Research articles for the 2019-08-05

A Hiccup in Turkey’s Prolonged Credit Fueled Economic Transition: A Comparative Analysis of Before and After the August Rout
Taskinsoy, John
Mustafa Kemal’s well-organized resistance army was victorious in the Turkish War of Independence, which expelled the occupying armies; subsequently, Mustafa Kemal abolished the Ottoman Empire in 1922 by overthrowing Sultan Mehmet VI Vahdettin and established the Turkish Republic in 1923. No doubt, there is absolutely no other event or development is more important than this in the young history of the Turkish Republic. Economically, the 2001 Turkish economic crisis was the greatest shock since 1923, which cost the government in excess of $50 billion and led to the signing of three standby agreements (over $ 40 billion) with the IMF. Turkey's near meltdown economy, a casualty of repeated speculative attacks on Turkish lira in August 2018 and the subsequent unfolding events, had contracted 5% or so in 2018 compared with that of 2017, and it is forecast to contract further in 2019 after a decade-long credit-fueled boom. It is feared that the farfetched implications of the August rout of 2018 could toss Turkey back in high inflationary mode; however, Turkish government authorities have dismissed the recent severe economic trouble and blamed the crisis on dysfunctional and hostile policies of non-economic basis. Regardless, in the immediate aftermath of the August shock, Turkish lira plummeted 42% of its value against dollar (i.e. from 5.09 on August 2 to 7.24 on August 13) and inflation (CPI) soared to 26% which prompted the Turkish central bank (TCMB) to hike the fund rate by 625 basis points to 24%. Although the Turkish lira has appreciated substantially against dollar since August 2018 (from 7.24 on August 13 to 5.61 on August 2, 2019), Turkey’s unemployment rate surged to 14.7 in February 2019, which is the highest level in a decade. Turkey’s depressed economic situation is in desperate need of foreign capital flows used by the financial authorities to service the debt obligations, but Turkey’s external barrowing have become substantially limited in recent years. With massive foreign debt stock (about $400 billion which is over 50% of its 2018 GDP), Turkey must find ways to attract capital inflows in the form of FDIs and FPIs.

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

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.

Analyst Coverage Overlaps and Interfirm Information Spillovers
Martens, Tim,Sextroh, Christoph J.
We investigate the role of financial analysts in facilitating the flow of relevant competitive information between firms. Using patent citations as a proxy for interfirm information spillovers, we find that firms are more likely to cite another firm's patent if that firm is covered by the same financial analyst. Difference-in-difference analyses exploiting exogenous shocks to analyst coverage overlaps over time suggest that the documented effect is not simply due to changes in firms' business models and corresponding changes in analyst coverage; consistent with a causal relationship between analyst coverage overlaps and interfirm information spillovers. The effect is stronger for analysts with a relatively higher industry-specialization, more experience, a larger coverage portfolio, and a higher forecast activity, as well as for firm pairs with a larger geographic or organizational diversity. Overall, our findings suggest that capital market relationships not only play an important role in reducing information asymmetries between firms and capital markets but also facilitate the production of business intelligence through feedback and interfirm information transfers.

Annual Report Narratives and the Cost of Equity Capital: U.K. Evidence of a U-Shaped Relation
Athanasakou, Vasiliki E.,Eugster, Florian,Schleicher, Thomas,Walker, Martin
We propose and test for a U-shaped relation between the cost of equity capital and the level of disclosure in annual report narratives. Using a computer-generated word-count-based score of the level of disclosure in U.K. annual report narratives, we document a negative relation with the cost of equity capital at low levels of disclosure, and a positive relation at higher levels of disclosure, together implying the presence of an optimal level of disclosure. We interpret the positive relation at higher levels of disclosure as evidence of uninformative clutter increasing the cost of equity capital. Additional analyses indicate the presence of both firm-level learning effects and the impact of regulatory corporate reporting initiatives as factors shaping adjustments towards optimum levels of disclosure. Finally, we present evidence on the relation between the cost of equity capital and disclosure for specific components of our disclosure index.

Anomaly Investing: Out-of-Sample Performance and Intertemporal Considerations
Guo, James Tengyu
I first show that the naïve equal-weighted 1/N investing in the set of 34 stock market anomalies is a robust implementation for out-of-sample diversification. Two types of popular portfolio optimization methods, including Sharpe-Ratio-optimizing with weight constraints and Dimension-Reduction with machine learning techniques, do not achieve robustly higher out-of-sample performance. Further to explore the gains and risks in investing stock market anomalies, I take this equal-weighted anomaly portfolio to an intertemporal CAPM framework with stochastic volatility to understand the investment considerations of a specific anomaly investor. Based on my estimation, only the correlation-induced volatility news carries a significant risk premium, which highlights the economic importance of the comovement in anomaly asset prices.

