# Research articles for the 2020-06-29

SSRN

We develop a flexible approach to solve a continuous-time, multi-asset/multi-option Kyle-Back model of informed trading under very general assumptions, including on the distribution of the belief about the fundamental, and the noise process. The main insight is to postulate the pricing rule of the market maker at maturity as an optimal transport map. The optimal control of the informed trader reduces to the computation of a conjugate convex function, explicit in some cases, and otherwise easily obtainable using fast numerical algorithms. To illustrate the power of our method, we apply it to a long-standing problem: how are informed investors splitting trades between a spot asset and its options? Our method allows to i) prove the existence of an equilibrium and characterize the informed trader's trading strategy in the spot and the option markets, even for non-Gaussian price priors (e.g., lognormal); ii) show there can be cross-market price impact between the spot market and multiple options even when their noise trading is independent; and iii) compare our pricing results to a simple Black-Scholes model and quantify the price distortion of the option due to strategic trading. In particular, we show that a Black-Scholes implied volatility (IV) smile/smirk can emerge because of the market marker's adaptation to asymmetric information.

SSRN

We employ the R-vine copula approach to study the dependence structures among non-ferrous metal commodity futures on the London Metal Exchange, focusing on the comparison before and after the 2008 financial crisis. We document that the center of dependence structure among non-ferrous metal futures has changed from copper to zinc after the crisis. We find that the risk diversification benefit among non-ferrous metals diminishes after the crisis, and there is a significantly increase in their tail dependence. We further develop a R-vine copula-based method for forecasting Value-at-Risk, and the back-testing results show superior forecast accuracy over benchmark methods. Our study is useful for market participants to enhance their risk management for non-ferrous metals.

SSRN

Stochastic Local Volatility models are suitable for exotic portfolio management. Here we calibrate the Madan-Qian-Ren model enhanced with a correlation between the forex spot rate and the stochastic volatility.For the numerical resolution, we use a two-dimensional ï¬nite differences scheme with two different ADI methods (Douglas-Rachford and Hundsdorfer-Verwer), and show that the selection of correct boundary conditions is a key factor for a robust calibration.

arXiv

This paper introduces a theory of equivalent expectation measures, such as the R measure and the RT1 measure, generalizing the martingale pricing theory of Harrison and Kreps (1979) for deriving analytical solutions of expected prices - both the expected current price and the expected future price - of contingent claims. We also present new R-transforms which extend the Q-transforms of Bakshi and Madan (2000) and Duffie et al. (2000), for computing the expected prices of a variety of standard and exotic claims under a broad range of stochastic processes. Finally, as a generalization of Breeden and Litzenberger (1978), we propose a new concept of the expected future state price density which allows the estimation of the expected future prices of complex European contingent claims as well as the physical density of the underlying asset's future price, using the current prices and only the first return moment of standard European OTM call and put options.

arXiv

As Mobility as a Service (MaaS) systems become increasingly popular, travel is changing from unimodal trips to personalized services offered by a platform of mobility operators. Evaluation of MaaS platforms depends on modeling both user route decisions as well as operator service and pricing decisions. We adopt a new paradigm for traffic assignment in a MaaS network of multiple operators using the concept of stable matching to allocate costs and determine prices offered by operators corresponding to user route choices and operator service choices without resorting to nonconvex bilevel programming formulations. Unlike our prior work, the proposed model allows travelers to make multimodal, multi-operator trips, resulting in stable cost allocations between competing network operators to provide MaaS for users. An algorithm is proposed to efficiently generate stability conditions for the stable outcome model. Extensive computational experiments demonstrate the use of the model to handling pricing responses of MaaS operators in technological and capacity changes, government acquisition, consolidation, and firm entry, using the classic Sioux Falls network. The proposed algorithm replicates the same stability conditions as explicit path enumeration while taking only 17 seconds compared to explicit path enumeration timing out over 2 hours.

arXiv

I study labor markets in which firms can hire via job referrals. Despite full equality in the initial time period (e.g., equal ability, employment, wages, and network structure), unequal wages and employment still emerge over time between majority and minority workers, due to homophily---the well-documented tendency for people to associate more with others similar to themselves. This inequality can be mitigated by minority workers having more social ties or a "stronger-knit" network. Hence, this paper uncovers a direct mechanism for discriminatory outcomes that neither relies on past inequality nor on discriminatory motives (i.e., neither of the prevailing economic models of taste-based and statistical discrimination). These findings introduce multiple policy implications, including disproving a primary justification for "colorblind" policies---namely disproving the position that such policies are inherently merit-enhancing.

SSRN

We investigate the effect of analyst distance in the credit rating industry and show that issuers with analysts located in more distant offices have lower default rates than issuers with closer analysts and the same rating. Our results are robust to an analyst home bias and suggest that more distant analysts are subject to a local informational disadvantage when conducting their rating analysis. Given an asymmetric reputational cost function that implies penalizing an overestimation of credit quality more heavily than an underestimation, we can demonstrate that it is rational for analysts to assign more conservative ratings for higher levels of information uncertainty.

arXiv

In a discrete-time setting, we study arbitrage concepts in the presence of convex trading constraints. We show that solvability of portfolio optimization problems is equivalent to absence of arbitrage of the first kind, a condition weaker than classical absence of arbitrage opportunities. We center our analysis on this characterization of market viability and derive versions of the fundamental theorems of asset pricing based on portfolio optimization arguments. By considering specifically a discrete-time setup, we simplify existing results and proofs that rely on semimartingale theory, thus allowing for a clear understanding of the foundational economic concepts involved. We exemplify these concepts, as well as some unexpected situations, in the context of one-period factor models with arbitrage opportunities under borrowing constraints.

SSRN

The underlying transparency of the Bitcoin blockchain allows transactions in the network to be tracked in near real-time. When someone transfers a large number of Bitcoins, the market receives this information and traders can adjust their expectations based on the new information. This paper investigates trading volume and its relation to asymmetric information around transfers on the Bitcoin blockchain. We collect data on 2132 large transactions on the Bitcoin blockchain between September 2018 and November 2019, where 500 or more Bitcoins were transferred. Using event study methodology, we identify significant positive abnormal trading volume for the 15-minute window before a large Bitcoin transaction as well as during and after the event. Using public information about Bitcoin addresses of cryptocurrency exchanges as proxies for information asymmetry, we find that transactions with high levels of information asymmetry negatively affect abnormal trading volume once the event becomes public knowledge, while some effects are even opposite for transactions with lower information asymmetry. The results show that blockchain transaction activity is a relevant aspect of Bitcoinâ€˜s microstructure, as informed traders make use of the information in general and adjust their expectations based on the degree of information asymmetry.

