Research articles for the 2020-02-03

A Network Analysis of Information Diffusion in the Financial Sector
Borochin, Paul,Rush, Stephen
We create and test two novel network-based measures of interconnectedness in the financial industry during 1996 to 2013. A network based on informed trading in financial firms predicts firm-specific risk and performance, while one formed on financial firm returns predicts future macroeconomic risk. The measure of informed trading is robust to variable order arrival rates more common in modern algorithmic trading. A trading strategy based on informed trading network centrality in the financial sector delivers an annualized risk-adjusted return of 7.73%. This risk-adjusted return shows that the network centrality has an economic impact that is relevant beyond the statistical results of the paper.

A Note on Long-Term Bayesian Modeling of Standard & Poor Composite Index Returns
Taran Grove,Andrey Sarantsev

This is a short note, which contains a simple dynamic factor model: Total (including dividends) real (inflation-adjusted) annual returns of Standard \& Poor Composite Index is regressed upon earnings yield, which is defined as earnings (net income) per share of this index (summed over all companies in this index), divided by the current value of this index. This earnings yield is modeled as a simple autoregression. We use 7-year trailing earnings yield, with earnings averaged over the last 7 years. This version of earnings yield has maximal correlation with next year's total real returns. Regression residuals fail standard normality tests, but we still use this model, since we are interested in long-run modeling. To account for shortage of data (1935--2019 annual), we use Bayesian inference. We confirm the conventional wisdom that future long-run stock market returns are likely to be lower than the historical averages.

An analysis of Uniswap markets
Guillermo Angeris,Hsien-Tang Kao,Rei Chiang,Charlie Noyes,Tarun Chitra

Uniswap---and other constant product markets---appear to work well in practice despite their simplicity. In this paper, we give a simple formal analysis of constant product markets and their generalizations, showing that, under some common conditions, these markets must closely track the reference market price. We also show that Uniswap satisfies many other desirable properties and numerically demonstrate, via a large-scale agent-based simulation, that Uniswap is stable under a wide range of market conditions.

Automation and occupational mobility: A data-driven network model
R. Maria del Rio-Chanona,Penny Mealy,Mariano Beguerisse-Díaz,Francois Lafond,J. Doyne Farmer

The potential impact of automation on the labor market is a topic that has generated significant interest and concern amongst scholars, policymakers, and the broader public. A number of studies have estimated occupation-specific risk profiles by examining the automatability of associated skills and tasks. However, relatively little work has sought to take a more holistic view on the process of labor reallocation and how employment prospects are impacted as displaced workers transition into new jobs. In this paper, we develop a new data-driven model to analyze how workers move through an empirically derived occupational mobility network in response to automation scenarios which increase labor demand for some occupations and decrease it for others. At the macro level, our model reproduces a key stylized fact in the labor market known as the Beveridge curve and provides new insights for explaining the curve's counter-clockwise cyclicality. At the micro level, our model provides occupation-specific estimates of changes in short and long-term unemployment corresponding to a given automation shock. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having very few job transition opportunities. Such insights could be fruitfully applied to help design more efficient and effective policies aimed at helping workers adapt to the changing nature of the labor market.

Behavioral Finance -- Asset Prices Predictability, Equity Premium Puzzle, Volatility Puzzle: The Rational Finance Approach
Svetlozar Rachev,Stoyan Stoyanov,Stefan Mittnik,Frank J. Fabozzi,Abootaleb Shirvani

In this paper we address three main objections of behavioral finance to the theory of rational finance, considered as anomalies the theory of rational finance cannot explain: Predictability of asset returns, The Equity Premium, (The Volatility Puzzle. We offer resolutions of those objections within the rational finance. We do not claim that those are the only possible explanations of the anomalies, but offer statistical models within the rational theory of finance which can be used without relying on behavioral finance assumptions when searching for explanations of those anomalies.

Bootstrapping Laplace Transforms of Volatility
Hounyo, Ulrich,Liu, Zhi,Varneskov, Rasmus Tangsgaard
This paper studies inference for the realized Laplace transform (RLT) of volatility in a fixed-span setting using bootstrap methods. Specifically, since standard wild bootstraps provide inconsistent inference, we propose local Gaussian (LG) and modified wild (MW) bootstrap procedures, and establish their first-order asymptotic validity. Moreover, motivated by its superior finite sample performance in simulations, we use Edgeworth expansions to show that the LG inference achieves second-order asymptotic refinements. To further broaden the scope of the bootstraps, we provide new Laplace transform-based estimators of the spot variance as well as the covariance, correlation and beta between two semimartingales, and adapt our inference procedures to the requisite scenario. We establish central limit theory for our estimators and show first-order asymptotic validity of their associated bootstraps. Not surprisingly, a Monte Carlo study shows that the LG bootstrap outperforms the MW bootstrap and existing (first-order) feasible inference theory in finite samples. Moreover, it demonstrates that our new spot measure estimators and inference procedures are very accurate. Finally, we illustrate the use of the new methods by examining the volatility of, and the coherence between, stocks and bonds during the large equity sell-off in December 2018.

Can We Learn From Lessons of the Past? A Closer Examination of the Corporate Policy Response of Asian Firms Around the Asian Financial Crisis
Yang, Jin Young,Segara, Reuben
Using a sample of firms from 8 East Asian countries, we document the corporate policy (cash holding, investment, financing, and payout) response to the Asian Financial Crisis of 1997-1998. Following the crisis, we find significant evidence of a build-up of cash holdings, a fall in capital spending, decreases in sourcing funds from capital markets, and a reduction in dividend payout offset with an increase in the use of repurchases. Our results suggest that such corporate policies used by Asian firms were designed to improve their financial strength by increasing financial flexibility.