Asymmetric Jump Beta Estimation with Implications for Portfolio Risk Management
Alexeev, Vitali,Urga, Giovanni,Yao, Wenying
We evaluate the impact of extreme market shifts on equity portfolios and study the difference in negative and positive reactions to market jumps with implications for portfolio risk management. Employing high-frequency data for the constituents of the S&P500 index over the period 2 January 2003 to 30 December 2017, we investigate to what extent the portfolio exposure to the downside and upside jumps can be mitigated. We contrast the risk exposure of individual stocks with those of the portfolios as the number of holdings increases. Varying the jump identification threshold, we show that the number of holdings required to stabilise portfolios’ sensitivities to negative jumps is higher than when positive jumps are considered and that the asymmetry is more prominent for more extreme events. Ignoring this asymmetry results in under-diversification of portfolios and increases exposure to sudden extreme negative market shifts.

Banking On Demography: Population Aging and Financial Integration
Doerr, Sebastian,Kabas, Gazi
This paper argues that an integrated financial sector mitigates negative effects of population aging. We show that U.S. counties with an aging population see an increase in local deposits, reflecting higher saving rates of seniors. Banks use these deposits to increase credit supply. Using detailed data on mortgage lending, we find that banks channel deposits from aging counties towards counties with a younger population. We find no evidence that banks engage in risky lending: they lend less to counties with a high share of sub-prime borrowers or low incomes, and do not lend disproportionately to low-income borrowers. The increase in credit supply has real effects. Counties with a higher market share of aging-exposed banks see an increase in house prices and building permits, as well as in firm formation. Results are robust to controlling for bank and county characteristics through granular fixed effects and instrumenting local aging with casualties during World War II.

Betting on Bitcoin: Does Gambling Volume on the Blockchain Explain Bitcoin Price Changes?
Conlon, Thomas,McGee, Richard
The wallets with the largest volume of transactions on the Bitcoin blockchain are gaming applications. We use the historical gaming transaction data of Bitcoin holders, extracted directly from the blockchain, to measure risk-loving (lottery) appetite. Changes in the volume spent on the most lottery-like gambling wallet explain a significant portion (32%) of variation in the returns to the BTC price in the first half of our sample, but this effect disappears post-2016. This date coincides with a significant decrease in the proportion of Bitcoin transactions involved in gambling and aligns with other work that finds a decrease in the proportion of Bitcoin transactions linked to illegal activities and an increase in buy and hold investors around the same date.

Central Bank Digital Currency: Benefits and Drawbacks
Koumbarakis, Antonios,Dobrauz-Saldapenna, Guenther
Prompted by technological advances and a decline in cash usage, many Central Banks are investigating whether it would be possible to issue a digital complement to cash, a so-called Central Bank Digital Currency (CBDC). Despite ongoing research and occasional pilots, Central Banks have shied away from introducing a CBDC for public use. Even though CBDCs would have the potential to counteract some of the problems that could arise for the payment system in the future when the use of cash is rapidly declining, they also present significant risks for financial stability.This article contributes to the discussion by setting out a CBDC framework and formulating broad design principles for CBDC in line with the central bank´s function as Lender of last Resort (LOLR). The attributes and functionality of a CBDC are highly determinative of the architectural design and technical solution chosen, particularly in the context of LOLR. Therefore, we argue in favour of a solid coin for e-emergency liquidity assistance, available 24 hours a day and seven days per week, anonymous, interest-bearing and unlimited, to prevent bank runs and restore financial stability in times of financial distress.

Collaborative knowledge creation: Evidence from Japanese patent data
Tomoya Mori,Shosei Sakaguchi

This paper presents micro-econometric evidence for collaborative knowledge creation at the level of individual researchers. The key determinant for developing new ideas is the exchange of differentiated knowledge among collaborators. To stay creative, inventors seek opportunities to shift their technological expertise to unexplored niches by utilizing the differentiated knowledge of new collaborators. Furthermore, a more active recombination of collaborators by an inventor facilitates the selection of collaborators to raise the amount of differentiated knowledge from their collaborators.

