# Research articles for the 2019-09-05

A Latent Factor Model for the Cross-Section of Option Returns
BÃ¼chner, Matthias,Kelly, Bryan T.
SSRN
We apply a latent factor modeling approach to equity index options in order to develop a better understanding for the risk-reward trade-off in option markets. Our method, Instrumented Principal Components (IPCA), recovers latent factors by instrumenting conditional loadings with option characteristics. Contrary to the underlying, options are closely defined through their characteristics as the contract migrates through time and moneyness. We find that five latent factors instrumented with relevant option characteristics explain more than 90% of the empirically observed variation in a panel of monthly S&P 500 option returns from 1996 to 2017. Simultaneously, the same set of factors is also at least as mean-variance efficient as extant observable option factor models. The latent IPCA factors are interpretable and relate to jump, maturity and volatility risks.

A Loan-Level Analysis of Bank Lending in Mexico
CantÃº, Carlos,Lobato, Roberto,LÃ³pez, Calixto,Lopez-Gallo, Fabrizio
SSRN
We use loan-level data from the Mexican credit registry to study how bank-specific characteristics in influence credit supply. We explore how these characteristics affect the transmission of monetary policy and their role in building banks' resilience to external shocks. Then, we compare the response of the credit supply of foreign subsidiaries to that of domestic banks. Finally, we study the impact of other micro characteristics on the credit supply and their influence on the transmission of shocks. Our results highlight the importance of banks' strong balance sheets and stable sources of funding for the provision of credit in Mexico. In general, these characteristics shelter banks from shocks.

A memory-based method to select the number of relevant components in Principal Component Analysis
Anshul Verma,Pierpaolo Vivo,Tiziana Di Matteo
arXiv

We propose a new data-driven method to select the optimal number of relevant components in Principal Component Analysis (PCA). This new method applies to correlation matrices whose time autocorrelation function decays more slowly than an exponential, giving rise to long memory effects. In comparison with other available methods present in the literature, our procedure does not rely on subjective evaluations and is computationally inexpensive. The underlying basic idea is to use a suitable factor model to analyse the residual memory after sequentially removing more and more components, and stopping the process when the maximum amount of memory has been accounted for by the retained components. We validate our methodology on both synthetic and real financial data, and find in all cases a clear and computationally superior answer entirely compatible with available heuristic criteria, such as cumulative variance and cross-validation.

An Experiment on Network Density and Sequential Learning
Krishna Dasaratha,Kevin He
arXiv

We conduct a sequential social learning experiment where subjects guess a hidden state after observing private signals and the guesses of a subset of their predecessors. A network determines the observable predecessors, and we compare subjects' accuracy on sparse and dense networks. Later agents' accuracy gains from social learning are twice as large in the sparse treatment compared to the dense treatment. Models of naive inference where agents ignore correlation between observations predict this comparative static in network density, while the result is difficult to reconcile with rational-learning models.

An arbitrage-free conic martingale model with application to credit risk
Cheikh Mbaye,Frédéric Vrins
arXiv

Conic martingales refer to Brownian martingales evolving between bounds. Among other potential applications, they have been suggested for the sake of modeling conditional survival probabilities under partial information, as usual in reduced-form models. Yet, conic martingale default models have a special feature; in contrast to the class of Cox models, they fail to satisfy the so-called \emph{immersion property}. Hence, it is not clear whether this setup is arbitrage-free or not. In this paper, we study the relevance of conic martingales-driven default models for practical applications in credit risk modeling. We first introduce an arbitrage-free conic martingale, namely the $\Phi$-martingale, by showing that it fits in the class of Dynamized Gaussian copula model of Cr\'epey et al., thereby providing an explicit construction scheme for the default time. In particular, the $\Phi$-martingale features interesting properties inherent on its construction easing the practical implementation. Eventually, we apply this model to CVA pricing under wrong-way risk and CDS options, and compare our results with the JCIR++ (a.k.a. SSRJD) and TC-JCIR recently introduced as an alternative.