Capturing Model Risk and Rating Momentum in the Estimation of Probabilities of Default and Credit Rating Migrations
Marius Pfeuffer,Goncalo dos Reis,Greig smith

We present two methodologies on the estimation of rating transition probabilities within Markov and non-Markov frameworks. We first estimate a continuous-time Markov chain using discrete (missing) data and derive a simpler expression for the Fisher information matrix, reducing the computational time needed for the Wald confidence interval by a factor of a half. We provide an efficient procedure for transferring such uncertainties from the generator matrix of the Markov chain to the corresponding rating migration probabilities and, crucially, default probabilities.

For our second contribution, we assume access to the full (continuous) data set and propose a tractable and parsimonious self-exciting marked point processes model able to capture the non-Markovian effect of rating momentum. Compared to the Markov model, the non-Markov model yields higher probabilities of default in the investment grades, but also lower default probabilities in some speculative grades. Both findings agree with empirical observations and have clear practical implications.

We illustrate all methods using data from Moody's proprietary corporate credit ratings data set. Implementations are available in the R package ctmcd.

Cointegration and Causality in Capital Markets
Inci, A. Can
Purpose â€" The purpose of this paper is to study the efficiency of different oil and gas markets. Most previous studies examined the issue using low frequency date sampled at monthly, weekly, or daily frequencies. In this study, 30-minute intraday data are used to explore efficiency in energy markets.Design/methodology/approach â€" Sophisticated statistical analysis techniques such as Granger-causality regressions, augmented Dickey-Fuller tests, cointegration tests, vector autoregressions are used to explore the transmission of information between oil and gas energy markets.Findings â€" This study provides evidence for efficiency in energy markets. The new information that arrives either to futures markets or spot markets is digested correctly, completely, and in a fast manner, and is propagated to the other market. The evidence indicates high efficiency.Originality/value â€" This study is one of the first papers that uses 30-minute interval intraday data to investigate efficiency in oil and gas commodity markets.

Cryptocurrencies: Applications and Investment Opportunities
Inci, A. Can,Lagasse, Rachel
Purpose â€" This study investigates the role of cryptocurrencies in enhancing the performance of portfolios constructed from traditional asset classes. Using a long sample period covering not only the large value increases but also the dramatic declines during the beginning of 2018, the study aims to provide a more complete analysis of the dynamic nature of cryptocurrencies as individual investment opportunities, and as components of optimal portfolios.Design/methodology/approach â€" The mean-variance optimization technique of Merton (1990) is applied to develop the risk and return characteristics of the efficient portfolios, along with the optimal weights of the asset class components in the portfolios.Findings â€" We provide evidence that as a single investment, the best cryptocurrency is Ripple, followed by Bitcoin and Litecoin. Furthermore, cryptocurrencies have a useful role in the optimal portfolio construction and in investments, in addition to their original purposes for which they were created. Bitcoin is the best cryptocurrency enhancing the characteristics of the optimal portfolio. Ripple and Litecoin follow in terms of their usefulness in an optimal portfolio as single cryptocurrencies. Including all these cryptocurrencies in a portfolio generates the best (most optimal) results. Contributions of the cryptocurrencies to the optimal portfolio evolve over time. Therefore, the results and conclusions of this study have no guarantee for continuation in an exact manner in the future. However, the increasing popularity and the unique characteristics of cryptocurrencies will assist their future presence in investment portfolios.Originality/value â€" This is one of the first studies that examine the role of popular cryptocurrencies in enhancing a portfolio composed of traditional asset classes. The sample period is the largest that has been used in this strand of the literature, and allows comparing optimal portfolios in early / recent subsamples, and during the pre- / post-cryptocurrency crisis periods.

Decentralised Monetary Systems
Camilla, Natalya
Digital currencies are rising in popularity owing to their purported benefits and the speculative profits that investors are making in the market. These currencies, though decentralised in substance, can be purchased or traded across multiple digital currency platforms. In Africa, these platforms are still at the nascent stages of growth and development, but evidence suggests a burgeoning potential in developing markets. This paper serves as an introductory guide to the market, its prominent currencies as well as some of its key characteristics.

Diversity and Sparsity: A New Perspective on Index Tracking
Yu Zheng,Timothy M. Hospedales,Yongxin Yang

We address the problem of partial index tracking, replicating a benchmark index using a small number of assets. Accurate tracking with a sparse portfolio is extensively studied as a classic finance problem. However in practice, a tracking portfolio must also be diverse in order to minimise risk -- a requirement which has only been dealt with by ad-hoc methods before. We introduce the first index tracking method that explicitly optimises both diversity and sparsity in a single joint framework. Diversity is realised by a regulariser based on pairwise similarity of assets, and we demonstrate that learning similarity from data can outperform some existing heuristics. Finally, we show that the way we model diversity leads to an easy solution for sparsity, allowing both constraints to be optimised easily and efficiently. we run out-of-sample backtesting for a long interval of 15 years (2003 -- 2018), and the results demonstrate the superiority of the proposed algorithm.