Corporate Governance, SSB Strength and the Use of Internal Audit Function by Islamic Banks: Evidence from Sudan
Sulub, Saed,Salleh, Zalailah,, Hafiza Aishah Hashim
Purpose: The paper aims to identify the effects of some Corporate Governance (CG) mechanisms and Shariah Supervisory Board (SSB) strength on the voluntary use of Internal Audit Function (IAF) by Islamic banks in Sudan. Design/Methodology/Approach: Based on Agency and Stakeholder theories, the paper hypothesizes that IAF is likely used by Islamic banks with strong CG and Shariah Governance systems. In order to test these hypotheses, we examine the annual reports of fourteen Sudanese banks for a period of five years following the global financial crisis in 2008, using Logistic Regression Analysis.Findings: The paper found that IAF is likely used by Islamic banks with higher CG Disclosure (CGD) and strong SSB. While the findings showed that the audit committee and IAF are likely used as substitutes, the paper also indicated that there is a negative association between levels of Unrestricted Investment Account Holders’ (UIAH) ownership and the use of IAF. However, the evidence of this study did not find any impact for the board of directors’ strength on the use of IAF.Research Limitations/Implications: There may be better measures for some variables in the study model. Additionally, the restriction of the study sample to Sudanese banks may limit the generalization of the results. Therefore, future studies may refine the model and expand the sample to Islamic banks in other countries.Practical Implications: The paper highlights the importance of IAF for Shariah governance in Islamic banks. Moreover, the insignificant association between the use of IAF and the strength of board of directors has important implications for board’s effectiveness in Islamic banks.Originality/value: This is the first study to investigate the factors that associate with the use of IAF by Islamic banks.

Decomposing Long Bond Returns: A Decentralized Modeling Approach
Carr, Peter,Wu, Liuren
This paper develops a decentralized theory that determines the fair value of the yield-to-maturity of a bond or bond portfolio based purely on the near-term dynamics of the yield itself. The theory decomposes the yield into three components: its expected change, its risk premium, and its convexity effects. The convexity effect can be constructed with a historical variance estimator. The expectation can come from statistical models or expert forecasts, leaving the remaining component of the yield as a risk premium estimate. Comparative yield analysis of different bonds can start with commonality assumptions on their risks, risk premiums, and expected change.

Do CSR Ratings Affect Loan Spreads?
Drago, Danilo,Carnevale, Concetta,Gallo, Raffaele
We investigate whether Corporate Social Responsibility (CSR) ratings affect syndicated loan spreads applied to European listed firms. We find evidence that borrowers’ CSR ratings have a significant impact on loan spreads. Banks apply lower loan spreads to firms that are rewarded with high CSR ratings. In addition, we find that the benefits of CSR are lower for smaller firms and for companies located in countries that pay less attention to CSR matters. Our results also hold considering crisis periods, alternative risk specifications, potential endogeneity issues, and lender characteristics. Overall, CSR engagement can enable companies to obtain more favourable financing terms. The availability of reliable CSR ratings can generate significant benefits for the improvement of CSR strategies and the relevance of CSR issues. Both managers and regulators can reliably identify the returns of their CSR decisions. At the same time, CSR ratings may reduce information asymmetries in firm valuation for investors and other stakeholders.

FRM Financial Risk Meter
Mihoci, Andrija,Althof, Michael,Chen, Cathy Yi‐Hsuan,Härdle, Wolfgang K.
A daily systemic risk measure is proposed accounting for links and mutual dependencies between financial institutions utilising tail event information. FRM (Financial Risk Meter) is based on Lasso quantile regression designed to capture tail event co-movements. The FRM focus lies on understanding active set data characteristics and the presentation of interdependencies in a network topology. Two FRM indices are presented, namely, FRM@Americas and FRM@Europe. The FRM indices detect systemic risk at selected areas and identifies risk factors. In practice, FRM is applied to the return time series of selected financial institutions and macroeconomic risk factors. Using FRM on a daily basis, we identify companies exhibiting extreme "co-stress", as well as "activators" of stress. With the SRM@EuroArea, we extend to the government bond asset class. FRM is a good predictor for recession probabilities, constituting the FRM-implied recession probabilities. Thereby, FRM indicates tail event behaviour in a network of financial risk factors.

Financial Trust in Social and Economic Network and Credit Risk
Muduli, Silu,Dash, Shridhar Kumar
The paper models usefulness of borrower’s social economic network in evaluating credit risk. We develop a methodology for lender to aggregate the individuals’ trust for the borrower in social economic network to obtain borrower’s aggregate trust on credit repayment. From borrower’s side, we bring social cost of default coming from social economic network which dis-incentivize credit default. Based on this association of social economic network with borrower and lender, paper develops a model using the aggregate trust, project riskiness, and social cost of default to evaluate credit risk. A borrower with a safe project and high social cost of default is likely to payback the credit. Whereas, a borrower with very less social cost of default and safe project is more likely to be a wilful defaulter.

