Research articles for the 2020-10-07

Anti-Money Laundering Requirements: Costs, Benefits & Perceptions
Yeandle, Mark,Mainelli, Michael,Berendt, Adrian,Healy, Brian
Today sees the release of a new report which gives a fascinating insight into the fight against Money Laundering. Commissioned jointly by the Corporation of London and the Institute of Chartered Accountants in England & Wales, and carried out by Z/Yen Limited, the main findings are:International requirements on anti-money laundering are implemented more rigorously in the UK than in other jurisdictions and the related costs are higher;The high costs in the UK do not generate greater benefits to UK-based organisations;Despite the high costs in the UK, the fight against money-laundering is not seen as more effective in deterring or detecting money laundering;The UK has not yet become competitively disadvantaged due to the high costs but it is approaching a tipping point;The UK can become more effective at deterring money laundering by raising the perceived likelihood of money launderers being caught and the perceived severity of the punishments;It seems likely that other jurisdictions will incur greater costs in the future as they raise the level of their regulations towards the UK level.The effectiveness of the efforts against money-laundering can be enhanced by closing regulatory and communication gaps. Areas of communications which, if improved, could yield significant results in terms of practicality and effectiveness include:Joined-Up Intelligence: Insufficient resources are aimed at this. Many professionals believe that the regulations could be more effective with a collective pooling of intelligence about money-laundering activity. In the UK, the National Criminal Intelligence Service has a very important role in collecting intelligence but currently does not have sufficient resources to perform this role as effectively as it might;Feedback to financial services institutions regarding the quality and quantity of their reporting appears to be inadequate;Publicity of successful convictions and asset seizures should be given a far higher profile.

Best Execution Compliance Automation
Yeandle, Mark
MiFID requires investment firms to be able to demonstrate that they have secured the best possible execution for their clients, taking into account the various characteristics of the trades involved. In this article, Mark Yeandle, Senior Consultant at Z/Yen, reviews the development and testing of Z/Yen’s risk/ reward prediction software that offers a ‘sifting engine’ designed to help firms automate the best execution compliance function.

Certainty Equivalent and Utility Indifference Pricing for Incomplete Preferences via Convex Vector Optimization
Birgit Rudloff,Firdevs Ulus

For incomplete preference relations that are represented by multiple priors and/or multiple -- possibly multivariate -- utility functions, we define a certainty equivalent as well as the utility buy and sell prices and indifference price bounds as set-valued functions of the claim. Furthermore, we motivate and introduce the notion of a weak and a strong certainty equivalent. We will show that our definitions contain as special cases some definitions found in the literature so far on complete or special incomplete preferences. We prove monotonicity and convexity properties of utility buy and sell prices that hold in total analogy to the properties of the scalar indifference prices for complete preferences. We show how the (weak and strong) set-valued certainty equivalent as well as the indifference price bounds can be computed or approximated by solving convex vector optimization problems. Numerical examples and their economic interpretations are given for the univariate as well as for the multivariate case.

Consumer Demand Shocks and Firm Linkages: Evidence from Demonetization in India
Kisat, Faizaan,Phan, Minh
Exploiting a unique natural experiment, the 2016 demonetization episode in India, this paper analyzes the extent to which a consumer demand shock propagates through firms’ input-output networks. In November 2016, India demonetized 86% of its currency, creating a nationwide demand shock. We construct measures of upstreamness to evaluate the impact of the demonetization shock on firms based on their position in the supply chain. Contrary to the predictions of many network models, we find that the shock does not meaningfully propagate across the supply chain. Revenues, wages, and investment decline substantially after demonetization, but these negative effects are largely limited to consumer facing firms. We identify several mechanisms, such as pricing power, inventory frictions, and export intensity, which independently explain this result. Our findings suggest that final goods producers are particularly susceptible to, and therefore must be protected against, unexpected declines in consumer demand.