Dynamic Equilibrium with Costly Short-Selling and Lending Market
Atmaz, Adem,Basak, Suleyman,Ruan, Fangcheng
We develop a tractable model of costly stock short-selling and lending market within a familiar dynamic asset pricing framework. The model addresses the vast empirical literature in this market and generates implications that support many of the empirical regularities. In the model, investors’ belief disagreement leads to the presence of stock lenders and short-sellers, who in turn pay shorting fees to lenders. We find that the equilibrium stock price increases in shorting fee, and both the stock price and shorting fee decrease in lenders’ size. We additionally show that the stock risk premium decreases in shorting fee, while the stock volatility is increased due to costly short-selling. Notably, we demonstrate that the equilibrium short interest increases in shorting fee and predicts future stock returns negatively. Furthermore, we find that short-selling risk matters in equilibrium, and show that a higher short-selling risk can lead to lower stock returns and less short-selling activity.

Dynamic Interaction between Shared Autonomous Vehicles and Public Transit: A Competitive Perspective
Baichuan Mo,Zhejing Cao,Hongmou Zhang,Yu Shen,Jinhua Zhao

The emerging autonomous vehicles (AV) can either supplement the public transportation (PT) system or be a competitor with it. This paper focuses on this competition in a hypothetical scenario--"if both AV and PT operators are profit-oriented," and uses an ABM to quantitatively evaluate the system performance in this competition from the perspectives of four stakeholders--AV operator, PT operator, passengers, and public authority. In our model, AV operator updates its supply by changing fleet sizes while PT by adjusting headways, and both use heuristic approaches to update supply in order to increase profits. We implement the model in the first-mile scenario in Tampines. In four regulation scenarios--two by two combinations regarding whether AV and PT are allowed to change supplies--we find that since AV can release the bus operator from low-demand routes, the competition can lead to higher profits of both, and higher system efficiency, simultaneously, rather than a one-sided loss-gain result. For PT, after supply updates, spatially the services are concentrated to short feeder routes directly to the subway station, and temporally concentrated to peak hours. For passengers, the competition reduces their travel time but increases their travel costs. Nonetheless, the generalized travel cost is still reduced when counting the value of time. For system efficiency and sustainability, bus supply adjustment can increase the bus average load and reduce total PCE, while the AV supply adjustment shows the opposite effect. For policy implications, the paper suggests that PT should be allowed to optimize its supply strategies under specific operation goal constraints, and AV operation should be regulated to relieve its externality on the system, including limiting the number of licenses, operation time, and service areas, which makes AV operate like a complementary mode to PT.

ETF Corporate Bond Ownership and Market Quality
Rhodes, Meredith,Mason, Joseph R.
This paper examines the role exchange-traded funds (ETFs) play in providing information to underlying corporate bond markets. We document liquidity improvements for individual corporate bonds regardless of market direction. That increased liquidity, however, comes at the cost of greater market sensitivity. Three separate tests show that increased ETF ownership increases the systematic risk component of bond prices and disrupts the flow of firm-specific information to underlying bonds. The results suggest, therefore, that while ETF ownership improves bond market liquidity, ownership is associated with a dissociation between bond prices and firm fundamentals. Mutual fund ownership does not have the same effect, suggesting the active intraday trading that is the hallmark of ETFs may also serve as the mechanism through which information flow is affected.

Efficiency of Brent Index and Futures Markets
Inci, A. Can
Previous studies on the efficiency of oiI and gas markets have used monthly, weekly, or daily data. With the fast evolving, high-speed transaction globalized financial markets; efficiency of markets is better-explored using intraday day. In this paper, data sampled at 30-minute intervals intraday are used for this purpose. The efficiency and effectiveness of information propagation is examined between spot and derivatives markets of oil and gas commodities. Furthermore, the interpretation of new information and its incorporation into the prices are also examined with high frequency sampled data. The evidence from oil and gas markets is indicative of well-functioning commodity markets with highly efficiency conduction of information.

Efficiency of Stock Market: A Study of Stock Price Responses to Earnings Announcements
Hawaldar, Iqbal Thonse ,Mallikarjunappa, T.
Market efficiency is examined in three forms: weak form, semi-strong form and strong form and each one deals with a different source of information. 1. Weak form efficient market - the prices of securities fully reflect all historical information and no excess returns can be earned by utilising historical share prices. 2. Semi-strong form - securities prices adjust instantaneously to available new information such as earnings announcements, bonus issue, merger and acquisition, etc. so that no excess returns can be earned by trading on that information. 3. Strong form efficient market - securities prices fully reflect all information, including inside or private information.

Efficient representation of supply and demand curves on day-ahead electricity markets
Mariia Soloviova,Tiziano Vargiolu

Our paper aims to model supply and demand curves of electricity day-ahead auction in a parsimonious way. Our main task is to build an appropriate algorithm to present the information about electricity prices and demands with far less parameters than the original one. We represent each curve using mesh-free interpolation techniques based on radial basis function approximation. We describe results of this method for the day-ahead IPEX spot price of Italy.

Elusive Longer-Run Impacts of Head Start: Replications Within and Across Cohorts
Remy J.-C. Pages,Dylan J. Lukes,Drew H. Bailey,Greg J. Duncan

Using an additional decade of CNLSY data, this study replicated and extended Deming's (2009) evaluation of Head Start's life-cycle skill formation impacts in three ways. Extending the measurement interval for Deming's adulthood outcomes, we found no statistically significant impacts on earnings and mixed evidence of impacts on other adult outcomes. Applying Deming's sibling comparison framework to more recent birth cohorts born to CNLSY mothers revealed mostly negative Head Start impacts. Combining all cohorts shows generally null impacts on school-age and early adulthood outcomes.

