Research articles for the 2020-06-04

(In)Stability for the Blockchain: Deleveraging Spirals and Stablecoin Attacks
Ariah Klages-Mundt,Andreea Minca
arXiv

We develop a model of stable assets, including noncustodial stablecoins backed by cryptocurrencies. Such stablecoins are popular methods for bootstrapping price stability within public blockchain settings. We derive fundamental results about dynamics and liquidity in stablecoin markets, demonstrate that these markets face deleveraging feedback effects that cause illiquidity during crises and exacerbate collateral drawdown, and characterize stable dynamics of the system under particular conditions. From these insights, we suggest design improvements that aim to improve long-term stability. We also introduce new attacks that exploit arbitrage-like opportunities around stablecoin liquidations. Using our model, we demonstrate that these can be profitable. These attacks may induce volatility in the `stable' asset and cause perverse incentives for miners, posing risks to blockchain consensus.



A New Look to Three-Factor Fama-French Regression Model using Sample Innovations
Javad Shaabani,Ali Akbar Jafari
arXiv

The Fama-French model is widely used in assessing the portfolio's performance compared to market returns. In Fama-French models, all factors are time-series data. The cross-sectional data are slightly different from the time series data. A distinct problem with time-series regressions is that R-squared in time series regressions is usually very high, especially compared with typical R-squared for cross-sectional data. The high value of R-squared may cause misinterpretation that the regression model fits the observed data well, and the variance in the dependent variable is explained well by the independent variables. Thus, to do regression analysis, and overcome with the serial dependence and volatility clustering, we use standard econometrics time series models to derive sample innovations. In this study, we revisit and validate the Fama-French models in two different ways: using the factors and asset returns in the Fama-French model and considering the sample innovations in the Fama-French model instead of studying the factors. Comparing the two methods considered in this study, we suggest the Fama-French model should be considered with heavy tail distributions as the tail behavior is relevant in Fama-French models, including financial data, and the QQ plot does not validate that the choice of the normal distribution as the theoretical distribution for the noise in the model.



Against Subversion, a Contribution to the Normative Theory of Trust Law
Bennett, Mark J.,Hofri-Winogradow, Adam S.
SSRN
This article closes a gap in the theory of trust law by supplying a normative account of the use of trusts to avoid and subvert other legal norms. While the use of trusts to subvert other law has been a major function thereof since the middle ages, a fact acknowledged by jurists, doctrinal and textbook authors for centuries, theorists of trust law have largely steered clear of this function. We evaluate the two most commonly proffered justifications for the use of trusts to subvert the law: that such use enhances users’ autonomy, and that trusts allow people to avoid or mitigate injustices found in law to which they are subject. We find that such justifications are not plausible in liberal legal systems, and so the subversion use of trusts should be, and usually is, curtailed, principally by anti-subversion norms found outside trust law.

An Analysis of the Potential Impact of Heightened Capital Requirements on Banks’ Cost of Capital
Mantecon, Tomas
SSRN
Critics of recent regulation to increase minimum bank capital requirements contend that this policy will increase the cost of doing business for banks. We investigate the potential impact of heightened capital requirements on banks’ cost of capital. In the cross-section, banks’ cost of equity, measured by the implied cost of capital (ICC), and banks’ cost of debt decline when equity capital increases. The negative association between capital and banks’ ICC is stronger after the onset of the financial crisis, consistent with prior work suggesting that equity is more valuable during periods of financial distress. The negative association between capital and banks’ cost of equity and debt, compensates for the difference in the costs of these sources of financing. As a consequence, the overall cost of capital remains unaltered when capital increases. Thus, our findings do not offer support the claim that additional equity has a negative impact on credit because equity increases banks’ cost of capital. An exception to these findings is found in the sample of large banks. There is no discernible association between capital and the costs of equity and debt of large banks and their WACC increases when they substitute debt with more expensive equity.

Are ISS Recommendations Informative? Evidence from Assessments of Compensation Practices
Albuquerque, Ana M.,Carter, Mary Ellen,Gallani, Susanna
SSRN
Using detailed information from the largest proxy advisor in the U.S., Institutional Shareholder Services (ISS), we examine whether proxy advisors’ assessments of firms’ compensation practices are able to identify poor compensation practices as measured by subsequent performance. While prior research provides consistent evidence of an association between shareholder voting outcomes and proxy advisors’ Say-on-Pay recommendations, the evidence is mixed over whether their recommendations are informative about the quality of firms’ compensation practices. We find that ISS “Against” recommendations and negative assessments are associated with worse future accounting performance, consistent with ISS being able to detect low quality compensation packages. However, workload compression has an effect, as we find that the relation between assessments and future performance only occurs during the off season (i.e. for firms with non-December fiscal year ends).

Biases in Long-Horizon Predictive Regressions
Boudoukh, Jacob,Israel, Ronen,Richardson, Matthew P.
SSRN
Analogous to Stambaugh (1999), this paper derives the small sample bias of estimators in J-horizon predictive regressions, providing a plug-in adjustment for these estimators. A number of surprising results emerge, including (i) a higher bias for overlapping than nonoverlapping regressions despite the greater number of observations, and (ii) particularly higher bias for an alternative long-horizon predictive regression commonly advocated for in the literature. For large J, the bias is linear in (J/T) with a slope that depends on the predictive variable’s persistence. The bias adjustment substantially reduces the existing magnitude of long-horizon estimates of predictability.

Bitcoin Sentiment Index, Performance and US Dollar Exchange Rate
Soomro, Ishfaque Ahmed,Oad Rajput, Suresh Kumar,Ali, Najma
SSRN
This study introduces a comprehensive Google search volume based Bitcoin sentiment index (BSI) by following the methodology of Da, Engelberg, and Gao (2014). BSI is investigated for its association with Bitcoin returns, trade volume, volatility, and United States dollar exchange rates (USD). Results of the simple OLS regression clarify that BSI has a positive impact on Bitcoin returns and trade volume while it has a negative impact on the volatility of Bitcoin returns. Furthermore, the Auto-regressive distributed lag (ARDL) model has been used to capture the relationship between BSI and Bitcoin price with USD. Empirical results of the ARDL model demonstrate that Bitcoin sentiments affect USD in the short-run but not long-run. However, Bitcoin's price can negatively affect USD in short as well as in the long-run. Error correction term represents a 38.50% adjustment towards the long-run equilibrium in one month if there is a deviation in the short-run. The results imply that investors in FOREX or public in general interested in Bitcoin trading should foresee sentiments of the public towards Bitcoin.

Boosting Poisson Regression Models with Telematics Car Driving Data
Gao, Guangyuan,Wang, He,Wuthrich, Mario V.
SSRN
With the emergence of telematics car driving data, insurance companies start to boost classical actuarial regression models for claim frequency prediction. In this paper, we propose two data-driven neural network approaches that process telematics car driving data to construct driving behavior risk factors. Neural networks simultaneously accommodate feature engineering and regression modeling. We conclude in our numerical analysis that both classical actuarial risk factors and telematics car driving data is necessary to receive the best predictive models. This indicates that these two sources of information interact and complement each other.

COVID-19 Mortgage Forbearance: Implications on the Housing Market
Capponi, Agostino,Rios, David Aaron
SSRN
Congress introduced mortgage forbearance into the CARES act signed into law on March 27, 2020.The act offers American homeowners mortgage forbearance until June 30, with a possible extension of 180 days. Our objective is to study the implications of this act on the housing market and prepayment rates, accounting for Federal Reserve intervention policies up to date, and to compare the outcome with the global 2007-2009 financial crisis. In this preliminary note, we give descriptive statistics of today’s mortgage markets in terms of outstanding notional and volume of delinquencies, along with their relation to current unemployment levels.

