Research articles for the 2019-03-28
SSRN
This paper provides an in-depth analysis of the green bond premium, so-called Greenium, using both, primary and secondary market data. We consider a large sample of over 2,000 green bonds issued worldwide and estimate the differences in yields of green and comparable conventional bonds. Our primary market results reveal a significantly negative premium of 20--30 bps for green bonds, implying that at issuance, green bonds are trading at higher prices than their conventional counterparts. This premium, however, varies across currencies and issuer types. In particular, credibility plays an important role as bonds backed by a collateral or issued by more credible entities are issued at lower yields. Using secondary markets data we find higher differences in yields for bonds with shorter time to maturity and larger issue sizes. Remarkably, bonds listed on exchanges with a dedicated green bond segment are traded at 20 bps lower yields, on average, pointing out the importance of transparency and clear standards for the growth of the green bonds market.
SSRN
In this rejoinder, we note that the complaint against the classic FCF WACC is misplaced because it incorrectly identifies the real source of the problem. The fault for the discrepancies, dear colleagues, lies not in the classic formulation of the FCF WACC. The real reason for the discrepancies is more technical, subtle and nuanced. In the valuation of cash flows, the discrepancies in the results from the three methods are due to the inconsistency between the specification of the discount rate for the tax shield KTS and the corresponding expression for the return to levered equity KE. The results from all the methods will always match if the analyst uses the correct expression for KE that corresponds to the value of KTS.Cautionary note: This rejoinder draws on and summarizes ideas that were discussed in regular, polite (?) emails between the authors; however key differences remain and need to be resolved. For the moment, this rejoinder represents the best (mis)understanding and interpretations of the fundamental concepts.
SSRN
Aggregate housing demand shocks are an important source of house price fluctuations in the standard macroeconomic models, and through the collateral channel, they drive macroeconomic fluctuations. These reduced-form shocks, however, fail to generate a highly volatile price-to-rent ratio that comoves with the house price observed in the data (the â€Å"price-rent puzzle�). We build a tractable heterogeneous-agent model that provides a microeconomic foundation for housing demand shocks. The model predicts that a credit supply shock can generate large comovements between the house price and the price-to-rent ratio. We provide empirical evidence from cross-country and cross-MSA data to support this theoretical prediction.
SSRN
This paper studies how future tense marking affects the terms of bank loans. We predict that languages that grammatically mark the future affect speakers’ intertemporal preferences and thereby reduce the perception of the risks associated with loan issuance. We test this hypothesis on a sample of 2,601 bank loans from 20 European countries. We observe that the use of a language with future tense marking is associated with lower loan spreads and lower collateral use in loan contracts. The results corroborate Chen (American Economic Review, 2013)’s hypothesis that future tense marking makes the future more distant than the present. They suggest that linguistic structure affects terms of loan contracts.
SSRN
This paper argues that banks should not be treated as intermediaries of loanable funds in order to determine optimal bank capital structure. This is because banks create deposits through lending. The Modiglianiâ€"Miller analysis cannot be applied to banks because when lending creates deposits the asset side of banks varies together with the liability side and equity behaves more like a sticky variable. In this setting, procyclical high leverage in the banking sector emerges almost mechanically. When banks increase equity through new issues or retained earnings they contract deposits by an equal amount. An empirical study using data on the aggregate balance sheet of all US commercial banks confirms that asset growth is highly correlated with leverage growth and changes in the supply of banks' deposits have a significant impact on liquidity and safety premia. It is argued that adverse changes in deposits’ convenience yields due to equity raising by banks could be counterbalanced with asset purchases from the central bank.
arXiv
The paper aims to explore the impacts of bi-demographic structure on the current account and growth. Using a SVAR modeling, we track the dynamic impacts between these underlying variables. New insights have been developed about the dynamic interrelation between population growth, current account and economic growth. The long-run net impact on economic growth of the domestic working population growth and demand labor for emigrants is positive, due to the predominant contribution of skilled emigrant workers. Besides, the positive long-run contribution of emigrant workers to the current account growth largely compensates the negative contribution from the native population, because of the predominance of skilled compared to unskilled workforce. We find that a positive shock in demand labor for emigrant workers leads to an increasing effect on native active age ratio. Thus, the emigrants appear to be more complements than substitutes for native workers.