Bank Market Power and Firm Finance: Evidence from Bank and Loan Level Data
Gomez-Gonzalez, Jose E,Tamayo Tobon, Cesar Eduardo,, Oscar M. Valencia
SSRN
We present new measures of market power for the banking industry in Colombia and estimate their effect on the cost of credit for non-financial firms.Our results suggest that bank competition increased during the 2006-2008 periodâ€"even as concentration increasedâ€"but decreased thereafter. Using a unique combination of loan, firm and bank-level datasets we are also able to show that banks loosing overall market powerâ€"measured by the average price-cost marginâ€"decrease interest rates to small firms, but increase rates to firms with which they have the oldest credit relationships. This suggests (i) the existence of market power that is specific to the bank-firm relationship (i.e., informational lock-in and hold-up problems due to switching costs), and (ii) that size may be capturing other firm attributes such as observable risk, scale effects or implicit collateral.

Banksâ€™ Business Model and Credit Supply in Chile: The Role of a State-Owned Bank
Biron, Miguel,CÃ³rdova, Felipe,Lemus, Antonio
SSRN
During the Global Financial Crisis, banks suffered losses on a scale not witnessed since the Great Depression, partly due to two major structural developments in the banking industry; deregulation combined with financial innovation. In the aftermath of the financial crisis, the regulatory response concentrated on the Basel III recommendations, raising core capital requirements for banking institutions, which affected their business models and funding patterns. Consequently, these changes have had significant implications for how banks grant loans, how they react to monetary policy shocks, and how they respond to external shocks. We find evidence of significant interactions between the bank lending channel and both monetary and global shocks in Chile. These links have changed significantly after the Global Financial Crisis. In particular, they have been shaped by the counter-cyclical behavior of a state-owned bank.

Believing the Bot - Model Risk in the Era of Deep Learning
Richman, Ronald,von Rummell, Nicolai,Wuthrich, Mario V.
SSRN
Deep Learning models are currently being introduced into business processes to support decision-making in insurance companies. At the same time model risk is recognized as an increasingly relevant field within the management of operational risk that tries to mitigate the risk of poor business decisions because of flawed models or inappropriate model use. In this paper we try to determine how Deep Learning models are different from established actuarial models currently in use in insurance companies and how these differences might necessitate changes in the model risk management framework. We analyse operational risk in the development and implementation of Deep Learning models using examples from pricing and mortality forecasting to illustrate specific model risks and controls to mitigate those risks. We discuss changes in model governance and the role that model risk managers could play in providing assurance on the appropriate use of Deep Learning models.

Yasuyuki Kusuda
arXiv

In this paper, we extend the model of Gao and Su (2016) and consider an omnichannel strategy in which inventory can be replenished when a retailer sells only in physical stores. With "buy-online-and-pick-up-in-store" (BOPS) having been introduced, consumers can choose to buy directly online, buy from a retailer using BOPS, or go directly to a store to make purchases without using BOPS. The retailer is able to select the inventory level to maximize the probability of inventory availability at the store. Furthermore, the retailer can incur an additional cost to reduce the BOPS ordering lead time, which results in a lowered hassle cost for consumers who use BOPS. In conclusion, we found that there are two types of equilibrium: that in which all consumers go directly to the store without using BOPS and that in which all consumers use BOPS.

Can a Deliberative Mindset Prompt Reduce Investorsâ€™ Reliance on Fake News?
Grant, Stephanie M.,Hodge, Frank D.,Seto, Samantha C.
SSRN
We examine if prompting investors to be in a deliberative mindset reduces their reliance on financial news when the news is later revealed to be fake. Consistent with theory, results show that investors reduce their reliance on news revealed to be fake, and that this reduction is magnified for investors who were previously prompted to be in a deliberative mindset. Importantly, results also reveal that prompting investors to be in a deliberative mindset does not affect their judgments when the news is later revealed to be true. Our study contributes to research on fake news in the financial markets and has practical implications for investors when evaluating news that may be true or fake.

Commodity Option Pricing Efficiency before Black Scholes Merton
Chambers, David,Saleuddin, Rasheed
SSRN
It is often thought that the arrival of the Black Scholes Merton (BSM) model of option pricing in the early 1970s allowed traders to understand how to price and value options with greater precision. Yet, our study suggests that interwar commodity option traders may have been able to intuit â€˜fairâ€™ value and to adjust their prices to changes in the market environment well before the advent of this innovative model. A scarcity of historical price data has limited empirical tests of option price efficiency well before BSM to prior studies of stock options in the 1870s and the early twentieth century which reach contrasting findings. This study deals with option pricing in a different market â€" commodities â€" during the interwar period. We conclude that option prices were closer to their BSM theoretical values than suggested by prior studies. Institutional differences between interwar commodity options market and stock option markets in the 1870s and the early twentieth century may partly account for this result. Furthermore, we find that interwar option prices were no more mispriced and were as sensitive to changes in volatility â€" the key valuation parameter in the BSM model â€" as in modern times.