Catch, Restrict, and Release: The Real Story of Bank Bailouts
Tsyplakov, Sergey,Berger, Allen N.,Ongena, Steven,Nistor, Simona
SSRN
Bank bailouts are not the "one-shot" events commonly described in the literature. These bailouts are instead dynamic processes in which regulators "catch" financially distressed banks; "restrict" their activities over time; and "release" the banks from restrictions at sufficiently healthy capital ratios. The "catch-restrict-release" approach is a global phenomenon, which we document using hand-collected data on capital injection and debt guarantee bailouts in the European Union (EU) over 2008-2014. We present a dynamic theoretical model of socially-optimizing regulators engaging in "catch-restrict-release" capital injection and debt guarantee bailouts, and empirically test model predictions. Observed EU bailouts are qualitatively consistent with optimizing behavior.

Coastal Flood Risk in the Mortgage Market: Storm Surge Models' Predictions vs. Flood Insurance Maps
Amine Ouazad
arXiv

Prior literature has argued that flood insurance maps may not capture the extent of flood risk. This paper performs a granular assessment of coastal flood risk in the mortgage market by using physical simulations of hurricane storm surge heights instead of using FEMA's flood insurance maps. Matching neighborhood-level predicted storm surge heights with mortgage files suggests that coastal flood risk may be large: originations and securitizations in storm surge areas have been rising sharply since 2012, while they remain stable when using flood insurance maps. Every year, more than 50 billion dollars of originations occur in storm surge areas outside of insurance floodplains. The share of agency mortgages increases in storm surge areas, yet remains stable in the flood insurance 100-year floodplain. Mortgages in storm surge areas are more likely to be complex: non-fully amortizing features such as interest-only or adjustable rates. Households may also be more vulnerable in storm surge areas: median household income is lower, the share of African Americans and Hispanics is substantially higher, the share of individuals with health coverage is lower. Price-to-rent ratios are declining in storm surge areas while they are increasing in flood insurance areas. This paper suggests that uncovering future financial flood risk requires scientific models that are independent of the flood insurance mapping process.



Credit Supply, Firms, and Earnings Inequality
Moser, Christian,Saidi, Farzad,Wirth, Benjamin,Wolter, Stefanie
SSRN
We study the distributional effects of a monetary policy-induced firm-level credit supply shock on individual wages and employment. To this end, we construct a novel data set that links worker employment histories to firms' bank credit relationships in Germany. We document that firms in relationships with banks that were more exposed to negative monetary policy rates in 2014 see a relative reduction in credit supply. A negative credit supply shock in turn is associated with lower firm-level average wages and employment. These effects are concentrated among distinct worker groups within firms, with initially lower-paid workers more likely to be fired and initially higher-paid workers more likely to receive wage cuts. At the same time, wages decline by more at initially higher-paying firms. Consequently, wage inequality within and between firms decreases. Our results suggest that monetary policy has important distributional effects in the labor market.

Deep Reinforcement Learning for Foreign Exchange Trading
Yun-Cheng Tsai,Chun-Chieh Wang
arXiv

Reinforcement learning can interact with the environment and is suitable for applications in decision control systems. Therefore, we used the reinforcement learning method to establish a foreign exchange transaction, avoiding the long-standing problem of unstable trends in deep learning predictions. In the system design, we optimized the Sure-Fire statistical arbitrage policy, set three different actions, encoded the continuous price over a period of time into a heat-map view of the Gramian Angular Field (GAF) and compared the Deep Q Learning (DQN) and Proximal Policy Optimization (PPO) algorithms. To test feasibility, we analyzed three currency pairs, namely EUR/USD, GBP/USD, and AUD/USD. We trained the data in units of four hours from 1 August 2018 to 30 November 2018 and tested model performance using data between 1 December 2018 and 31 December 2018. The test results of the various models indicated that favorable investment performance was achieved as long as the model was able to handle complex and random processes and the state was able to describe the environment, validating the feasibility of reinforcement learning in the development of trading strategies.



Determinants of Indebtedness: Influence of Behavioral and Demographic Factors
Masud, PhD, Md. Abdul Kaium
SSRN
This study aims to examine the influence of behavioral and demographic factors on indebtedness by constructing a model using specific determinants. The exploratory method is used through the partial least square (SmartPLS) technique, by surveying 320 respondents in Kuala Lumpur, Malaysia. A self‐administered questionnaire was administered to respondents, addressing both demographic and behavioral factors. The results confirmed four of the eight hypotheses stated. Among the determinants, risk perception had a highly significant relationship with both materialism and emotion, while indebtedness had a relationship with emotion and materialism. The findings also indicated that significant differences exist between indebtedness and behavioral factors on the basis of gender, marital status, age, income, and dependence on credit cards and loans. The results may assist various economic players to design better models for credit offerings and address the credit problem in the long term.

Digital Currency and the Economic Crisis: Helping States Respond
Geoffrey Goodell,Hazem Danny Al-Nakib,Paolo Tasca
arXiv

The current crisis, at the time of writing, has had a profound impact on the financial world, introducing the need for creative approaches to revitalising the economy at the micro level as well as the macro level. In this informal analysis and design proposal, we describe how infrastructure for digital assets can serve as a useful monetary and fiscal policy tool and an enabler of existing tools in the future, particularly during crises, while aligning the trajectory of financial technology innovation toward a brighter future. We propose an approach to digital currency that would allow people without banking relationships to transact electronically and privately, including both internet purchases and point-of-sale purchases that are required to be cashless. We also propose an approach to digital currency that would allow for more efficient and transparent clearing and settlement, implementation of monetary and fiscal policy, and management of systemic risk. The digital currency could be implemented as central bank digital currency (CBDC), or it could be issued by the government and collateralised by public funds or Treasury assets. Our proposed architecture allows both manifestations and would be operated by banks and other money services businesses, operating within a framework overseen by government regulators. We argue that now is the time for action to undertake development of such a system, not only because of the current crisis but also in anticipation of future crises resulting from geopolitical risks, the continued globalisation of the digital economy, and the changing value and risks that technology brings.



Disclosure Services and Endogenous Segmentation in Takeover Markets
Kawakami, Kei
SSRN
We present a competitive model of takeovers among heterogeneous firms. Each firm owns a tradeable "project" and non-tradeable "skill". The complementarity between them generates takeovers. We construct an equilibrium with two segmented markets. In one market, firms pay a fee to an intermediary to fully disclose their project quality. In the other market, firms reveal at no cost that their project quality is above a minimum standard. The latter market matches projects to skill randomly. Yet, it significantly improves welfare by raising the elasticity of the demand for the full disclosure service. Regulations necessary to support this equilibrium are discussed.

Dividend Taxes and Investment Efficiency: Evidence from the 2003 U.S. Personal Taxation Reform
Chay, J.B. (Jong-Bom),Chong, Byung-Uk,Im, Hyun Joong
SSRN
We examine the effect of a large dividend tax cut on corporate investment efficiency by exploiting the 2003 tax reform in the U.S. as a quasi-natural experiment. We find that the dividend tax cut significantly improved the investment efficiency of firms that were likely to have tax-paying individuals as marginal investors. Our evidence suggests that the 2003 dividend tax cut significantly improved the investment efficiency of U.S. listed firms by mitigating agency problems associated with excessive free cash flows of over-investing firms while relaxing financial constraints of under-investing firms. We find no evidence that the dividend tax cut increased the level of investment of our sample firms that were more likely to be affected by the large decrease in taxes imposed on dividends.