SSRN

We show that the class of linear-rational square-root (LRSQ) model is able to match the cross section of yields and the time variability of conditional yield volatility simultaneously. Models in this class are, in this regard, able to break the tension noted for the affine term structure models from matching the conditional first and second moments of yields. Using a panel data set of US Treasury yields and realized yield volatilities, we evaluate the performance of various LRSQ model specifications based on in-sample and out-of-sample exercises and find that the preferred specification relies on three unspanned stochastic volatility factors, which, correlate strongly withthe level and slope factor of conditional yield volatility.

SSRN

This paper shows that securities with a non-linear payoff design can foster household risk-taking. We demonstrate this effect empirically by exploiting the introduction of capital guarantee products in Sweden from 2002 to 2007. The fast and broad adoption of these products is associated with an increase in expected financial portfolio returns, which is especially strong for households with a low risk appetite ex ante. We explore possible economic explanations by developing a life-cycle model of consumption-portfolio decisions. The capital guarantee substantially increases risk-taking by households with pessimistic beliefs or preferences combining loss aversion and narrow framing. The welfare gains from financial innovation are stronger for households that are less willing to take risk ex ante. Our results illustrate how security design can mitigate behavioral biases and enhance economic well-being.

SSRN

A particularly important issue in retirement income provision is longevity risk. There are two components to longevity risk. The first is the uncertainty over how long any particular pension scheme member is going to live after retirement. This is known as idiosyncratic longevity risk. Both individuals and schemes face idiosyncratic longevity risk. The second is uncertainty over how long members of a particular age cohort are going to live after retirement. This is known as systematic longevity risk. Only schemes face systematic longevity risk. Individuals have a poor understanding of idiosyncratic longevity risk.832 Pension schemes can reduce idiosyncratic longevity risk by pooling the risk amongst a large number of scheme members, i.e., by taking advantage of the law of large numbers. Systematic longevity risk, however, cannot be reduced in this way: it needs to be hedged using a suitable hedging instrument.

arXiv

I analyze Osaka factory worker households in the early 1920s, whether idiosyncratic income shocks were shared efficiently, and which consumption categories were robust to shocks. While the null hypothesis of full risk-sharing of total expenditures was rejected, factory workers maintained their households, in that they paid for essential expenditures (rent, utilities, and commutation) during economic hardship. Additionally, children's education expenditures were possibly robust to idiosyncratic income shocks. The results suggest that temporary income is statistically significantly increased if disposable income drops due to idiosyncratic shocks. Historical documents suggest microfinancial lending and saving institutions helped mitigate risk-based vulnerabilities.

SSRN

Analyzing unique data on loan applications by individuals who are majority owners of small firms, we detail how a bankâ€™s credit decisions affect their future income. We use the bankâ€™s cutoff rule, which is based on the applicantsâ€™ credit scores, as the discontinuous locus providing exogenous variation in the decision to grant loans. We show that application acceptance increases recipientsâ€™ income five years later by more than 10 percent compared to denied applicants. This effect is mostly driven by the use of borrowed funds to undertake investments, and is stronger when individuals are more credit-constrained.

SSRN

This paper studies whether the choice of the crisis start dates affects the magnitude of contagion estimates. Contagion models generally use exogenously determined crisis start date by relying on event-based markers. We conduct structural break tests and endogenously determine the start dates of the global financial crisis for markets in three regions. We then estimate models with regime switching that incorporates these start dates to test for contagion. We present evidence in favour of contagion through correlation and coskewness. Finally, we evaluate whether there are differences in estimates based on contagion models with exogenously or endogenously determined crisis start dates. We find that there are substantial differences in estimates and that the estimation error in correlation is trivial, but enormous for coskewness. We show that properly identifying the crisis start date through econometric tests is crucial for avoiding potential bias from sample selection and estimation errors induced by this bias.

SSRN

This paper investigates the effect of COVID-19 pandemic on stock market in KSA applying an Autoregressive Distributed Lag (ARDL) cointegration approach. More especially, we analyze the relationship between the natural logarithm of trading volume of Tadawull All shares index (TASI) and the natural logarithm of daily COVID-19 confirmed cases both in the short-run and the long-run. The bounds test for cointegration is carried out for daily series over the period from March 02, 2020 till May 20, 2020.Toda-Yamamoto causality test is implemented between variables. Our findings indicate that there is a negative impact of COVID-19 on stock market only in the long-run. Causality test reveals a unidirectional causality from COVID-19 prevalenceâ€™s measure to stock market. Robustness check seems to be conclusive.

SSRN

We find evidence that investors categorize stocks into a new investment style based on the theme of disruption. We identify disruption style stocks by their extreme return sensitivity to Bitcoin returns during the 2010 to 2019 period. These stocks experience temporary over-valuation and subsequent return reversal that exceeds âˆ'1% per month. Additional tests indicate that this trading habitat is dominated by retail clientele. Our evidence suggests that investors evaluate these stocks in a way that is consistent with the probability weighting features of prospect theory.

SSRN

This paper analyzes stock returns during the two-candidate race prior to the 2016 US presidential election. We investigate whether excess returns of different industries reflect changes in the actual probability of Donald Trump's victory. To do so, we develop a measure based on opinion polls that serves as a signal and analyze its impact in a GARCH-M model. We find that industries corresponding to about 30% of the S&P Composite 1500 index (S&P 1500) market capitalization are significantly affected with an absolute average impact on daily returns of 37 basis points. For industries corresponding to 19% of the S&P 1500 market capitalization, the effect is negative with an impact of âˆ'33 basis points on average. The signs of return changes are consistent with post-election stock price movements and can be aligned with Trump's economic positions announced during the election campaign.

SSRN

We examine whether high CEO pay inequality, measured by the share of total managerial pay captured by the CEO (CEO pay slice or CPS), is an outcome of poor corporate governance, and its implications for shareholder wealth. We exploit the 2002 NYSE and NASDAQ governance reforms that mandated firms to have majority independent boards as a quasi-exogenous source of variation in the internal governance environment of firms. Results show that CPS decreases following the passage of these exchange listing regulations, for firms with entrenched CEOs affected by the exchange listing regulations. Firm value also increases for firms that likely suffer from agency conflicts in the pre-regulation period. Overall, our results suggest that poor governance environments are associated with high CPS and consequently lower firm valuations, supporting the view that high CEO pay inequality reflects managerial entrenchment.