Corporate Social Responsibility: An Umbrella or a Puddle on a Rainy Day? Evidence Surrounding Corporate Financial Misconduct
Bae, John,Choi, Wonik,Lim, Jongha
SSRN
We examine the way a fraudulent firmâ€™s preâ€ and postmisconduct corporate social responsibility engagement is associated with its stock performance to investigate the reputational role of corporate social responsibility (CSR). In the short term, firms with good CSR performance suffer smaller market penalties upon the revelation of financial wrongdoing, supporting the buffer effect, as opposed to the backfire effect, of a good social image. We also find that the misbehaving firmsâ€™ postâ€misconduct CSR efforts are negatively associated with delisting probabilities, and positively with stock returns. These findings support the argument that increasing postâ€crisis CSR engagement can be an effective remedy for a damaged reputation.

Determinants of Credit Growth and the Bank-Lending Channel in Peru: A Loan Level Analysis
SSRN
This paper uses loan-level data from Peru's credit registry to determine how the role of bank-specific characteristics (i.e. bank size, liquidity, capitalization, funding, revenue, and profitability) may affect the supply of credit in domestic and foreign currency. Also, we analyze how these characteristics affect the banks' response to monetary policy shocks. Finally, we assess how the link between bank-specific characteristics and credit supply is affected by global financial conditions and commodity price changes. Our results show that well-capitalized, high-liquidity, low-risk, more profitable banks tend to grant more credit, especially in domestic currency. Moreover, we found evidence that reserve requirements both in domestic and foreign currency are effective in curbing domestic credit in Peru, giving support to the BCRP's active use of RRs as a macroprudential tool to smooth out the credit cycle. Last, we found that banks with more diversified funding sources are less affected after a negative commodity price change.

Do Exchange Traded Funds affect Corporate Cash Holdings?
Lin, Beiqi,Tan, Kelvin Jui Keng,Zhang, Lei
SSRN
We examine the effects of corporate ownership by exchange traded funds (ETFs) on corporate cash holdings. Using a panel regression, we show that firms increase their cash holdings to hedge against higher anticipated stock risks induced by ETFs. To establish a causality interpretation, we use the exogenous changes to membership in the Russell index as an instrument for ETF ownership. We further show that shareholders place a higher value on additional cash held by firms with higher ETF ownership and these findings are more pronounced in financially constrained firms and good governance firms. Overall, our results suggest that firms hold more precautionary cash to mitigate future funding needs due to higher anticipated risks.

Do Sell-Side Analysts Say Buy While Whispering Sell?
Shi, Yushui
SSRN
We investigate whether sell-side stock analysts disclose different information to mutual fund managers than to the public. We focus on one specific identifiable phenomenon that analysts tell the public to buy while whispering fund managers to sell. We measure the likelihood of such behaviors based upon the percentage of managersâ€™ selling stocks that analysts recommend to buy. Using mutual fund managers voting for sell-side analysts in a Chinese â€œstar analystâ€ competition as a proxy for managersâ€™ evaluations of analysts, we find that managers are more likely to vote for the analysts who exhibit more say-buy-whisper-sell behaviors with these managers. The positive relationship between the managersâ€™ voting and the analystsâ€™ say-buy-whisper-sell behaviors supports our hypothesis that analysts provide private information to fund managers. In contrast, an alternative hypothesis where managers and analysts respond independently to common market information predicts a negative relationship. Consistent with fund managers receiving precise information from analysts, we find that, among analystsâ€™ buy recommendations, stocks sold by the connected managers â€" who vote for the analysts â€" underperform stocks bought by these managers. Moreover, the stocks sold by the connected managers still have positive abnormal returns on the recommendation dates, but followed by negative abnormal returns, suggesting a form of information asymmetry caused by analystsâ€™ differential disclosure behaviors.

ECBâ€™s Unconventional Monetary Policy and Cross-Financial-Market Correlation Dynamics
Kenourgios, Dimitris,Drakonaki, Emmanouela,Dimitriou, Dimitrios I.
SSRN
This paper examines the effects of the unconventional monetary policy (UMP) launched by the European Central Bank on the cross-market correlations between bond, stock and currency forward markets. Using a dynamic conditional correlation analysis and several robustness tests, we investigate possible differences on the correlation dynamics across four UMP periods and across a range of developed countries and emerging market economies. The empirical results indicate a spillover effect on both developed and emerging markets, although this impact is not identical across assets and countries. We also find that the new UMP phase started in 2014 has a more prominent impact, highlighting differences on the impact between the earlier and the new wave of UMPs and across cross-market correlations.

