Research articles for the 2019-02-25

A Dynamic Model of Intermediated Consumer Credit and Liquidity
Gomis-Porqueras, Pedro,Sanches, Daniel R.
We construct a model of consumer credit with payment frictions, such as spatial separation and unsynchronized trading patterns, to study optimal monetary policy across different interbank market structures. In our framework, intermediaries play an essential role in the functioning of the payment system, and monetary policy influences the equilibrium allocation through the interest rate on reserves. If interbank credit markets are incomplete, then monetary policy plays a crucial role in the smooth operation of the payment system. Specifically, an equilibrium in which privately issued debt claims are not discounted is shown to exist provided the initial wealth in the intermediary sector is sufficiently large relative to the size of the retail sector. Such an equilibrium with an efficient payment system requires setting the interest rate on reserves sufficiently close to the rate of time preference.

A Sustainable Platform Economy & the Future of Corporate Governance
Fenwick, Mark,Vermeulen, Erik P. M.
A significant development in the global economy over the last two decades has been the emergence of businesses that organize and define themselves as “platforms.” By platform, we refer to any organization that uses digital or other emerging technologies to create value by facilitating or coordinating connections between two or more groups of users. Think Amazon (connecting buyers and sellers), Facebook (connecting friends and family), or Uber (connecting service providers and service users). Over the last decade, platforms have grown to become some of the largest companies in the world and all companies and other organizations are now obliged to consider integrating platform ideas and experience into their operations. However, platforms are increasingly controversial. Most obviously, they raise concerns about privacy (think Facebook and Google) and market power (think Amazon and Google). And as platforms have expanded in size, they have struggled to maintain their initial promise and brands that were initially disruptive have lost much of their initial appeal (think Facebook or Uber).In this paper, we identify the distinctive features of a “platform business model” (though a comparison with the modern company) and introduce the concept of a “sustainable platform,” to describe a platform-style business that is both innovative and socially responsible. The main argument of the paper is to suggest that there is a “disconnect” between the current business needs and values of sustainable platforms and contemporary policies and regulation, particularly corporate governance. Overcoming this disconnect â€" developing a new “platform governance” â€" is crucial for the long-term prospects of sustainable platforms, and the economy more generally.

A changepoint approach for the identification of financial extreme regimes
Chiara Lattanzi,Manuele Leonelli

Inference over tails is usually performed by fitting an appropriate limiting distribution over observations that exceed a fixed threshold. However, the choice of such threshold is critical and can affect the inferential results. Extreme value mixture models have been defined to estimate the threshold using the full dataset and to give accurate tail estimates. Such models assume that the tail behavior is constant for all observations. However, the extreme behavior of financial returns often changes considerably in time and such changes occur by sudden shocks of the market. Here we extend the extreme value mixture model class to formally take into account distributional extreme changepoints, by allowing for the presence of regime-dependent parameters modelling the tail of the distribution. This extension formally uses the full dataset to both estimate the thresholds and the extreme changepoint locations, giving uncertainty measures for both quantities. Estimation of functions of interest in extreme value analyses is performed via MCMC algorithms. Our approach is evaluated through a series of simulations, applied to real data sets and assessed against competing approaches. Evidence demonstrates that the inclusion of different extreme regimes outperforms both static and dynamic competing approaches in financial applications.

An alternative quality of life ranking on the basis of remittances
Dóra Gréta Petróczy

Remittances mean an important connection between people working abroad and their home countries. This paper considers them as a measure of preferences revealed by workers, underlying a ranking of countries around the world. We use the World Bank bilateral remittances data between 2010 and 2015 to compare European countries. The database contains international salaries and interpersonal transfers. The suggested least squares method makes the ranking invariant to country sizes and satisfies the property of bridge country independence. Our ranking reveals a crucial aspect of quality of life and may become an alternative to various composite indices.

