Research articles for the 2019-07-22

A Model of the Optimal Selection of Crypto Assets
Silvia Bartolucci,Andrei Kirilenko

We propose a modelling framework for the optimal selection of crypto assets. Crypto assets differ by two essential features: security (technological) and stability (governance). Investors make choices over crypto assets similarly to how they make choices by using a recommender app: the app presents each investor with a pair of crypto assets with certain security-stability characteristics to be compared. Each investor submits its preference for adopting one of the two assets to the app. The app, in turn, provides a recommendation on whether the proposed adoption is sensible given the assets' essential features, information about the adoption choices of all other investors, and expected future economic benefits of adoption. Investors continue making their adoption choices over all pairs of crypto assets until their expected future economic benefits can no longer be improved upon. This constitutes an optimal selection decision. We simulate optimal selection decisions considering the behaviour of different types of investors, driven by their attitudes towards assets' features. We find a variety of possible emergent outcomes for the investments in the crypto-ecosystem and the future adoption of the crypto assets.

Active vs. Passive, The Case of Sector Equity Funds
Fan, Yuhong,Lin, Crystal Yan
This paper examines the performance of actively managed U.S. equity funds that track S&P 500 sectors, and their peer Exchanged Traded Funds (SPDR ETFs). Results do not show considerable evidence that actively managed sector funds outperform their passive counterparties. None of the mutual fund portfolios produces a significant positive alpha through factor models or delivers a significant positive alpha against their peer ETFs. When focusing on the performance of the nine oldest actively managed Fidelity sector funds, outperformance appears to fade away as time passes. Results support the view that U.S. sector equity market has reached more efficiency in the past decade.

An Axiomatic Foundation for the Expected Shortfall
Wang, Ruodu,Zitikis, Ricardas
In the recent Basel Accords, the Expected Shortfall (ES) replaces the Value-at-Risk (VaR) as the standard risk measure for market risk in the banking sector, making it the most popular risk measure in financial regulation. Although ES is - in addition to many other nice properties - a coherent risk measure, it does not yet have an axiomatic foundation. In this paper we put forward four intuitive economic axioms for portfolio risk assessment - which are monotonicity, law invariance, prudence and no reward for concentration - that uniquely characterize the family of ES. The herein developed results, therefore, provide the first economic foundation for using ES as a globally dominating regulatory risk measure, currently employed in Basel III/IV. Key to the main results, several novel notions such as tail events and risk concentration naturally arise, and we explore them in detail.

Analyzing and Implementing a Mobile Reminder System for Alzheimer’s Patients
Alharbi, Shooq,Altamimi, Aisha,Al-Qahtani, Fadwa,Aljofi, Bashair,Alsmadi, Mutasem,Alshabanah, Muneerah,Alrajhi, Daniah,Almarashdeh, Ibrahim
Recently, M-health or mobile health has been receiving a lot of attention worldwide from healthcare professionals, patients, network service providers, application developers and researchers. Mobile phone software applications or apps are available for a variety of useful healthcare tasks such as psycho-education, symptom assessment, resource location, and tracking of treatment progress. This study focused on creating an application for smart phones with android system. The main aim of the proposed system is to help an important category of the society which is the alzheimer’s patients, this system gives them the ability to have small memory which can help them to remember all tasks to live, which may contribute to the prevention of progression of the disease rapidly, the technology provides the best care because it is not susceptible to forgetfulness or damage. The design of the proposed system presented in this study includes reminding them of their families through memories and family photos and information, and the dates of their medications, the amount of medicine and hospital appointments

Analyzing, Designing and Implementing a Consulting Company for Management Information Systems
Alomari, Eman,Alshammry, Munira,Alhamil, Sarah,Alsmadi, Mutasem,Alshabanah, Muneerah,Alrajhi, Daniah,Almarashdeh, Ibrahim,Eljawad, Lubna
Nowadays, due to business diversification, globalization and growing number of different business projects, the need to support people involved in tasks related to project management is becoming increasingly important. Accurate data and time needed in the projects plans, related costs and progress are extremely important for the project managers to assure the success of the project. In this work, a Consulting Company for Management Information Systems (CCFMIS) is required to facilitate consultations in the field of MIS such as analysis of information systems, database design, development of information systems, programming and other consultation that meet their needs. The proposed CCFMIS was designed and implemented using the UML (in order to illustrate the architectural model), Microsoft Access 2016 and Visual Studio-ASP.NET programming language. In the proposed CCFMIS, the UML offers several diagrams to enable the new functions to be updated and added easily such as use cases, sequences and class diagrams, and user interfaces.