EVA Approach versus BCG Approach: Evidence from Tehran Stock Exchange (TSE)
Maleki Nia, Nahid ,Alouj, Hosein Asgari,Pireivatlou, Ayyoub Sarafraz
SSRN
Financial performance measurement of companies in decision-making process is one of the most important subjects in financial and economic scope regarding development and importance of market role. Economic value added (EVA), refined economic value added (REVA), market value added (MVA) as EVA-based measures, also Cash Value Added(CVA) and Cash Flow Return on Investments(CFROI) as BCG-based measures and traditional performance measures(ROI,ROE and EPS) are among the most important criteria of financial performance measurement. The most important purpose of the present research is to make clear the theoretical indices of financial performance measurement, test the relationship between these indices with intrinsic value of firm and offer necessary evidences using simple and multivariate regression and compared by rank order of adjusted R2 in order to get appropriate performance measurement and to help the Iranian capital market participants to make rational decision in investment process. Finding shows although the contributions of measures are statistically significant separately, all are not economically significant when combined into the various measures, also explains traditional accounting measures are not able outperform VBM indicators and the EVA-based measures are able to outperform the BCG -based measures.

Edgar Lawrence Smithâ€™s Contributions to Financial Economics
Woods, J.E.
SSRN
In 1924, Edgar Lawrence Smith published a Monograph in which he presented evidence aimed at overturning the conventional view that Equities were speculative and Bonds were the only longâ€"term investments. This was immediately so successful that such eminent commentators as Irving Fisher and Benjamin Graham agreed that the Monograph had had a material impact on market psychology, playing an instrumental role in The Great Crash. In this article, we examine Smithâ€™s approach in detail, arguing that he made significant, enduring contributions to finance theory, empirical finance and portfolio management practice. He was influential in creating the Cult of the Equity, providing the basis for subsequently identifying the Equity Risk Premium and introducing a risk metric and equallyâ€"weighted portfolios. His influence is felt nowadays not only in the methodology employed in empirical work but also the conventional approach to portfolio management, which is based on his blueâ€"print.

Hedging U.S. Metals & Mining Industryâ€™s Credit Risk With Industrial and Precious Metals
SSRN
This study examines the conditional correlation and the resulting optimal hedge ratios between the Credit Default Swap (CDS) spreads of the U.S. metal and mining industries, and the prices of copper, platinum, silver and gold using the daily date from December 14, 2007 to August 18, 2018. It compares volatility and conditional correlation of the CDSs and the metal prices by employing multivariate GARCH family models which capture distinct characteristics of financial time series. It utilizes rolling window estimation techniques and constructs the one-step-ahead out-of-sample forecasts for the dynamic conditional correlations and thereafter the optimal hedge ratios. In general, our results show that copper provides the best possible hedge for dealing with the U.S. metals and mining industriesâ€™ credit risks. Our results are robust under alternate model specifications, choice of model refits and distributional assumptions.

How Do Bank-Specific Characteristics Affect Lending? New Evidence Based on Credit Registry Data from Latin America
CantÃº, Carlos,Claessens, Stijn,Gambacorta, Leonardo
SSRN
This paper focuses on the recent changes in banking systems and how bank-specific characteristics have affected credit supply in five Latin American countries (Brazil, Chile, Colombia, Mexico and Peru). We use detailed credit registry data and apply a common empirical strategy. Since data confidentiality prevents the pooling of the data, we use meta-analysis techniques to summarise the results. We find that large and well-capitalised banks with low risk indicators, stable sources of funding, and a commercial business model generally supply more credit. Such banks are also more sheltered from monetary and global shocks, with the role of specific characteristics varying by the type of shock.