Cyclical phenomena in technological change
Mario Coccia

The process of technological change can be regarded as a non-deterministic system governed by factors of a cumulative nature that generate cyclical phenomena. In this context, the process of growth and decline of technology can be systematically analyzed to design best practices for technology management of firms and innovation policy of nations. In this perspective, this study focuses on the evolution of technologies in the U.S. recorded music industry. Empirical findings reveal that technological change in the sector under study here has recurring fluctuations of technological innovations. In particular, cycle of technology has up wave phase longer than down wave phase in the process of evolution in markets before it is substituted by a new technology. Results suggest that radical innovation is one of the main sources of cyclical phenomena for industrial and corporate change, and as a consequence, economic and social change.

Deposit Insurance Premiums and Bank Risk-Taking
Kim, Edward,Rezende, Marcelo
Deposit insurance premiums impose costs on banks' balance sheets, narrowing profit margins and inducing banks to "search for yield." This paper estimates the effects of deposit insurance premiums on bank risk-taking using supervisory data and a kink in the schedule of deposit insurance premiums. We show that deposit insurance premiums weaken bank demand for reserves--a liquid asset with no credit risk--and strengthen the supply of short-term interbank loans|a liquid asset with credit risk. We discuss the implications of these findings for optimal deposit insurance pricing and monetary policy implementation.

Don't Stop Believing: The State & Future Of UK Occupational Pensions
Keating, Con
"Don't Stop Believing: The State & Future Of UK Occupational Pensions" is the second Finance Short on pension written by Con Keating, which considers in detail the position of UK private occupational pensions. It discusses the reasons for the decline in funded defined benefit (DB) provision in the UK and, as collective DB is shown to be an efficient institutional design, proposes remedies that may resuscitate this ailing sector.

Dynamic coalitions in complex task environments: To change or not to change a winning team?
Dario Blanco-Fernandez,Stephan Leitner,Alexandra Rausch

Decision makers are often confronted with complex tasks which cannot be solved by an individual alone, but require collaboration in the form of a coalition. Previous literature argues that instability, in terms of the re-organization of a coalition with respect to its members over time, is detrimental to performance. Other lines of research, such as the dynamic capabilities framework, challenge this view. Our objective is to understand the effects of instability on the performance of coalitions which are formed to solve complex tasks. In order to do so, we adapt the NK-model to the context of human decision-making in coalitions, and introduce an auction-based mechanism for autonomous coalition formation and a learning mechanism for human agents. Preliminary results suggest that re-organizing innovative and well-performing teams is beneficial, but that this is true only in certain situations.

Has the Stock Market Become Less Representative of the Economy?
Schlingemann, Frederik P.,Stulz, René M.
The firms listed on the stock market in aggregate as well as the top market capitalization firm contribute less to total non-farm employment and GDP now than in the 1970s. A major reason for this development is the decline of manufacturing and the growth of the service economy as firms providing services are less likely to be listed on exchanges. We develop quantitative measures of representativeness showing how firms’ market capitalizations differ from their contribution to employment and GDP. Representativeness is worst when the market is most highly valued and worsens over time for employment, but not for value added.

Information Asymmetry and Insurance in Africa
Asongu, Simplice,Odhiambo, Nicholas
In this study, we assess the relevance of decreasing information asymmetry on life and non-life insurance consumption, by using data from 48 African countries during the period 2004-2014. Reduced information asymmetry is proxied by information sharing offices, namely: public credit registries and private credit bureaus. The empirical evidence is based on the Generalised Method of Moments. The findings show that information sharing offices increase insurance consumption with a comparatively higher magnitude in life insurance penetration, relative to non-life insurance penetration. Practical and theoretical implications are discussed.