Estimating the Welfare Effects of School Vouchers
Vishal Kamat,Samuel Norris

We analyze the welfare effects of voucher provision in the DC Opportunity Scholarship Program (OSP), a school voucher program in Washington, DC, that randomly allocated vouchers to students. To do so, we develop new discrete choice tools to show how to use data with random allocation of school vouchers to characterize what we can learn about the welfare benefits of providing a voucher of a given amount, as measured by the average willingness to pay for that voucher, and these benefits net of the costs of providing that voucher. A novel feature of our tools is that they allow specifying the relationship of the demand for the various schools with respect to prices to be entirely nonparametric or to be parameterized in a flexible manner, both of which do not necessarily imply that the welfare parameters are point identified. Applying our tools to the OSP data, we find that provision of the status-quo as well as a wide range of counterfactual voucher amounts has a positive net average benefit. We find these positive results arise due to the presence of many low-tuition schools in the program, removing these schools from the program can result in a negative net average benefit.

Financials Sector Intraday Volatility Characteristics in the Emerging Turkish Economy
Inci, A. Can
The Financials sector in the Turkish economy has grown at a tremendous rate over the last 35 years. The liberalization and the opening of the economy to international and foreign investors in the 1990s, and the overhaul of the structure of the Turkish banking system with numerous reforms after the economic crisis in the beginning of the 2000s have strengthened the sector. The purpose of this study is to examine the volatility characteristics of the sector in recent years. Using intraday data, the efficiency of the Financials Sector and the five sub-sectors: Banking, Insurance, Financial Factoring, Investments, Real Estate are examined. The impacts of global, regional, and domestic events are analyzed. Public policy decisions of financial regulators to accommodate the changing economic and political conditions are investigated, as is the efficacy of such decisions.

Firm-Initiated Clawback Provisions and Insider Trading
Le, Trinh Hue,Oliver, Barry R.,Tan, Kelvin Jui Keng
This paper investigates the causal effect of firm-initiated compensation clawback provisions on the profitability of insider trading. We find that clawback provisions reduce the ability of insiders to generate profits from their trades, especially insider sales, based on their information advantage. However, this effect is not associated with prior information asymmetry conditions as the literature suggests. Instead, our evidence suggests that firm-initiated clawback provisions prevent firm insiders from extracting wealth relative to other market participants. Overall, our findings suggest that clawback provisions are effective in preventing insiders from withholding value-relevant information to trade gainfully.

Firming up the capital base of the Austrian business sector - Consolidating Austria's business sector strengths and its social role in the face of new challenges
Dlugosch, Dennis,Gönenç, Rauf,Kim, Eun Jung,Paciorek, Aleksandra
While small- and medium sized firms in Austria are generally more productive, export more, and engage more in higher technology activities than in comparable countries, they need to adapt better to the knowledge economy to maintain their relative performance levels. The capital structure of Austrian SMEs are biased towards debt-financing and stronger equity, growth and venture capital markets would provide them with further resources for their long-term knowledge based investments. Skills shortages, in particular in advanced digital technologies, should be overcome. As around one third of all SMEs are up for ownership transmissions, ensuring successful business transfers will be crucial for maintaining the broad-based entrepreneurial dynamism. Meeting these challenges would also help to lift constraints on upscaling that many SMEs face and would provide the fruitful soil for future innovative activities.This Working Paper relates to the 2019 OECD Economic Survey of Austria (

Gender Pay Gap, Labor Unions and Firm Performance
Dugardin, Fabien-Antoine,Ginglinger, Edith
Using detailed employee-employer administrative data, we analyze the impact of the gender pay gap on the performance of firms and find that it depends on the presence of labor unions. When the firm is not unionized, the gender pay gap reduces profitability. In contrast, when unions are present, the gender gap has no effect on profitability in male-dominated firms and increases profitability in female-dominated firms. Our evidence suggests that when there is no union, giving priority to cohesion and pay equality is value-enhancing. In highly feminized firms, unions provide employees with the option of nonpecuniary benefits, with females opting for better work-life balance and males opting for higher salaries. Our findings indicate that in these firms, the gender pay gap may reflect the divergent interests of female and male employees and can positively affect firm value.

Herding and Anchoring in Cryptocurrency Markets: Investor Reaction to Fear and Uncertainty
Gurdgiev, Constantin,O'Loughlin, Daniel
Cryptocurrencies have emerged as an innovative alternative investment asset class, traded in data-rich markets by globally distributed investors. Although significant attention has been devoted to their pricing properties, to-date, academic literature on behavioral drivers remains less developed. We explore the question of how price dynamics of cryptocurrencies are influenced by the interaction between behavioral factors behind investor decisions and publicly accessible data flows. We use sentiment analysis to model the effects of public sentiment toward investment markets in general, and cryptocurrencies in particular on crypto-assets’ valuations. Our results show that investor sentiment can predict the price direction of cryptocurrencies, indicating direct impact of herding and anchoring biases. We also discuss a new direction for analyzing behavioral drivers of the crypto assets based on the use of natural language AI to extract better quality data on investor sentiment.