Interest Rate Risk of Corporate Bond Prices on Bombay Stock Exchange (BSE) â€"Empirical Test of the Duration, Modified Duration and Convexity
Maleki Nia, Nahid ,Alouj, Hosein Asgari,Pireivatlou, Ayyoub Sarafraz
SSRN
Duration and convexity are important measures in fixed-income portfolio management and help develop methodologies in interest rate risk management. This article presents valuation of corporate Bonds on Bombay Stock Exchange (BSE) and empirical test of duration, modified duration and convexity of the corporate bonds at BSE in order to determine sensitivity of bonds prices on interest rate changes. The sensitivity of corporate Bonds in BSE on interest rate changes is tested and determined that convexity is more accurate measure as approximation of bond prices changes than duration. The main goal of this study is to determine how non-linear estimation models fit in case of corporate bonds that are traded on BSE and to verify whether they offer reliable results compared with linear regression model on BSE. Also the most relevant contribution of the paper is to obtain a better curve estimation during the time period of March, 2009 -June, 2012 for duration and convexity exposures that contribute to the marginal increment of the coefficient of determination and the construction of a best nonlinear regression model that overcomes the linearity models.

Interest Rate Risk of Zero-Coupon Bond Prices on Bombay Stock Exchange (BSE) â€"Empirical Test of the Duration, Modified Duration, Convexity and Immunization Risk
Alouj, Hosein Asgari,Maleki Nia, Nahid ,Amiri, Seyed Masoud Sajjadian
SSRN
Duration and convexity are important measures in fixed-income portfolio management and help develop methodologies in interest rate risk management. This article presents empirical test of duration and convexity of Zero-Coupon Bonds( ZCBs )at BSE in order to determine sensitivity of ZCBs prices on interest rate changes. The sensitivity of ZCBs in BSE on interest rate changes is tested and determined that convexity is more accurate measure as approximation of ZCBs prices changes than duration. The empirical results provide evidence that first duration is an increasing function of the interest rate and next there is no relationship between convexity and interest rate. The estimated percentage changes in ZCBs price using duration decrease by raising the percentage change in interest rate and we have non-parallel shift in lines for different level of duration. By non-parallel shifting of duration downward, the percentage change using only duration decreases and indicates higher negative difference and hence higher sensitivity at higher duration levels. As the interest rate increases the percentage change in ZCBs price using duration and convexity increases and again we have non-parallel shift in lines for different level of duration. By non-parallel shifting of duration upward, the percentage change using both duration and convexity increases and indicates higher positive difference and hence higher sensitivity at higher duration levels and by non-parallel shifting of duration downward, the percentage change using both duration and convexity decreases and indicates higher negative value and hence higher sensitivity at shorter duration levels. Also it has tested empirically whether convexity is return enhancing or return diminishing. Results of empirical tests over time periods under consideration show ZCBs convexity to be either significantly or negatively related to ex ante ZCBs returns. Further, the magnitude of ZCBs convexity is shown to be related indirectly and significantly to the immunization risk inherent in a bond portfolio. The main goal of this study is to determine how non-linear estimation models fit in case of ZCBs that are traded on BSE and to verify whether they offer reliable results compared with linear regression model on BSE. Also the most relevant contribution of the paper is to obtain a better curve estimation during the time period of March, 2009 -June, 2012 for duration and convexity exposures that contribute to the marginal increment of the coefficient of determination and the construction of a best nonlinear regression model that overcomes the linearity models.

Interest Rate Risk of Zero-Coupon Bond Prices on National Stock Exchange (NSE) â€" Empirical Test of the Duration, Modified Duration, Convexity and Immunization Risk
Maleki Nia, Nahid ,Alouj, Hosein Asgari,Pireivatlou, Ayyoub Sarafraz
SSRN
Duration and convexity are important measures in fixed-income portfolio management and help develop methodologies in interest rate risk management. This article presents empirical test of duration and convexity of Zero-Coupon Bonds( ZCBs )at NSE in order to determine sensitivity of ZCBs prices on interest rate changes. The sensitivity of ZCBs in NSE on interest rate changes is tested and determined that convexity is more accurate measure as approximation of ZCBs prices changes than duration. The empirical results provide evidence that first duration is an increasing function of the interest rate and next the convexity is an increasing function of interest rate for short maturities and duration. The estimated percentage changes in ZCBs price using duration decrease by raising the percentage change in interest rate and we have non-parallel shift in lines for different level of duration. By non-parallel shifting of duration downward the percentage change increases and indicates higher difference and hence higher sensitivity at higher duration levels. As the interest rate increases the percentage change in ZCBs price using duration and convexity increases and again we have non-parallel shift in lines for different level of duration. By nonparallel shifting of duration upward the percentage change increases and indicates higher difference and hence higher sensitivity at higher duration levels. It has tested empirically whether convexity is return enhancing or return diminishing. Results of empirical tests over time periods under consideration show ZCBs convexity to be either insignificantly or negatively related to ex ante ZCBs returns. Further, the magnitude of ZCBs convexity is shown to be related indirectly and insignificantly to the immunization risk inherent in a bond portfolio. The main goal of this study is to determine how non-linear estimation models fit in case of ZCBs that are traded on NSE and to verify whether they offer reliable results compared with linear regression model on NSE. Also the most relevant contribution of the paper is to obtain a better curve estimation during the time period of March, 2009 -June, 2012 for duration and convexity exposures that contribute to the marginal increment of the coefficient of determination and the construction of a best nonlinear regression model that overcomes the linearity models.