Analytical Validation Formulas for Best Estimate Calculation in Traditional Life Insurance
Simon Hochgerner,Florian Gach

Within the context of traditional life insurance, a model-independent relationship about how the market value of assets is attributed to the best estimate, the value of in-force business and tax is established. This relationship holds true for any portfolio under run-off assumptions and can be used for the validation of models set up for Solvency~II best estimate calculation. Furthermore, we derive a lower bound for the value of future discretionary benefits. This lower bound formula is applied to publicly available insurance data to show how it can be used for practical validation purposes.

Banking Regulation with Risk of Sovereign Default
D'Erasmo, Pablo,Livshits, Igor,Schoors, Koen
Banking regulation routinely designates some assets as safe and thus does not require banks to hold any additional capital to protect against losses from these assets. A typical such safe asset is domestic government debt. There are numerous examples of banking regulation treating domestic government bonds as â€Å"safe,� even when there is clear risk of default on these bonds. We show, in a parsimonious model, that this failure to recognize the riskiness of government debt allows (and induces) domestic banks to â€Å"gamble� with depositors’ funds by purchasing risky government bonds (and assets closely correlated with them). A sovereign default in this environment then results in a banking crisis. Critically, we show that permitting banks to gamble this way lowers the cost of borrowing for the government. Thus, if the borrower and the regulator are the same entity (the government), that entity has an incentive to ignore the riskiness of the sovereign bonds. We present empirical evidence in support of the key mechanism we are highlighting, drawing on the experience of Russia in the run-up to its 1998 default and on the recent Eurozone debt crisis.

Buy-Sell Imbalances around Round Numbers and High-Frequency Trading
Lee, Albert J.
I show that the growth of high-frequency trading, due to its heavy reliance on computer algorithms, can be associated with a reduction of human errors and financial anomalies in the market. Trades in which a non-high-frequency trader is the liquidity demander exhibit abnormally high buy (sell) pressure when prices are immediately below (above) a round number due to psychological effects, while the pattern is completely reversed when a high-frequency trader is the liquidity demander. As a result, the overall sample does not exhibit such imbalances. Furthermore, high-frequency traders earn higher returns when trading around round number prices.

Categorizing Variants of Goodhart's Law
David Manheim,Scott Garrabrant

There are several distinct failure modes for overoptimization of systems on the basis of metrics. This occurs when a metric which can be used to improve a system is used to an extent that further optimization is ineffective or harmful, and is sometimes termed Goodhart's Law. This class of failure is often poorly understood, partly because terminology for discussing them is ambiguous, and partly because discussion using this ambiguous terminology ignores distinctions between different failure modes of this general type. This paper expands on an earlier discussion by Garrabrant, which notes there are "(at least) four different mechanisms" that relate to Goodhart's Law. This paper is intended to explore these mechanisms further, and specify more clearly how they occur. This discussion should be helpful in better understanding these types of failures in economic regulation, in public policy, in machine learning, and in Artificial Intelligence alignment. The importance of Goodhart effects depends on the amount of power directed towards optimizing the proxy, and so the increased optimization power offered by artificial intelligence makes it especially critical for that field.

Climate Change and Agriculture: Subsistence Farmers' Response to Extreme Heat
Fernando M. Aragón,Francisco Oteiza,Juan Pablo Rud

This paper examines how subsistence farmers respond to extreme heat. Using micro-data from Peruvian households, we find that high temperatures reduce agricultural productivity, increase area planted, and change crop mix. These findings are consistent with farmers using input adjustments as a short-term mechanism to attenuate the effect of extreme heat on output. This response seems to complement other coping strategies, such as selling livestock, but exacerbates the drop in yields, a common measure of agricultural productivity. Using our estimates, we show that accounting for land adjustments is important to quantify damages associated with climate change.

Closed-End Formula for options linked to Target Volatility Strategies
Luca Di Persio,Luca Prezioso,Kai Wallbaum

Recent years have seen an emerging class of structured financial products based on options linked to dynamic asset allocation strategies. One of the most chosen approach is the so-called target volatility mechanism. It shifts between risky and riskless assets to control the volatility of the overall portfolio. Even if a series of articles have been already devoted to the analysis of options linked to the target volatility mechanism, this paper is the first, to the best of our knowledge, that tries to develop closed-end formulas for VolTarget options. In particular, we develop closed-end formulas for option prices and some key hedging parameters within a Black and Scholes setting, assuming the underlying follows a target volatility mechanism.