High Dimensional Estimation, Basis Assets, and Adaptive Multi-Factor Models
Liao Zhu,Sumanta Basu,Robert A. Jarrow,Martin T. Wells

The paper proposes a new high-dimensional algorithm, the Groupwise Interpretable Basis Selection (GIBS) algorithm to estimate a new Adaptive Multi-Factor (AMF) asset pricing model, implied by the recently developed Generalized Arbitrage Pricing Theory, which relaxes the convention that the number of risk-factors is small. We first obtain an adaptive collection of basis assets and then simultaneously test which basis assets correspond to which securities. Since the collection of basis assets is quite large and highly correlated, high-dimension methods are used. The AMF model along with the GIBS algorithm is shown to have a significantly better fit than the Fama-French 5-factor model.

Higher Purpose, Corporate Culture and Governance in Banking
Thakor, Anjan V.
This paper provides a brief assessment of how organizational higher purpose, ethics, culture and corporate governance have evolved in banking since the financial crisis. It concludes that we need to strengthen capital ratios and equity governance in banking to improve ethics and culture, and de-emphasize liquidity regulation. It also advocates the embrace of authentic organizational higher purpose in banking as a way to foster stability and growth.

How Mixed Ownership Affects Decision Making in Turbulent Times: Evidence From the Digital Revolution in Telecommunications
Wehrheim, David,Dalay, Hakki Dogan,Fosfuri, Andrea,Helmers, Christian
This study examines how the ownership structure of corporations shapes their responses to technological change. We predict that mixed ownership, a situation in which, following privatization, the shares of a company are partly privately held and partly held by the government, is associated with lower responsiveness to technological change. We theorize that the top management of corporations with mixed ownership is exposed to conflicting views regarding how companies should address the challenges posed by technological change, thereby making them more likely to maintain the status quo. In addition, we argue that mixed ownership is particularly problematic when firms attempt to integrate extramural technology to manage technological transformation. Our data on European telecommunications operators that had to adapt to the advent of Internet-based communication services support our predictions.

Insurable Losses, Pre-filled Claims Forms and Honesty in Reporting
Ruffle, Bradley J.,Morrison, William
We design a series of laboratory experiments to investigate the effects of purchasing insurance and of pre-filled claim forms on dishonesty in loss reporting. In our experiment, participants report the outcome of privately rolling two dice where the numbers rolled map to a payoff distribution with the possibility of losses in earned income. Prior to this reporting task, participants bid for a limited number of insurance contracts which issue an indemnity payment equal to each insured individual’s reported loss. We find that dishonest reporting is significantly more prevalent among insured individuals relative to the uninsured, consistent with an 'entitlement bias’. Further we find that prefilling the reporting form with the most probable outcome only modestly constrains dishonest reporting among both insured and uninsured individuals. We explore reasons why pre-filled forms should be applied with caution.

Mergers in the Digital Economy
Gautier, Axel,Lamesch, Joe
Over the period 2015-2017, the five giant technologically leading firms, Google, Amazon, Facebook, Amazon and Microsoft (GAFAM) acquired 175 companies, from small start-ups to billion dollar deals. By investigating this intense M&A, this paper ambitions a better understanding of the Big Five’s strategies. To do so, we identify 6 different user groups gravitating around these multi-sided companies along with each company’s most important market segments. We then track their mergers and acquisitions and match them with the segments. This exercise shows that these five firms use M&A activity mostly to strengthen their core market segments but rarely to expand their activities into new ones. Furthermore, most of the acquired products are shut down post acquisition, which suggests that GAFAM mainly acquire firm’s assets (functionality, technology, talent or IP) to integrate them in their ecosystem rather than the products and users themselves. For these tech giants, therefore, acquisition appears to be a substitute for in-house R&D. Finally, from our check for possible â€Å"killer acquisitions�, it appears that just a single one in our sample could potentially be qualified as such.

NAPLES;Mining the lead-lag Relationship from Non-synchronous and High-frequency Data
Katsuya Ito,Kei Nakagawa

In time-series analysis, the term "lead-lag effect" is used to describe a delayed effect on a given time series caused by another time series. lead-lag effects are ubiquitous in practice and are specifically critical in formulating investment strategies in high-frequency trading. At present, there are three major challenges in analyzing the lead-lag effects. First, in practical applications, not all time series are observed synchronously. Second, the size of the relevant dataset and rate of change of the environment is increasingly faster, and it is becoming more difficult to complete the computation within a particular time limit. Third, some lead-lag effects are time-varying and only last for a short period, and their delay lengths are often affected by external factors. In this paper, we propose NAPLES (Negative And Positive lead-lag EStimator), a new statistical measure that resolves all these problems. Through experiments on artificial and real datasets, we demonstrate that NAPLES has a strong correlation with the actual lead-lag effects, including those triggered by significant macroeconomic announcements.

Noncompliance in randomized control trials without exclusion restrictions
Masayuki Sawada

For randomized experiments with noncompliance, I propose a method to identify treatment effects without exclusion restrictions. It exploits a baseline survey that is commonly available in randomized experiments. I show the identification of the average treatment effect on the treated (ATT) and the local average treatment effect (LATE), assuming that a baseline variable maintains similar rank orders to the control outcome. I apply this strategy to a microcredit experiment with one-sided noncompliance to identify the ATT. I find that the instrumental variable (IV) estimate of log revenue is 2.2 times larger than my preferred estimate. Supplemental materials are available online.