Is the Transition Risk Material? Testing the Net Environmental Contribution Metric on a Universe of Listed European Equities
Peladan, Jean-Guillaume
In 2017, BNP Paribas Securities Services and Sycomore AM joined forces to accelerate the testing and enable the quicker deployment of a new advanced metric. This metric had been designed to measure the alignment of any economic activity with globally established goals around energy and ecological transition, and climate change mitigation. This metric, the Net Environmental Contribution™ or NEC, provides a single figure on a scale ranging from -100% (negative net contribution/obstruction) to +100% (clear positive contribution/full alignment). Sycomore AM provided BNP Paribas Securities Services with the individual NEC for each of a set of +1,200 companies, covering its whole invested universe and major European indices. This article explores the financial and environmental performance of stocks within the STOXX 600 universe, using the evidence produced by the NEC.Key learnings are:• The NEC key features - distribution and scope of application - are different from environmental (E) ratings provided by extra-financial agencies and high E ratings do not automatically translate into a high contribution to the environmental transition;• Patterns between the NEC and stocks prices emerge when studying three- and five-year periods;• Among the tested strategies, a portfolio of stocks with NECs ranging from +10% to +100% and an average NEC of +25% appears to offer both the highest return and the highest risk-adjusted return (approximated by the Sharpe ratio) over three-year and five-year periods;• As the NEC is a proxy for the degree of alignment with the environmental and energy transition, the preliminary results show it could be material to equity returns and risk-adjusted returns over a period as short as three years.In conclusion, the NEC beta version we tested seems to be useful already, both for constructing an investment strategy and for meeting French article 173 reporting requirements and some of the TCFD recommendations. It seems the NEC methodology, which is moving towards an open-source model, is worth being further improved and rolled out to a broader universe.

Judge Shopping
Kahan, Marcel,McKenzie, Troy A.
We examine related case rules, which are local rules adopted by federal district courts to determine whether a newly filed civil action will be assigned to a randomly chosen judge or, instead, to a judge presiding over a previously-filed similar case. Different federal districts have adopted divergent approaches to the definition of “relatedness” as well as to the process for determining whether a case satisfies the definition. We analyze how these design choices affect the ability of parties to engage in strategic manipulations to direct a case toward (or away from) a particular judge to gain an advantage in litigation and set forth suggestions for the optimal design of the assignment rules for related cases.

Long-Term Foreign Exchange Risk Premia and Inflation Risk
Moneta, Fabio,Kim, Daehwan
As highlighted by recent literature, long-term foreign exchange risk premia (FRP) of a currency pair tend to covary negatively with short-term real interest rates differentials (RIRD) of the pair. We fit an affine term structure model for 9 major currencies against the US dollar and estimate two components of this covariance: the real risk premia (RRP) component and the inflation risk premia differential (IRPD) component. We find that the IRPD component is significantly negative for all currency pairs in our sample. We propose a macro-finance model to understand the type of shocks that generates such covariance.

Modeling Realized Covariance Measures with Heterogeneous Liquidity: A Generalized Matrix-Variate Wishart State-Space Model
Gribisch, Bastian,Hartkopf, Jan P.
We propose to generalize the Wishart state-space model for realized covariance matrices of asset returns in order to capture complex measurement error structures induced by heterogeneous liquidity across assets. Our model assumes that the latent covariance matrix of the assets is observed through their realized covariance matrix with a Riesz measurement density, which generalizes the Wishart to monotone missing data. The Riesz alleviates the Wishart-implied attenuation of measurement errors for less liquid assets and translates into a convenient likelihood factorization which facilitates inference using simple Bayesian MCMC procedures. The statespace approach allows for a flexible description of the covariance dynamics implied by the data and an empirical application shows that the model performs very well in- and out-of-sample.

Modeling the commodity prices of base metals in Indian commodity market using a Higher Order Markovian Approach
Suryadeepto Nag,Sankarshan Basu,Siddhartha P. Chakrabarty

A Higher Order Markovian (HOM) model to capture the dynamics of commodity prices is proposed as an alternative to a Markovian model. In particular, the order of the former model, is taken to be the delay, in the response of the industry, to the market information. This is then empirically analyzed for the prices of Copper Mini and four other bases metals, namely Aluminum, Lead, Nickel and Zinc, in the Indian commodities market. In case of Copper Mini, the usage of the HOM approach consistently offer improvement, over the Markovian approach, in terms of the errors in forecasting. Similar trends were observed for the other base metals considered, with the exception of Aluminum, which can be attributed the volatility in the Asian market during the COVID-19 outbreak.

