in auto loan originations in March‒April followed by a near rebound in May‒June. Originations remain slightly depressed until October and fall again in November‒December. We document the largest drop and the smallest rebound in the subprime segment. We do not find any suggestive evidence that used car loan originations exhibited patterns significantly different from the rest of the market. We also document a more pronounced impact in the Northeast and the Pacific, seemingly influenced by the higher urbanization rate in these regions. Bank-financed originations experienced the largest drop and the smallest rebound, thus resulting in a loss of market share and continuing a 10-year trend of bank share loss in auto lending. We find that the drop in auto loans originated by banks was particularly significant among subprime borrowers. The impact of the COVID-19 crisis across origination channels contrasts with the experience during the Great Recession when banks contributed the largest support to the auto loan origination segment during periods of stress and finance company-originated auto loans were depressed.
arXiv
We show that the Adomian decomposition method proposed by Ke et al [ANZIAM J. \textbf{59} (2018) 349] is just the Taylor series approach in disguise. The latter approach is simpler, more straightforward and yields a recurrence relation free from integrals.
SSRN
Historically, cat bonds have provided high single-digit average annual returns, paired with a low volatility and little correlation to other asset classes. While there is an extensive literature that explains (ex-ante) cat bonds spreads, there is no factor model in the academic literature that explains this (ex-post) realized return puzzle. Based on monthly quoted prices for the complete cat bond market from 2001 to 2020, we provide insights into relevant risk factors in the cross-section of cat bond returns. After investigating a battery of possible cat bond return factors in bivariate and multivariate portfolio sorts as well as Fama-MacBeth regressions, we propose a four-factor cat bond model. Its factors are the seasonality adjusted probability of first loss, a separate seasonality adjustment factor and the two corporate bond factors TERM and DEF from Fama & French. This novel four-factor model predicts 60% of the time series variation of the historical cat bond market returns - as opposed to 4% for the Fama & French three- or five-factor model - and substantially reduces the observable alpha of the cat bond market.
SSRN
Does dealership discretion to mark up interest rates hurt subprime auto borrowers? We use unique transaction-level data to examine finance and vehicle profits in the subprime auto market with three main results. First, financing subprime customers is costly for dealerships due to loan discounts that are only partially offset by proceeds from interest rate markups. Second, financing is costliest to dealers for deep subprime customers with low credit scores and low incomes. Third, instead of offsetting financing costs, vehicle markups are lowest for deep subprime customers. Finance margins and vehicle markups are also positively correlated more generally.
SSRN
In 2013, a paper by Google DeepMind kicked off an explosion in Deep Reinforcement Learning (DRL), for games. In this talk, we show that DRL can also be applied to portfolio allocation given various tricks and adaptation specific to non stationary data in finance. We present in particular how to Boost DRL.
SSRN
Diversification is a fundamental topic for all investors but there remains little agreement on how to measure it. Often it is defined ambiguously through risk-based portfolio construction techniques. Recently it has been suggested to connect maximising diversification with minimising risk instability, via kurtosis, which presents practical optimisation challenges. In particular, minimising kurtosis is a non-convex problem that is typically solved using deterministic Branch-and-Bound methods, that do not scale well, or stochastic methods that provide limited guarantees on finding minima. We thus apply a deterministic hierarchical polynomial optimization framework that allows realistic asset allocation problems to be readily solved and also provides a numerical certificate of optimality.
SSRN
The practice of quarterly interim financial reporting with mandatory monthly sales announcements in the Taiwanese stock markets is a unique setting in reporting frequency worldwide. This study compares the information content of quarterly earnings across before, bundled, and after monthly sales disclosures by examining their associations with current and future market reactions to earnings news. The study finds that earnings news after monthly sales news is associated with weaker earnings announcement (EA) returns and post-earnings announcement drift (PEAD) relative to earnings news before or bundled with monthly sales news. The phenomenon wherein information content of earnings diminished by timely monthly sales occurs predominantly for firms with double-positive news (i.e., positive earnings and monthly sales news). When a firm reports positive earnings and negative monthly sales, bundled earnings news or after-sales news is associated with higher EA returns and lower PEAD. At that time, earnings fixation results in immediate overreaction to the positive earnings news, followed by a reversal in abnormal returns. Further, the study finds that earnings news before and bundled with monthly sales news generates insignificantly different EA returns and PEAD, indicating that investor information overload contributes to the muted market reaction to the concurrent disclosure.