Machine Learning in Least-Squares Monte Carlo Proxy Modeling of Life Insurance Companies
Anne-Sophie Krah,Zoran Nikolić,Ralf Korn
arXiv

Under the Solvency II regime, life insurance companies are asked to derive their solvency capital requirements from the full loss distributions over the coming year. Since the industry is currently far from being endowed with sufficient computational capacities to fully simulate these distributions, the insurers have to rely on suitable approximation techniques such as the least-squares Monte Carlo (LSMC) method. The key idea of LSMC is to run only a few wisely selected simulations and to process their output further to obtain a risk-dependent proxy function of the loss. In this paper, we present and analyze various adaptive machine learning approaches that can take over the proxy modeling task. The studied approaches range from ordinary and generalized least-squares regression variants over GLM and GAM methods to MARS and kernel regression routines. We justify the combinability of their regression ingredients in a theoretical discourse. Further, we illustrate the approaches in slightly disguised real-world experiments and perform comprehensive out-of-sample tests.

Machine Learning on EPEX Order Books: Insights and Forecasts
Simon Schnürch,Andreas Wagner
arXiv

This paper employs machine learning algorithms to forecast German electricity spot market prices. The forecasts utilize in particular bid and ask order book data from the spot market but also fundamental market data like renewable infeed and expected demand. Appropriate feature extraction for the order book data is developed. Using cross-validation to optimise hyperparameters, neural networks and random forests are proposed and compared to statistical reference models. The machine learning models outperform traditional approaches.

Monetary Policy Surprises and Employment: Evidence from Matched Bank-Firm Loan Data on the Bank Lending-Channel
Gonzalez, Rodrigo
SSRN
This paper investigates the bank lending-channel of monetary policy (MP) surprises. To identify the effects of MP surprises on credit supply, I take the changes in interest rate derivatives immediately after each MP announcement and bring this high-frequency identification strategy to comprehensive and matched bank-firm data from Brazil. The results are robust and stronger than those obtained with Taylor residuals or the reference rate. Consistently with theory, heterogeneities across financial intermediaries, e.g. bank capital, are relevant. Firms connected to stronger banks mitigate about one third of the effects of contractionary MP on credit and about two thirds on employment.

New Exercises in Decomposition Analysis
Woods, J.E.
SSRN
Decomposition analysis, which breaks down the Total Return on an asset into constituents of Income Yield, Income Growth and the Revaluation Effect, can be used prospectively and retrospectively. To date, it has been mainly applied retrospectively to Equities. In this article, we break new ground, demonstrating that, with appropriate data series, it can be extended to Bonds, which means that Equity and Bond returns and their constituents can now be compared on a likeâ€"forâ€"like basis. Empirical analysis of UK Index data since 1976 produces some unexpected results on Fixed Interest and Indexâ€"Linked Gilts: for example, throughout the period, the Revaluation Effect has been a consistently significant contributor to the Total Returns of both classes and at a much higher average level than that for Equities; also, the Revaluation Effect for Indexâ€"Linked Gilts has recently been at an unprecedented level for any asset class. Seeking to explain them, we examine the role of regulatory activity, arguing that it has created a dangerous dynamic on unsound foundations. We demonstrate that our method of analysis does not consist only of technical operations devoid of practical applications but actually enables us to address important issues in economics and political economy.

Persistent Predictors and the Cross-Section of Stock Returns
Basu, Devraj,Szymanowska, Marta
SSRN
We show that when returns are predictable, persistent predictors, known to bias time-series predictive regressions, also bias the estimation of the cross-sectional moments of asset return distribution, especially the variance-covariance matrix of returns. Hence, they also bias the estimation of the various stochastic discount factor bounds, Shanken's (1985) cross-sectional regression test statistic, and Hansen and Jagannathan's (1997) distance measure, except when conditioning information is used efficiently. However, the empirical distributions of these statistics are biased, even with efficient use of conditioning information. We define a test statistic that is immune to this bias and shows consistent results across the persistence levels in our simulations.