Does Algorithmic Trading Affect Analyst Research Production?
Bilinski, Pawel,Karamanou, Irene,Kopita, Anastasia,Panayides, Marios A.
SSRN
We document that Algorithmic Traders (ATs) reduce analysts’ stock coverage and the number of analyst research reports. This evidence reflects that ATs pre-empt trades on new information, which reduces non-AT investment-driven demand for analyst research. Consistently, the effects we document dominate (i) when analysts produce new information rather than simply disseminate public information; (ii) when there are more institutional investors demanding research for trading purposes rather than for monitoring purposes; (iii) for stock recommendations rather than earnings forecasts (as the latter also serve a monitoring purpose); (iv) when stock liquidity is higher, as ATs require high liquidity for profitable trades; (v) for smaller stocks where the analyst’s reputational cost of dropping coverage is lower. We address endogeneity using firm-fixed effects, regressions in changes, and using a natural experiment based on the tick-size pilot programme. Overall, our results suggest that an unintended consequence of algorithmic trading is lower analyst research production.

Dynamic Hostile Takeover: Managerial Reputation and Acquirer Learning
Hu, Zehao,Huang, Chong
SSRN
This paper studies dynamics of hostile takeovers, incorporating target manager reputation for deterring takeover bids and acquirer exogenous learning about target manager's resoluteness of maintaining management position. By exogenous learning, the acquirer's posterior about the true resoluteness approaches one over time. Surprisingly, an acquirer who learns slowly never bids in equilibrium, since target manager reputation dominates acquirer learning ultimately. If the acquirer learns fast, he may bid in equilibrium. There may be a delay of the earliest possible bid, which decreases in the acquirer's exogenous learning speed. After the first bid, the acquirer bids frequently. These results generate new empirical implications. We also derive a strong reputation result: the target manager receives her "commitment payoff,'' even if he is infinitely more patient.

Earnings Management in IPOs: Moral Hazard or Signalling?
Dai, Yun,Zhu, Jiahua,Bao, Te
SSRN
This paper aims to shed light on the long-standing debate on opportunistic and information perspectives of earnings management from a controlled laboratory experiment. Our results are in favor of the moral hazard explanation over the explanation based on the signaling motive. When we introduce a limit on the degree of earnings management (as a proxy for the regulatory power), earnings management are used more often as a signalling device. In the treatments with limit, reported earnings become a more informative indicator of actual earnings, as low-quality firms reduce earnings inflation while high-quality firms increase upward earnings manipulation. Consequently, market pricing efficiency improves, and it leads to better investor protection. Our findings highlight the importance of accounting standards as a tool to reduce management misbehavior and enhance market quality.

Effect of Working Capital Management on Financial Performance of Quoted Conglomerate Firms in Nigeria.
Adamu, Abdul
SSRN
This study examined the effect of working capital management (WCM) on the financial performance of quoted conglomerate firms in Nigeria for the period 2006 to 2016. Account receivable period (ARP), account payable period (APP), inventory turnover period (INV) and cash conversion cycle (CCC) were adopted as the proxies for WCM while return on equity (ROE), return on assets (ROA) and return on investments (ROI) were adopted as proxies for financial performance. Secondary data were obtained from ten (10) quoted conglomerate firms' financial statements and Structural Equation Modeling (SEM) was used for the analysis. The study reveals that APP and CCC have positive effect on financial performance; while ARP and INV have negative effect on financial performance. The general result indicates that there is significant effect of WCM on financial performance (ROA, ROE and ROI) of quoted conglomerate firms in Nigeria. It is recommended that the companies should; ensure speedy collections of account receivables; increase account payable period; formulate and implement effective strategies for inventory management system that minimizes inventory turnover period and management should ensure that investments in working capital is optimized by reducing the length of time from the actual outlay of cash for purchases until the collection of receivables resulting from the sales of goods or services.

Estimating Spillover Effects in Property Casualty Insurance Consumption
Bujakowski, Douglas,Kamiya, Shinichi
SSRN
The determinants of insurance consumption have been extensively studied, yet spatial correlations are rarely considered within this framework. In this paper, we discuss several channels through which spatial dependence may arise and then test for spatial dependence using six years (2009-2014) of province-level data from China. Results suggest that spatial spillover effects are large and have the potential to seriously bias marginal effect estimates if neglected. Specifically, when regions experience similar changes in determinants, marginal effect estimates in spatial models are roughly 1.5 times that implied by aspatial models. Moreover, the findings of this study demonstrate that properly modeling spatial dependence is of paramount importance in accurately assessing the impact of insurance consumption determinants.

Evolution in Pecunia
Amir, Rabah,Evstigneev, Igor V.,Hens, Thorsten,Potapova, Valeriya,Schenk-Hoppé, Klaus Reiner
SSRN
The paper models evolution in pecunia in the realm of finance. Financial markets are explored as evolving biological systems. Investors pursuing diverse investment strategies compete for the market capital. Some `survive' and some `become extinct.' A central goal is to identify evolutionary stable, i.e. guaranteeing survival, investment strategies. The problem is studied in a framework combining stochastic dynamics and evolutionary game theory. The model proposed employs only objectively observable market data, in contrast with traditional settings relying upon unobservable investors characteristics (utilities and beliefs). The main result is a construction of an evolutionary stable strategy in the model at hand.

Executive Compensation and Risk-Taking of Chinese Banks
Huang, Qiubin
SSRN
We document a significantly positive relationship between executive compensation and risk-taking of Chinese listed banks over the 2007â€"2018 period. The finding is robust to the risk measures (Z-score, systematic risk and stock return volatility) used, the way to calculate executive compensation, and model specifications as well as estimation techniques. Further analysis suggests that bank past performance (captured by return on equity) strongly moderates the relationship between executive compensation and risk-taking. We also find a modest U-shaped association of bank Z-score with executive compensation. Our study appears to support the regulation on executive compensation for the sake of bank stability.

Factor Momentum, Investor Sentiment, and Option-Implied Volatility-Scaling
Rutanen, Jere,Grobys, Klaus
SSRN
Factor momentum produces robust average returns that exhibit a similar economic magnitude as documented for stock price momentum. To the extent that the PEAD factor captures mispricing, winner factors profit from being long on underpriced stocks and short on overpriced stocks. Oppositely, loser factors’ negative exposure to the PEAD factor suggests that loser factors capture mispricing by being long on overpriced stocks and short on underpriced stocks. Option-implied volatility scaling increases both the economic magnitude and statistical significance of factor momentum. Factor momentum is not exposed to the same crashes as stock price momentum and could therefore serve as a hedge for stock price momentum crash risks.