arXiv
Mobile phone-based sports betting has exploded in popularity in many African countries. Commentators worry that low-ability gamblers will not learn from experience, and may rely on debt to gamble. Using data on financial transactions for over 50 000 Kenyan smartphone users, we find that gamblers do learn from experience. Gamblers are less likely to bet following poor results and more likely to bet following good results. The reaction to positive and negative feedback is of equal magnitude and is consistent with a model of Bayesian updating. Using an instrumental variables strategy, we find no evidence that increased gambling leads to increased debt.
arXiv
To protect his teaching evaluations, an economics professor uses the following exam curve: if the class average falls below a known target, $m$, then all students will receive an equal number of free points so as to bring the mean up to $m$. If the average is above $m$ then there is no curve; curved grades above $100\%$ will never be truncated to $100\%$ in the gradebook. The $n$ students in the course all have Cobb-Douglas preferences over the grade-leisure plane; effort corresponds exactly to earned (uncurved) grades in a $1:1$ fashion. The elasticity of each student's utility with respect to his grade is his ability parameter, or relative preference for a high score. I find, classify, and give complete formulas for all the pure Nash equilibria of my own game, which my students have been playing for some eight semesters. The game is supermodular, featuring strategic complementarities, negative spillovers, and nonsmooth payoffs that generate non-convexities in the reaction correspondence. The $n+2$ types of equilibria are totally ordered with respect to effort and Pareto preference, and the lowest $n+1$ of these types are totally ordered in grade-leisure space. In addition to the no-curve ("try-hard") and curved interior equilibria, we have the "$k$-don't care" equilibria, whereby the $k$ lowest-ability students are no-shows. As the class size becomes infinite in the curved interior equilibrium, all students increase their leisure time by a fixed percentage, i.e., $14\%$, in response to the disincentive, which amplifies any pre-existing ability differences. All students' grades inflate by this same (endogenous) factor, say, $1.14$ times what they would have been under the correct standard.
arXiv
In this work, we explore the relationship between monetary poverty and production combining relatedness theory, graph theory, and regression analysis. We develop two measures at product level that capture short-run and long-run patterns of poverty, respectively. We use the network of related products (or product space) and both metrics to estimate the influence of the productive structure of a country in its current and future levels of poverty. We found that poverty is highly associated with poorly connected nodes in the PS, especially products based on natural resources. We perform a series of regressions with several controls (including human capital, institutions, income, and population) to show the robustness of our measures as predictors of poverty. Finally, by means of some illustrative examples, we show how our measures distinguishes between nuanced cases of countries with similar poverty and production and identify possibilities of improving their current poverty levels.
SSRN
We propose a shadow rate no-arbitrage DTSM with drifting trends to estimate the natural rate of interest. With the shadow rate reflecting overall financial market condition (Wu and Zhang (2019)), its long run forecast (in real term), dened as our natural rate, provides a useful measure against which monetary policy stance may be assessed. We apply our model to treasury yields data in the United States, the United Kingdom, and Germany for the sample from November 1972 to December 2019. We find that all three natural rates have been declining since as early as the 1990s and have all turn negative in the most recent few years. Furthermore, there is a strong co-movement among the three natural rates indicating that global factors contribute significantly to the natural rate declining dynamics, corroborating findings in Holston et al. (2017). The term premium estimates from our model are quite stationary and are significantly and positively correlated with several inflation uncertainty measures, consistent with Wright (2011).
arXiv
We study the cross-sectional returns of the firms connected by news articles. A conservative algorithm is proposed to tackle the type-I error in identifying firm tickers and the well-defined directed news networks of S&P500 stocks are formed based on a modest assumption. After controlling for many other effects, we find strong evidence for the comovement effect between news-linked firms' stock returns and reversal effect from lead stock return on 1-day ahead follower stock return, however, returns of lead stocks provide only marginal predictability on follower stock returns. Furthermore, both econometric and portfolio test reveals that network degree provides robust and significant cross-sectional predictability on monthly stock returns, and the type of linkages also matters for portfolio construction.
arXiv
We establish connections between optimal transport theory and the dynamic version of the Kyle model, including new characterizations of informed trading profits via conjugate duality and Monge-Kantorovich duality. We use these connections to extend the model to multiple assets, general distributions, and risk-averse market makers. With risk-averse market makers, liquidity is lower, assets exhibit short-term reversals, and risk premia depend on market maker inventories, which are mean reverting. We illustrate the model by showing that implied volatilities predict stock returns when there is informed trading in stocks and options and market makers are risk averse.