Arabic Voice Recognition Using Fuzzy Logic and Neural Network
Eljawad, Lubna,Aljamaeen, Rami,Alsmadi, Mutasem,Almarashdeh, Ibrahim,Abouelmagd, Hayam,Alsmadi, Sanaa,Haddad, Firas,Alkhasawneh, Raed,alzughoul, Mohammed,Alazzam, Malik
This research adapted and implemented an algorithm for commanding using speech recognition in ARABIC language in addition to English, and the ability to train the system using other languages. The recognition based on discrete coefficient of the wavelet transform. Intelligent recognizer is built for two models, the first is Neural Networks, and the second is Fuzzy Logic Recognizer. The proposed speech recognition system consists of three phases; preprocessing phase (two processes are performed on the sound, DC level removal and resizing of sample for 2000 samples for each sound), feature extraction phase (features that distinguish each sound from another, it is wavelet transform coefficients), and recognition phase (many classifiers could be used for speaker recognition, in this research supervised neural networks, MLP and Fuzzy Logic classifiers are used. This research is also concerned with studying the recognition ability of MLP neural Network and Suggeno type Fuzzy Logic systems, for the recognition of Arabic and English Languages. The neural networks trained with features extracted from discrete wavelet transform. The use of Wavelet Transformation enables to extract an exact features form the speech. The research illustrates the effect of using two different intelligent approaches using MATLAB, and by applying the voice commands directly to an automated wheeled vehicle.

Audit Committee Financial Expertise and Information Asymmetry
El Mahdy, Dina F.,Hao, Jia,Cong, Yu
We examine the association between audit-committee expertise and asymmetric information in the U.S. equity market. Using precise private information extracted from a decomposed bid-ask spread, we find that the existence of an audit committee with financial expertise is negatively associated with information asymmetry. We further find CEO duality to mediate the association between audit-committee financial expertise and information asymmetry. More specifically, we document a significant positive association between the interaction term of CEO duality and audit-committee financial expertise and information asymmetry. Our results are robust to several market-microstructure measures of asymmetric information (e.g., quoted spread, effective spread, price impact, the probability of informed trading), firm-specific characteristics, and market-liquidity measures.

Consistent upper price bounds for exotic options given a finite number of call prices and their convergence
Nicole Bäuerle,Daniel Schmithals

We consider the problem of finding a consistent upper price bound for exotic options whose payoff depends on the stock price at two different predetermined time points (e.g. Asian option), given a finite number of observed call prices for these maturities. A model-free approach is used, only taking into account that the (discounted) stock price process is a martingale under the no-arbitrage condition. In case the payoff is directionally convex we obtain the worst case marginal pricing measures. The speed of convergence of the upper price bound is determined when the number of observed stock prices increases. We illustrate our findings with some numerical computations.

Cryptocurrencies, Currency Competition and the Impossible Trinity
Benigno, Pierpaolo,Schilling, Linda,Uhlig, Harald
We analyze a two-country economy featuring a home, a foreign and a global (crypto)currency. For the benchmark case that markets are complete and that the global currency is used in both countries, We show that the home and foreign nominal interest rates must be equal and that the exchange rate between the home and the foreign currency is a risk- adjusted martingale. We call this result Crypto-Enforced Monetary Policy Synchronization (CEMPS). The classical Impossible Trinity becomes even less reconcilable. We discuss the dangers for monetary policies, seeking to escape this restriction, and calculate the implications for the exchange rate dynamics.

Day Trading for a Living?
Chague, Fernando,De-Losso, Rodrigo,Giovannetti, Bruno
We analyze all retail investors who began to day trade future contracts in Brazil from 2013 to 2015 and who persisted for at least 300 trading sessions. Results are alarming: 97% of them lost money, only 1.0% was able to earn more than the minimum wage, and just 0.4% earned more than a bank teller. Moreover, there is no evidence of learning by day trading. Our findings contradict the idea propagated by brokerage houses and course providers, who claim to be possible to day trade for a living.