Government Assistance and Capital Structure: A Growing, Off-Balance Sheet Financing Source
Hess, Ryan
I investigate whether firms treat government assistance as an additional source of external capital beyond debt or equity. I find corporations in the highest decile of size-adjusted government assistance received have meaningfully lower leverage ratios, about two basis points below those in the bottom decile. Only direct government assistance like cash grants, but not loans or tax relief, is negatively associated with firm debt ratios. The negative association is consistent with the pecking order theory of capital structure. I also find firms with lower debt ratios have higher investment commitments to governments, implying government assistance often creates off-balance sheet obligations. These findings are relevant to the FASB as it deliberates requiring additional disclosure on government assistance under Topic 832, which would make such off-balance sheet financing more visible to financial statement users.

Graph Theory and Environmental Algorithmic Solutions to Assign Vehicles: Application to Garbage Collection in Vietnam
Truong, Buu-Chau,Pho, Kim-Hung,Nguyen, Van-Buol,Tuan, Bui Anh,Wong, Wing-Keung
The problem of finding the shortest path including garbage collection is one of the most important problems in environmental research and public health. Usually, the road map has been modeled by a connected undirected graph with the edge representing the path, the weight being the length of the road, and the vertex being the intersection of edges. Hence, the initial problem becomes a problem finding the shortest path on the simulated graph. Although the shortest path problem has been extensively researched and widely applied in miscellaneous disciplines all over the world and for many years, as far as we know, there is no study to apply graph theory to solve the shortest path problem and provide solution to the problem of “assigning vehicles to collect garbage” in Vietnam. Thus, to bridge the gap in the literature of environmental research and public health. We utilize three algorithms including Fleury, Floyd, and Greedy algorithms to analyze to the problem of “assigning vehicles to collect garbage” in District 5, Ho Chi Minh City, Vietnam. We then apply the approach to draw the road guide for the vehicle to run in District 5 of Ho Chi Minh city. To do so, we first draw a small part of the map and then draw the entire road map of District 5 in Ho Chi Minh city. The approach recommended in our paper is reliable and useful for managers in environmental research and public health to use our approach to get the optimal cost and travelling time.

Hierarchical adaptive sparse grids and quasi Monte Carlo for option pricing under the rough Bergomi model
Christian Bayer,Chiheb Ben Hammouda,Raul Tempone

The rough Bergomi (rBergomi) model, introduced recently in [4], is a promising rough volatility model in quantitative finance. It is a parsimonious model depending on only three parameters, and yet exhibits remarkable fit to empirical implied volatility surfaces. In the absence of analytical European option pricing methods for the model, and due to the non-Markovian nature of the fractional driver, the prevalent option is to use Monte Carlo (MC) simulation for pricing. Despite recent advances in the MC method in this context, pricing under the rBergomi model is still a time-consuming task. To overcome this issue, we design a novel, alternative, hierarchical approach, based on i) adaptive sparse grids quadrature (ASGQ), and ii) quasi Monte Carlo (QMC). Both techniques are coupled with Brownian bridge construction and Richardson extrapolation. By uncovering the available regularity, our hierarchical methods demonstrate substantial computational gains with respect to the standard MC method, when reaching a sufficiently small relative error tolerance in the price estimates across different parameter constellations, even for very small values of the Hurst parameter. Our work opens a new research direction in this field, i.e. to investigate the performance of methods other than Monte Carlo for pricing and calibrating under the rBergomi model.

ICT Capital-Skill Complementarity and Wage Inequality: Evidence from OECD Countries
Hiroya Taniguchi,Ken Yamada

Although it is well known that wage inequality has evolved over recent decades, it is not known the extent to which the evolution of wage inequality is attributed to observed factors such as capital and labor quantities or unobserved factors such as labor-augmenting technology in many countries. To examine this issue, we use cross-country panel data from 14 OECD countries for the years 1970 to 2005 and estimate the aggregate production function extended to allow for capital-skill complementarity and skill-biased technological change. Our results point to a strong influence of the observed expansion of ICT capital equipment relative to high-skilled labor around the world.

Implications of Bank Regulation for Loan Supply and Bank Stability: A Dynamic Perspective
Bucher, Monika,Dietrich, Diemo,Hauck, Achim
We show that internal funds play a particular role in the regulation of bank capital, which has not received much attention, yet. A bank's decision on loan supply and capital structure determines its immediate bankruptcy risk as well as the future availability of internal funds. These internal funds in turn determine a bank's future costs of external finance and its future vulnerability to bankruptcy risks. Using a partial equilibrium model, we study how internal funds affect these intra- and intertemporal links. Moreover, our positive analysis identifies the effects of risk-weighted capital-to-asset ratios, liquidity coverage ratios and regulatory margin calls on the dynamics of internal funds and thus loan supply and bank stability. Only regulatory margin calls or large liquidity coverage ratios achieve bank stability for all risk levels, but for large risks a bank will stop credit intermediation.