Controlling Sellers Who Provide Advice: Regulation and Competition
Bardey, David,Gromb, Denis,Martimort, David,Pouyet, Jerome
A monopoly seller advises buyers about which of two goods best fits their needs but may be tempted to steer buyers towards the higher margin good. For the seller to collect information about a buyer's needs and provide truthful advice, the profits from selling both goods must lie within an implementability cone. In the optimal regulation, pricing distortions and information-collection incentives are controlled separately by price regulation and fixed rewards respectively. This no longer holds when the seller has private information about costs as both problems interact. We study the extent to which competition and the threat by buyers to switch sellers can substitute for regulation.

Discovering Language of the Stocks
Marko Poženel,Dejan Lavbič

Stock prediction has always been attractive area for researchers and investors since the financial gains can be substantial. However, stock prediction can be a challenging task since stocks are influenced by a multitude of factors whose influence vary rapidly through time. This paper proposes a novel approach (Word2Vec) for stock trend prediction combining NLP and Japanese candlesticks. First, we create a simple language of Japanese candlesticks from the source OHLC data. Then, sentences of words are used to train the NLP Word2Vec model where training data classification also takes into account trading commissions. Finally, the model is used to predict trading actions. The proposed approach was compared to three trading models Buy & Hold, MA and MACD according to the yield achieved. We first evaluated Word2Vec on three shares of Apple, Microsoft and Coca-Cola where it outperformed the comparative models. Next we evaluated Word2Vec on stocks from Russell Top 50 Index where our Word2Vec method was also very successful in test phase and only fall behind the Buy & Hold method in validation phase. Word2Vec achieved positive results in all scenarios while the average yields of MA and MACD were still lower compared to Word2Vec.

Diversity and its decomposition into variety, balance and disparity
Alje van Dam

Diversity is a central concept in many fields. Despite its importance, there is no unified methodological framework to measure diversity and its three components of variety, balance and disparity. Current approaches take into account disparity of the types by considering their pairwise similarities. Pairwise similarities between types do not adequately capture total disparity, since they fail to take into account in which way pairs are similar. Hence, pairwise similarities do not discriminate between similarity of types in terms of the same feature and similarity of types in terms of different features. This paper presents an alternative approach which is based similarities of features between types over the whole set. The proposed measure of diversity properly takes into account the aspects of variety, balance and disparity, and without having to set an arbitrary weight for each aspect of diversity. Based on this measure, the 'ABC decomposition' is introduced, which provides separate measures for the variety, balance and disparity, allowing them to enter analysis separately. The method is illustrated by analyzing the industrial diversity from 1850 to present while taking into account the overlap in occupations they employ. Finally, the framework is extended to take into account disparity considering multiple features, providing a helpful tool in analysis of high-dimensional data.

Do Tax Cuts Encourage Rent Seeking by Top Corporate Executives? Theory and Evidence
Andersen, Dana C.,López, Ramón
This paper explores the role of tax policy in shaping incentives for executive effort (labor supply) and rent seeking within the firm. We develop a theoretical model that distinguishes between effort and rent‐seeking responses to income taxes, and provides a framework to estimate a lower bound for the rent‐seeking response. Using executive compensation and governance data, we find that rent seeking represents an important component of the response to changes in tax rates, especially among executives in firms with the worst corporate governance.

Dynamic Advisor-Based Ensemble (dynABE): Case study in stock trend prediction of critical metal companies
Zhengyang Dong

Stock trend prediction is a challenging task due to the market's noise, and machine learning techniques have recently been successful in coping with this challenge. In this research, we create a novel framework for stock prediction, Dynamic Advisor-Based Ensemble (dynABE). dynABE explores domain-specific areas based on the companies of interest, diversifies the feature set by creating different "advisors" that each handles a different area, follows an effective model ensemble procedure for each advisor, and combines the advisors together in a second-level ensemble through an online update strategy we developed. dynABE is able to adapt to price pattern changes of the market during the active trading period robustly, without needing to retrain the entire model. We test dynABE on three cobalt-related companies, and it achieves the best-case misclassification error of 31.12% and an annualized absolute return of 359.55% with zero maximum drawdown. dynABE also consistently outperforms the baseline models of support vector machine, neural network, and random forest in all case studies.