Do Stock Markets Lead or Lag Macroeconomic Variables? Evidence from Select European Countries
Camilleri, Silvio John,Scicluna, Nicolanne,Bai, Ye
This study examines the connections between stock prices and key macroeconomic indicators: inflation, industrial production, interest rates, money supply and select interactions between the latter group of variables. Such links are evaluated through vector-autoregressions (VARs) on monthly data spanning over the period 1999-2017, for Belgium, France, Germany, Netherlands and Portugal. We check whether such relations are confirmed across different sub-periods and also adopt a non-parametric approach by using a Pesaran-Timmermann test. We find different contemporaneous and lead-lag relationships between stock prices and the selected variables, although there are variations across countries. VAR models indicate that stock prices significantly lead inflation across all countries during the sample period and in most cases this relationship was positive. In addition, stock prices significantly lead industrial production in four of the sampled countries and these relationships were positive as well. Contrary to long-established finance theories, we did not find numerous significant links between interest rates and stock indices; however the interaction between interest rates and money supply was a leading indicator of stock prices in France, Germany and Portugal.

Economic Neutral Position: How to best replicate not fully replicable liabilities
Andreas Kunz,Markus Popp

Financial undertakings often have to deal with liabilities of the form 'non-hedgeable claim size times value of a tradeable asset', e.g. foreign property insurance claims times fx rates. Which strategy to invest in the tradeable asset is risk minimal? We generalize the Gram-Charlier series for the sum of two dependent random variable, which allows us to expand the capital requirements based on value-at-risk and expected shortfall. We derive a stable and fairly model independent approximation of the risk minimal asset allocation in terms of the claim size distribution and the moments of asset return. The results enable a correct and easy-to-implement modularization of capital requirements into a market risk and a non-hedgeable risk component.

Efficiency in Islamic Vs. Conventional Banking: The Role of Capital and Liquidity
Bitar, Mohammad,Pukthuanthong, Kuntara,Walker, Thomas John
We show that higher capital and liquidity ratios increase the efficiency of conventional and Islamic banks. Using conditional quantile regressions, we further show that the effect is stronger for highly efficient, small, highly liquid, and highly capitalized conventional banks. We also find that more capitalized and liquid banks were more efficient during the 2008/2009 financial crisis and the Arab Spring. Our findings support the view that the constraints imposed by Sharia'a law, may widen the efficiency gap between the two bank types, at the expense of Islamic banks. Furthermore, our findings suggest that the efficiency of conventional banks not only depends on bank capital and liquidity, but also on the level of bank efficiency while the relationship is inconclusive for Islamic banks. These findings provide insight into how capital and liquidity can shape bank efficiency. It suggests that higher capital and liquidity buffers serve a constraint on policymakers and may function very differently depending on the level of bank efficiency.

Gaussian Process Regression for Pricing Variable Annuities with Stochastic Volatility and Interest Rate
Ludovic Goudenège,Andrea Molent,Antonino Zanette

In this paper we investigate price and Greeks computation of a Guaranteed Minimum Withdrawal Benefit (GMWB) Variable Annuity (VA) when both stochastic volatility and stochastic interest rate are considered together in the Heston Hull-White model. We consider a numerical method the solves the dynamic control problem due to the computing of the optimal withdrawal. Moreover, in order to speed up the computation, we employ Gaussian Process Regression (GPR). Starting from observed prices previously computed for some known combinations of model parameters, it is possible to approximate the whole price function on a defined domain. The regression algorithm consists of algorithm training and evaluation. The first step is the most time demanding, but it needs to be performed only once, while the latter is very fast and it requires to be performed only when predicting the target function. The developed method, as well as for the calculation of prices and Greeks, can also be employed to compute the no-arbitrage fee, which is a common practice in the Variable Annuities sector. Numerical experiments show that the accuracy of the values estimated by GPR is high with very low computational cost. Finally, we stress out that the analysis is carried out for a GMWB annuity but it could be generalized to other insurance products.

Generalized statistical arbitrage concepts and related gain strategies
Christian Rein,Ludger Rüschendorf,Thorsten Schmidt

Generalized statistical arbitrage concepts are introduced corresponding to trading strategies which yield positive gains on average in a class of scenarios rather than almost surely. The relevant scenarios or market states are specified via an information system given by a $\sigma$-algebra and so this notion contains classical arbitrage as a special case. It also covers the notion of statistical arbitrage introduced in Bondarenko (2003).

Relaxing these notions further we introduce generalized profitable strategies which include also static or semi-static strategies. Under standard no-arbitrage there may exist generalized gain strategies yielding positive gains on average under the specified scenarios.