Optical Proof of Work
Michael Dubrovsky,Marshall Ball,Bogdan Penkovsky

Most cryptocurrencies rely on Proof-of-Work (PoW) "mining" for resistance to Sybil and double-spending attacks, as well as a mechanism for currency issuance. Hashcash PoW has successfully secured the Bitcoin network since its inception, however, as the network has expanded to take on additional value storage and transaction volume, Bitcoin PoW's heavy reliance on electricity has created scalability issues, environmental concerns, and systemic risks. Mining efforts have concentrated in areas with low electricity costs, creating single points of failure. Although PoW security properties rely on imposing a trivially verifiable economic cost on miners, there is no fundamental reason for it to consist primarily of electricity cost. The authors propose a novel PoW algorithm, Optical Proof of Work (oPoW), to eliminate energy as the primary cost of mining. Proposed algorithm imposes economic difficulty on the miners, however, the cost is concentrated in hardware (capital expense-CAPEX) rather than electricity (operating expenses-OPEX). The oPoW scheme involves minimal modifications to Hashcash-like PoW schemes, inheriting safety/security properties from such schemes.

Rapid growth and improvement in silicon photonics over the last two decades has led to the commercialization of silicon photonic co-processors (integrated circuits that use photons instead of electrons to perform specialized computing tasks) for low-energy deep learning. oPoW is optimized for this technology such that miners are incentivized to use specialized, energy-efficient photonics for computation. Beyond providing energy savings, oPoW has the potential to improve network scalability, enable decentralized mining outside of low electricity cost areas, and democratize issuance. Due to the CAPEX dominance of mining costs, oPoW hashrate will be significantly less sensitive to underlying coin price declines.

Optimal exercise of American options under stock pinning
Bernardo D'Auria,Eduardo García-Portugués,Abel Guada-Azze

We address the problem of optimally exercising American options based on the assumption that the underlying stock's price follows a Brownian bridge whose final value coincides with the strike price. In order to do so, we solve the discounted optimal stopping problem endowed with the gain function $G(x) = (S - x)^+$ and a Brownian bridge whose final value equals $S$. These settings came up as a first approach of optimally exercising an option within the so-called "stock pinning" scenario. The optimal stopping boundary for this problem is proved to be the unique solution, up to certain regularity conditions, of an integral equation, which is then numerically solved by an algorithm hereby exposed. We face the case where the volatility is unspecified by providing an estimated optimal stopping boundary that, alongside with pointwise confidence intervals, provide alternative stopping rules. Finally, we demonstrate the usefulness of our method within the stock pinning scenario through a comparison with the optimal exercise time based on a geometric Brownian motion. We base our comparison on the contingent claims and the 5-minutes intraday stock price data of Apple and IBM for the period 2011-2018. Supplementary materials with the main proofs and auxiliary lemmas are available online.

Optimal portfolio choice with path dependent labor income: the infinite horizon case
Enrico Biffis,Fausto Gozzi,Cecilia Prosdocimi

We consider an infinite horizon portfolio problem with borrowing constraints, in which an agent receives labor income which adjusts to financial market shocks in a path dependent way. This path-dependency is the novelty of the model, and leads to an infinite dimensional stochastic optimal control problem. We solve the problem completely, and find explicitly the optimal controls in feedback form. This is possible because we are able to find an explicit solution to the associated infinite dimensional Hamilton-Jacobi-Bellman (HJB) equation, even if state constraints are present. To the best of our knowledge, this is the first infinite dimensional generalization of Merton's optimal portfolio problem for which explicit solutions can be found. The explicit solution allows us to study the properties of optimal strategies and discuss their financial implications.

PCA for Implied Volatility Surfaces
Marco Avellaneda,Brian Healy,Andrew Papanicolaou,George Papanicolaou

Principal component analysis (PCA) is a useful tool when trying to construct factor models from historical asset returns. For the implied volatilities of U.S. equities there is a PCA-based model with a principal eigenportfolio whose return time series lies close to that of an overarching market factor. The authors show that this market factor is the index resulting from the daily compounding of a weighted average of implied-volatility returns, with weights based on the options' open interest (OI) and Vega. The authors also analyze the singular vectors derived from the tensor structure of the implied volatilities of S&P500 constituents, and find evidence indicating that some type of OI and Vega-weighted index should be one of at least two significant factors in this market.

Political Turmoil and the Impact of Foreign Orders on Equity Prices
Tiniç, Murat,Savaser, Tanseli
This paper examines whether foreign investors possess an information advantage over local investors in the Turkish stock market between 2007 and 2015. We find that foreign investors have an information advantage in 24 stocks, corresponding to seven percent of the sample firms. Foreign investors’ information advantage tends to prevail primarily during a period of political instability, which started with the Gezi Park protests in June 2013. The adverse selection component of the foreign trade spreads, which reflects a permanent change in stock prices, rises significantly after June 2013, by 66 bps. Our results suggest that domestic investors’ funding constraints, which limit their ability to impart their information on stock prices, may give foreign investors a relative information advantage during periods of political turmoil.