SSRN
This study examines the effect of peer-level analyst transitions (i.e., switching between brokerage houses) on associated regular incumbent analysts’ forecasting performance. We employ a difference-in-differences research design with analyst fixed effects and compare incumbent analysts of different groups within the same broker and same time periods. We find that incumbents who cover at least one common industry as the transiting analyst (i.e., affected incumbents) issue more accurate and timely forecasts after a transiting analyst arrives than incumbents who cover different industries (i.e., unaffected incumbents). Further, affected incumbents issue less accurate forecasts after a transiting analyst leaves than do unaffected incumbents. We also examine potential mechanisms of knowledge spillover and find some evidence that the effect is more salient when the transiting analyst switches from a larger brokerage house, has greater industry scope, or covers geographically linked firms.
SSRN
In this article, we examine the persistence in performance of Korean equity mutual funds between 1990 and 2020. South Korea is the country with the second largest number of mutual funds registered globally after the US; it has more funds domiciled than UK or Japan. The country is the world’s 12th-biggest economy, in the following five years; it is set to make the 10th-biggest contribution to global growth, more than France or Italy and approximately the same as the UK. Using a daily return sample, we show a strong existence of performance persistence in the Korean mutual fund market during the 30-year sample period included in our study. We find this result using a non-parametric methodology based on contingency tables checked by statistical tests, which show statistical significance at 1% level.
arXiv
We consider the problem of finding Pareto-optimal allocations of risk among finitely many agents. The associated individual risk measures are law invariant, but with respect to agent-dependent and potentially heterogeneous reference probability measures. Moreover, we assume that the individual risk assessments are consistent with the respective second-order stochastic dominance relations. We do not assume their convexity though. A simple sufficient condition for the existence of Pareto optima is provided. Its proof combines local comonotone improvement with a Dieudonn\'e-type argument, which also establishes a link of the optimal allocation problem to the realm of "collapse to the mean" results. Finally, we extend the results to capital requirements with multidimensional security markets.
SSRN
This paper examines sovereign wealth fund (SWF) equity investments in publicly traded firms according to a SWF’s investment purpose and home country political regime. Savings funds focus on long-term value creation; foreign exchange reserve funds focus on reducing the negative carry costs of holding reserves or earning higher returns on excess reserves. The results indicate savings funds located in an authoritarian regime are more activist, their targets experience a positive short-term market reaction but the performance of their targets over the subsequent three years varies depending on the performance metric used.
arXiv
We attempt to reconcile Gabaix and Koijen's (GK) recent Inelastic Market Hypothesis with the order-driven view of markets that emerged within the microstructure literature in the past 20 years. We review the most salient empirical facts and arguments that give credence to the idea that market price fluctuations are mostly due to order flow, whether informed or non-informed. We show that the Latent Liquidity Theory of price impact makes a precise prediction for GK's multiplier $M$, which measures by how many dollars, on average, the market value of a company goes up if one buys one dollar worth of its stocks. Our central result is that $M$ increases with the volatility of the stock and decreases with the fraction of the market cap. that is traded daily. We discuss several empirical results suggesting that the lion's share of volatility is due to trading activity.
SSRN
This chapter examines the extent to which cartel activity is morally wrongful and the resultant implications for cartel law more generally. It argues that while the focus of morality lies mainly in the question of whether cartel behaviour should be treated as crime, it is actually important to the legitimacy of all cartel enforcement because it is punitive and not regulatory in nature. It also speaks to the extent to which individuals are willing to comply with cartel law and report it to an employer or competition authority. The chapter then goes on to ask the extent to which cartels are considered morally wrongful. It is argued that as a fluid concept, what determines morally offensive cartel conduct is various pull factors, that make it more likely cartel conduct will attract moral opprobrium, and push factors that have the opposite effect. These help us identify the types of cartel conduct that are most likely to be considered morally offensive, and the potential policy tools for strengthening the moral opprobrium associated with cartel behaviour more generally.