SSRN

By exploiting the worldâ€™s largest E-Commerce shopping holiday, Chinaâ€™s Singles Day, we study how E-Commerce affects spending at offline retailers. Consumerâ€™s credit and debit card spending at the brick-and-mortar stores increases by an average 10.6% on the Singles Day during the period of 2013-2017. The increase is concentrated in physical retail goods, with no change in spending on dining, entertainment and travel. The response is prevalent across years and among consumers with different demographics and preferences. Gauging the source of online-offline complementarity, we show a stronger (and more persistent) spending increase on the shopping-experience-dependent products. Despite large(r) price promotions offered online, the offline spending (via bank cards) on the Singles Day amounts to over 60% of Alibabaâ€™s same-day online sales in our sample period.

SSRN

We show that, when forming expectations about aggregate inflation, consumers rely on the prices of goods in their personal grocery bundles. Our analysis uses novel representative micro data that uniquely match individual expectations, detailed information about consumption bundles, and item-level prices. The data also reveal that the weights consumers assign to price changes depend on the frequency of purchase, rather than expenditure share, and that positive price changes loom larger than similar-sized negative price changes. Prices of goods offered in the same store but not purchased (any more) do not affect inflation expectations, nor do other dimensions such as the volatility of price changes. Our results provide empirical guidance for models of expectations formation with heterogeneous consumers.

SSRN

This paper identifies shocks to credit conditions based on aggregate firmsâ€™ debt composition. I develop a model where firms fund production with bonds and loans. Only financial shocks imply opposite movements in the two types of debt as firms adjust their debt composition to new credit conditions. I use this result to inform a signâ€'restriction VAR and identify the sources of US business cycles. Financial shocks account for a third of output fluctuations. I construct an index of financial stress to test the identification strategy.

SSRN

This paper studies the adoption of automated mortgage underwriting technology during the 1990s, and measures its effect on leverage and house prices. I document that Freddie Macâ€™s underwriting system, Loan Prospector, applied a proprietary set of underwriting rules, which were different from Freddieâ€™s manual guidelines and allowed lenders to approve loans with high debt-to-income ratios. I obtain a list of lenders who were using Loan Prospector shortly after its release in 1995, and use geographic variation in the market share of these lenders to study the effect on house prices. I show that more exposed counties experienced substantial relative growth in house prices starting in 1995. To address identification challenges, I also construct an analogous measure of exposure to early adopters of Fannie Maeâ€™s system, Desktop Underwriter. While Desktop Underwriter offered similar benefits in terms of processing efficiency, it did not initially incorporate any new lending rules. Based on my estimates, I argue that gradual adoption of the GSEsâ€™ systems can explain a large share of U.S. house price growth during the late 90s.

SSRN

This paper studies the implication of persistent private information on a firmâ€™s optimal financing and investment policies. In a dynamic agency model, an investor supplies capital to an entrepreneur with an opaque production technology. The investor observes neither the true productivity of the technology nor the actual amount of the output produced. The entrepreneur can generate private benefit from misreporting productivity and diverting output, both of which bear a persistent negative effect on the long-term growth of the technology. Two special cases are considered: one in which the entrepreneur is risk-neutral with a liquidity constraint, and one in which the entrepreneur is risk-averse with CARA utility. For the investor, the model predicts both under- and over-investment as well as non- monotonic financing policies under the optimal contract. The model also generates rich dynamics regarding the investment-q sensitivity and investment-cash-flow sensitivity consistent with empirical observations.

SSRN

The government-sponsored Five-Star Quality Rating System (FSQRS) aggregates multiple measures of nursing home quality into a standardized overall rating. Previous research has found that the FSQRS affected consumer demand and correspondingly motivated a strategic shift towards competing for higher ratings, most notably among nursing homes in more competitive markets. The primary objective of this paper is to provide evidence on whether it produced a complementary change in the weight placed on quality ratings in senior management retention decisions. Using the Florida nursing home administrator files from 2007 to 2013, our analysis reveals that the FSQRS motivated a substantial and significant increase in the sensitivity of administrator turnover to star ratings, particularly in more competitive nursing home markets.

SSRN

We use data across European corporate boards to investigate the effects of quota-induced female representation, under minimal possible identification assumptions. We find that having more women in board causally increases Tobin's Q, despite some negative effects on operating performance and more likely employment downsizings. We interpret this evidence as firms scaling down inefficient operations. Our results highlight that gender quotas are not necessarily a costly way of promoting equality.

SSRN

Expectations about economic variables vary systematically across genders. In the domain of inflation, women have systematically higher expectations than men. We argue that traditional gender roles are a significant factor in generating this gender expectations gap as they expose women and men to different economic signals in their daily lives. Using unique data on the participation of men and women in

SSRN

We reconcile the empirically flat relation between historical betas and stock returns (flat security market line) with the common usage of the CAPM based on historical betas in valuation. Analysts bias cash flow growth expectations upwards for high-beta firms, so that the value-reducing effect of higher historical systematic risk cancels out and buy/sell-recommendations remain unrelated to beta. The association between beta and growth overestimation is driven by estimates conventionally used in the industry (e.g., Bloomberg betas), suggesting that analysts adjust growth expectations to offset beta's valuation effects, instead of exhibiting a coincidental overoptimism for high-beta firms.