Productivity and finance: the intangible assets channel - a firm level analysis
Demmou, Lilas,Franco, Guido,Stefanescu, Irina
Using a cross-country firm level panel dataset from 1995 to 2015, this paper revisits the finance–productivity nexus by looking at the role of intangible assets. It argues that due to their specific characteristics, such as valuation uncertainty and lower pledgeability, financing the purchase of intangible assets is more difficult than that of tangible assets. As a result, financial frictions are expected to be more binding for productivity growth in sectors where intangibles have become a pivotal component in firms production function. The analysis relies on a panel fixed effects econometric approach, several indices to capture financial frictions at the firm level and a new measure of intangible intensity at the industry level. We provide evidence that financial frictions act as a drag on productivity growth and especially so with respect to firms operating in intangible intensive sectors. These findings, which are robust to alternative specifications, shed light on the role of financial factors in explaining the productivity slowdown in OECD countries and provide support for using intangible intensity as a new dimension to proxy the relative exposure of industries to financing frictions.

Randomized optimal stopping algorithms and their convergence analysis
Christian Bayer,Denis Belomestny,Paul Hager,Paolo Pigato,John Schoenmakers

In this paper we study randomized optimal stopping problems and consider corresponding forward and backward Monte Carlo based optimisation algorithms. In particular we prove the convergence of the proposed algorithms and derive the corresponding convergence rates.

Real-Time Macro Information and Bond Return Predictability: Does Deep Learning Help?
Feng, Guanhao,Fulop, Andras,Li, Junye
This paper examines whether deep/machine learning can help find any statistical and economic evidence of out-of-sample bond return predictability when real-time, instead of fully-revised, macro variables are taken as predictors. First, we find some statistical evidence for forecasting non-overlapping excess bond returns using the deep learning models. Second, for forecasting overlapping excess bond returns, we find more apparent statistical evidence, for which the two nonlinear regression tree models, boosted tree and random forest, outperform the deep learning models. However, this statistical evidence is weaker than that from using fully-revised macro data and cannot generate any economic gains for a mean-variance investor, regardless of her level of risk aversion and whether she can take short positions.

Shareholder Satisfaction with Overlapping Directors
Li, Rachel,Schwartz-Ziv, Miriam
Mutual fund shareholders are particularly supportive of “overlapping directors”â€"directors who serve simultaneously on a corporate board and a mutual fund board. Such support is observed on behalf of both connected funds (sharing a director with the company) and non-connected funds (not sharing a director with the company), and is particularly prominent when monitoring is needed. Our results suggest that the benefits offered by overlapping directors to all fund shareholders exceed the costs arising from their potential conflicts of interest, and that the benefits they offer are more valuable to mutual fund shareholders than to other types of shareholders.

Sleeping With the Enemy: Should Investment Banks Be Allowed to Engage in Prop Trading?
Charitou, Andreas,Karamanou, Irene
In the midst of the controversy regarding the consequences of the Volcker Rule, we examine whether conflicts of interest exist between the research and proprietary (prop) trading departments of investment banks. Consistent with the existence of a prop trading incentive, our results suggest that banks trade both ahead of and against their upgrades and downgrades for stocks not affiliated with the investment banking department and with small institutional interest. Our results are robust to a vast array of validation and sensitivity analyses, alleviating concerns that they are driven by unobserved factors. Our analysis also suggests that the global settlement, which targeted the investment banking incentive, has accentuated the prop trading incentive. Similarly, our results do not suggest that the financial crisis and the recent attention of regulators to conflicts of interest arising from prop trading have had any success in curtailing the prop trading incentive.

Stewardship and Collective Action: The Australian Experience
Bowley, Tim,Hill, Jennifer G.
Institutional shareholder stewardship codes (‘stewardship codes’) exist in many jurisdictions. They reflect the growing importance of institutional shareholders in capital markets, and a belief that increased engagement by institutional shareholders improves corporate decision-making and provides protection against excessive risk-taking. In theory, there is considerable sense in shareholders undertaking their stewardship activities collectively. By acting collectively, shareholders leverage their power, pool their resources and share costs, thereby making stewardship more feasible and less speculative. Consistently, the stewardship codes of many jurisdictions refer to, and implicitly support, collective action by institutional investors.This paper examines the role of collective action as a form of stewardship, with particular reference to the Australian context. Australia provides favourable conditions for institutional investor stewardship and is, therefore, an interesting case study concerning the potential of collective action as a stewardship tool. This paper’s examination of collective action in Australia reveals, however, a nuanced image of this governance practice. Evidence indicates that investors do not routinely engage in direct forms of collective action, such as forming a coalition for the purpose of intervening in a company’s governance. Instead, investors more typically leverage their collective influence through intermediary organisations, such as industry bodies and service providers that undertake behind-the-scenes engagement activities for investors. The nuanced image of collective action emerging from the Australian experience highlights that collective action by institutional shareholders is by no means a simple governance phenomenon. The paper explores the implications of this insight for how securities and takeover laws apply to collective action, and how the issuers of stewardship codes frame their codes’ expectations regarding collective action. This analysis is relevant to policy makers, regulators and researchers who are interested in the role and regulation of collective action as a corporate governance tool.

Taxation and Valuation
Leonid A. Levin

The greatest harm from highway robbers lies not in seized wallets but in inhibited travel. Similarly, incentives for tax-reducing strategies put much sand in the wheels of the economy. Demands to replace our monumental tax code with a simple, graceful one that does not distort economic incentives heat up periodically in political debate, but such dreams never materialize. A FUNDAMENTAL obstacle, not yet well understood in the economic literature, is the impossibility of objectively evaluating the tax base -- assets, income, etc. One can see this even in toy examples, say, trying to assess the value of a position in chess: great masters' assessments will all differ. Here computer theory can add an insight not provided by classical economics tools.