Index Fund Enforcement
Platt, Alexander I.
Corporate America today is astonishingly beholden to three large financial institutions: BlackRock, Vanguard, and State Street Global Advisors. As investors have moved their money into low cost, highly-diversified investment vehicles known as index funds, the so-called “Big Three” institutional fund managers that dominate the index fund industry have grown rapidly and accumulated unprecedented economic power and influence. For instance, these three institutions now vote one out of every four shares of stock issued by large U.S. companies. Policymakers and scholars have begun to sound the alarm about this concentration of corporate ownership, and have proposed reforms to reduce or eliminate these institutions’ influence over portfolio companies.But concentrated power has its benefits, too. In this paper, I argue that the remarkable size, permanence, and cross-market scope of the Big Three’s ownership stakes gives them the capacity and, in some cases, the incentive to punish and deter fraud and misconduct by portfolio companies. Corporate governance and securities regulation scholars have argued that these institutions have generally overriding incentives to refrain from meaningful corporate stewardship, but the facts on the ground tell a somewhat different story. Drawing on a comprehensive review of the Big Three’s enforcement activities and interviews with key decision-makers for these institutions, I show how they have been using engagement, voting, and litigation to discipline culpable companies and managers. I also identify the “pro-enforcement” incentives that explain these actions.Policymakers and scholars are now engaging in a heated debate over indexation and the future of the Big Three. To date, however, participants have overlooked the potentially beneficial role these institutions may play in the enforcement ecosystem. This paper corrects this oversight, bringing Index Fund Enforcement into focus. Policymakers should embrace regulatory reforms designed to enhance Index Fund Enforcement, not weaken it.

Interbank Borrowing and Lending Between Financially Constrained Banks
Dietrich, Diemo,Hauck, Achim
Some stylized facts about transactions among banks are not easily reconciled with coinsurance of short-term liquidity risks. In our model, interbank markets play a different role. We argue that lending to another bank can reduce a bank’s overall portfolio risk through diversification. If insolvency is costly, this diversification improves the interbank lender’s funding liquidity, boosting credit supply to nonbanks. However, diversification comes at an endogenous cost that depends on bank-specific factors of interbank borrower and lender. The model provides a framework for understanding the importance of interbank lending for aggregate credit supply and the stability of banking systems. The model’s predictions are consistent with evidence documented in the literature that other theories cannot consistently explain.

Linkages and systemic risk in the European insurance sector: Some new evidence based on dynamic spanning trees
Anna Denkowska,Stanisław Wanat

This paper is part of the research on the interlinkages between insurers and their contribution to systemic risk on the insurance market. Its main purpose is to present the results of the analysis of linkage dynamics and systemic risk in the European insurance sector which are obtained using correlation networks. These networks are based on dynamic dependence structures modelled using a copula. Then, we determine minimum spanning trees (MST). Finally, the linkage dynamics is described by means of selected topological network measures.

Managing with Private Equity Style: CEOs’ Prior Buyout Target Experiences and Corporate Policies
Hsu, Scott,Jandik, Tomas,Lu, Juntai
We examine the effects of public firm CEOs’ prior private equity (PE) target experiences on corporate policies. CEOs previously serving as CEOs in PE targets reduce investment by 34 percent and cut employment by 23 percent, compared to CEOs without such experiences. The effects are stronger if CEOs (1) have more recent PE target experiences, (2) worked in PE targets invested by more reputable PE firms, and (3) worked in PE targets invested by PE firms prone to cutting more investment and/or employment. These CEOs are also more likely to file patents, improve operating efficiency, increase leverage and firm value.

On Aggregability of Risk Averse and Risk Seeking Preferences into One Representative Agent
Obrimah, Oghenovo A.
This study provides formal theoretical evidence for nesting of probability measures that are generated by risk aversion in probability measures that are generated by risk seeking preferences. In presence of highlighted nesting, conditional on independent parameterization of expectations (probability distributions) that are conditioned on either of risk aversion, or risk seeking preferences, the two sets of preferences aggregate into one representative agent. This is a novel result that simultaneously is not trivial. Non-triviality is evident in the accompanying prediction that formation of expectations (probability distributions) over entirety of assets within stock markets, this without recourse to heterogeneity of preferences, does not induce existence of a single representative agent. The formal theoretical evidence demonstrates that the value-growth anomaly - the superior return performance of `value' stocks in relation to `growth' stocks - is induced by deviations from rational expectations equilibriums, as such lacks characterization as an anomaly.