No data? No problem! A Search-based Recommendation System with Cold Starts
Pedro M. Gardete,Carlos D. Santos

Recommendation systems are essential ingredients in producing matches between products and buyers. Despite their ubiquity, they face two important challenges. First, they are data-intensive, a feature that precludes sophisticated recommendations by some types of sellers, including those selling durable goods. Second, they often focus on estimating fixed evaluations of products by consumers while ignoring state-dependent behaviors identified in the Marketing literature.

We propose a recommendation system based on consumer browsing behaviors, which bypasses the "cold start" problem described above, and takes into account the fact that consumers act as "moving targets," behaving differently depending on the recommendations suggested to them along their search journey. First, we recover the consumers' search policy function via machine learning methods. Second, we include that policy into the recommendation system's dynamic problem via a Bellman equation framework.

When compared with the seller's own recommendations, our system produces a profit increase of 33%. Our counterfactual analyses indicate that browsing history along with past recommendations feature strong complementary effects in value creation. Moreover, managing customer churn effectively is a big part of value creation, whereas recommending alternatives in a forward-looking way produces moderate effects.

Optimal Capital Structure, Ambiguity Aversion, and Leverage Puzzles
Attaoui, Sami,Cao, Wenbin,Duan, Xiaoman,Liu, Hening
We introduce ambiguity about assets’ value dynamics into a trade-off framework of capital structure to explain the empirically observed zero-leverage and underleverage puzzles. We utilize the decision framework of Chen and Epstein (2002) to characterize investors’ ambiguity aversion. We show that highly ambiguity-averse equity holders perceive that the asset value dynamics of a firm is “too valuable to lose” upon bankruptcy. They optimally choose zero leverage and forgo the tax benefits of debt to avoid possible default. Next, moderately ambiguity-averse equity investors will participate in the debt market, and ambiguity aversion distorts downwards their optimal leverage and debt capacity obtained from the benchmark model with risk aversion only. This distortion effect is stronger (weaker) when a firm’s equity and the debt markets are segmented (integrated). We utilize alternative measures for ambiguity aversion and for market segmentation and find empirical support for our theoretical results.

Promoting UK Cyber Prosperity: Public-Private Cyber-Catastrophe Reinsurance
Mainelli, Michael,Von Gunten, Chiara,Duff, Mark
This Long Finance research project sought to explore how cyber-catastrophe reinsurance might help mitigate cyber-risk, establish some evidence of the appetite for such reinsurance, and examine how government might best provide support for the establishment of an efficient, largely free-market solution.Started in May 2015, the resulting report entitled "Promoting UK Cyber Prosperity: Public-Private Cyber-Catastrophe Reinsurance" was released in July 2015 (press release).Co-sponsored by APM Group, the report explores the nature of cyber-risk and the role of cyber insurance and reinsurance as a risk mitigation tool with a focus on cyber-catastrophe events that is cyber events that could seriously affect the economy. The report explores how a public-private cyber-catastrophe reinsurance scheme could help secure ICT-based prosperity in the UK by helping insurers insure themselves to insure others. The scheme would provide cover to a group of insurers above a catastrophic loss threshold, in effect a pool funded by the insurance industry. The UK government’s role would be one of promotion and (possibly) a last resort insurer only in the event that industry retention and the scheme’s reserves have been exhausted. In all likelihood, the UK government would be a last resort insurer anyway during a cyber-catastrophe, but would benefit by having already promoted risk reduction and mitigation, as well as having accrued some financial reserves.Long Finance engaged key stakeholders including insurance experts and professionals (existing cyber underwriters and specialist brokers), reinsurance professionals, other financial services firms (e.g. major exchanges or fintech firms), providers of cyber-protection services, law and accountancy firms and government through over 80 semi-structured interviews, a round-table, and a webinar.