SSRN

Although merger and acquisitions (M&As) are acknowledged as an important means to access innovative assets and know-how, firmsâ€™ inventive output often declines in the post-M&A period. Financial, managerial and organizational constraints related to the M&A event contribute to inventive output declines and inventorsâ€™ departure. Prior literature treats the acquiring firm as a passive observer of invention declines. This study argues that acquiring firms can take measures by hiring new key inventors. We show that the hiring of new key inventors in the post-M&A period can counteract invention declines in two ways. First, these newly hired inventors are associated with an increase of corporate inventive output after the M&A. Second, they are also associated with an improved inventive output of inventors already working for the acquiring firm. These results suggest that an appropriate hiring policy can counteract declining inventive output of firms in the aftermath of M&As.

arXiv

Automated market makers, first popularized by Hanson's logarithmic market scoring rule (or LMSR) for prediction markets, have become important building blocks, called 'primitives,' for decentralized finance. A particularly useful primitive is the ability to measure the price of an asset, a problem often known as the pricing oracle problem. In this paper, we focus on the analysis of a very large class of automated market makers, called constant function market makers (or CFMMs) which includes existing popular market makers such as Uniswap, Balancer, and Curve, whose yearly transaction volume totals to billions of dollars. We give sufficient conditions such that, under fairly general assumptions, agents who interact with these constant function market makers are incentivized to correctly report the price of an asset and that they can do so in a computationally efficient way. We also derive several other useful properties that were previously not known. These include lower bounds on the total value of assets held by CFMMs and lower bounds guaranteeing that no agent can, by any set of trades, drain the reserves of assets held by a given CFMM.

SSRN

There is ever-increasing investor interest in corporate social responsibility (CSR) generally and environmental social governance (ESG) in particular. Investorsâ€™ desires have triggered increased corporate ESG disclosures. As pressure for ESG-related disclosures continues to rise, there is increasing pressure on the SEC to support enhanced ESG disclosures.Notwithstanding many calls for mandatory ESG disclosures, the SEC has not implemented such a requirement. Instead ESG disclosures are voluntary. Voluntary ESG disclosures are common but to a large extent are marred by a lack of standardization in ESG data methodology. The increasing investor interest in ESG have led publicly held companies to take various approaches in framing their ESG disclosures. Many observers have asked the SEC to take a more active role with respect to ESG disclosures. Some observers call for mandatory ESG disclosures. To date, the SECâ€™s approach has been limited to providing guidance for companies electing to make ESG disclosures. This article analyzes the various ways in which the SEC could mandate or encourage better ESG disclosures. The article concludes that regardless of whether the SEC imposes mandatory disclosures or continues its voluntary approach, the SEC should a adopt a safe harbor rule. A safe harbor rule would encourage ESG disclosures while at the same time limiting but not eliminating the risk of liability for defective ESG-related disclosures.The article begins with a description of the current state of ESG disclosures. This is followed by a brief overview of the securities lawsâ€™ disclosure obligations. The article then explains materiality â€" a concept that is the lynchpin of the securities lawsâ€™ disclosure requirements. This is followed by exploration of the potential ways to enhance CSR and ESG disclosures including the advisability of mandating disclosure or taking additional steps to encourage voluntary disclosure. Specifically, the article suggests that a safe harbor rule would be an important step in improving ESG disclosures.

arXiv

With the aggravation of the global economic crisis and inflation, the precious metals with safe-haven function have become more popular. An improved MF-DFA method is proposed to analyze price fluctuations of the precious metals market. Based on the widely used multifractal detrended fluctuation analysis method (MF-DFA), we compare these two methods and find that the Bi-OSW-MF-DFA method possesses better efficiency. This article analyzes the degree of multifractality between spot gold market and spot silver market as well as their risks. From the numerical results and figures, it is found that two elements constitute the contributions in the formation of multifractality in time series and the risk of the spot silver market is higher than that of the spot gold market. This attempt could lead to a better understanding of complicated precious metals market.

SSRN

Motivated by the introduction of share repurchases regulations in 1998 and 2007 coupled with unique characteristics of the Indonesian market, we investigate the effect of firmsâ€™ sub-optimal financial position on their share repurchases decisions. Then, we study the effect of these determinants through an exogenous shock, the 2007 regulatory change. We show that sub-optimal financial positions play a role in the corporate share repurchases decisions. Further, we find that the enactment of the regulations has a significant effect on firmsâ€™ undertaking share repurchases programs. Unlike the common perception and findings in the literature, we observe that the underpricing of shares has a weak effect on the Indonesian firmsâ€™ decisions to repurchase their stocks. Our results hold using several estimation methods that account for potential endogeneity issues.

SSRN

We study the rise and risks in bank issuance of Wealth Management Products (WMPs), which

SSRN

This paper investigates, theoretically and empirically, the impact of corporate hedging activities on firm value/performance. In a perfect market, with self-less management, aiming to maximise shareholder wealth, it may be expected that hedging would improve firm performance and add value. Our major contribution in this paper is that we first demonstrate theoretically the conditions under which hedging can increase or decrease firm value. Our theoretic model demonstrates that the ambiguous relationship between hedging and firm value may be due to a subtle combination of economic (managerial self-interest, agency problems/moral hazard, managerial ability, managerial risk aversion) and behavioural factors (overconfidence). Our empirical analysis confirms the ambiguous effect of hedging on firm performance. Empirically, we focus on the use of derivatives in the corporate hedging of three types of financial risk (foreign currency, interest rate and commodity price risks), and examine the effect on value and performance of listed UK corporations during 2005-2017. We demonstrate that the positive or negative effects of the hedging strategies varies significantly across both the financial risk that is hedged and the type of derivatives contracts used in the hedging as well as the time period in consideration.

arXiv

We introduce stochastic volatility models, in which the volatility is described by a time-dependent nonnegative function of a reflecting diffusion. The idea to use reflecting diffusions as building blocks of the volatility came into being because of a certain volatility misspecification in the classical Stein and Stein model. A version of this model that uses the reflecting Ornstein-Uhlenbeck process as the volatility process is a special example of a stochastic volatility model with reflection. The main results obtained in the present paper are sample path and small-noise large deviation principles for the log-price process in a stochastic volatility model with reflection under rather mild restrictions. We use these results to study the asymptotic behavior of binary barrier options and call prices in the small-noise regime.

SSRN

Liquidity creation (the transformation of liquid liabilities into illiquid assets) is a key function of banks. We show that liquidity creation is positively associated with economic growth at both country and industry levels. In particular, liquidity creation helps growth by boosting tangible, but not intangible investment. Our results suggest an important non-linearity; liquidity creation does not contribute to growth in countries with a higher share of industries relying on intangible assets. We rationalize these results using a model in which banks increase aggregate investment by reducing liquidity risk, but low asset tangibility hampers liquidity creation by exacerbating moral hazard problems. Together, these findings provide new insights into the functions of banks, but also highlight their more limited role in supporting innovative industries.