SSRN
Generalized linear models have the important property of providing unbiased estimates on a portfolio level. This implies that generalized linear models manage to provide accurate prices on a portfolio level. On the other hand, neural networks may provide very accurate prices on an individual policy level, but state-of-the-art use of neural networks does not pay attention to unbiasedness on a portfolio level. In fact, this is an implicit consequence of using early stopping rules in gradient descent methods for model fitting. In the present paper we discuss this deficiency and we provide two different techniques that remove this drawback of neural network model fitting.
SSRN
Using live trade execution data from an institutional money manager, we measure the real-world costs and challenges a trader faces when demanding significant liquidity of Bitcoin. We provide a novel characterization of the market to purchase digital assets across exchanges and over-the-counter (“OTCâ€) dealers. We find that most displayed digital asset liquidity on exchanges is not readily accessible to institutional investors. However, by purchasing digital assets OTC from regulated counterparties, institutional investors can achieve comparable or better execution quality while fulfilling their fiduciary obligations.
SSRN
Boards of directors play their role in corporate governance by advising and/or monitoring managers. In the corporate disclosure literature, prior research has documented directors’ monitoring role, yet empirical evidence on directors’ advising role is limited. Since the advising role often entails information transfer, we examine directors who concurrently serve as directors or executives in the firms’ related industries (DRIs) and hence possess valuable information about the firms’ external operating environment. We hypothesize and find that more DRIs on boards are associated with more accurate management forecasts. This association is stronger when firms face greater uncertainty, and holds in settings where DRIs are unlikely to monitor managers, suggesting a distinct advising role of DRIs. Our study highlights directors’ role as information suppliers and advisors who help shape corporate voluntary disclosure.
SSRN
In knowledge-intensive industries, targets often get acquired for their human capital. However, acquisitions are also known to trigger employee exit, which may diminish the very asset acquirers are trying to get under their control. We argue that acquisitions disrupt the complementarity between employee skills and employer activities and thereby impact the productivity in the value creation process, which ultimately drives exit decisions. Analyzing vertical acquisitions in the U.S. video game industry we find strong evidence that a higher degree of individual disruption translates into a higher likelihood of post-acquisition employee exit. Moreover, employees with specialized skills are more strongly affected by disruption, while generalized employees are less affected by disruption through acquisition. The findings have implications for the likely success of related and unrelated acquisitions.
SSRN
We examine the impact of corporate social responsibility (CSR) disclosure strategies on equity market liquidity. Using data on CSR disclosure from Bloomberg, we find that equity market liquidity improves as firms increase their CSR disclosure transparency. Specifically, firms with more transparent CSR disclosure strategies have narrower spreads and exhibit improvements in common measures of equity market liquidity. Additionally, we document that improvements in equity market liquidity occur contemporaneously with changes in firms’ CSR disclosure strategies suggesting that markets respond to the transparent disclosure of CSR initiatives without necessarily knowing the ultimate efficacy of the initiative itself. We condition our findings on firm transparency and provide evidence that CSR disclosure transparency acts to reduce information asymmetry thus acting as the mechanism to improve equity market liquidity. Overall, our results suggest that CSR disclosure transparency leads to reductions in asymmetric information, ultimately making financial markets more equitable.
SSRN
We study the unintended consequences of consumer financial regulations, focusing on the CARD Act, which restricts consumer credit card issuers’ ability to raise interest rates. We estimate the competitive responsiveness-the degree to which a credit card issuer changes offered interest rates in response to changes in interest rates offered by its competitors-as a measure of competition in the credit card market. Using small business card offers, which are not subject to the Act, as a control group, we find a significant decline in the competitive responsiveness after the Act. The decline in responsiveness is more pronounced for competitors’ reductions, as opposed to increases, in interest rates, and is more pronounced in areas with more subprime borrowers. The reduced competition underscores the potential unintended consequence of regulating the consumer credit market and contributes toward a more comprehensive and balanced evaluation of the costs and benefits of consumer financial regulations.
arXiv
We propose a family of stochastic volatility models that enable predictive estimation of time-varying extreme event probabilities in time series with nonlinear dependence and power law tails. The models are a white noise process with conditionally log-Laplace stochastic volatility. In contrast to other, similar stochastic volatility formalisms, this process has an explicit, closed-form expression for its conditional probability density function, which enables straightforward estimation of dynamically changing extreme event probabilities. The process and volatility are conditionally Pareto-tailed, with tail exponent given by the reciprocal of the log-volatility's mean absolute innovation. These models thus can accommodate conditional power law-tail behavior ranging from very weakly non-Gaussian to Cauchy-like tails. Closed-form expressions for the models' conditional polynomial moments also allows for volatility modeling. We provide a computationally straightforward, probabilistic method-of-moments estimation procedure that uses an asymptotic approximation of the process' conditional large deviation probabilities. We demonstrate the estimator's usefulness with a simulation study. We then give an empirical application, which shows that this simple modeling method can be effectively used for dynamic and predictive tail inference in heavy-tailed financial time series.