Real-time tracking of COVID-19 impacts across Europe reveals that seeking "herd immunity" provides no economic benefits
Carlo Fezzi,Valeria Fanghella

This paper develops a methodology for tracking in real time the impact of the COVID-19 pandemic on economic activity by analyzing high-frequency electricity market data. The approach is validated by several robustness tests and by contrasting our estimates with the official statistics on the recession caused by COVID-19 in different European countries during the first two quarters of 2020. Compared with the standard indicators, our results are much more chronologically disaggregated and up-to-date and, therefore, can inform the current debate on the appropriate policy response to the pandemic. Unsurprisingly, we find that nations that experienced the most severe initial outbreaks also grappled with the hardest economic recessions. However, we detect diffused signs of recovery, with economic activity in most European countries returning to its pre-pandemic level by August 2020. Furthermore, we show how delaying intervention or pursuing 'herd immunity' are not successful strategies, since they increase both economic disruption and mortality. The most effective short-run strategy to minimize the impact of the pandemic appears to be the introduction of early and relatively less stringent non-pharmaceutical interventions.

Retirement Implications of a Low Wage Growth, Low Real Interest Rate Economy
Scott, Jason,Shoven, John B.,Slavov, Sita,Watson, John G.
Using a life-cycle model, the authors examine the implications of persistent low real interest rates and low wage growth for individuals nearing retirement. Low returns and low wage growth are found to affect welfare substantially, often producing large compensating variations. Low economy-wide wage growth has a much larger welfare effect than low individual wage growth, largely because the Social Security benefit formula is progressive and incorporates wage indexing. Low economy-wide wage growth undercuts the effects of wage indexation as average wages fall along with individual wages. Low returns raise the optimal Social Security claiming age and the marginal benefit of working longer, while low wage growth decreases the marginal benefit of working longer. Low returns also increase the relative price of consumption during retirement, suggesting that individuals may wish to reduce future consumption relative to current consumption. The authors then compare these findings with standard financial planning advice.

Robust pricing and hedging of options on multiple assets and its numerics
Stephan Eckstein,Gaoyue Guo,Tongseok Lim,Jan Obloj

We consider robust pricing and hedging for options written on multiple assets given market option prices for the individual assets. The resulting problem is called the multi-marginal martingale optimal transport problem. We propose two numerical methods to solve such problems: using discretisation and linear programming applied to the primal side and using penalisation and deep neural networks optimisation applied to the dual side. We prove convergence for our methods and compare their numerical performance. We show how adding further information about call option prices at additional maturities can be incorporated and narrows down the no-arbitrage pricing bounds. Finally, we obtain structural results for the case of the payoff given by a weighted sum of covariances between the assets.

Sentiment of tweets and socio-economic characteristics as the determinants of voting behavior at the regional level. Case study of 2019 Polish parliamentary election
Grzegorz Krochmal

This work is dedicated to finding the determinants of voting behavior in Poland at the poviat level. 2019 parliamentary election has been analyzed and an attempt to explain vote share for the winning party (Law and Justice) has been made. Sentiment analysis of tweets in Polish (original) and English (machine-translations), collected in the period around the election, has been applied. Amid multiple machine learning approaches tested, the best classification accuracy has been achieved by Huggingface BERT on machine-translated tweets. OLS regression, with sentiment of tweets and selected socio-economic features as independent variables, has been utilized to explain Law and Justice vote share in poviats. Sentiment of tweets has been found to be a significant predictor, as stipulated by the literature of the field.

Tail-risk protection: Machine Learning meets modern Econometrics
Bruno Spilak,Wolfgang Karl Härdle

Tail risk protection is in the focus of the financial industry and requires solid mathematical and statistical tools, especially when a trading strategy is derived. Recent hype driven by machine learning (ML) mechanisms has raised the necessity to display and understand the functionality of ML tools. In this paper, we present a dynamic tail risk protection strategy that targets a maximum predefined level of risk measured by Value-At-Risk while controlling for participation in bull market regimes. We propose different weak classifiers, parametric and non-parametric, that estimate the exceedance probability of the risk level from which we derive trading signals in order to hedge tail events. We then compare the different approaches both with statistical and trading strategy performance, finally we propose an ensemble classifier that produces a meta tail risk protection strategy improving both generalization and trading performance.