On the Optimal Combination of Annuities and Tontines
Chen, An,Rach, Manuel,Sehner, Thorsten
Tontines, retirement products constructed in such a way that the longevity risk is shared in a pool of policyholders, have recently gained vast attention from researchers and practitioners. Typically, these products are cheaper than annuities, but do not provide stable payments to policyholders. This raises the question whether, from the policyholders' viewpoint, the advantages of annuities and tontines can be combined to form a retirement plan which is cheaper than an annuity and carries less risk than a tontine. In this article, we analyze and compare three approaches of combining annuities and tontines in an expected utility framework: The “tonuity” introduced in Chen et al. (2019), a product very similar to the tonuity which we call “antine” and a portfolio consisting of an annuity and a tontine. We show that the payoffs of a tonuity or an antine can be replicated by a portfolio consisting of an annuity and a tontine. Consequently, policyholders achieve higher expected utility levels when choosing the portfolio over the novel retirement products tonuity and antine.

Private Credit Under Political Influence: Evidence from France
Delatte, Anne Laure,Matray, Adrien,Pinardon Touati, Noémie
Politicians influence the lending decisions of independent private banks in order to increase their chances of being re-elected. In exchange, they grant these banks access to the profitable market for loans to local government entities. Using the French credit registry between 2007-2017, we find that credit to the private sector increases by 9% the year before a powerful incumbent faces a contested election. Consistent with politicians returning the favor, banks that grant more credit to private firms in pre-election years gain market shares in the market for local government debt after the election. Our results show that as long as there exist rents that politicians can allocate discretionarily, formal independence is insufficient to severe the link between political motives and the private sector.

Relatively growth optimal investment strategies in a market model with competition
Yaroslav Drokin,Mikhail Zhitlukhin

We consider a game-theoretic model of a market where investors compete for payoffs yielded by several assets. The main result consists in a proof of existence and uniqueness of a strategy, called relatively growth optimal, such that the logarithm of the share of its wealth in the total wealth of the market is a submartingale for any strategies of the other investors. It is also shown that this strategy is asymptotically optimal in the sense that it achieves the maximal capital growth rate when compared to competing strategies. Based on the obtained results, we study the asymptotic structure of the market when all the investors use the relatively growth optimal strategy.

Risk Management via Anomaly Circumvent: Mnemonic Deep Learning for Midterm Stock Prediction
Xinyi Li,Yinchuan Li,Xiao-Yang Liu,Christina Dan Wang

Midterm stock price prediction is crucial for value investments in the stock market. However, most deep learning models are essentially short-term and applying them to midterm predictions encounters large cumulative errors because they cannot avoid anomalies. In this paper, we propose a novel deep neural network Mid-LSTM for midterm stock prediction, which incorporates the market trend as hidden states. First, based on the autoregressive moving average model (ARMA), a midterm ARMA is formulated by taking into consideration both hidden states and the capital asset pricing model. Then, a midterm LSTM-based deep neural network is designed, which consists of three components: LSTM, hidden Markov model and linear regression networks. The proposed Mid-LSTM can avoid anomalies to reduce large prediction errors, and has good explanatory effects on the factors affecting stock prices. Extensive experiments on S&P 500 stocks show that (i) the proposed Mid-LSTM achieves 2-4% improvement in prediction accuracy, and (ii) in portfolio allocation investment, we achieve up to 120.16% annual return and 2.99 average Sharpe ratio.

Self-Assessed Financial Literacy in Housing Markets
Abramson, Boaz,Yany, Andres
This paper introduces a novel dimension of household heterogeneity that plays an important role in housing markets. Households who self-assess themselves to be more financially literate are 1) more likely to own a house and 2) take on higher leverage on their home. We solve a heterogeneous agent portfolio choice model to infer the role of mortgage terms and of expectations on future house prices for the empirical patterns. We find that households with higher levels of self-assessed financial literacy are in fact better at the parts of the transaction that are relevant to them, namely access to more accommodating mortgage terms when they are young and better risk-return trade-offs when they are old. Moreover, by ignoring heterogeneity in financial literacy, standard models introduce quantitatively substantial biases in evaluating housing market policies. Housing demand elasticity with respect to wealth is downsized by approximately 40% when taking financial literacy into account.