Financial Intermediation and Economic Growth: From Idiosyncratic Shocks to Aggregate Fluctuations
Kundu, Shohini,Vats, Nishant
SSRN
The objective of this study is to identify the effect of financial intermediation linkages on the cross-border transmission of idiosyncratic shocks. We document the change in the relationship between interstate spillovers of idiosyncratic shocks and state-level economic growth during the Great Moderation. We document that idiosyncratic shocks in state i are positively correlated with economic growth in state j during the late 1970s and early 1980s. This relation suggests that two states operate as complements to each other in aggregate during this period. However, the relation monotonically changes after 1984 through 1994. Exploiting a natural experiment that established banking linkages across states in a staggered fashion, we attribute the changing relation between idiosyncratic shocks in state i and economic growth in state j to banking integration between the two states. Hence, we argue that in the presence of banking linkages, states behave as substitutes. This is driven by banks allocating capital away from states that experience negative shocks. Lastly, by identifying the effect of idiosyncratic shocks in state i on bank lending in state j under banking integration, we estimate the causal elasticity of bank loan supply on economic growth.

Financial Literacy and Home Bias in Household Investments
Bransch, Felix
SSRN
Using data from the RAND American Life Panel, I investigate differences in households’ investments in foreign assets with special emphasis on financial literacy. The results indicate that American households overweigh their portfolio with domestic assets and that financially literate households are more likely to invest as well as hold a greater fraction of their portfolio in foreign assets. When taking the selection into financial asset ownership into account, the positive relationship between financial knowledge and foreign asset ownership remains unchanged. Additionally, I exploit information about the education level of the respondents’ parents to remedy the potential problem of endogeneity of financial literacy. Interestingly, professional financial advice does not deplete the positive association between financial literacy and foreign asset holdings. Improving financial knowledge can, beyond increasing stock market participation, improve portfolio performance by reducing home bias and foster resilience of households’ retirement savings against country specific risks.

Financial Markets and Institutions: A European Perspective (Chapter 1)
de Haan, Jakob,Schoenmaker, Dirk,Wierts, Peter
SSRN
Written for undergraduate and graduate students of finance, economics and business, the fourth edition of Financial Markets and Institutions provides a fresh analysis of the European financial system. Combining theory, data and policy, this successful textbook examines and explains financial markets, financial infrastructures, financial institutions and the challenges of monetary policy, financial supervision and competition policy.The fourth edition features not only greater discussion of the financial and euro crises and post-crisis reforms, but also new market developments like FinTech, block-chain, cryptocurrencies and shadow banking. On the policy side, new material covers unconventional monetary policies, the Banking Union, the Capital Markets Union, Brexit, the Basel 3 capital adequacy framework for banking supervision and macro-prudential policies. The new edition also features wider international coverage, with greater emphasis on comparisons with countries outside the European Union, including the United States, China and Japan.

Greece Debt Crisis: Scenario Planning For Future Global Impacts
ul Haq, Bina
SSRN
Greece Debt Crisis: Scenario Planning For Future Global ImpactsEconomy | Market Outlook • Scenario planning is key for companies to prepare for potential shifts in the global business picture from the ongoing Greek crises.• Global financial firms such as Citigroup, Bank of America, and JPMorgan Chase and Company have already begun to reduce their exposure.• Companies with direct operations in Greece, such as Vodafone will need to consider these potential outcomes as the situation continues to evolve.

Human Interactions and Financial Investment: A Video-Based Approach
Hu, Allen,Ma, Song
SSRN
Economic decisions are often made after human interactions. This paper proposes an empirical approach to process and quantify features of micro-level human interactions, documents their connections to financial investment decisions, and investigates the underlying economic mechanisms. Using machine learning (ML)-based algorithms with videos as data input, we quantify human interactions in three-V dimensions---visual, vocal, and verbal---and construct interpretable metrics along these dimensions. We apply our method to videos of entrepreneurs pitching investors for funding. We find that venture investors are more likely to invest in startup teams that show more positivity (i.e., happy, warm, passionate), and the penalty of deviating from these features is larger for women. This relation does not appear to be driven by investors correctly calibrating startup quality using pitch features. Instead, through pitch data analysis and an experiment, we show that interaction features affect economic decisions through both the taste-based channel (18 percent) and the inaccurate beliefs channel (82 percent). Overall, the evidence is consistent with interaction-induced biases.

Instabilities in Multi-Asset and Multi-Agent Market Impact Games
Francesco Cordoni,Fabrizio Lillo
arXiv

We consider the general problem of a set of agents trading a portfolio of assets in the presence of transient price impact and additional quadratic transaction costs and we study, with analytical and numerical methods, the resulting Nash equilibria. Extending significantly the framework of Schied and Zhang (2018), who considered two agents and one asset, we focus our attention on the conditions on the value of transaction cost making the trading profile of the agents, and as a consequence the price trajectory, wildly oscillating and the market unstable. We find that the presence of more assets, the heterogeneity of trading skills (e.g. speed or cost), and a large number of agents make the market more prone to large oscillations and instability. When the number of assets is fixed, a more complex structure of the cross-impact matrix, i.e. the existence of multiple factors for liquidity, makes the market less stable compared to the case when a single liquidity factor exists.



Interconnectedness in the Global Financial Market
Matthias Raddant,Dror Y. Kenett
arXiv

The global financial system is highly complex, with cross-border interconnections and interdependencies. In this highly interconnected environment, local financial shocks and events can be easily amplified and turned into global events. This paper analyzes the dependencies among nearly 4,000 stocks from 15 countries. The returns are normalized by the estimated volatility using a GARCH model and a robust regression process estimates pairwise statistical relationships between stocks from different markets. The estimation results are used as a measure of statistical interconnectedness, and to derive network representations, both by country and by sector. The results show that countries like the United States and Germany are in the core of the global stock market. The energy, materials, and financial sectors play an important role in connecting markets, and this role has increased over time for the energy and materials sectors. Our results confirm the role of global sectoral factors in stock market dependence. Moreover, our results show that the dependencies are rather volatile and that heterogeneity among stocks is a non-negligible aspect of this volatility.



Is it Better to be Active or Passive Manger? Evidence from the Dow Jones Industrial Average
Salameh, Hussein
SSRN
This paper compares between the performance of an active manger that tries to beat the market and constructs an optimal risky portfolio of companies that are listed in the Dow Jones Industrial Average (DJIA), and the performance of a passive manger that creates a portfolio similar to the DJIA. We followed the methodology of Markowitz in building the efficient frontier. Our findings advocate the passive investment strategy which does not attempt to outperform the market; i.e., being a passive manger is better than being an active manger.

Liquidity Constraints and Real Effects of Financial Intermediaries: Risk Intensification and Collapse in the Leveraged Loan Market
Kundu, Shohini
SSRN
The objective of this paper is to study how externalities of CLO contracts affect asset prices that can lead to inefficient liquidation. The discrepancy in the reported default rate of CLOs and the underlying leveraged loans motivates the study of managerial trading decisions and their real outcomes. I document several new findings. Unlike their CDO counterparts, there is evidence of selection, monitoring, and turnover in the CLO market. With regard to distressed firms, CLOs run on loans issued by distressed firms before they file for bankruptcy. This is driven by liquidity constraints, and, results in price pressure in the secondary loan market, with stark differences in returns for constrained and unconstrained managers. Moreover, upon experiencing liquidity constraints, managers sell more liquid loans relative to illiquid loans, with substantial implications for affected firms. Firms with a larger share of debt held by constrained managers ("share") face higher financing costs in the loan and bond markets, and obtain less external financing. The changes in loan terms are larger for tranches that banks retain on their balance sheet, as compared with tranches that are securitized. Additionally, firms with a greater share experience lower cash flow, inventory, employment, size, and profitability. They also have access to less liquidity from existing lines of credit. As an extension, I use this set-up to analyze the sensitivity of cash and investment to cash flow. Firms with low external and internal funds exhibit negative sensitivity of investment to cash-flow (risk-shifting); with high internal funds and low external funds, firms exhibit positive sensitivity of investment to cash-flow. With low internal and external funds, firms exhibit positive sensitivity of cash-flow to cash. Lastly, I show that firms with a greater share have higher default risk, which increases the probability of default. Thus, I illustrate the mechanism through which firm distress can propagate to other firms through CLO intermediaries.