Taking Money Off the Table: Suboptimal Early Exercises, Risky Arbitrage, and American Put Returns
Aretz, Kevin,Garrett, Ian,Gazi, Adnan
Many studies report that American option investors often exercise their positions suboptimally late. Yet, when that can happen in case of puts, there is an arbitrage opportunity in perfect markets, exploitable by longing the asset-and-riskfree-asset portfolio replicating the put and shorting the put. Using early exercise data, we show that the arbitrage strategy also earns a highly significant mean return with low risk in real single-stock put markets, in which exactly replicating options is impossible. In line with theory, the strategy performs particularly well on high strike-price puts in high interest-rate regimes. It further performs well on short time-to-maturity puts on low volatility stocks, consistent with evidence that investors do not correctly incorporate those characteristics into their exercise decisions. The strategy survives accounting for trading and short-selling costs, at least when executed on liquid assets.

The Blockchain Evolution and Revolution of Accounting
George, Kimberlyn,Patatoukas, Panos N.
Blockchain, the technology behind digital currency, is a decentralized, distributed ledger that records transactions in digital assets. By authenticating and recording immutable transactions, decentralized blockchains perform the same function as many intermediaries in our society that establish trust and maintain integrity between transacting parties. Due to its natural relation to accounting and possible uses in accounting functions, business operations and financial services, it is important that accountants learn about blockchain technology and its opportunities and limitations. This chapter explores applications of blockchain technology in finance, auditing, financial reporting and supply chain. We first discuss the classification, characteristics and issuance of cryptoassets and the evolving regulatory environment. Then, we address potential innovative uses of blockchain in auditing and financial reporting, keeping in mind the limitations of its application. Finally, we explore how blockchain technology can enhance communication and trust between organizations in a supply chain or in contracting relationships.

The Competitive Position of London as a Global Financial Centre
Mainelli, Michael,Yeandle, Mark,Berendt, Adrian
In June 2003 the Corporation of London published Sizing up the City â€" London’s Ranking as a Financial Centre, a report written by the Centre for the Study of Financial Innovation based on a survey of City opinion of London’s competitive position as an international financial services centre.The 2003 report compared directly London, New York, Paris and Frankfurt. In order to draw direct comparisons, this report also examines those centres but then expands the scope of the study to cover other financial centres.The 2003 report considered six main competitive factors (skilled labour, regulatory competence, tax regime, government responsiveness, regulatory “touch” and living environment). This study expands this to 14 competitive factors, with just one question on the issue of regulation instead of the two contained in the 2003 report.The financial services industry is a major segment of the UK economy and accounts for almost 5.5% of GDP and employs in excess of one million people. The UK has the largest trade surplus in financial services in the world ($25.3bn in 2003, followed by Switzerland $11.0bn). The vast majority of the UK financial services industry is in London. London has long been an important financial centre for a number of good reasons. A trading culture has been maintained since the UK was the dominant trading country in the world in the 18th and 19th centuries. London has a history of openness and a tradition of welcoming foreign traders. The prevalence of the English language has played its part as has the geographical position between the USA and Asian time zones.However, a successful history is no guarantee of future success â€" as the UK textile industry demonstrates. New technology and improved communications infrastructure have reduced the need to be close to financial markets and companies are becoming more skilled at managing operations remotely. London is a relatively expensive city to operate from, the transport infrastructure is regularly criticised and terrorism is still seen as a threat.Can London remain a leading financial centre? How sustainable is the competitive edge that London has enjoyed? Are there likely to be challenges to London’s position as a leading global financial centre? If there are challenges, where will these come from?This study seeks to examine how competitive London is today and how competitive it might be in the future. We have approached this task by asking individuals engaged in the industry what factors they feel makes a financial centre competitive and how important each of these factors is in the competitive mix. We have then assessed these responses to determine how the main financial centres are rated in terms of each of these factors.