SSRN

This paper studies the MAX effect, the relationship between maximum daily returns and future returns in the cryptocurrency market. The cryptocurrency market is an ideal setting for the MAX effect, due to its lottery-like features (i.e., large positive skewness). Contrary to findings in other markets, we demonstrate that cryptocurrencies with higher maximum daily returns tend to achieve higher returns in the future and call this the â€œMAX momentumâ€ effect. We also find that the magnitude of the MAX momentum varies with market conditions, investor sentiment, and trading months and is more pronounced in underpriced cryptocurrencies. Additionally, this effect is robust to longer holding periods, different MAX measures, and the exclusion of small cryptocurrencies.

SSRN

Many people can now see that the EU project has lost touch with the normal arrangements that govern successful western economies. But less obvious is that the EUâ€™s financial system and its legal underpinnings are weak. As this analysis shows, EU law sidesteps the Basel standards â€" the international rules which protect the financial system from systemic risk. But, whereas the UK has until now helped to manage the risk by applying its own controls to the business it regulates, after Brexit much will depend on whose laws govern trade.Managing Euro Risk explains how the problem has arisen. Legally, the Eurozone has circumvented the Basel rules. Eurozone states can raise funds on the debt markets, behaving as sovereign, but in fact are â€˜sub sovereignâ€™ â€' and without the currency being backed by a single sovereign. The EUâ€™s supra-national bodies, its central bank (the ECB) and investment bank (the EIB) operate under the same misassumptions. The problems have been exacerbated by an absence of transparent accounting practices. The upshot is that the Eurozoneâ€™s financial sector today is under-capitalised, under-collateralised and less liquid than it should be.The authors, Barnabas Reynolds, a UK and international financial services lawyer, David Blake, an academic economist and Robert Lyddon, a bank accounting and financial analyst, warn that the potential for systemic risk spreading to the UK or globally is grave, endangering businesses, savers and investors - a danger likely to become acute after Brexit.The authors explain how the risk can be managed and contagion contained. They propose that the EU should be obliged to apply the Basel and accounting standards properly, with Eurozone member states adopting joint-and-several liability for each other's debts. Above all, the UK should insist that future financial services trade with the bloc will be on an Enhanced Equivalence basis, with UK trade governed by UK law. If the EU refuses, the UK and US, the regulators of the global financial market, must take whatever steps are needed to prevent systemic risk.

arXiv

We propose a data-driven Neural Network (NN) optimization framework to determine the optimal multi-period dynamic asset allocation strategy for outperforming a general stochastic target. We formulate the problem as an optimal stochastic control with an asymmetric, distribution shaping, objective function. The proposed framework is illustrated with the asset allocation problem in the accumulation phase of a defined contribution pension plan, with the goal of achieving a higher terminal wealth than a stochastic benchmark. We demonstrate that the data-driven approach is capable of learning an adaptive asset allocation strategy directly from historical market returns, without assuming any parametric model of the financial market dynamics. Following the optimal adaptive strategy, investors can make allocation decisions simply depending on the current state of the portfolio. The optimal adaptive strategy outperforms the benchmark constant proportion strategy, achieving a higher terminal wealth with a 90% probability, a 46% higher median terminal wealth, and a significantly more right-skewed terminal wealth distribution. We further demonstrate the robustness of the optimal adaptive strategy by testing the performance of the strategy on bootstrap resampled market data, which has different distributions compared to the training data.

SSRN

We propose a data-driven Neural Network (NN) optimization framework to determine the optimal multi-period dynamic asset allocation strategy for outperforming a general stochastic target. We formulate the problem as an optimal stochastic control with an asymmetric, distribution shaping, objective function. The proposed framework is illustrated with the asset allocation problem in the accumulation phase of a defined contribution pension plan, with the goal of achieving a higher terminal wealth than a stochastic benchmark. We demonstrate that the data-driven approach is capable of learning an adaptive asset allocation strategy directly from historical market returns, without assuming any parametric model of the financial market dynamics. Following the optimal adaptive strategy, investors can make allocation decisions simply depending on the current state of the portfolio. The optimal adaptive strategy outperforms the benchmark constant proportion strategy, achieving a higher terminal wealth with a 90% probability, a 46% higher median terminal wealth, and a significantly more right-skewed terminal wealth distribution. We further demonstrate the robustness of the optimal adaptive strategy by testing the performance of the strategy on bootstrap resampled market data, which has different distributions compared to the training data.

arXiv

We consider an auction market in which market makers fill the order book during a given time period while some other investors send market orders. We define the clearing price of the auction as the price maximizing the exchanged volume at the clearing time according to the supply and demand of each market participants. Then we derive in a semi-explicit form the error made between this clearing price and the efficient price as a function of the auction duration. We study the impact of the behavior of market takers on this error. To do so we consider the case of naive market takers and that of rational market takers playing a Nash equilibrium to minimize their transaction costs. We compute the optimal duration of the auctions for 77 stocks traded on Euronext and compare the quality of price formation process under this optimal value to the case of a continuous limit order book. Continuous limit order books are found to be usually sub-optimal. However, in term of our metric, they only moderately impair the quality of price formation process. Order of magnitude of optimal auction durations is from 2 to 10 minutes.

arXiv

Each year since 2018, more than 10,000 UK firms have been required to publicly disclose their gender pay gap and gender composition. This paper studies how this transparency policy affects the occupational outcomes and wages of male and female workers. Theoretically, pay transparency represents an information shock that alters the bargaining power of male and female employees vis-\`a-vis the firm in an asymmetric way. As women are currently underpaid, this shock may improve women's relative outcomes. We test these theoretical predictions using a difference-in-difference strategy that exploits the variation in the UK mandate across firm size and time. Our results show that pay transparency increases the probability that women are hired in above-median-wage occupations by 5 percent compared to the pre-policy mean. Additionally, it leads to a 2.8 percent decrease in male real hourly pay in treated firms compared to control ones. Combining the difference-in-difference strategy with a text analysis of job listings, we also find suggestive evidence that treated firms in industries with a high gender pay gap become more likely to post wage information than firms in the control group.

SSRN

In this paper, we document the importance of memory in machine learning (ML)-based models relying on firm characteristics for asset pricing. We come to three empirical conclusions. First, the pure out-of-sample fit of the models is often poor: we find that most R^2 measures are negative, especially when training samples are short. Second, we show that poor fit does not necessarily matter from an investment standpoint: what actually counts are measures of cross-sectional accuracy, which are seldom reported in the literature. Third, memory is key. The accuracy of models is maximal when both labels and features are highly autocorrelated. Relatedly, we show that investments are the most profitable when they are based on models driven by strong persistence. Average realized returns are the highest when the size of training samples is large and when the horizon of the predicted variable is also long.