SSRN
To understand how practitioners operationalize evaluations of earnings quality, we obtain a proprietary dataset of 1,029 reports on aggressive reporting practices over 2003-2015 for 348 unique firms published by a research firm (RF) that sells such data to institutional clients. From these reports, we identify 121 measures of poor earnings quality under four major categories: (i) sales quality; (ii) margin quality; (iii) cash flow quality; and (iv) others. As a first-cut to short-list stocks for detailed fundamental analysis, the RF appears to screen for larger, growing firms with lower barriers to arbitrage. The firms flagged by the RF also have higher M-score, F-score, and total and abnormal accruals. The average two (251) days abnormal return after the stock is first flagged by the RF is -1.30 (-18.5) percent, and such return is incremental to the return attributable to mispricing of accruals. Modified Jones and Dechow-Dichev models of abnormal accruals do not appear to capture RF identified signals well suggesting that such models are too coarse to pick up nuanced fundamental analysis conducted by the RF. In out of sample analyses, we find that the RF signals are associated with future restatements, AAERs, and GAAP-related lawsuits after controlling for other earnings quality indicators. We develop an improved earnings quality indicator (RFSCORE) for firms in the retail, durable manufacturing, and business services sectors using the RF’s signals which are based on granular, context- and industry-specific fundamental analysis. To the Street, our paper suggests that fundamental analysis, beyond just the magnitude of accruals, can predict future stock returns. To academics, our research demonstrates that granular, context-specific analysis of public data can supplement and improve the workhorse models used to identify poor earnings quality.
SSRN
Financial Reynolds Number is a new quest of Econophysics way of finding a new proxy for the volatility of any stochastic time series. This sums up the literature survey in the same quest.
SSRN
This paper develops a theory of optimal ethical standards, capital requirements and talent allocation in banking wherein two types of banks, one being protected by regulatory safety nets ("depositories") and the other not so protected ("shadow banks"), innovate financial products and compete for managerial talent. Ethical violations are"mis-selling" products to customers who would not benefit from them, and they entail financial losses and regulatory penalties for the miscreant bank. Bank capital is shown to be more efficient than a penalty for implementing ethical standards. For any capital level, banks choose higher ethical standards and experience fewer ethical violations when bank managers are more talented. However, banks adopting higher ethical standards experience managerial talent migration to banks with lower standards. In equilibrium, endogenously-determined regulatory capital and ethical standards are higher in depositories than in shadow banks, and this difference is bigger with talent competition than without. Consequently, depositories hire less talented managers and innovate less, implying that prudential bank regulation has unavoidable labor market consequences in financial services.
SSRN
We investigate the comparability of non-IFRS performance measures and adjusting items (exclusions) disclosed by companies from eight countries adopting IFRS Standards (Australia, France, Germany, Hong Kong, Italy, Singapore, Sweden and the United Kingdom) in their annual reports for the years 2005, 2008, 2011 and 2013 (1,577 company-years). Presently performance measures may be based on undefined IFRS subtotals (e.g., operating profit, EBIT, EBITDA) or may exclude items from IFRS defined totals (e.g., underlying net profit excludes IFRS line items) reflecting managers’ voluntary disclosure choices. We find some categories of adjustments are similar between countries (e.g., for impairment and merger and acquisition expenses) but the incidence and amount of adjustments vary widely between firms. The type of non-IFRS performance measures disclosed differ by country, likely reflecting prior national practices and positions of security market regulators. Based on our evidence, we conclude the IASB’s consideration of mandatory defined subtotals in the statement of financial performance would necessitate changes in financial statement presentation for companies but should improve comparability between them.