Lottery Preference and Anomalies
Jiang, Lei,Wen, Quan,Zhou, Guofu,Zhu, Yifeng
SSRN
We construct a lottery factor that aggregates the information of 16 commonly used lottery features. The lottery factor significantly improves the explanatory power of the four-factor q model in Hou, Xue, and Zhang (2015) and explains all but a few major anomaly returns. In assessing the implication of lottery preference on profitability of anomaly-based trading strategies, we find that anomaly returns are significantly stronger among stocks with strong lottery preference. Moreover, the anomaly spread portfolios are mainly driven by the short leg among stocks with stronger lottery preference. The effect of lottery feature on anomalies is not driven by financial distress and is related to investors being reluctant to short sell stocks with high lottery features due to the high upside risk.

Medicaid Expansion and Medical Liability Costs
Luo, Jingshu,Chen, Hua,Grace, Martin F.
SSRN
This paper examines the impact of health insurance expansion on medical liability costs using the case of the Affordable Care Act’s (ACA) Medicaid expansion. Medicaid expansion has increased the demand for medical services, but in doing so it may also have increased physicians’ liability in medical practices. By studying medical malpractice insurers’ performance in the U.S. for the period 2010â€"2018, we find insurers operating in states with Medicaid expansion experienced significantly higher medical liability costs than those in non-expansion states. While insurers in expansion states did increase premiums, the increase was not enough to fully offset rising costs. In addition, we do not find evidence that tort reforms mitigate ACA-induced malpractice liability costs. By exploring the frequency and severity of malpractice claims, we find Medicaid expansion increased malpractice costs mainly by increasing the claim frequency, while tort reforms generally focus on reducing claim severity.

Multivariate Distributions for Financial Returns
Madan, Dilip B.
SSRN
Multivariate return distributions consistent with bilateral gamma marginals are formulated and termed multivariate bilateral gamma (MBG). Tail probability distances and Wasserstein Distances between return data, model simulations and their squares evaluate model performance. A full Gaussian copula (FGC) is taken as an alternate test model and the MBG delivers a comparatively better performance for equity pairs. The MBG is however inadequate for the S&P 500 index return when paired with VIX returns. Applying MBG to the S&P 500 index and regressions residuals of the VIX on the S&P 500 index return is successful. This model is termed MBGR. If the residual are taken independent bilateral gamma delivers the model MBGIR. Characteristic function estimations are employed to develop asset specific VIX levels and their joint returns with the asset return are studied. The CBOE skew index is generalized to be asset specific and triples of returns for the asset, its VIX and its Skew are studied using all four models and performance statistics. The model MBGR continues to deliver a good performance.

New Tests of Expectation Formation with Applications to Asset Pricing Models
Kuang, Pei,Zhang, Renbin,Zhang, Tongbin
SSRN
We develop new tests for expectation formation in financial and macroeconomic models under various informational assumptions. Survey data suggests stock price forecasts are not anchored by consumption forecasts and rejects this aspect of the formation of stock price expectations in a wide range of asset pricing models. The evidence casts some doubt on the modeling of expectation formation in the asset pricing models which assume agents possess the knowledge of the equilibrium pricing function as in Rational Expectations and Bayesian Rational Expectations models. Relaxing this knowledge appears necessary for models to reconcile the survey evidence and potential resolutions are discussed.

No Arbitrage SVI
Martini, Claude,Mingone, Arianna
SSRN
We fully characterize the absence of Butterfly arbitrage in the SVI formula for implied total variance proposed by Gatheral in 2004. The main ingredient is an intermediary characterization of the necessary condition for no arbitrage obtained for any model by Fukasawa in 2012 that the inverse functions of the -d1 and -d2 of the Black-Scholes formula, viewed as functions of the log-forward moneyness, should be increasing. A natural rescaling of the SVI parameters and a meticulous analysis of the Durrleman condition allow then to obtain simple range conditions on the parameters. This leads to a straightforward implementation of a least-squares calibration algorithm on the no arbitrage domain, which yields an excellent fit on the market data we used for our tests, with the guarantee to yield smiles with no Butterfly arbitrage.

No Collateral Channel: How Real Estate Shocks Do Not Affect Corporate Investment
Welch, Ivo
SSRN
My paper finds no association between real-estate prices and corporate investment, as claimed by Chaney, Sraer, and Thesmar (2012). First, most of their regressions use the same time-varying denominator (lagged PP&E) on both their independent variable (real-estate holdings) and their dependent variable (corporate capital expenditures). This is not necessarily cured by an additive control (for 1/Lagged PP&E), as introduced in Chaney, Sraer, and Thesmar (2020). Given their specification, even absurd variables (such as the constant 1.0) show an effect on both investment and real-estate holdings. Second, their results are normalization sensitive. Third, their real-estate prices are persistent, leaving the timing of shocks poorly identified. Fourth, firms without real- estate started out observably different. They were smaller and had higher initial capital expenditures (subsequently declining). Merely allowing firms without real-estate a different average investment trend is enough to render information about their actual real-estate holding values, real-estate prices, real-estate price changes, or real-estate shocks unimportant even in their best specification. An extended analysis shows no real-estate collateral channel in the Great Recession of 2008.

Optimal Control of Investment for an Insurer in Two Currency Markets
Qianqian Zhou,Junyi Guo
arXiv

In this paper, we study the optimal investment problem of an insurer whose surplus process follows the diffusion approximation of the classical Cramer-Lundberg model. Investment in the foreign market is allowed, and therefore, the foreign exchange rate model is considered and incorporated. It is assumed that the instantaneous mean growth rate of foreign exchange rate price follows an Ornstein-Uhlenbeck process. Dynamic programming method is employed to study the problem of maximizing the expected exponential utility of terminal wealth. By soloving the correspoding Hamilton-Jacobi-Bellman equations, the optimal investment strategies and the value functions are obtained. Finally, numerical analysis is presented.



Optimal Time-Consistent Debt Policies
Malenko, Andrey,Tsoy, Anton
SSRN
We study time-consistent debt policies in a trade-off model of debt in which the firm can freely issue new debt and repurchase existing debt. A debt policy is time-consistent if in any state equityholders prefer to follow it rather than to deviate from it but lose credibility in sustaining debt discipline in the future. In a class of policies, the optimal time-consistent debt policy consists of an interest coverage ratio (ICR) target and two regions for the ICR: the stable and the distress regions. In the stable region, the firm actively manages liabilities to the ICR target by issuing/repurchasing debt. A sufficiently large negative shock to cash flows pushes the firm into the distress region, where it abandons the target and waits until either cash flows recover or further negative shocks trigger bankruptcy. Credit spreads are sensitive to cash flow shocks in the distress region but not in the stable region. The optimal policy captures realistic features of debt dynamics, such as active debt management in both directions, interior optimal debt maturity, and dynamics of “fallen angels.”