Rational Explanation for Rule-of-Thumb Practices in Asset Allocation
Simaan, Majeed,Simaan, Yusif
SSRN
Naive asset allocation and other ad-hoc techniques are commonly practiced by fund managers in the industry. Such strategies, however, are deemed mean-variance (MV) sub-optimal according to modern portfolio theory. Nonetheless, taking estimation risk into considerations, such practices are consistent with rational theory. In practice, the potential advantage of MV optimization is weighed against the severity of estimation risk. This paper proposes a set of decision rules to determine the optimal fund under estimation risk. A mixed strategy that deploys the proposed decision rules implies a convex improvement in terms of out-of-sample Sharpe-ratio.

Super-Normal Profit in Real Estate Development
Geltner, David,Kumar, Anil,Van de Minne, Alex
SSRN
This paper explores the question of whether real estate development projects systematically present positive net present value (NPV) and therefore, provide super-normal profit. Such projects are the products of a business operation that governs the exercise of the real call option on development that is represented by developable land. We find that super-normal profits do tend to exist in the investment property development projects produced by publicly-traded equity real estate investment trusts (REITs), an important sector in the stock market. Such REIT development typically produces over \$30 billion of capital formation per year in the US, some 20% of all development of investment properties. We find that REITs with higher development investment present significantly higher price-to-earnings ratios, as compared to otherwise similar firms. Over the 1998-2018 period, the P/E of a representative REIT increases by a factor of 13.3 as a function of its ratio of development assets to total assets, even after controlling for the general Tobin's-Q ratio (market/book value) of the firm. For the typical REIT this equates to a magnitude of development project positive NPV equal to 46% of the costs of the development assets. This positive NPV is at the firm level, therefore net of overhead and search costs associated with the real estate development business operation. The positive NPV appears to be associated primarily with the stock marketâ€™s valuation of contemporary construction projects in progress, but also significantly from the value land held for future development. The magnitude of this value creation process suggests either that the commercial real estate development industry tends to be broadly characterized by super-normal profits, or that there is a beneficial capital allocational efficiency effect of the stock market in attracting, supporting or cultivating firms that are particularly successful in that industry. We also explore some correlates of the price/earnings effect, and find that super-normal profits from development are more likely to be earned by REITs that are headquartered in larger metropolitan areas.

Survival investment strategies in a continuous-time market model with competition
Mikhail Zhitlukhin
arXiv

We consider a stochastic game-theoretic model of an investment market in continuous time with short-lived assets and study strategies, called survival, which guarantee that the relative wealth of an investor who uses such a strategy remains bounded away from zero. The main results consist in obtaining a sufficient condition for a strategy to be survival and showing that all survival strategies are asymptotically close to each other. It is also proved that a survival strategy allows an investor to accumulate wealth in a certain sense faster than competitors.

Tail Risk Targeting: Target VaR and CVaR Strategies
Rickenberg, Lars
SSRN
We present dynamic trading strategies that target a predefined level of risk measured by volatility, Value-at-Risk (VaR) or Conditional-Value-at-Risk (CVaR). Recent studies have shown that volatility targeting increases the risk-adjusted performance and heightens utility gains for mean-variance investors. We find that downside risk targeting outperforms volatility targeting in terms of a higher Sharpe Ratio, better drawdown protection and higher utility gains for mean-variance, CRRA and loss-averse investors. In particular, a loss-averse investor is not willing to pay a positive fee to switch from a static portfolio to a volatility managed strategy, whereas this investor would pay a fee of 18% per year to have access to the downside risk managed strategy. We also find that the performance of risk targeting can further be enhanced by switching between volatility and CVaR targeting based on estimates of whether the market will be in a bull or bear regime.

The Economic Consequences of Criminal Firms
Fabrizi, Michele,Malaspina, Patrizia,Parbonetti, Antonio
SSRN
This paper investigates the economic consequences of firms connected to organized crime (criminal firms) and shows that when a criminal firm is eliminated from an industry, the performance of non-criminal competitors significantly increases. We also show that the positive effect on the performance of non-criminal competitors after the elimination of the criminal competitor includes improved efficiency and reduced procurement costs. Finally, we document that financially constrained firms benefit the most from the elimination of the criminal competitors and that the presence of criminal firms reduces the level of investment of peers firms.