A way around is to avoid evaluations by expressing the tax in natural units, not in cash. For publicly traded corporations, these could be corporate shares. I discuss a simple (postcard-sized in ALL details) corporate tax system that avoids ANY distortion of incentives. (Tax tools MEANT to influence corporate policies should be set as explicit separate taxes or credits, open to public scrutiny, not hidden between lines of an incomprehensible tax code.) Roughly, the~system is to periodically take a t*i fraction of shares to auction, where t is the tax rate, i is the interest rate. It replaces all income taxes on publicly traded corporations, their subsidiaries, and shareholders.

The interest rate is defined via specially designed bonds, so that the whole system can be shown PRECISELY equivalent to a flat tax on INVESTMENT RETURN. Note that taxing the return DIRECTLY is impossible: it would invite manipulation of stock market~prices. The main feature is that nothing corporations and investors do can change their tax (t*i fraction of shares), so they would do business exactly the SAME WAY they would WITHOUT TAXES.

The Impact of Speculation on Commodity Prices: A Meta-Granger Analysis
Wimmer, Thomas,Geyer-Klingeberg, Jerome,Hütter, Marie,Schmid, Florian,Rathgeber, Andreas
This paper uses meta-analysis to explain and summarize the mixed results in the literature on the impact of financial speculation on commodity prices. The sample covers 2,106 manually collected p-values from Granger causality tests reported in 54 prior papers. Meta-Granger analysis shows that the heterogeneity in previous findings can be largely explained by the commodity type under examination, the examined time period of the data, the measurement of the focus variables (return, volatility or spread), and the inclusion of control variables in the Granger test. Even after accounting for 23 observable differences in study and test design, our results indicate that studies published in higher ranked journals present significantly less evidence for speculation to drive commodity prices. Moreover, we use the Meta-Granger results to predict ‘best choice’ models considering preferred model setups. The results reveal that the hypothesis of Granger non-causality between speculation and commodity prices cannot be rejected at standard significance levels when assuming a best choice study design and various variations of it. Taken together, the empirical literature as a whole implies no overall speculation effects in agricultural, energy and metal markets.

The Post-Crisis Evolution of Banks and Markets: Introduction
Boot, Arnoud W. A.,Thakor, Anjan V.
This paper reviews the papers that were presented at a conference at Washington University in St. Louis, a subset of which were published in a special issue of The Journal of Financial Intermediation. The papers cover a wide range of issues on how banks and financial markets have evolved since the financial crisis and the blurring of boundaries between institutions and markets.

The Relationship of Financial Factors in Asset Pricing: The Case of Indonesian Market
Aryani, Sinta,Wiryono, Sudarso,Koesrindartoto, Deddy P.
Purpose of the study: The study shows how the financial factor of Leverage affects the empirical model of asset pricing together with other financial factors, i.e. Size, Book to Market, Operating Profit, and Investment. The contribution of Leverage in asset pricing will be tested, and its effect will be shown in the excess return of the asset.Methodology: The methodology used in this paper is based on the Fama and French model of asset pricing with additional factors added in the model. Data processing follows the Fama-Mc Beth procedure. Data comes from the Indonesian Stock Market, which consists of more than 500 stocks for ten years period of observation.Main Findings: The financial factor of Leverage affects the empirical model of asset pricing together with, i.e. Size, Book to Market, Operating Profit, and Investment. All the financial factors in the model are stationary around their mean, or they are non-stationary due to unit-roots. All the independents' variables have P-Value less than 10%.Implications: This study will be useful for financial investors in building an effective portfolio stock investment. By applying this model to their portfolio investment, the investors could effectively manage their portfolio return. On the management side, managing their financing structure, e.g. Leverage is the objective of the firm to maximize returns of the firms.Novelty/Originality of this study: The empirical research with the involvement of the financial factor of Leverage has not been performed in Indonesia. The Leverage as the single factor of asset pricing has been considered as a significant financial factor for asset pricing, however, how the Leverage contributes to asset pricing compares to other financial factors has not examined yet.

Transportation Infrastructure Development and Tax Avoidance: Evidence From a Quasi-Natural Experiment
Ouyang, Caiyue,Xiong, Jiacai,Yao, Jun,Fan, Lyu
Utilizing the launch of high-speed railway (HSR) service in China as a quasi-natural experiment, we identify an important social benefit of the development of transportation infrastructure: the reduction of firms’ value-destroying tax avoidance. Specifically, we find that after the opening of HSR lines to the cities where firms are located, firms have lower information asymmetry and engage in less tax avoidance, which leads to enhanced firm value. In further analysis, we find that this relation is more prominent for firms whose managers have a high propensity to extract rents through aggressive tax strategies. Our results indicate that the launch of HSR service reduces the cost of monitoring, thereby constraining insiders’ ability to extract private benefits under the guise of tax avoidance. To rule out alternative explanations, we conduct several additional analyses.

Weather Variability, Credit Scores and Access to Credit: Evidence from Colombian Coffee Farmers
de Roux, Nicolás
This paper studies how weather variability affects credit scores and credit access in developing countries. Using rich administrative data on loans to coffee farmers from a large Colombian bank, I show that negative weather shocks lead to lower loan repayment, lower credit scores and more frequent denials of future loan applications. I present evidence that affected farmer's income and ability to repay recover more quickly from weather shocks than credit access. Therefore, the interplay of weather variability and credit scores can lead to the exclusion from credit markets of farmers who could repay a loan.