Option Pricing in Markets with Informed Traders
Yuan Hu,Abootaleb Shirvani,Stoyan Stoyanov,Young Shin Kim,Frank J. Fabozzi,Svetlazor T. Rachev
arXiv

The objective of this paper is to introduce the theory of option pricing for markets with informed traders within the framework of dynamic asset pricing theory. We introduce new models for option pricing for informed traders in complete markets where we consider traders with information on the stock price direction and stock return mean. The Black-Scholes-Merton option pricing theory is extended for markets with informed traders, where price processes are following continuous-diffusions. By doing so, the discontinuity puzzle in option pricing is resolved. Using market option data, we estimate the implied surface of the probability for a stock upturn, the implied mean stock return surface, and implied trader information intensity surface.



Private Information behind Insider Trades: Evidence from Cross Section and Time Series
Chi, Yeguang,Liu, Linchen,Qiao, Xiao
SSRN
We examine the private information associated with insider trades using a Chinese data set. Insider buys positively forecast individual stock returns and insider sales negatively forecast individual stock returns. Classifying insiders as corporate managers and institutional investors, we find that the trades by these two types have different asset pricing implications. Cross-sectionally, stocks more heavily bought by corporate managers have higher average returns compared to their less-bought counterparts, but institutional investor trading has no impact on cross-sectional differences in average returns. The economic value of institutional investors’ trades primarily derives from their time-series return predictability, as the collective buy-to-sell ratio of institutional investors significantly forecasts market returns. In contrast, the buy-to-sell ratio of corporate managers shows no predictive power.

Shallow Neural Hawkes: Non-parametric kernel estimation for Hawkes processes
Sobin Joseph,Lekhapriya Dheeraj Kashyap,Shashi Jain
arXiv

Multi-dimensional Hawkes process (MHP) is a class of self and mutually exciting point processes that find wide range of applications -- from prediction of earthquakes to modelling of order books in high frequency trading. This paper makes two major contributions, we first find an unbiased estimator for the log-likelihood estimator of the Hawkes process to enable efficient use of the stochastic gradient descent method for maximum likelihood estimation. The second contribution is, we propose a specific single hidden layered neural network for the non-parametric estimation of the underlying kernels of the MHP. We evaluate the proposed model on both synthetic and real datasets, and find the method has comparable or better performance than existing estimation methods. The use of shallow neural network ensures that we do not compromise on the interpretability of the Hawkes model, while at the same time have the flexibility to estimate any non-standard Hawkes excitation kernel.



Shareholderism Versus Stakeholderism â€" a Misconceived Contradiction. A Comment on 'The Illusory Promise of Stakeholder Governance' by Lucian Bebchuk and Roberto Tallarita
Mayer, Colin
SSRN
This paper critiques an assessment by Bebchuk and Tallarita (BT) of the relative merits of shareholder and stakeholder governance. BT’s paper argues that stakeholder governance is either nothing more than enlightened shareholder value, or it imposes unmanageable tradeoffs on directors of companies. But trade-offs are ubiquitous not just in stakeholder but also in shareholder governance, and the resulting judgments that are required of directors should not be viewed as an anathema but a fundamental function of a board, without which untenable outcomes result. The complexity that BT see in implementing a stakeholder system reflects a failure to recognize the way in which business routinely makes judgments based on its purposes and values. Purpose and values hold management to account to a degree that enlightened long-term shareholder value cannot. In seeking to demonstrate that directors are not motivated or able to promote anything other than shareholder value in a shareholder-oriented system, BT merely describe the system that they see rather than analyse what it could or should be. The paper therefore fails to provide a benchmark against which it is possible to evaluate either the comparative merits of shareholder and stakeholder systems, or alternative proposals for reform.

Short-Run Health Consequences of Retirement and Pension Benefits: Evidence from China
Plamen Nikolov,Alan Adelman
arXiv

This paper examines the impact of the New Rural Pension Scheme (NRPS) in China. Exploiting the staggered implementation of an NRPS policy expansion that began in 2009, we use a difference-in-difference approach to study the effects of the introduction of pension benefits on the health status, health behaviors, and healthcare utilization of rural Chinese adults age 60 and above. The results point to three main conclusions. First, in addition to improvements in self-reported health, older adults with access to the pension program experienced significant improvements in several important measures of health, including mobility, self-care, usual activities, and vision. Second, regarding the functional domains of mobility and self-care, we found that the females in the study group led in improvements over their male counterparts. Third, in our search for the mechanisms that drive positive retirement program results, we find evidence that changes in individual health behaviors, such as a reduction in drinking and smoking, and improved sleep habits, play an important role. Our findings point to the potential benefits of retirement programs resulting from social spillover effects. In addition, these programs may lessen the morbidity burden among the retired population.



Syndicate Structure, Primary Allocations, and Secondary Market Outcomes in Corporate Bond Offerings
Bessembinder, Hendrik,Jacobsen, Stacey E.,Maxwell, William F.,Venkataraman, Kumar
SSRN
We describe and test hypotheses regarding underwriting syndicate structure, primary placement transactions, and secondary market outcomes for Corporate Bond offerings. We document that perceived deal risk and complexity are determinants of syndicate structure. Consistent with the reasoning that the syndicate obtains valuable information regarding investor interest during book-building, we show that the syndicate “over-allocates”, thereby entering short positions, deals with weaker or more uncertain secondary market demand. We show that while the syndicate incurs trading losses on the short-covering secondary market purchases that support over-allocated deals, these issues are less under-priced, i.e., appreciate less in the aftermarket. We find secondary market spreads are narrower for over-allocated issues, and investigate relations between syndicate structure, primary market allocations, and secondary market pricing.

The ATM Around the Corner - How Financial Development, Access, and Integration Influence Economic Growth and Inequality
Gehrung, Marcel
SSRN
Besides the often mentioned driving factors behind inequality like globalization, demography, technological progress, or the different accumulation of human capital financial development and the structure of the financial sector were long overlooked. Furthermore, the economic analysis of income inequality mostly rests on macroeconomic variables and is often performed for a single country or small samples. However, increased financial access and development work for a significant part on microeconomic levels. Well developed and decentralized financial systems are widely spread across an economy with a high number of bank branches and are readily accessible for economic agents. By pooling savings and acting as delegated monitors, banks improve the credit allocation in such a way, that even people without an initial endowment of wealth can overcome financing restrictions and achieve their entrepreneurial ambitions. By using a more micro-based set for 266 countries over the period of 1960 to 2014, we show that financial development and liberalization in the form of domestic credit to the private sector, a higher number of ATMs, bank accounts, and bank branches increases economic growth and reduces income inequality. We employ a fixed-effects panel regression and system GMM methodology. Especially in the short-run, lower parts of the income distribution benefit from financial development and can improve their incomes and economic growth.

The Costs of Public Audit Oversight: Evidence from the EU
Florou, Annita,Shuai, Yuan
SSRN
We examine the audit pricing consequences of auditor inspections under the public oversight regime in EU. We document an inspections audit fees premium for EU listed companies, whose auditors are inspected by the national Public Oversight Body (POB) in the post-inspection period. More importantly, we exploit the diversity of POBs functioning and inspection processes across EU countries. We find that the inspections-related increase in audit costs is concentrated in POBs with sufficient inspector or overall staff resources; as well as in countries, where inspectors cannot join an audit firm immediately after departing from the POB, the new oversight system is funded by multiple stakeholders, and inspections occur both at the auditor’s and the regulator’s premises. Overall, our study provides evidence suggesting that audit costs increase for clients of inspected auditors but only when the inspection process is potentially more laborious, independent, rigorous and time-consuming.