In the first part of the paper we characterize these generalized statistical no-arbitrage notions. In the second part of the paper we construct several profitable generalized strategies with respect to various choices of the information system. In particular, we consider several forms of embedded binomial strategies and follow-the-trend strategies as well as partition-type strategies. We study and compare their behaviour on simulated data. Additionally, we find good performance on market data of these simple strategies which makes them profitable candidates for real applications.

Hong Kong - Shanghai Connect / Hong Kong - Beijing Disconnect (?): Scaling the Great Wall of Chinese Securities Trading Costs
Ravi Kashyap

We utilize a fundamentally different model of trading costs to look at the effect of the opening of the Hong Kong Shanghai Connect that links the stock exchanges in the two cities, arguably the biggest event in international business and finance since Christopher Columbus set sail for India. We design a novel methodology that compensates for the lack of data on trading costs in China. We estimate trading costs across similar positions on the dual listed set of securities in Hong Kong and China, hoping to provide useful pieces of information to help scale 'The Great Wall of Chinese Securities Trading Costs'. We then compare actual and estimated trading costs on a sample of real orders across the Hong Kong securities in the dual listed pair to establish the accuracy of our measurements. The primary question we seek to address is 'Which market would be better to trade to gain exposure to the same (or similar) set of securities or sectors?' We find that trading costs on Shanghai, which might have been lower than Hong Kong, might have become higher leading up to the Connect. What remains to be seen is whether this increase in trading costs is a temporary equilibrium due to the frenzy to gain exposure to Chinese securities or whether this phenomenon will persist once the two markets start becoming more and more tightly coupled. It would be interesting to see if this pioneering policy will lead to securities exchanges across the globe linking up one another, creating a trade anything, anywhere and anytime marketplace. Looking beyond mere trading costs, such studies can be used to gather some evidence on what effect the mode of governance and other aspects of life in one country have on another country, once they start joining up their financial markets.

Integrated Financial Statements for Leveraged Buyouts
Ayash, Brian
This paper presents integrated financial statements for a sample of large leveraged buyouts of publicly traded U.S. firms by private equity funds for a seven year window beginning three years prior to, and ending four years after, the leveraged buyout. The exposition is such that researchers and policy makers can read a set of financial statements, including cash flow statements, and understand the financial figures, investment, taxes, and their changes.

Is It Always Profitable to Be a Member of the EU? â€" Part II â€" on the Purchasing Power Inequality of a Box of Cigarettes and Budget Losses from Smuggling
Banov, Bancho
Summary: Britain's EU referendum or so-called Brexit questioned whether it is always beneficial for an EU member to join the EU. This article is the second of a few on the issue of some losses a member of the EU has suffered because of its membership. The first part concerns the bankruptcy of a large bank in Bulgaria - Corporate Commercial Bank in 2014, and why because of the high EU deposit guarantee threshold the guarantee fund was emptied and the state had to grant a loan to the fund of 1.5 (1.6) billion BGN, which is likely to be simplified and paid by taxpayers. This second part of the series deals with the losses that Bulgaria suffers because of another requirement of the EU - to increase the excise duty on cigarettes in Bulgaria, which from 23 BGN on 1000 pieces it reaches 155 BGN on 1000 pieces. Losses are not late - in Bulgaria 6 billion cigarettes are smoked less. Smuggling is increasing and, according to some sources, Bulgaria is losing 1.5-2% of its total tax revenue from this smuggling - 10 times more than Germany and 16 times more than the Netherlands.

Leveraged Buyouts and Financial Distress
Ayash, Brian,Rastad, Mahdi
Do leveraged buyout transactions increase the chance of bankruptcy? While corporate finance theory predicts that such sharp changes in capital structure increase financial distress costs by raising the probability of bankruptcy for each company, previous studies seem to fail to find any supporting empirical evidence. Using a propensity score matching method, we provide new evidence that is consistent with the prediction of the theory. Tracking a sample of 484 public to private LBOs for 10 years after going private, we find a bankruptcy rate of approximately 20%, an order of magnitude greater than the 2% bankruptcy rate for the control sample. Our analysis is robust to macro and industry shocks as potential driving forces behind bankruptcy.

Linear Credit Risk Models
Damien Ackerer,Damir Filipović

We introduce a novel class of credit risk models in which the drift of the survival process of a firm is a linear function of the factors. The prices of defaultable bonds and credit default swaps (CDS) are linear-rational in the factors. The price of a CDS option can be uniformly approximated by polynomials in the factors. Multi-name models can produce simultaneous defaults, generate positively as well as negatively correlated default intensities, and accommodate stochastic interest rates. A calibration study illustrates the versatility of these models by fitting CDS spread time series. A numerical analysis validates the efficiency of the option price approximation method.