Financial Stability and Public Confidence in Banks
Chernykh, Lucy ,Davydov, Denis,Sihvonen, Jukka
We use a novel, household opinions-based measure â€" Public Confidence in a Bank â€" to explore the role of bank-level and system-wide determinants of customers’ trust in banks. Our study covers a panel of approximately 260 large Russian commercial banks publicly monitored during 2010â€"2017. We find that public confidence in a bank is highly sensitive to the industry-level financial stability indicators, but less sensitive to bank-level risk characteristics. This result reveals an important role of overall banking sector stability in determining public perception of the safety and soundness of individual banks.

Flexible Optimal Models for Predicting Stock Market Returns
Jeong, Jin-Gil,Mukherji, Sandip
This study assesses the usefulness of flexible optimal models of business cycle variables for predicting stock market returns. We find that variable estimation periods identify structural breaks in months with large absolute returns and the optimal models recognize regime switches. Flexible optimal models have much greater predictive power for stock market returns than fixed univariate or multivariate models. The dividend yield has consistent predictive power for stock market returns, but different variables make significant contributions to predicting stock market returns in different periods. These findings highlight the importance of employing flexible optimal models to consistently predict stock market returns.

From SA-CCR to RSA-CCR: Making SA-CCR Self-Consistent and Appropriately Risk-Sensitive by Cashflow Decomposition in a 3-Factor Gaussian Market Model
Berrahoui, Mourad,Islah, Othmane,Kenyon, Chris
The technical appendix to this paper can be found at: has major issues including: lack of self-consistency for linear trades; lack of appropriate risk sensitivity (zero positions can have material add-ons; moneyness is ignored); dependence on economically-equivalent confirmations. We show that SA-CCR is, by parameter identification and re-construction, based on a 3-factor Gaussian Market Model. Hence we propose a Revised SA-CCR (RSA-CCR) based on cashflow decomposition and this 3-factor Gaussian Market Model. RSA-CCR is free of SA-CCR's issues, simple to use in practice, and can be extended easily given that it is model-based. We recommend updating SA-CCR to RSA-CCR in order to resolve SA-CCR's issues of lack of self-consistency for linear trades, lack of appropriate risk sensitivity (zero positions can have material add-ons; moneyness is ignored), dependence on economically-equivalent confirmations, and ambiguity of application for cases not explicitly described.

Influencing factors that determine the usage of the crowd-shipping services
Tho V. Le,Satish V. Ukkusuri

The objective of this study is to understand how senders choose shipping services for different products, given the availability of both emerging crowd-shipping (CS) and traditional carriers in a logistics market. Using data collected from a US survey, Random Utility Maximization (RUM) and Random Regret Minimization (RRM) models have been employed to reveal factors that influence the diversity of decisions made by senders. Shipping costs, along with additional real-time services such as courier reputations, tracking info, e-notifications, and customized delivery time and location, have been found to have remarkable impacts on senders' choices. Interestingly, potential senders were willing to pay more to ship grocery items such as food, beverages, and medicines by CS services. Moreover, the real-time services have low elasticities, meaning that only a slight change in those services will lead to a change in sender-behavior. Finally, data-science techniques were used to assess the performance of the RUM and RRM models and found to have similar accuracies. The findings from this research will help logistics firms address potential market segments, prepare service configurations to fulfill senders' expectations, and develop effective business operations strategies.