arXiv
A first attempt at obtaining market--directional information from a non--stationary solution of the dynamic equation "future price tends to the value that maximizes the number of shares traded per unit time" [1] is presented. We demonstrate that the concept of price impact is poorly applicable to market dynamics. Instead, we consider the execution flow $I=dV/dt$ operator with the "impact from the future" term providing information about not--yet--executed trades. The "impact from the future" on $I$ can be directly estimated from the already--executed trades, the directional information on price is then obtained from the experimentally observed fact that the $I$ and $p$ operators have the same eigenfunctions (the exact result in the dynamic impact approximation $p=p(I)$). The condition for "no information about the future" is found and directional prediction quality is discussed. This work makes a substantial contribution toward solving the ultimate market dynamics problem: find evidence of existence (or proof of non--existence) of an automated trading machine which consistently makes positive P\&L on a free market as an autonomous agent (aka the existence of the market dynamics equation). The software with a reference implementation of the theory is provided.
SSRN
We evaluate the institutional frameworks developed to implement time-varying macroprudential policies in 58 countries. We focus on new financial stability committees (FSCs) that have grown dramatically in number since the global financial crisis, and their interaction with central banks, and infer countries’ revealed preferences for effectiveness versus political economy considerations. Using cluster analysis, we find that only one-quarter of FSCs have both good processes and good tools to implement macroprudential actions, and that instead most FSCs have been designed to improve communication and coordination among existing regulators. We also find that central banks are not especially able to take macroprudential actions when FSCs are not set up to do so. We conclude that about one-half of the countries do not have structures to take or direct actions and avoid risks of policy inertia. Rather countries’ decisions appear to be consistent with strengthening the political legitimacy of macroprudential policies with prominent roles for the ministry of finance and avoiding placing additional powers in central banks that already are strong in microprudential supervision and have high political independence for monetary policy. The evidence suggests that countries are placing a relatively low weight on the ability of policy institutions to take action and a high weight on political economy considerations in developing their financial stability governance structures.
arXiv
We address the problem of optimally exercising American options based on the assumption that the underlying stock's price follows a Brownian bridge whose final value coincides with the strike price. In order to do so, we solve the discounted optimal stopping problem endowed with the gain function $G(x) = (S - x)^+$ and a Brownian bridge whose final value equals $S$. These settings came up as a first approach of optimally exercising an option within the so-called `stock pinning' scenario. The optimal stopping boundary for this problem is proved to be the unique solution, up to certain conditions, of an integral equation, which is then numerically solved by an algorithm hereby exposed. We face the case where the volatility is unspecified by providing an estimated optimal stopping boundary that, alongside with pointwise confidence intervals, provide alternative stopping rules. Finally, we demonstrate the usefulness of our method within the stock pinning scenario through a comparison with the optimal exercise time based on a geometric Brownian motion. We base our comparison on the contingent claims and the 5-minutes intraday stock price data of Apple and IBM for the period 2011--2018. Supplementary materials with the main proofs and auxiliary lemmas are available online.
SSRN
We propose a Realized-GARCH-Kernel model to predict realized volatilities of 50 ETF in China and S&P500 index in U.S..The Kernel density fitting on disturbance term and semi-parametric method make our model perform well both statistically and economically. First, our model has the lowest in- and out-of-sample prediction errors among five comparable prediction models. The result is robust in eight measures of realized volatility. Second, in both China and U.S. markets, straddle option trading strategies with volatilities predicted with our model generate larger monthly profit and greater Sharpe ratio. Our model is useful in practical investment.
SSRN
Today, no major securities exchange can appear hostile to the possible introduction of distributed ledger technology (DLT), particularly blockchain. The fit is good, as core functions of DLT overlap significantly with those of securities settlement system processes. Nevertheless, securities settlement in its current form is understood as reliable, secure and efficient. Its central counterparty component has even been prescribed globally to counter the risks of over-the-counter (OTC) derivatives trading. It is therefore unlikely that cash-poor securities exchanges operating in a highly fragmented market where they must fight for trading volume will expensively rip out their core technology and replace it with DLT unless the change can offer a qualitative improvement over legacy systems. We think a number of such improvements are within reach. First, DLT would allow direct holding to replace the current ‘indirect holding system’ in which depositories are the legal owners of all securities while investors trade claims against the contents of accounts held by such institutions. Because indirect holding must guarantee securities are in the account when a book-entry is made, financial intermediaries are given power, in effect, to create securities that might not exist (“over-issueâ€). Direct holding will reintroduce robust property rights of investors by returning control over security issue to the issuers, which will permit full transparency of holdings and eliminate “over-issue†risks. Second, a DLT “lightning†network would allow an instantaneous linking of all order-matching venues, so as to re-establish uniform pre- and post-trade information as existed prior to the fragmentation of markets that began around 2000. Risk management can also be improved through empowering order-matching venues as gatekeepers.This paper presents a model DLT-network for order-matching and settlement in which broker-dealers, issuers and trade-matching venues are nodes of a permissioned/private network and have different authorities within the network ledger. Although all information would be available to all nodes, trade-matching venues would have sole authority to match bid and ask orders, broker-dealers would have sole authority to send an order and confirm a matched trade for settlement, and issuers would have sole authority to book securities to registers evidencing the existence and ownership of those securities.