Machine Learning Implications for Banking Regulation
McPhail, Lihong,McPhail, Joseph
Machine Learning (ML) automates prediction, making it cheaper and more accurate. The amount and variety of financial data will continue to increase, and with it the value of ML. A key implication for regulators is that the banking industry is likely to rely increasingly on ML methods for decisions that, by design, cannot be fully understood by their developers. As a result, regulators at all levels will increasingly confront ML models they can’t fully comprehend.Examination is impacted through the need for supervisors to opine on model risk. ML models contain more and complex features. Examiners may need to understand the implications of ML on transparency and associated operational risks. Use of historical data to train models may also have fair lending implications. Some banks and FinTech firms are already using ML for a broad range of banking services such as fraud detection, risk management and pricing.Policy may be impacted through at least two channels; operational risk and market behavior. ML has a direct impact on model risk, a component of operational risk. Banks are subject to model risk management regulatory guidance which has not been updated since April 2011. Some aspects of this guidance may be challenging to apply to ML tools due to their “black-box” nature. ML could also be changing the very nature of market behavior for some liquid assets.We provide an overview of ML and explore these and other implications for banking regulation.

Mid-price Prediction Based on Machine Learning Methods with Technical and Quantitative Indicators
Adamantios Ntakaris,Juho Kanniainen,Moncef Gabbouj,Alexandros Iosifidis

Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical and quantitative analysis and tested their validity on short-term mid-price movement prediction. We focus on a wrapper feature selection method using entropy, least-mean squares, and linear discriminant analysis. We also build a new quantitative feature based on adaptive logistic regression for online learning, which is constantly selected first among the majority of the proposed feature selection methods. This study examines the best combination of features using high frequency limit order book data from Nasdaq Nordic. Our results suggest that sorting methods and classifiers can be used in such a way that one can reach the best performance with a combination of only very few advanced hand-crafted features.

Momentum-Managed Equity Factors
Flögel, Volker,Schlag, Christian,Zunft, Claudia
Managed portfolios that exploit positive first-order autocorrelation in monthly excess returns of equity factor portfolios produce large alphas and gains in Sharpe ratios. We document this finding for factor portfolios formed on the broad market, size, value, momentum, investment, profitability, and volatility. The value-added induced by factor management via short-term momentum is a robust empirical phenomenon that survives transaction costs and carries over to multi-factor portfolios. The novel strategy established in this work compares favorably to well-known timing strategies that employ e.g. factor volatility or factor valuation.

Paying Too Much? Price Dispersion in the US Mortgage Market
Bhutta, Neil,Fuster, Andreas,Hizmo, Aurel
We document wide dispersion in the mortgage rates that households pay on identical loans, and assess the role of financial knowledge and shopping in the rates obtained. To study dispersion, we draw on new data where we observe the rates being offered by lenders, the rates consumers actually "lock in", and key rate covariates including discount points, rate-lock date, and all underwriting information. We find a difference between the 90th and 10th percentile interest rate that identical borrowers pay for the same loan, with the same points, in the same market, and on the same day, of 53 basis points â€" equivalent to about $6,750 in upfront costs (points) for the average loan. Even with the same loan officer borrowers can end up with substantially different rates, suggesting an important role for financial knowledge and negotiation. Comparing locked rates to the median offer rate for the same type of borrower in the same market on the same day, we find that this lock-offer spread is widest for low-FICO and high- LTV borrowers, implying that such borrowers pay more not just because of credit risk, but also because of less effective search and negotiation. However, this spread compresses when Treasury rates rise, suggesting that a rising level of borrowing costs encourages more search and negotiation. Finally, using the new National Survey of Mortgage Originations, we provide novel direct evidence that mortgage rates decline with mortgage knowledge and shopping; that knowledge and shopping vary substantially across borrowers and are correlated with socioeconomic characteristics; and that shopping activity intensifies in higher interest rate environments.

Polynomial Jump-Diffusion Models
Damir Filipović,Martin Larsson

We develop a comprehensive mathematical framework for polynomial jump-diffusions in a semimartingale context, which nest affine jump-diffusions and have broad applications in finance. We show that the polynomial property is preserved under polynomial transformations and L\'evy time change. We present a generic method for option pricing based on moment expansions. As an application, we introduce a large class of novel financial asset pricing models with excess log returns that are conditional L\'evy based on polynomial jump-diffusions.