SSRN
We provide the first aggregate perspective on the evolution of mutual fund offerings worldwide. Applying textual analysis to the names of over 39,000 equity mutual funds sold in 77 different countries between 1931 and 2016, we find that the dimensionality of the fund menu is small: 20 common words appear in over 50% of the fund names, and 10 categories are sufficient to classify over 85% of all funds. Moreover, the menu of funds available in each country converges over time to a common (â€œglobalâ€) menu. We trace this surprisingly simple and uniform process of global menu convergence to the actions of individual fund families who follow similar growth paths: small families start by offering funds with more unique names but progressively conform to the main style categories as they grow. Our results shed new light on the aggregate process of financial innovation and the industrial organization of the asset management industry that appears to produce the same â€œwholesaleâ€ menu around the world.

The Ownership Structure of Private Firms: Concentration and Persistence
BÃ¸hren, Ã˜yvind,Iancu, Dianaâ€Cristina,Radulescu, Georgiana,StrÃ¸m, R. Ã˜ystein
SSRN
We find that ownership concentration is much larger in private firms than in public firms, much more persistent, and changes more once change happens. Analyzing the population of Norwegian firms during fifteen years, we show that the average largest owner of a private (public) firm holds 49% (26%) of the equity, holds the same stake in two consecutive years in 82% (14%) of the cases, and alters the stake by 9 (8) percentage units when the stake changes. These differences are greater when the largest owner is a family. This evidence suggests that control rights in private firms provide particularly high benefits that are costly to trade. We use system GMM to show that the strong persistence of ownership makes past ownership dominate any other determinant of current ownership proposed in the literature, and that the relationship becomes highly misleading if we use economic models or econometric techniques that ignore ownership persistence. These findings also suggest that ownership can be considered an exogenous determinant of economic outcomes in private firms.

Trust and Disclosure Transparency in Financial Reporting of Government Agencies
Allee, Kristian D.,Baik, Bok,Han, Seung-Youb,Kim, Bong Hwan
SSRN
This study examines the impact of trust on disclosure transparency in financial reporting of government agencies. Using unique data from Korean central government agencies for the period of 2011-2015, we provide evidence that trust enhances government agenciesâ€™ financial disclosure transparency. Specifically, we document that high-trust agencies are more likely to classify their accounting errors as material and recognize these errors (as a separate line item) in financial statements. This contrasts with the practice of low-trust agencies that classify similar-magnitude accounting errors as immaterial, obfuscating the information from potential scrutiny. We further find that high-trust (low-trust) agencies tend to provide more disaggregated (aggregated) service cost information. In cross-sectional analyses, we find that the impact of trust on both disclosure of accounting errors and disaggregation of service cost information is amplified when agencies have an outsider head, are more decentralized, and face higher parliamentary inspection pressures, the situations in which more information coordination is required. Taken together, our findings suggest that trust contributes to higher disclosure transparency of government financial reporting by facilitating active information production and dissemination within an organization.

Why the Ability-to-Repay Rule Is Vital To Financial Stability
McCoy, Patricia A.,Wachter, Susan M.
SSRN
Following the 2008 financial crisis, Congress required residential mortgage lenders to make a reasonable determination of borrowersâ€™ ability to repay before extending credit. Most regard this ability-to-repay rule as a consumer protection provision. But what is less well appreciated is the ruleâ€™s importance in protecting financial stability.We respond to a landmark 2015 critique in the University of Pennsylvania Law Review arguing that the rule will fail to limit bubbles because mortgage lenders will ignore it when home prices are rapidly appreciating by underestimating their liability exposure. On the contrary, we argue that the ability-to-repay rule acts as a circuit breaker that helps prevent poorly underwritten loans from fueling a future bubble in housing prices, with the risk of financial collapse. Without that rule, loan-to-value limits are not enough to curb property bubbles. While loan-to-value limits are important to constraining risk, the denominator â€" the value â€" will be artificially elevated during a bubble, and will only fall after the bust is in process, failing to provide information at origination of the elevated default risk, and giving false confidence that mortgage risk is contained. Moreover, we know from the crisis that it is the inability to repay that makes foreclosure and the resulting further depression of housing prices inevitable. The ability-to-repay rule is a collective action solution to this source of systemic risk and a vital mainstay of financial stability.