SSRN
We use supervisory data to investigate the ex-ante credit risk taken by different types of lenders in the U.S. syndicated term loan market during the LSAPs period. We find that nonbank lenders, mutual funds and structured-finance vehicles, take higher risk when longer-term interest rates decrease. The results are stronger for mutual funds that charge higher fees. Banks accommodate other lenders' investment choices by originating riskier loans and selling them off. These results are consistent with "search for yield" by nonbanks and with a risk-taking channel of monetary policy. Over the sample we study, lower longer-term interest rates appear to have only a minimal effect on loan spreads.
arXiv
Short sales are regarded as negative purchases in textbook asset pricing theory. In reality, however, the symmetry between purchases and short sales is broken by a variety of costs and risks peculiar to the latter. We formulate an optimal stopping model in which the decision to cover a short position is affected by two short sale-specific frictions---margin risk and recall risk. Margin risk refers to the fact that short sales are collateralised transactions, which means that short sellers may be forced to close out their positions involuntarily if they cannot fund margin calls. Recall risk refers to a peculiarity of the stock lending market, which permits lenders to recall borrowed stock at any time, once again triggering involuntary close-outs. We examine the effect of these frictions on the optimal close-out strategy and quantify the loss of value resulting from each. Our results show that realistic short selling constraints have a dramatic impact on the optimal behaviour of a short seller, and are responsible for a substantial loss of value relative to the first-best situation without them. This has implications for many familiar no-arbitrage identities, which are predicated on the assumption of unfettered short selling.
arXiv
The purpose of this research is to apply technical analysis of Sutte Indicator in stock trading which will assist in the investment decision making process i.e. buying or selling shares. This research takes data of "A" on the Indonesia Stock Exchange(IDX or BEI) 29 November 2006 until 20 September 2016 period. To see the performance of Sutte Indicator, other technical analysis are used as a comparison, Simple Moving Average (SMA) and Moving Average Convergence/Divergence (MACD). To see a comparison of the level of reliability prediction, the stock data were compared using the mean absolute deviation (MAD), mean of square error (MSE), and mean absolute percentage error (MAPE). The result of this research is that Sutte Indicator can be used as a reference in predicting stock movements, and if it is compared to other indicator methods (SMA and MACD) via MAD, MSE, and MAPE, the Sutte Indicator has a better level of reliability.
SSRN
We show that the housing wealth collapse of 2006-09 had a persistent impact on employment across counties in the U.S. In particular, localities that had a larger loss in housing net worth during that period had more depressed employment as late as 2016, without a commensurate population response. The use of IV's and controls to identify the causal impact of the wealth shock amplifies those results, leading to an estimate that a 10 percent change in housing net worth between 2006 and 2009 causes a 4.5 percent decline in local employment by 2016, as compared with a 2006 baseline. We do not find a long-term causal impact of the shock on wages. Sectoral results indicate, however, that the results are unlikely to be purely a result of persistently low demand, since, contrary to the short-run effects, the effect over the longer horizon is less concentrated in the non-tradables sectors and is instead more prominent in the high-skilled services sector.
SSRN
In this short note, we present a nontechnical retrospection on the unbearable longevity of the classic WACC (Weighted Average Cost of Capital) for the Free Cash Flow (FCF) in perpetuity. Over the past two decades, researchers in finance have increased greatly our understanding of the properties of the WACC. This means that the usefulness of the classic FCF WACC has long expired. However, inexplicably, it continues to live on in textbooks and websites. The resilience of the classic FCF WACC is puzzling. We discuss some unsatisfactory reasons why the classic FCF WACC continues to thrive.