Privacy as a Public Good: A Case for Electronic Cash
Garratt, Rodney,van Oordt, Maarten R.C.
Privacy is a feature inherent to the use of cash for payments. With steadily increasing market shares of commercial digital payments platforms, privacy in payments may no longer be attainable in the future. In this paper, we explore the potential welfare impact of reductions in privacy in payments in a dynamic framework. In our framework, firms may use data collected through payments to price discriminate among future customers. A public good aspect of privacy in payments arises because individual customers do not bear the full costs of failing to protect their privacy. As a consequence, they may sub-optimally choose not to preserve their privacy in payments. When left to market forces alone, the use of privacy-preserving means of payments, such as cash, may decline faster than is optimal.

Securities Lending Strategies: Exclusive Valuations and Auction Bids
Ravi Kashyap

We derive valuations of a portfolio of financial instruments from a securities lending perspective, under different assumptions, and show a weighting scheme that converges to the true valuation. We illustrate conditions under which our alternative weighting scheme converges faster to the true valuation when compared to the minimum variance weighting. This weighting scheme is applicable in any situation where multiple forecasts are made and we need a methodology to combine them. Our valuations can be useful either to derive a bidding strategy for an exclusive auction or to design an appropriate auction mechanism, depending on which side of the fence a participant sits (whether the interest is to procure the rights to use a portfolio for making stock loans such as for a lending desk, or, to obtain additional revenue from a portfolio such as from the point of view of a long only asset management firm). Lastly, we run simulations to establish numerical examples for the set of valuations and for various bidding strategies corresponding to different auction settings.

Securities Lending Strategies: Valuation of Term Loans using Option Theory
Ravi Kashyap

We develop models to price long term loans in the securities lending business. These longer horizon deals can be viewed as contracts with optionality embedded in them and can be priced using established methods from derivatives theory, becoming to our limited knowledge, the first application that can lead to greater synergies between the operations of derivative and delta-one trading desks, perhaps even being able to combine certain aspects of the day to day operations of these seemingly disparate entities. We run numerical simulations to demonstrate the practical applicability of these models. These models are part of one of the least explored yet profit laden areas of modern investment management.

We develop a heuristic that can mitigate the loss of information that sets in when parameters are estimated first and then the valuation is performed by directly calculating the valuation using the historical time series. This can lead to reduced models errors and greater financial stability. We illustrate how the methodologies developed here could be useful for inventory management. All these techniques could have applications for dealing with other financial instruments, non-financial commodities and many forms of uncertainty. An unintended consequence of our efforts, has become a review of the vast literature on options pricing, which can be useful for anyone that attempts to apply the corresponding techniques to the problems mentioned here.

Admittedly, our initial ambitions to produce a normative theory on long term loan valuations are undone by the present state of affairs in social science modeling. Though we consider many elements of a securities lending system at face value, this cannot be termed a positive theory. For now, if it ends up producing a useful theory, our work is done.

Static vs Adaptive Strategies for Optimal Execution with Signals
Claudio Bellani,Damiano Brigo,Alex Done,Eyal Neuman

We compare optimal static and dynamic solutions in trade execution. An optimal trade execution problem is considered where a trader is looking at a short-term price predictive signal while trading. When the trader creates an instantaneous market impact, it is shown that transaction costs of optimal adaptive strategies are substantially lower than the corresponding costs of the optimal static strategy. In the same spirit, in the case of transient impact it is shown that strategies that observe the signal a finite number of times can dramatically reduce the transaction costs and improve the performance of the optimal static strategy.

The Determinants of Securities Trading Activity: Evidence from Four European Equity Markets
Camilleri, Silvio John,Galea, Francelle
PurposeThe main objective of this study is to obtain new empirical evidence about the connections between equity trading activity and five possible liquidity determinants: market capitalisation, dividend yield, earnings yield, company growth, and the distinction between recently-listed firms as opposed to more established ones.Design / Methodology / ApproachWe use a sample of 172 stocks from four European markets and estimate models using the entire sample data and different sub-samples to check the relative importance of the above determinants. We also conduct a factor analysis to re-classify the variables into a more succinct framework. FindingsThe evidence suggests that market capitalisation is the most important trading activity determinant, and the number of years listed ranks thereafter. Research limitations / implicationsThe positive relation between trading activity and market capitalisation is in line with prior literature, while the findings relating to the other determinants offer further empirical evidence which is a worthy addition in view of the contradictory results in prior research. Practical implicationsThis study is of relevance to practitioners who would like to understand the cross-sectional variation in stock liquidity at a more detailed level. Originality / valueThe originality of the paper rests on two important grounds: (a) we focus on trading turnover rather than on other liquidity proxies, since the former is accepted as an important determinant of the liquidity generation process, and (b) we adopt a rigorous approach towards checking the robustness of the results by considering various sub-sample configurations.