SSRN

Suppose an economy within which rational expectations equilibriums (REE) are predicated on the distribution of ability, and the extent to which economic agents are doubtful (`doubtfulness') as to true realizations of their ability. Let a `societal REE' denote an REE that, simultaneously constitutes a dominant equilibrium for each of individual economic agents, and society. This study provides formal theoretical evidence that cumulative layering of each of risk preferences (risk aversion or risk seeking) and heterogeneity as to altruism on economic agents does not induce any alterations to societal REE that are predicated on ability and doubtfulness. Layering of heterogeneity with respect to preference for a (professional) Technocracy on all of the preceding factors induces a societal REE that Pareto Dominates all preceding REE. Suppose technocrats that are appointees of politicians (`political technocrats') coexist with professional technocrats and do not practice `power grabbing', that is, arrive at policy decisions on basis of scientific, as opposed to political merits of alternate courses for action. In presence of stated coexistence, there is arrival at a societal REE, which Pareto Dominates the societal REE that is induced by presence only of professional technocrats. In this respect, presence of political technocrats who act on scientific merits induces unilateral increase to incomes of professional technocrats. In the societal REE in context of which political technocrats practice power grabbing, resources of society are sub-optimally directed away from efforts at generation and implementation of innovations. There is arrival then at an economy that revolves around government. Consistent with sub-optimality of a `power grabbing' economy, while government consists of three-tenths of the workforce in context of political technocrats who act on scientific merits, introduction of power grabbing induces allocation of five-sixths of the workforce to the government sector.

arXiv

When estimating the risk of a financial position with empirical data or Monte Carlo simulations via a tail-dependent law invariant risk measure such as the Conditional Value-at-Risk (CVaR), it is important to ensure the robustness of the statistical estimator particularly when the data contain noise. Kratscher et al. [1] propose a new framework to examine the qualitative robustness of estimators for tail-dependent law invariant risk measures on Orlicz spaces, which is a step further from earlier work for studying the robustness of risk measurement procedures by Cont et al. [2]. In this paper, we follow the stream of research to propose a quantitative approach for verifying the statistical robustness of tail-dependent law invariant risk measures. A distinct feature of our approach is that we use the Fortet-Mourier metric to quantify the variation of the true underlying probability measure in the analysis of the discrepancy between the laws of the plug-in estimators of law invariant risk measure based on the true data and perturbed data, which enables us to derive an explicit error bound for the discrepancy when the risk functional is Lipschitz continuous with respect to a class of admissible laws. Moreover, the newly introduced notion of Lipschitz continuity allows us to examine the degree of robustness for tail-dependent risk measures. Finally, we apply our quantitative approach to some well-known risk measures to illustrate our theory.

arXiv

In the knowledge that the ex-post performance of Markowitz efficient portfolios is inferior to that implied ex-ante, we make two contributions to the portfolio selection literature. Firstly, we propose a methodology to identify the region of risk-expected return space where ex-post performance matches ex-ante estimates. Secondly, we extend ex-post efficient set mathematics to overcome the biases in the estimation of the ex-ante efficient frontier. A density forecasting approach is used to measure the accuracy of ex-ante estimates using the Berkowitz statistic, we develop this statistic to increase its sensitivity to changes in the data generating process. The area of risk-expected return space where the density forecasts are accurate, where ex-post performance matches ex-ante estimates, is termed the consistency region. Under the 'laboratory' conditions of a simulated multivariate normal data set, we compute the consistency region and the estimated ex-post frontier. Over different sample sizes used for estimation, the behaviour of the consistency region is shown to be both intuitively reasonable and to enclose the estimated ex-post frontier. Using actual data from the constituents of the US Dow Jones 30 index, we show that the size of the consistency region is time dependent and, in volatile conditions, may disappear. Using our development of the Berkowitz statistic, we demonstrate the superior performance of an investment strategy based on consistent rather than efficient portfolios.

arXiv

We study the real-time signals provided by the Aruoba-Diebold-Scotti Index of Business conditions (ADS) for tracking economic activity at high frequency. We start with exit from the Great Recession, comparing the evolution of real-time vintage beliefs to a "final" late-vintage chronology. We then consider entry into the Pandemic Recession, again tracking the evolution of real-time vintage beliefs. ADS swings widely as its underlying economic indicators swing widely, but the emerging ADS path as of this writing (late June) indicates a return to growth in May. The trajectory of the nascent recovery, however, is highly uncertain -- particularly as COVID-19 spreads in the South and West -- and could be revised or eliminated as new data arrive.

arXiv

This paper analyzes the market behavior and optimal investment strategies to attain relative arbitrage both in the $N$ investors and mean field regimes. An investor competes with a benchmark of market and peer investors, expecting to outperform the benchmark and minimizing the %proportion of initial capital.

With market price of risk processes depending on the stock market and investors respectively, the minimal initial capital required is the optimal cost in the $N$-player games and mean field games. It can be characterized as the smallest nonnegative continuous solution of a Cauchy problem. The measure flow of wealth appears in the cost, while the joint flow of wealth and strategy is in state processes. We modify the extended mean field game with common noise and its notion of the uniqueness of Nash equilibrium. There is a unique equilibrium in $N$-player games and mean field games with mild conditions on the equity market.

arXiv

This paper presents a novel framework for valuation and hedging of the insurer's net liability on a Guaranteed Minimum Maturity Benefit (GMMB) embedded in variable annuity (VA) contracts whose underlying mutual fund dynamics evolve under the influence of the regime-switching model. Numerical solutions for valuations and Greeks (i.e. valuation sensitivities with respect to model parameters) of GMMB under stochastic mortality are derived. Valuation and hedging is performed using an accurate, fast and efficient Fourier Space Time-stepping (FST) algorithm. The mortality component of the model is calibrated to the American male population. Sensitivity analysis is performed with respect to various parameters. The hedge effectiveness is assessed by comparing profit-and-loss performances for an unhedged and three statically hedged portfolios. The results provide a comprehensive analysis on valuation and hedging the longevity risk, interest rate risk and equity risk for the GMMB embedded in VAs, and highlight the benefits to insurance providers who offer those products.

arXiv

Recursive marginal quantization (RMQ) allows the construction of optimal discrete grids for approximating solutions to stochastic differential equations in d-dimensions. Product Markovian quantization (PMQ) reduces this problem to d one-dimensional quantization problems by recursively constructing product quantizers, as opposed to a truly optimal quantizer. However, the standard Newton-Raphson method used in the PMQ algorithm suffers from numerical instabilities, inhibiting widespread adoption, especially for use in calibration. By directly specifying the random variable to be quantized at each time step, we show that PMQ, and RMQ in one dimension, can be expressed as standard vector quantization. This reformulation allows the application of the accelerated Lloyd's algorithm in an adaptive and robust procedure. Furthermore, in the case of stochastic volatility models, we extend the PMQ algorithm by using higher-order updates for the volatility or variance process. We illustrate the technique for European options, using the Heston model, and more exotic products, using the SABR model.