The Economic Role of Alliances during Industry Shocks
Mantecon, Tomas
SSRN
The market for corporate control plays an important role during industry shocks. However, this market fails in the presence of asymmetric information. I investigate the consequences of market failures for efficient firms that face difficulties to adapt to shocks because of informational frictions. I propose that alliances are a valuable alternative for these firms because ownership-sharing ameliorates informational frictions that induce market failures. I report empirical evidence supporting this hypothesis. Valuation uncertainty and the cost to access external credit increases the odds of establishing alliances during shocks and these alliances create more value than alliances announced in other periods.

The Electronic Evolution of Corporate Bond Dealers
O'Hara, Maureen,Zhou, Xing (Alex)
SSRN
Technology transformed the trading of financial assets but has been slower to come to corporate bond trading. Combining proprietary data from MarketAxess with regulatory TRACE data, we investigate how electronic request for quote (RFQ) trading affects bond dealers and trading more generally. We demonstrate that electronic trading remains fairly small and segmented, but has wide-ranging effects on transaction costs and execution quality in both electronic and voice trading, and the inter-dealer market. We identify features particular to bond markets that have and may continue to limit electronic bond trading growth. We provide an intriguing portrait of a market in transition.

The FDIC Should Not Allow Commercial Firms to Acquire Industrial Banks
Wilmarth, Arthur E.
SSRN
On March 17, 2020, the Federal Deposit Insurance Corporation (“FDIC”) published a proposed rule (the “Proposed ILC Rule”), which would govern applications for deposit insurance, changes in control, and mergers involving FDIC-insured industrial banks and industrial loan companies (“ILCs”). If adopted, the Proposed ILC Rule would open the door to widespread acquisitions of ILCs by commercial firms engaged in industrial, retail, information technology, and other types of nonfinancial activities. In addition, on March 18, 2020, the FDIC approved deposit insurance applications filed by ILCs owned by two commercial firms â€" Square and Nelnet. The FDIC’s issuance of the Proposed ILC Rule and the FDIC’s approvals of Square’s and Nelnet’s applications represent a fundamental change in policy. Those actions effectively reverse the FDIC’s previous policy of barring acquisitions of ILCs by commercial firms. The FDIC imposed an 18-month moratorium on acquisitions of ILCs by commercial firms between July 2006 and January 2008. The Dodd-Frank Act placed a three-year moratorium on such acquisitions between July 2010 and July 2013. The FDIC did not allow any firms engaged in commercial activities to acquire ILCs from July 2006 (when the FDIC imposed its moratorium) until March 2020 (when the agency approved Square’s and Nelnet’s applications). The Proposed ILC Rule does not explain why the FDIC decided to initiate such a major change in policy with potentially transformative effects on our financial system, economy, and society. If adopted, the Proposed ILC Rule would be contrary to the public interest and unlawful for the following reasons: (1) Further acquisitions of ILCs by commercial firms would (a) undermine Congress’s longstanding policy of separating banking and commerce, (b) threaten to inflict large losses on the federal “safety net” for financial institutions during future systemic crises, and (c) pose grave dangers to the stability of our financial system and the health of our economy. (2) Further acquisitions of ILCs by commercial firms â€" including “Big Tech” firms like Alphabet (Google), Amazon, Apple, Facebook, and Microsoft â€" would create toxic conflicts of interest and would also pose serious threats to competition and consumer welfare. (3) The FDIC’s limited supervisory powers over parent companies and other affiliates of ILCs are plainly inadequate to prevent the systemic risks, conflicts of interest, and threats to competition and consumer welfare generated by commercially-owned ILCs. (4) Adoption of the Proposed ILC Rule would be contrary to the public interest factors specified in the Federal Deposit Insurance Act and would also violate the Administrative Procedure Act (“APA”). This article explains why adopting the Proposed ILC Rule would be contrary to the public interest and unlawful. In addition, the FDIC should not adopt the Proposed ILC Rule while our nation is preoccupied with the challenges of responding to the global COVID-19 pandemic. The FDIC should withdraw the Proposed ILC Rule, or postpone any further action on the Rule, until (1) the enormous problems caused by the pandemic have been successfully resolved, and (2) as required by the APA, the FDIC has completed the following actions: (a) explaining the factual, legal, and policy basis for its change in policy on acquisitions of ILCs by commercial firms, and (b) providing public notice of that explanation and affording the public a reasonable opportunity to submit comments on the FDIC’s change in policy and the agency’s stated reasons for making that change. The FDIC should not approve any additional acquisitions of ILCs by commercial firms until all of the foregoing actions have been completed.

The Sensitivity of GCC Firms’ Stock Returns to Exchange Rate, Interest Rate, and Oil Price Volatility
Alenezi, Marim,Alqatan, Dr. Ahmad,Phiri, Obby
SSRN
This study seeks to investigate the sensitivity of stock returns to exchange rate, interest rate and oil price volatility in the Gulf Cooperation Council (GCC) countries. It employs both the multivariate ordinary least square (OLS) regression and the exponential generalized autoregressive conditional heteroscedastic in mean (EGARCH-M) models to analyse the data collected from Bloomberg and DataStream on the GCC countries (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and the United Arab Emirates) for the period January 2007 to June 2012. The study shows that stock returns in GCC countries are influenced by the exchange rate risk, interest rate risk and oil price risk. However, the exposure is highest for exchange rate risk and lowest for interest rate risk. While the effects of these risks were mixed, overall, exchange rate risk and oil price risk showed a positive and significant relationship as compared to the interest rate risk that showed a negative significant effect on firm values. The level of the effect of these risks also differed from country to country. Further, foreign operations and firm size had a significant influence on the extent of the firms’ exposure to all three risks. The study findings suggest that the volatility of stock returns affected by changes in the risk factors could indicate non-prioritisation of risk management by firms. This has implications in terms of consideration of the long-term exposure of firms to these three risks and thus, the need for effective risk management strategies.

The Step Stochastic Volatility Model (SSVM)
Friz, Peter,Pigato, Paolo,Seibel, Jonathan
SSRN
Stochastic Volatility Models (SVMs) are ubiquitous in quantitative finance. But is there a Markovian SVM capable of producing extreme (T^(-1/2)) short-dated implied volatility skew?We here propose a modification of a given SVM "backbone", Heston for instance, to achieve just this - without adding jumps or non-Markovian "rough" fractional volatility dynamics. This is achieved via non-smooth leverage function, such as a step function. The resulting Step Stochastic Volatility Model (SSVM) is thus a parametric example of local stochastic volatility model (LSVM). From an IT perspective, SSVM amounts to trivial modifications in the code of existing SVM implementations. From a QF perspective, SSVM offers new flexibility in smile modelling and towards assessing model risk. For comparison, we then exhibit the market-induced leverage function for LSVM, calibrated with the particle method.

Time Delay and Investment Decisions: Evidence from an Experiment in Tanzania
Plamen Nikolov
arXiv

Attitudes toward risk underlie virtually every important economic decision an individual makes. In this experimental study, I examine how introducing a time delay into the execution of an investment plan influences individuals' risk preferences. The field experiment proceeded in three stages: a decision stage, an execution stage and a payout stage. At the outset, in the Decision Stage (Stage 1), each subject was asked to make an investment plan by splitting a monetary investment amount between a risky asset and a safe asset. Subjects were informed that the investment plans they made in the Decision Stage are binding and will be executed during the Execution Stage (Stage 2). The Payout Stage (Stage 3) was the payout date. The timing of the Decision Stage and Payout Stage was the same for each subject, but the timing of the Execution Stage varied experimentally. I find that individuals who were assigned to execute their investment plans later (i.e., for whom there was a greater delay prior to the Execution Stage) invested a greater amount in the risky asset during the Decision Stage.