The Danger of Developing Then Dashing Expectations: The Lesson from Lehman?
Huertas, Thomas
In the economy expectations exercise enormous effects. Indeed, in finance prices and yields predominantly reflect current expectations about future cash flows and future interest rates. Change those expectations, prices and yields change as well. Change expectations radically enough, the change in prices and yields may be large enough to impact financial markets and the economy at large. The failure of Lehman in September 2008 is a case in point. Prior to its bankruptcy on 15 September 15, 2008, the economy was treading water. Thereafter it sank like a stone, until the massive stimulus programs put in place by governments and central banks began to pull the economy up again.This paper suggests that what made the Great Recession great was the entry of Lehman into bankruptcy. This suddenly swung market expectations concerning government policy from “too big to fail” to “let the chips fall where they may”. Following Lehman’s declaration of bankruptcy, panic ensued, as market participants rushed to adjust to the new situation. This set off a downward debt-deflation spiral that caused the world economy contract rapidly. Only massive monetary and fiscal stimulus, together with explicit government support to systemically important financial institutions (SIFIs) arrested the decline and turned what might have become the Great(er) Depression into the Great Recession. This weakened economies around the world, leading to further crises and changing the political landscape.In concept therefore, allowing implicit guarantees such as “too big to fail” to develop generates not only moral hazard but also creates what might be called public hazard. This is the risk to financial stability and the economy at large, if the government fails to fulfil the implicit guarantee, when called upon to do so. This is a lesson that governments would do well to bear in mind as they wrestle with how to taper off the massive support that they are currently giving to firms and individuals to enable them to offset the economic consequences of COVID-19.

The Effect of State Antitakeover Laws on Corporate Tax Avoidance
Gao, Xinghua,Jia, Yonghong,Kim, Chansog (Francis)
We examine the implications of enhanced managerial control afforded by state anti-takeover laws for tax avoidance and find the strength of anti-takeover statutes in a state is negatively related to tax avoidance of firms incorporated in that state. In testing underlying mechanisms, we find that the empirical results support the price discount concern hypothesis (i.e., managers refrain from tax avoidance activities to prevent potential stock price discounts induced by heightened investor perception of tax-related rent extraction in firms with severe agency problems). By contrast, the results are inconsistent with the quiet life hypothesis (i.e., managers entrenched by state anti-takeover protection enjoy the quiet life by under-investing in tax planning opportunities). Our findings are generally consistent with the takeover market phenomenon that one of managers' concerns lies in their inability to re-contract away the adverse consequences of perceived agency problems arising from state anti-takeover protection.

The Impact of Quantitative Easing and Carry Trade on the Real Estate Market in Hong Kong
Miyakoshi, Tatsuyoshi,Li, Kui-Wai,Shimada, Junji,Tsukuda, Yoshihiko
This paper examines how the quantitative easing (QE) policy conducted by Japan, EU and the US raised Hong Kong’s real estate prices through activities in carry trade and in Hong Kong’s real estate investment trust (H-REIT) market. The empirical results demonstrated two new channels of impact. The first new channel shows that Japan’s QE policy did affect the H-REIT prices in money market, which then led to a rise in office price after a lag of three months. The office prices were more persistently affected by the channel through the H-REIT than through the stock prices. Another new channel shows that the QE policy by Japan, the EU and the US since 2008 directly pushed up the office prices. These two new channels imply that the QE policy spilled over to not only the money market, but also the real estate market through the H-REIT market and carry trade. Moreover, the empirical finding is stronger in the price of the ordinary grade office than in the high-grade office, suggesting these new channels have already become common. Moreover, even though introducing control variables in the real estate economics literature, the results are robust.

The Price of Property Rights: Institutions, Finance, and Economic Growth
Alquist, Ron,Chabot, Benjamin Remy,Yamarthy, Ram
Using a unique data set of foreign equities traded on the London Stock Exchange in the late 19th century, we study the relation between expropriation risk, finance, and economic development. We find that British investors demanded a higher cost of equity capital from firms located in countries with weak property-rights institutions than they did from similarly risky firms in other countries. Further, the country-level cost of capital associated with expropriation risk is negatively related to present-day income and financial development. A simple equilibrium model of international capital flows and the expropriation risk premium rationalizes these results. Taken together, this evidence suggests that the quality of institutions influence growth and development, in part, through its effect on asset prices.