Investment Timing and Capacity Decisions with Time-to-Build in a Duopoly Market
Jeon, Haejun
We investigate firms' optimal investment timing and capacity decisions in the presence of time-to-build and competition. Due to the uncertainty in time-to-build, the product of the leader who makes the first investment might enter the market later than that of the follower. We show that a firm dominated by investment lags can become a leader and that the leader's optimal capacity increases in the size of the dominated firm's lags, even when the dominated firm becomes the leader. This result is consistent with the electric vehicles market, in which a relatively new firm lacking experience in mass production makes an aggressive investment, while the biggest car makers capable of mass production with shorter lags are timing their investment. With a welfare-maximizing policy, however, the dominant firm always becomes the leader. Compared to investments according to the welfare-maximizing policy, the leader and follower's investment choices in the market are inefficiently late and early, respectively. The welfare-maximizing capacities of both the leader and the follower are much higher than those determined in the market, but the difference is more pronounced in the leader's capacity. There is a significant loss of social welfare resulting from the dominated firm becoming the leader, and the loss increases as the dominated firm's time-to-build increases.

Lottery Loans in the Eighteenth Century
Velde, Francois R.
In the 18th century Britain frequently issued lottery loans, selling bonds whose size was determined by a draw soon after the sale. The probability distribution was perfectly known ex-ante and highly skewed. After the draw the bonds were identical (except for size) and indistinguishable from regular bonds. I collect market prices for the lottery tickets and show that investors were paying a substantial premium to be exposed to this purely artificial risk. I show that investors were well-to-do and included many merchants and bankers. I turn to cumulative prospect theory to make sense of these observations and estimate the equilibrium model of Barberis and Huang (2008). The preference parameters can account for the level of the lottery premium but cannot always match the systematic rise of prices over the course of the draws.

Managerial Overconfidence, Compensation Induced Risk Taking, and Earnings Management
Li, Chun An,Lin, Tse-Mao,Huang, Yu Wen
This study examined Taiwanese listed company and OTC (Over-the-Counter) firms to explore empirically managerial overconfidence and compensation incentives induced risk-taking, and the impact on accrualbased earnings management (AEM) and real earnings management (REM). The study results show that overconfident managers are more likely to adopt REM than AEM. Compensation induced Delta risk-taking is irrelevant to AEM but could lower the propensity for REM, and compensation induced Vega risk-taking could increase the magnitude of AEM but lower the magnitude of REM. These results remain robust after including interaction dummy between overconfidence and Delta risk-taking, and interaction dummy between overconfidence and Vega risk-taking for further analysis and Logistic Regression. In addition, this study also finds that overconfidence could mitigate the positive relationship between Vega risk-taking and AEM.

Market efficiency, liquidity, and multifractality of Bitcoin: A dynamic study
Tetsuya Takaishi,Takanori Adachi

This letter investigates the dynamic relationship between market efficiency, liquidity, and multifractality of Bitcoin. We find that before 2013 liquidity is low and the Hurst exponent is less than 0.5, indicating that the Bitcoin time series is anti-persistent. After 2013, as liquidity increased, the Hurst exponent rose to approximately 0.5, improving market efficiency. For several periods, however, the Hurst exponent was found to be significantly less than 0.5, making the time series anti-persistent during those periods. We also investigate the multifractal degree of the Bitcoin time series using the generalized Hurst exponent and find that the multifractal degree is related to market efficiency in a non-linear manner.

Online Appendix: The Determinants of IPO Withdrawal - Evidence from Europe
Helbing, Pia,Lucey, Brian M.,Vigne, Samuel
The full-text version of this paper can be found at: This online appendix provides supplemental discussion and analysis for our manuscript The Determinants of IPO Withdrawal - Evidence from Europe. The supplemental information, tables and tests are provided in addition to the paper. We organise this online appendix by sections. Please cite as Helbing, Pia, Brian M. Lucey and Samuel A. Vigne. "The Determinants of IPO Withdrawal-Evidence from Europe." (2018).