The Effect of Unconventional Monetary Policy on Cross‐Border Bank Loans: Evidence from an Emerging Market
Alper, Koray,Altunok, Fatih,Çapacıoğlu, Tanju,Ongena, Steven
We analyze the impact of quantitative easing by the Federal Reserve, European Central Bank and Bank of England on cross‐border credit flows. Relying on comprehensive loan‐level data, we find that Fed QE strongly boosts cross‐border credit granted to Turkish banks by banks located in the US, Euro Area and UK, while ECB and BoE QEs work only moderately through banks in the EA and UK, respectively. In general QE works at short maturities across bank locations and loan currencies, more strongly for weaker lenders and borrowers, and may have resulted in maturity mismatches in Turkish banks searching for yield.

The Impact of Execution Delay on Kelly-Based Stock Trading: High-Frequency Versus Buy and Hold
Chung-Han Hsieh,B. Ross Barmish,John A. Gubner

Stock trading based on Kelly's celebrated Expected Logarithmic Growth (ELG) criterion, a well-known prescription for optimal resource allocation, has received considerable attention in the literature. Using ELG as the performance metric, we compare the impact of trade execution delay on the relative performance of high-frequency trading versus buy and hold. While it is intuitively obvious and straightforward to prove that in the presence of sufficiently high transaction costs, buy and hold is the better strategy, is it possible that with no transaction costs, buy and hold can still be the better strategy? When there is no delay in trade execution, we prove a theorem saying that the answer is ``no.'' However, when there is delay in trade execution, we present simulation results using a binary lattice stock model to show that the answer can be ``yes.'' This is seen to be true whether self-financing is imposed or not.

The Impact of Financial Risk on Systematic Risks: International Evidence
Wagdi, Osama,Tarek, Yasmeen
The study focused on the impact of the short-term and long-term financial risk on systematic risks through analyzing 120 corporations listed in the international and emerging stock exchange markets of the United States, Germany, South Korea, and Egypt, (30 from each country). The variability in common stock’s systematic risks was explained by 93.58% according to short- and long-term financial risk under two control variables which are market capitalization of the corporation and the efficiency of the stock exchange. When our results were compared to those of Hamada, 1972, Lee and Jang, 2007, and Alaghi, 2011, the study found that short-term financial risk increased which was explained by common stock’s systematic risk. Finally, the study found a positive relationship between each quick ratio & total debt to equity on one hand and a common stock’s systematic risk on another hand.

The Size Effect Revisited
Brandon Flores,Taran Grove,Yi Liu,Andrey Sarantsev

We compare performance of US stocks based on their size (market capitalization). We regress alpha and beta over size and other factors for individual stocks in Standard & Poor 500, for randomly generated portfolios. The novelty of our research is that we compare exchange-traded funds (ETFs) consisting of large-, mid- and small-cap stocks, including international ETFs. Conclusions: Size and market exposure (beta) are inversely related (strong evidence for ETFs, weaker for individual stocks). No conclusive evidence about dependence of excess return (alpha) on size, or international markets.

Toward a Mission Statement for Mutual Funds in Shareholder Litigation
Griffith, Sean J.,Lund, Dorothy S.
This paper analyzes the conduct of mutual funds in shareholder litigation. We begin by reviewing the basic forms of shareholder litigation and the benefits such claims might offer mutual fund investors. We then investigate, though an in-depth docket review, whether and how the ten largest mutual funds participate in shareholder litigation. We find that although shareholder suits offer potential benefits, the largest mutual funds have essentially forfeited their use of litigation. This finding is particularly striking given that index funds and other long-term oriented mutual funds generally cannot sell their shares when they are dissatisfied with company performance, leaving them with only two levers in corporate governanceâ€"voting and suing. Mutual funds vote, but they do not sue.We analyze potential explanations for the failure of mutual funds to litigate on behalf of their investors. Collective action problems and conflicts of interest raise significant obstacles to mutual fund participation in shareholder litigation. Yet, we argue, there are situations in which shareholder litigation could create value for mutual fund investors. We therefore turn to the normative question: how should mutual funds litigate on behalf of their investors? Answering this question allows us to articulate a mission statement for mutual funds in shareholder litigation.Our mission statement is grounded on the perspective of the broadly diversified “market investor.” The repeat-play incentives and broad diversification of many mutual funds, index funds in particular, suggests that they could create value by focusing principally on deterrence objectives. Mutual funds should bring shareholder suits against portfolio companies when doing so would meaningfully enhance deterrence. They should also scrutinize the litigation brought by other shareholders, objecting to outcomes that fail to promote meaningful deterrence. At the same time, mutual funds should focus on compensatory goals in litigation against non-portfolio defendants because extra-portfolio claims do not raise circularity concerns. In addition, mutual funds should consider whether litigation can be used to implement corporate governance reforms. Finally, in all cases, mutual funds should closely monitor litigation agency costs. We close by suggesting ways in which the incentives of mutual funds might be restructured to bring these changes about.