SSRN

We show that economic downturns can "scar" consumers in the long-run. Having lived through times of high unemployment consumers remain pessimistic about the future financial situation and spend significantly less years later, controlling for income, wealth, and employment. Their actual future income is uncorrelated with past experiences. Due to experience-induced frugality, scarred consumers accumulate more wealth. Using a stochastic life-cycle model we show that the negative relationship between past downturns and consumption cannot arise from financial constraints, income scarring, or unemployment scarring. Our results suggest a novel micro-foundation of fluctuations in aggregate demand and imply long-run effects of macroeconomic shocks.

SSRN

This paper assembles a comprehensive sectoral capital flows dataset for 64 advanced and emerging economies from 2000-18, including direct, portfolio, and other investment to and from five sectors: namely, central banks (CB), general government (GG), banks (BKs), non-financial corporates (NFCs) and other financial corporates (OFCs). Using this data, the paper highlights the usefulness of a sectoral approach in assessing capital flow covariates, co-movements, and the effectiveness of capital controls. We show that 1) sectoral flows have varying sensitivities to measures of the global financial cycle and different cyclicality with respect to output growth; 2) co-movements in intra-sectoral resident and non-resident and co-movements with OFC sectoral flows explain a large part of the observed positive correlation between gross inflows and outflows; and, 3) sector-specific tightening capital control measures appear effective in reducing the volume of flows to NFCs and OFCs.

arXiv

In this paper, we analyze maximum Sharpe ratio when the number of assets in a portfolio is larger than its time span. One obstacle in this large dimensional setup is the singularity of the sample covariance matrix of the excess asset returns. To solve this issue, we benefit from a technique called nodewise regression, which was developed by Meinshausen and Buhlmann (2006). It provides a sparse/weakly sparse and consistent estimate of the precision matrix, using the Lasso method. We analyze three issues. One of the key results in our paper is that mean-variance efficiency for the portfolios in large dimensions is established. Then tied to that result, we also show that the maximum out-of-sample Sharpe ratio can be consistently estimated in this large portfolio of assets. Furthermore, we provide convergence rates and see that the number of assets slow down the convergence up to a logarithmic factor. Then, we provide consistency of maximum Sharpe Ratio when the portfolio weights add up to one, and also provide a new formula and an estimate for constrained maximum Sharpe ratio. Finally, we provide consistent estimates of the Sharpe ratios of global minimum variance portfolio and Markowitz's (1952) mean variance portfolio. In terms of assumptions, we allow for time series data. Simulation and out-of-sample forecasting exercise shows that our new method performs well compared to factor and shrinkage based techniques.

SSRN

We study the impacts of two forms of leveraged trading, namely margin trading and short selling, on the trading liquidity of individual stocks in China. We find that trading liquidity for relevant stocks generally improves after the restriction of leveraged trading was removed. Margin trading and short selling, however, has opposite impacts on liquidity. In ordinary time periods, margin trading benefits liquidity whereas short selling damages liquidity. However, in market downturns, their roles reversed. We also provide evidence suggesting that short sellers are informed traders in China and short selling reduces stock liquidity due to the increased risk of adverse selection faced by uninformed traders.

SSRN

We examine how a firmâ€™s operational slack is associated with current income and future stock price crash risk. By doing so, we test the validity of a firmâ€™s alternative motivations for holding operational slack. We show that Supply Chain Slack, which is based on excess working capital, is associated with higher current profits and higher future crash risk. This evidence is consistent with the firm hoarding bad news. In contrast, SG&A Slack, which is based on excess selling, general, and administrative expenses, is associated with lower current income and lower future crash risk. This evidence is consistent with the firm insuring against rare and adverse events. Furthermore, a firmâ€™s stock price crash risk is lower when a slack type is more costly, consistent with both motivations. Overall, our findings suggest a stronger profit-crash risk tradeoff when firms hold more operational slack.

arXiv

First, we consider the problem of hedging in complete binomial models. Using the discrete-time F\"ollmer-Schweizer decomposition, we demonstrate the equivalence of the backward induction and sequential regression approaches. Second, in incomplete trinomial models, we examine the extension of the sequential regression approach for approximation of contingent claims. Then, on a finite probability space, we investigate stability of the discrete-time F\"ollmer-Schweizer decomposition with respect to perturbations of the stock price dynamics and, finally, perform its asymptotic analysis under simultaneous perturbations of the drift and volatility of the underlying discounted stock price process, where we prove stability and obtain explicit formulas for the leading order correction terms.

SSRN

We analyze how regulatory constraints on household leverage-in the form of loan-to-income and loan-to-value limits-affect residential mortgage credit and house prices as well as other asset classes not directly targeted by the limits. Supervisory loan level data suggest that mortgage credit is reallocated from low-to high-income borrowers and from urban to rural counties. This reallocation weakens the feedback loop between credit and house prices and slows down house price growth in "hot" housing markets. Consistent with constrained lenders adjusting their portfolio choice, more-affected banks drive this reallocation and substitute their risk-taking into holdings of securities and corporate credit.

SSRN

An economic laboratory experiment is used to test the validity of Bessembinder and Lemmon's (2002) seminal risk premium theory. The theory predicts that forward premia in electricity markets are determined by the statistical properties of demand. The existing empirical evidence is mixed, possibly as a result of the lack of observability of key variables. Specifically, the experiment tests if an increase in the variance of demand makes the forward premia more negative for specific parameters and implementation details. The experimental results corroborate the theoretical predictions.