Over-the-Counter Market Liquidity and Securities Lending
Foley-Fisher, Nathan,Gissler, Stefan,Verani, Stephane
This paper studies how over-the-counter market liquidity is affected by securities lending. We combine micro-data on corporate bond market trades with securities lending transactions and individual corporate bond holdings by U.S. insurance companies. Applying a difference-in-differences empirical strategy, we show that the shutdown of AIG's securities lending program in 2008 caused a statistically and economically significant reduction in the market liquidity of corporate bonds predominantly held by AIG. We also show that an important mechanism behind the decrease in corporate bond liquidity was a shift towards relatively small trades among a greater number of dealers in the interdealer market.

Public Market Information and Venture Capital Investment
Gibbons, Brian
I examine the use of public market information by venture capital firms (VCs) before financing a private company. I develop a novel data set that identifies individual VC firms’ traffic to public filings hosted on EDGAR. I document that VC’s are sensitive to the marginal benefits that public information provides, with high reputation VCs choosing to conduct less research on the platform. Attention towards public market information is positively related to investment outcomes, but only for “low reputation” VCs. Using exogenous shocks to a firm’s workload, I find that low reputation VCs conduct less public market research when investing in more deals â€" indicating that binding resource constraints cause VCs to forego beneficial public market research. Resource-constrained, low reputation VCs also free-ride in investment syndicates, reducing public market information acquisition when financing a round with experienced or reputable co-investors.

Risk management with machine-learning-based algorithms
Simon Fécamp,Joseph Mikael,Xavier Warin

We propose some machine-learning-based algorithms to solve hedging problems in incomplete markets. Sources of incompleteness cover illiquidity, untradable risk factors, discrete hedging dates and transaction costs. The proposed algorithms resulting strategies are compared to classical stochastic control techniques on several payoffs using a variance criterion. One of the proposed algorithm is flexible enough to be used with several existing risk criteria. We furthermore propose a new moment-based risk criteria.

Seasonal Variations in Two-Year Treasury Note Yields
Liu, Lan
We study seasonality in the two-year Treasury Note yields. We find that most anecdotally observed seasonal variations of yields do not pass the more rigorous statistical significance test. In addition, the seasonality findings depend on how me measure yields and what kind of seasonal patterns we test. No statistical significance is found with tests using nominal yields, most likely due to the fact that yields have been dropping substantially since the 1980s which distorted the mean values of yields. When we instead use the rank of monthly yields in a year to test the seasonality, however, we find strong statistical significance to support the variation of high yields from March to August and low yields from September to February.

Technical Appendix To: From SA-CCR to RSA-CCR: Making SA-CCR Self-Consistent and Appropriately Risk-Sensitive by Cashflow Decomposition in a 3-Factor Gaussian Market Model
Berrahoui, Mourad,Islah, Othmane,Kenyon, Chris
The full-text version of this paper can be found at: SA-CCR has major issues including: lack of self-consistency for linear trades; lack of appropriate risk sensitivity (zero positions can have material add-ons; moneyness is ignored); dependence on economically-equivalent confirmations. We show that SA-CCR is, by re-construction, based on a 3-factor Gaussian Market Model with particular calibration to volatility and inter-bucket correlation structure. Hence we proposed RSA-CCR (Berrahoui, Islah and Kenyon, 2019) based on cashflow decomposition and this 3-factor Gaussian Market Model. RSA-CCR solves the issues with SA-CCR for linear trades and is calibrated to SA-CCR apart from avoiding SA-CCR's issues. This Technical appendix provides background material, proofs and technical details behind RSA-CCR not present in the source paper (Berrahoui, Islah and Kenyon 2019). There is some duplication to make this appendix more readable.

U.S. Tax Inversions and Shareholder Wealth Effects
Laing, Elaine,Gurdgiev, Constantin,Durand, Robert B. B.,Boermans, Boris
We examine a sample of corporate inversions from 1993 to 2015 by firms active in the U.S. markets and find that shareholders experience positive abnormal returns in the short-run. In the long-run, inversions have a deleterious effect on shareholder wealth. The form of the inversion and country-pair differences in geographic distance, economic development and corporate governance standards are determinants of shareholder wealth. Furthermore, we find evidence of a negative and non-linear relation between CEO total return and long-run shareholder returns.