Time-Series Forecasting of Mortality Rates using Deep Learning
Perla, Francesca,Richman, Ronald,Scognamiglio, Salvatore,Wuthrich, Mario V.
SSRN
The time-series nature of mortality rates lends itself to processing through neural networks that are specialized to deal with sequential data, such as recurrent and convolutional networks. Although appealing intuitively, a naive implementation of these networks does not lead to enhanced predictive performance. We show how the structure of the Lee Carter model can be generalized, and propose a relatively simple convolutional network model that can be interpreted as a generalization of the Lee Carter model, allowing for its components to be evaluated in familiar terms. The model produces highly accurate forecasts on the Human Mortality Database, and, without further modification, generalizes well to the United States Mortality Database.

Trust and the Value of CSR during the Global Financial Crisis
Berkman, Henk,Li, Michelle,Lu, Helen
SSRN
Lins, Servaes, and Tamayo (2017) (LST) show that during the Global Financial Crisis (GFC) US firms with high corporate social responsibility (CSR) ratings increased in value relative to firms with low CSR ratings. Our study raises questions about the internal and external validity of the inferences in LST. For the similar sample of US stocks, we find no evidence that high CSR firms outperformed low CSR firms during the GFC when we use a calendar-time portfolio analysis that controls for industry, or uses value-weighted portfolios. For a sample of Japanese stocks, we also fail to confirm the results reported in LST.

US Government Bond Liquidity during the COVID-19 Pandemic
Ermolov, Andrey
SSRN
US government bond illiquidity measures began rising during the last week of February 2020. Several of them surpassed the Great Recession levels during the second week of March. The illiquidity spikes do not seem to match with proposed explanatory events. The illiquidity measures of the most actively traded securities declined after the first Federal Reserve intervention, but normalizing the liquidity of other bonds required the second intervention. Liquidity measures were mostly back to normal by late April. The inflation-linked bonds illiquidity spike was milder but more persistent and less correlated with Federal Reserve actions compared to nominal Treasuries.

Uncovering the mesoscale structure of the credit default swap market to improve portfolio risk modelling
Ioannis Anagnostou,Tiziano Squartini,Diego Garlaschelli,Drona Kandhai
arXiv

One of the most challenging aspects in the analysis and modelling of financial markets, including Credit Default Swap (CDS) markets, is the presence of an emergent, intermediate level of structure standing in between the microscopic dynamics of individual financial entities and the macroscopic dynamics of the market as a whole. This elusive, mesoscopic level of organisation is often sought for via factor models that ultimately decompose the market according to geographic regions and economic industries. However, at a more general level the presence of mesoscopic structure might be revealed in an entirely data-driven approach, looking for a modular and possibly hierarchical organisation of the empirical correlation matrix between financial time series. The crucial ingredient in such an approach is the definition of an appropriate null model for the correlation matrix. Recent research showed that community detection techniques developed for networks become intrinsically biased when applied to correlation matrices. For this reason, a method based on Random Matrix Theory has been developed, which identifies the optimal hierarchical decomposition of the system into internally correlated and mutually anti-correlated communities. Building upon this technique, here we resolve the mesoscopic structure of the CDS market and identify groups of issuers that cannot be traced back to standard industry/region taxonomies, thereby being inaccessible to standard factor models. We use this decomposition to introduce a novel default risk model that is shown to outperform more traditional alternatives.



VAT tax gap prediction: a 2-steps Gradient Boosting approach
Giovanna Tagliaferri,Daria Scacciatelli,Pierfrancesco Alaimo Di Loro
arXiv

Tax evasion is the illegal evasion of taxes by individuals, corporations, and trusts. The revenue loss from tax avoidance can undermine the effectiveness and equity of the government policies. A standard measure of tax evasion is the tax gap, that can be estimated as the difference between the total amounts of tax theoretically collectable and the total amounts of tax actually collected in a given period. This paper presents an original contribution to bottom-up approach, based on results from fiscal audits, through the use of Machine Learning. The major disadvantage of bottom-up approaches is represented by selection bias when audited taxpayers are not randomly selected, as in the case of audits performed by the Italian Revenue Agency. Our proposal, based on a 2-steps Gradient Boosting model, produces a robust tax gap estimate and, embeds a solution to correct for the selection bias which do not require any assumptions on the underlying data distribution. The 2-steps Gradient Boosting approach is used to estimate the Italian Value-added tax (VAT) gap on individual firms on the basis of fiscal and administrative data income tax returns gathered from Tax Administration Data Base, for the fiscal year 2011. The proposed method significantly boost the performance in predicting with respect to the classical parametric approaches.



Valuation for Early-Stage Technology Companies
Jones, Kingsley
SSRN
The valuation of early-stage technology companies is challenging due to: the lack of clear operating history; disruptive new business models; a rapidly changing landscape for new entrants; and the unpredictable competitive push-back of powerful incumbent players. Revenue based multiples are standard, but these need to be reconciled with a terminal valuation stuck on profitability. There is a simple method to do this, we call it the "Golden Rule", which embodies simple accounting identities that tie present value via sales uplift over five years to a future profit number struck on net margin. This can be used to square valuations against differing profitability metrics by industry.

What’s Wrong With Modern Credit Risk Management?
Voloshyn, Ihor
SSRN
This paper explores the processes of provisioning a bank’s allowance for credit losses from the point of statistics and insurance. It is shown the similarity of protection against credit risk by banks and insured risk by insurance companies. It is shown that the banking protection against credit risk implies an implicit hidden insurance contract. An approach has been developed to address this shortcoming. So, to increase the transparency of lending, a borrower and a bank should sign an explicit insurance contract. Such a contract should negotiate a credit premium and an insurance amount. The agreed-upon insurance amount allows dropping the burden on a borrower in a case of its default. The consistent use of the principle “An allowance for expected credit losses should fully cover realized losses within the expected ones” allows also dropping the burden on a bank. As far as, the bank does not bear any additional expenses for the provisioning of allowance in a case of borrowers’ defaults. A bank's capital should cover a part of credit losses that exceed the expected ones. It is considered the influence of fiscal and monetary policies on the systemic level of defaults in the economy.

eXtensible Business Reporting Language: A Review and Directions for Future Research
Hoitash, Rani,Hoitash, Udi,Morris, Landi
SSRN
This study seeks to advance research related to eXtensible Business Reporting Language (XBRL). XBRL is an open standard for reporting structured financial information which enables the efficient gathering of data and automated comparison of financial information over time and across firms. To encourage research using XBRL we describe the unparalleled richness of XBRL data and sources from which it can be obtained. We follow with a review of the literature, beginning with research examining the adoption of XBRL and the use of the data by capital market participants. Next, we discuss data quality concerns that may impact the use of XBRL data, followed by a discussion of how auditors can use XBRL data and their potential role in the assurance of the data. We then present burgeoning literature that uses meta and underlying XBRL data to examine different financial statement characteristics and disclosure properties. Based on the review of the literature, we identify topics with the greatest potential for future research. Overall, we strongly believe that using and investigating XBRL presents ample research opportunities. Data Availability: Data are available from http://www.xbrlresearch.com.