Solving high-dimensional optimal stopping problems using deep learning
Sebastian Becker,Patrick Cheridito,Arnulf Jentzen,Timo Welti

Nowadays many financial derivatives which are traded on stock and futures exchanges, such as American or Bermudan options, are of early exercise type. Often the pricing of early exercise options gives rise to high-dimensional optimal stopping problems, since the dimension corresponds to the number of underlyings in the associated hedging portfolio. High-dimensional optimal stopping problems are, however, notoriously difficult to solve due to the well-known curse of dimensionality. In this work we propose an algorithm for solving such problems, which is based on deep learning and computes, in the context of early exercise option pricing, both approximations for an optimal exercise strategy and the price of the considered option. The proposed algorithm can also be applied to optimal stopping problems that arise in other areas where the underlying stochastic process can be efficiently simulated. We present numerical results for a large number of example problems, which include the pricing of many high-dimensional American and Bermudan options such as, for example, Bermudan max-call options in up to 5000~dimensions. Most of the obtained results are compared to reference values computed by exploiting the specific problem design or, where available, to reference values from the literature. These numerical results suggest that the proposed algorithm is highly effective in the case of many underlyings, in terms of both accuracy and speed.

Speed Matters: Supply-Chain Information Diffusion and Price Feedback Effects
Cen, Ling,Hertzel, Michael G.,Schiller, Christoph
This paper provides evidence of price feedback effects in a supply-chain setting using the speed with which information diffuses from customer to supplier stock prices to identify private supply-chain information in prices. We find that the speed of supply-chain information diffusion positively (negatively) affects the sensitivity of supplier investment to its own (customer’s) price. These results are consistent with learning from prices and suggest that supplier managers vary their reliance on their own versus their customer’s stock prices depending upon their relative price informativeness. Consistent with supplier managers using information in prices to make better investment decisions, we find that higher speed of supply-chain information diffusion predicts positive future supplier performance and enhances investment coordination between suppliers and customers.

Strategic Payments in Financial Networks
Nils Bertschinger,Martin Hoefer,Daniel Schmand

In their seminal work on systemic risk in financial markets, Eisenberg and Noe proposed and studied a model with $n$ firms embedded into a network of debt relations. We analyze this model from a game-theoretic point of view. Every firm is a rational agent in a directed graph that has an incentive to allocate payments in order to clear as much of its debt as possible. Each edge is weighted and describes a liability between the firms. We consider several variants of the game that differ in the permissible payment strategies. We study the existence and computational complexity of pure Nash and strong equilibria, and we provide bounds on the (strong) prices of anarchy and stability for a natural notion of social welfare. Our results highlight the power of financial regulation -- if payments of insolvent firms can be centrally assigned, a socially optimal strong equilibrium can be found in polynomial time. In contrast, worst-case strong equilibria can be a factor of $\Omega(n)$ away from optimal, and, in general, computing a best response is an NP-hard problem. For less permissible sets of strategies, we show that pure equilibria might not exist, and deciding their existence as well as computing them if they exist constitute NP-hard problems.

Tail Dependence Structure of Metal Commodity Futures in London Metal Exchange
Han, Xuyuan,Liu, Zhenya,Wang, Shixuan
Since the 2008 financial crisis, academics and practitioners have paid more attention to the dependence structures among futures contracts in futures market. We use the vine-copula approach to study the dependence structures among major metal commodity futures in the London Metal Exchange, with a focus on analyzing the change after the crisis. We find that the core of metal futures moves from copper to zinc after the crisis. The risk diversification benefit among metal futures is shown to diminish. However, the dependence structure between core futures and the futures who exhibits the highest (lowest) concordance with core futures remains unchanged after the crisis.

The CDS-Loan Basis Across Firms and the Business Cycle
Drago, Danilo,Carnevale, Concetta,Gallo, Raffaele
We analyze the difference between credit default swap (CDS) and syndicated loan spreads, defined as the “CDS-loan basis”. Our results indicate that the CDS-loan basis is greater when the cost of information asymmetry is higher, such as for riskier borrowers and in economic downturns. Our findings suggest that loan spreads applied to riskier borrowers are less correlated with the business cycle than CDS spreads. Overall, our analysis is consistent with the hypothesis that, at least in part, banks still play a special role in the current financial system compared with other investors.

The Real Effects of Forced Sales of Corporate Bonds
Aslan, Hadiye,Kumar, Praveen
What are the real effects of forced sales of corporate securities? Our theoretical analysis shows that model uncertainty can generate distorted negative (positive) capital investment effects during price declines (reversals) in equilibrium when there is information feedback from financial markets. Empirically, we find that forced sales of corporate bonds by financial institutions had a significant negative impact on the capital investment and product market competitiveness --- measured by market shares and price-cost margins --- of exposed firms during the financial crisis. These adverse real effects on exposed firms were also vertically transmitted to their suppliers and customers.