The Top 5 Predictable Effects of New Entries in Robinhood’s ‘100 Most Popular’ List
Stein, Roberto
The trading app Robinhood maintains a list of the 100 stocks most widely held by its users. Using a novel dataset of stock popularity with Robinhood user, I focus on new securities that enter the list. I document the strong effect that salience of new Top 100 listing events has on the attention of Robinhood users, who are between 5 to 7 times likelier to buy these newly listed securities. The resulting demand causes a dramatic, though short-term price increase. A strategy that buys stocks a day after listing and sells them two days later, obtains a return of 458% over the period studied, compared with 24% generated by the market. This effect is mostly observed in smaller stocks, and is not accompanied by market-wide trading. Since retail investors tend to consume information available exclusively within their app or web site of choice, these apps wield increasingly more influence on how investors make trading decisions, even through means as simple as a list. As FinTech reduces trading costs and attracts users, this power can reach beyond the app's ecosystem to the market itself, to directly affecting asset prices.

Time To Stop Betting The House: Mortgages, Resilience & The Long Finance
Steven, David
"Time To Stop Betting The House" pulls together the story of the role of mortgages in the financial crisis of 2007/2008. It analyses the situation and presents us with two clear, as well as two quite different, regulatory visions for a more resilient mortgage market. The Edited Choice vision offers borrowers a limited menu of mortgage options, while the Melt the Glue vision aims to create resilience from the ground up. Neither vision is exclusive; both are worthy of discussion and debate.

To Act or not to Act? Political competition in the presence of a threat
Arthur Fishman,Doron Klunover

We present a model of political competition in which an incumbent politician, may implement a costly policy to prevent a possible threat to, for example, national security or a natural disaster.

U.S. Securities and Exchange Commission MIDAS Market Information Data Analytics System: An Observation
Sommers, Fred
The U.S. Securities and Exchange Commission (SEC) rolled out Market Information Data Analytics System (MIDAS) in 2013 which is:“…the SEC’s implementation of a new system that combines advanced technologies with empirical data to promote better understanding of markets….”This paper uses available public, peer-re-viewable data, and operational outcomes to assess SEC MIDAS reported public data. These public data and outcomes demonstrate that SEC MIDAS data is incomplete. In particular, transactions effected otherwise than on an exchange and reported though the three FINRA Trade Reporting Facilities (TRFs) are not included in SEC MIDAS data. SEC MIDAS is expected to be a comprehensive research facility with collected data from self-regulatory organizations, trading venues, and proprietary sources. Essential SEC rule making offices such as the Division of Economic and Risk Analysis (DERA) and Division of Trading and Markets rely on MIDAS data. Both the public and the academic and economic groups have an expectation that MIDAS data and research using MIDAS data promotes empirical understanding of market hypotheses, market behavior, and market regulation.

Uses & Abuses Of Discount Rates: A Primer For The Wary
Goddard, Nick
Long Finance research seeks to explore the concept of discount rates, their use and implications over time. The research on this topic has involved a variety of people over the years, most notably Dr Nick Goddard, Arjuna Sittampalam, and Michael Mainelli.Discounted cash flow (DCF) and net present value (NPV) analyses have long been part of the financial analyst's toolbox. In order to use both tools we need to decide on a discount rate and use that discount rate in some exponential equations. Exponential equations lead in turn to infinities and are thus inherently problematic in a constrained world. The use of discount rate tools leads to conflict in values over time.Realizing the misconceptions and perceived complexity surrounding the concept of discount rate, Dr Nick Goddard volunteered to provide an overview of discount rates. "Uses and Abuses of Discount Rates: A Primer for the Wary" was published as a free-to-download Long Finance publication in September 2015 (press release).

Volatility Persistence and Momentum
Lee, Woongki
Volatility persistence is an important channel for understanding rational momentum effects. Since risk premia are, ceteris paribus, proportional to the volatility of the aggregate market or individual assets, momentum in the risk premia is expected to be strong when the volatility is highly persistent. I present empirical evidence that volatility persistence could capture the autoregressive risk premium. It also suggests that momentum profits can be attributed to time-varying risk. Furthermore, after controlling for risk-based momentum effect, the relationship between past and current returns turns out to be unclear, meaning that momentum exists mostly at the risk premium level.