Trade Credit, Ownership and Informal Financing in China
Wang, Xiaoming,Wu, Weijun,Yin, Chen,Zhou, Sili
We investigate informal financing such as trade credit in China. The credit for both state-owned enterprises (SOEs) and non-SOEs dramatically increased over time. Our results suggest that non-SOEs rely more on trade credit financing, but this effect is mitigated by supplier’s liquidity position. Further results show that during financial crisis, non-SOEs reduce their account receivables due to high financing costs. Our research highlights the importance of informal financing and ownership structure in emerging markets.

Venture Capital Contracts
Ewens, Michael,Gorbenko, Alexander S.,Korteweg, Arthur G.
We estimate the impact of venture capital (VC) contract terms on startup outcomes and the split of value between the entrepreneur and investor, accounting for endogenous selection via a novel dynamic search and matching model. The estimation uses a new, large data set of first financing rounds of startup companies. Consistent with efficient contracting theories, there is an optimal equity split between agents that maximizes the probability of success. However, VCs use their bargaining power to receive more investor-friendly terms compared to the contract that maximizes startup values. Better VCs still benefit the startup and the entrepreneur, due to their positive value creation. Counterfactual exercises show that eliminating certain contract terms benefits entrepreneurs and enables low-quality entrepreneurs to finance their startups more quickly, increasing the number of deals in the market. Lowering search frictions shifts the bargaining power to VCs and benefits them at the expense of entrepreneurs. The results show that selection of agents into deals is a first-order factor to take into account in studies of contracting.

Volatility in the Cryptocurrency Market
Liu, Jinan,Serletis, Apostolos
"How do cryptocurrency prices evolve? Is there any interdependence among cryptocurrency returns and/or volatilities? Are there any return spillovers and volatility spillovers between the cryptocurrency market and other financial markets? To answer these questions, we use GARCH-in-mean models to examine the relationship between volatility and returns of leading cryptocurrencies, to investigate spillovers within the cryptocurrency market, and also from the cryptocurrency market to other financial markets. Overall, we find statistically significant transmission of shocks and volatilities among the leading cryptocurrencies. We also find statistically significant spillover effects from the cryptocurrency market to other financial markets in the United States, as well as in other leading economies (Germany, the United Kingdom, and Japan).

Реформы социального страхования: поиск баланса (Social Insurance Reforms: Finding Balance)
Grishchenko, Natalia
Russian Abstract: Ð"инамизм изменений в экономической и социальной среде влияет на своевременность трансформации социального страхования, его соответствие требованиям застрахованных лиц, повышение эффективности предоставляемых социальных услуг и устойчивость в долгосрочной перспективе. Актуальные требования к социальному страхованию со стороны общества и государства состоят в улучшении качества предоставляемых социальных услуг и снижении их стоимости. Основным механизмом для этого является совершенствование административно-территориальной структуры и информационного обслуживания. Настоящая работа направлена на изучение современных российских и зарубежных тенденций в области социального страхования, его реформ и нахождение баланса в финансировании, организации и управлении.English Abstract: The dynamism of changes in the economic and social environment affects the timeliness of transformation of social insurance, its compliance with the requirements of the insured persons, increasing the efficiency of social services provided, and sustainability in the long-run period. Actual requirements for social insurance on the part of society and the state consist in improving the quality of social services provided and reducing their costs. The main mechanism for this is the improvement of the administrative-territorial structure and information service. The present work is aimed at studying current Russian and foreign trends in social insurance, its reforms and finding a balance in financing, organization and management.