The Time Importance for Prospect Theory
José Cláudio do Nascimento

A theory usually comprises assumptions and deduced predictions from them. In this paper, empirical evidences corroborate with assumptions about time for a decision making facing known probabilities and outcomes.

The Yield Curve and the Stock Market: Mind the Long Run
Faria, Gonçalo,Verona, Fabio
We extract cycles from the term spread and study their role for predicting the equity premium using linear models. When properly extracted, the trend of the term spread is a strong and robust out-of-sample equity premium predictor, both from a statistical and an economic point of view. It outperforms several variables recently proposed as good equity premium predictors. Our results support recent Findings in the asset pricing literature that the low-frequency components of macroeconomic variables play a crucial role in shaping the dynamics of equity markets. Hence, for policymakers and financial market participants interested in gauging equity market developments, the trend of the term spread is a promising variable to look at.

Trade Credit in Transition Economies: Does State Ownership Matter?
Boubaker, Sabri,Ly, Kim Cuong,Tran, Nam
We investigate the influence of residual state ownership on firm behaviors in providing and receiving trade credit by using a Vietnamese government’s privatization experiment. Our robust results show that a substantial withdrawal of state capital from listed state-owned enterprises (SOEs) does not disturb these firms’ supply of and demand for trade credit, affirming the state sector’s disinclination for trade credit redistribution in the context that trade credit may be not a source of soft budget constraints and local privatization programs have not been motivated by efficiency. The finding is featured as a transitional phenomenon in a state-dominated economy that is inadequately supportive of private sector development and a poor legal system encouraging informal contract enforcement. Vietnamese firms with more accounting conservatism, probably in response to their creditors’ increasing demand for earnings quality, are found to provide less trade credit, implying trade credit-reducing effect of accounting conservatism. We suggest that improvements in financial report audit and corporate governance quality during Vietnam’s recent privatization programs increase the effectiveness of the capital market.

Volatility and Returns: Evidence from China
Chi, Yeguang,Qiao, Xiao,Yan, Sibo,Deng, Binbin
Long-short factors and industry portfolios in the Chinese A-share stock market tend to have higher returns the months following high volatility. Due to this positive relationship between lagged volatility and returns, volatility-managed portfolios of Moreira and Muir (2017) do not work well in China - they are spanned by the original portfolios. Volatility-scaled portfolios, which increase portfolio exposure in volatile times, are not spanned by the original portfolios and expand the investor’s opportunity set. For industry portfolios and long-short factors, the investor’s mean-variance frontier shifts towards more desirable regions when volatility-scaled portfolios are added to the investment mix.

What Can Volatility Smiles Tell Us about the Too Big to Fail Problem?
Puente M., Diego
In this paper, I exploit the information content of option prices to construct a forward-looking measure of bank exposure to significant price drops (i.e. tail-risk). I then use this measure to document a permanent increase in tail-risk for U.S. banks in the period after the Global Financial Crisis, except for large banks explicitly identified as institutions whose failure could threaten the financial stability of the U.S. economy. I propose implicit guarantees and effective regulation as mutually exclusive explanations for this differential effect and show evidence consistent with size-based government guarantees as responsible for the lower exposure to downside risk large banks have post-crisis.

calculation worst-case Value-at-Risk prediction using empirical data under model uncertainty
Wentao Hu

Quantification of risk positions under model uncertainty is of crucial importance from both viewpoints of external regulation and internal management. The concept of model uncertainty, sometimes also referred to as model ambiguity. Although we know the family of models, we cannot precisely decide which one to use. Given the set $\mathcal{P}$, the value of the risk measure $\rho$ varies in a range over the set of all possible models. The largest value in such a range is referred to as a worst-case value, and the corresponding model is called a worst scenario. Value-at-Risk(VaR) has become a very popular risk-measurement tool since it was first proposed. Naturally, WVaR(worst-case Value-at-Risk) attracts the attention of many researchers. Although many literatures investigated WVaR, the implications for empirical data analysis remain rare. In this paper, we proposed a special model uncertainty market model to simply the $\mathcal{P}$ to a set contain finite number of probability distributions. The model has the structure of the two-layer mixed distribution model. We used change point detection method to divide the returns series and then used EM algorithm to estimate the parameters. Finally, we calculated VaR, WVaR(worst-case Value-at-Risk) and BVaR(best-case Value-at-Risk) for four financial markets and then analyzed their different performance.