SSRN
In January 2020, I completed a book (Taming the Megabanks: Why We Need a New Glass-Steagall Act) analyzing the financial crises that precipitated the Great Depression of the 1930s and the recent Great Recession. My book argued that the world’s financial system was caught in a “global doom loop†at the beginning of 2020. Bailouts and economic stimulus programs during and after the global financial crisis of 2007-09 (GFC) imposed heavy debt burdens on most governments, and leading central banks were carrying bloated balance sheets. The rescues arranged by governments and central banks during the GFC created a widely-shared expectation that they would continue to intervene to ensure the stability of major financial institutions and important financial markets. That expectation encouraged speculative risk-taking by financial institutions and investors as well as dangerous growth in private and public debts. I warned that the global doom loop was planting the seeds for the “next†financial crisis, which could overwhelm the already strained resources of governments and central banks.The “next†global crisis began only two months later, in March 2020. The rapid spread of the Covid-19 pandemic caused governments in most developed countries to shut down large sectors of their economies and impose social distancing mandates. Many thousands of businesses closed, setting off a downward spiral in economic activity that paralyzed global financial markets. Investors, businesses, and financial institutions “scrambled for cash†and engaged in panicked “fire sales†of financial assets. Governments and central banks in the U.S. and other advanced economies adopted fiscal stimulus measures and financial rescue programs with a size, speed, and scope that far surpassed the emergency actions taken during the GFC.The pandemic financial crisis and the extraordinary responses of governments and central banks demonstrate that policymakers have not addressed the root causes of the GFC. Major financial institutions and financial markets remain highly unstable. They continue to underwrite rapidly rising levels of private and public debts based on their shared expectation of future government bailouts. Governments and central banks have expanded their “safety nets†far beyond banks and now protect the entire financial system, including short-term wholesale credit markets, systemically important nonbanks, and the corporate bond market. As a practical matter, governments and central banks have “bankified†the financial system, thereby undermining market discipline, stimulating dangerous asset bubbles, and increasing social inequality.Our financial system must be reformed so that it no longer promotes unsustainable booms, fueled by reckless growth in private debts, followed by destructive busts that require massive bailouts and huge increases in government debts. My recent book provides a blueprint for needed reforms, including a new Glass-Steagall Act. A new Glass-Steagall Act would break up financial giants by separating banks from the capital markets and by prohibiting nonbanks from financing their operations with functional substitutes for bank deposits. A new Glass-Steagall Act would establish a financial system that is more stable, more competitive, and more responsive to the needs of consumers, communities, and business firms. Properly implemented, a new Glass-Steagall Act would provide the most direct and practical way to break the global doom loop and end the toxic boom-and-bust cycles of the past quarter century.
SSRN
In September 2008, in the midst of the broader financial crisis, the Federal Reserve Board of Governors used its emergency authority under Section 13(3) of the Federal Reserve Act to authorize the largest loan in its history, a $85 billion collateralized credit line to American International Group (AIG), a $1 trillion insurance and financial company that was experiencing severe liquidity strains. In connection with the loan, the government received an equity interest representing 79.9% of the company’s ownership. AIG continued to experience a depressed stock price, asset devaluations, and the risk of ratings downgrades leading to questions about its solvency. To stabilize the company, the government committed additional assistance, including equity investments under the Troubled Assets Relief Program and asset purchases, for a total commitment of $182.3 billion. AIG survived as a smaller entity and repaid all amounts owed to the government, which, along with the government’s sale of its AIG equity stake, resulted in a profit of $22.7 billion for the government and taxpayers (Treasury 2013, 14). In this case we discuss the government’s actions on an aggregate basis and analyze how the rescue was conceived and executed in order to better understand the unique lessons to be learned and possibly applied to future crisis events.
SSRN
The purposes of financial regulation have traditionally been related to correcting market failure and maximizing market efficiency. This approach to public policy has been challenged by an approach that focuses on maximising public value rather than solely correcting market. This article identifies that significant problems with the orthodox approach to financial regulation and sets out how the concept of public value could provide a useful conceptual framework for the design and assessment of financial regulation. The article also looks at practical examples of how the concept of public value could be applied to financial regulation.
SSRN
Using data from 43 countries for the period of 1992-2018, we show that growth opportunities explain the cross-country difference in firm value more than profitability. We measure their relative importance in the country-wide corporate valuation using the cross-sectional relation between firm value and free cashflows within the country (FCF beta). A positive FCF beta in a country means that, in the country, firm value increases with profits kept internally, whereas a negative FCF beta means that firm value increases with growth opportunities funded externally. Our finding is that, across countries, those with a more negative FCF beta have a higher valuation. This relation is sharper (absent) when both the country-wide valuation and the FCF beta are estimated with growth (mature) firms in the country, further confirming the role of growth opportunities.