SSRN

Attitudes towards capital markets and stock-market investment still differ widely between Western and formerly communist countries, but there is also significant heterogeneity within the East. We argue that the speed of convergence is predicted by the quality of life-time experiences under communism. Utilizing novel German brokerage and bank data we document that, decades after Reunification, East Germans invest significantly less in stocks and hold more negative views on capital markets if they had unrelated positive experiences, e.g., from Olympic games or living in celebrated showcase cities. Results reverse for East Germans with negative experiences, like environmental pollution and religious oppression.

SSRN

Current corporate risk management theories predict that young firms should hedge more than the established ones. However, the claim is not supported by empirical observations, which also present mixed evidence on whether hedging creates value. This paper attempts to address this puzzle by including model uncertainty as part of risk management process. We develop a dynamic model in which agents learn about a firmâ€™s hedgeability, gauged by the correlation between its operating cash flow and underlying asset of hedging instruments, while weighing the costs and benefits of different risk management tools. The model predicts that resolving model uncertainty accelerates the process of building up hedging positions, but this is not necessarily accompanied with firm value creation. We conclude that dynamic information acquisition is an important determinant of corporate risk management.

SSRN

The FDA grants a 180-day period of marketing exclusivity to reward the first generic manufacturer challenging the monopoly status of patent-protected drugs. Institutional horizontal shareholdings --- the generic shareholders' ownership in the brand-name incumbent relative to their ownership in the generic manufacturer --- are positively associated with the likelihood that the first generic enters into a settlement agreement with the brand. The results are not driven by systemic differences between private and public firms, and survive from a panel instrumental variable strategy that exploits the combination of the two largest investors. Horizontal shareholdings are positively associated with the brandâ€™s abnormal daily stock returns around the settlement agreement. Following settlements, the first generic manufacturers are more likely to delay the sale of generic substitutes if they have higher horizontal shareholdings with the brand. These delays preclude other generic manufacturers from entering the market. Generic manufacturers with higher horizontal shareholdings are more likely to be the first patent challengers. The findings suggest commonly owned incumbent and competitors coordinate in response to the threat of entry.

SSRN

Investors rely on corporate disclosure to make informed decisions about the value of companies they invest in. The COVID-19 pandemic provides a unique opportunity to examine disclosure practices of companies relative to peers in real time about a somewhat unprecedented shock that impacted practically every publicly listed company in the U.S. We examine how companies respond to such a situation, the choices they make, and how disclosure varies across industries and companies. We ask: â€¢ What motivates some companies to be forthcoming about what they are experiencing, while others remain silent?â€¢ Do differences in disclosure reflect different degrees of certitude about how the virus would impact businesses, or differences in management perception of its obligations to shareholders?â€¢ What insights will companies learn to prepare for future outlier events?

SSRN

The Tax Cut and Jobs Act (TCJA) slashed corporations' median effective tax rates from 31.7% to 20.8%. Nevertheless, 15% of firms experienced an increase. One fifth of firms recorded nonrecurring tax costs or benefits exceeding 3% of total assets. Proxies that existing studies employ to assess the TCJA's impacts account for just half of actual impacts. Stock prices impounded those proxies during the legislative process. Total impacts were impounded the following year, once firms published their financials. These results indicate that investors find it hard to predict even large and immediate changes to company cash flows due to unfamiliar events.

RePEC

This study assesses the effects of the magnitude of oil price shocks i.e. large negative, positive and moderate oil price shocks on equity market returns in BRICS countries during different market circumstances by making use of quantile-on-quantile regression. The current study differs from studies that employ quantile-on-quantile in assessing the relationship between oil price shocks and equity returns in different aspects. Firstly, the study intends to assess how this relationship differs per countries given their factor endowment (i.e. whether they export or import oil) within the BRICS grouping. Secondly, we also differ from Sim Zhou (2015) and Tchatoka et al. (2018) because we introduce the supply shocks by following the same structure as Kilian and Park (2009) but changing the Cholesky decomposition by ordering real oil price first, assuming the contemporaneous response of global production to oil price. The results of the empirical analysis show that distinction should be made between the demand-driven and supply-driven oil price shocks and that the outcome of this relationship depends on whether a country is a net importer or exporter of crude oil. For most of the net oil-importing countries, the low oil price demand shocks, which translate to lower oil prices, further stimulate equity markets when they are at peak. And for oil-producing countries in general, high demand oil price shocks provide an incentive for the expansion of equity markets during bad market conditions.

arXiv

We consider the problem of neural network training in a time-varying context. Machine learning algorithms have excelled in problems that do not change over time. However, problems encountered in financial markets are often time-varying. We propose the online early stopping algorithm and show that a neural network trained using this algorithm can track a function changing with unknown dynamics. We compare the proposed algorithm to current approaches on predicting monthly U.S. stock returns and show its superiority. We also show that prominent factors (such as the size and momentum effects) and industry indicators, exhibit time varying stock return predictiveness. We find that during market distress, industry indicators experience an increase in importance at the expense of firm level features. This indicates that industries play a role in explaining stock returns during periods of heightened risk.

SSRN

CNBCâ€™s â€œFast Moneyâ€ regularly covers unusual option activity and refers to it as â€œsmart moneyâ€. We investigate the impact of the CNBC coverage on underlying stock prices and whether investors can profit by following the â€œsmart moneyâ€. We document an immediate spike in trading volume and abnormal returns at the time of the CNBC coverage. While options trades significantly predict stock returns prior to the CNBC coverage, there is a significant reversal in underlying stock prices following the CNBC coverage. Using similar criteria, we identify unusual option activities for a large sample of stocks. We show that options trades significantly predict underlying stock returns and there is no evidence of reversal in underlying stock price. Our findings suggest that the CNBC coverage of unusual option activity has a destabilizing effect on underlying stock prices and investors cannot profit by simply following the CNBC reporting on the â€œsmart moneyâ€.

SSRN

We show that cheap credit to impaired firms has a disinflationary effect. By helping distressed firms to stay afloat, "zombie credit" can create excess production capacity, and in turn, put downward pressure on markups and prices. We test this mechanism exploiting granular inflation and firm-level data from twelve European countries. In the cross-section of industries and countries, we find that a rise of zombie credit is associated with a decrease in firm defaults and entries, firm markups and product prices; lower productivity; and, an increase in aggregate sales as well as material and labor cost. These results hold at the firm-level, where we document spillover effects to healthy firms in markets with high zombie credit. Our partial equilibrium estimates suggest that without a rise in ...