Viability and Arbitrage under Knightian Uncertainty
Matteo Burzoni,Frank Riedel,H. Mete Soner

We reconsider the microeconomic foundations of financial economics under Knightian Uncertainty. We remove the (implicit) assumption of a common prior and base our analysis on a common order instead. Economic viability of asset prices and the absence of arbitrage are equivalent. We show how the different versions of the Efficient Market Hypothesis are related to the assumptions one is willing to impose on the common order. We also obtain a version of the Fundamental Theorem of Asset Pricing using the notion of sublinear pricing measures. Our approach unifies recent versions of the Fundamental Theorem under a common framework.

We are All Behavioral, More or Less: Measuring and Using Consumer-Level Behavioral Sufficient Statistics
Stango, Victor,Zinman, Jonathan
Can a behavioral sufficient statistic empirically capture cross-consumer variation in behavioral tendencies and help identify whether behavioral biases, taken together, are linked to material consumer welfare losses? Our answer is yes. We construct simple consumer-level behavioral sufficient statistics—â€Å"B-counts�—by eliciting seventeen potential sources of behavioral biases per person, in a nationally representative panel, in two separate rounds nearly three years apart. B-counts aggregate information on behavioral biases within-person. Nearly all consumers exhibit multiple biases, in patterns assumed by behavioral sufficient statistic models (a la Chetty), and with substantial variation across people. B-counts are stable within-consumer over time, and that stability helps to address measurement error when using B-counts to model the relationship between biases, decision utility, and experienced utility. Conditional on classical inputs—risk aversion and patience, life-cycle factors and other demographics, cognitive and non-cognitive skills, and financial resources—B-counts strongly negatively correlate with both objective and subjective aspects of experienced utility. The results hold in much lower-dimensional models employing â€Å"Sparsity B-counts� based on bias subsets (a la Gabaix) and/or fewer covariates, illuminating lower-cost ways to use behavioral sufficient statistics to help capture the combined influence of multiple behavioral biases for a wide range of research questions and applications.

What Causes the Efficiency and the Technology Gap Under Different Ownership Structures in the Chinese Banking Industry?
Lee, Chi‐Chuan,Huang, Tai-Hsin
This paper estimates and compares the cost efficiency of the Chinese banking industry among different ownership types for the period 2003–2014, using the stochastic metafrontier model. We find that foreign banks have the lowest cost frontier, while state‐owned commercial banks undertake the least sophisticated technology. Moreover, the results of the upward trend in the technology gap ratio (TGR) and in metafrontier cost efficiency support that a more open financial market is able to enhance banking efficiency. As for the role of environmental conditions, off‐balance sheet items, non‐performing loans, and financial market structure significantly impact the TGRs of different bank types.

What Drives the Short-Term Fluctuations of Banks' Exposure to Interest Rate Risk?
Memmel, Christoph
We investigate whether banks actively manage their exposure to interest rate risk in the short run. Using bank-level data of German banks for the period 2011Q4- 2017Q2, we find evidence that banks actively manage their interest rate risk exposure in their banking books: They take account of their regulatory situation and adjust their exposure to the earning opportunities of this risk. We also find that the customers' preferences predominantly determine the fixed-interest period of housing loans and that the fixed-interest period of these loans has an impact on the banks' overall exposure to interest rate risk. This last finding is not in line with active interest rate risk management.

Who Values Access to College?
Athreya, Kartik,Ionescu, Felicia,Neelakantan, Urvi,Vidangos, Ivan
At first glance, college appears to be of great value to most, given its mean returns and sharply subsidized tuition. An empirically-disciplined human capital model that allows for variation in college readiness suggests otherwise: Nearly half of high school completers place zero value on access to college. This renders blanket subsidies potentially inefficient. As proof of principle, we show that redirecting subsidies away from those who would nonetheless enroll--towards a stock index retirement fund for those who do not even when college is subsidized--increases ex-ante welfare by 1 percent of mean consumption, while preserving enrollment and budget neutrality.

Working Paper: Improved Stock Price Forecasting Algorithm based on Feature-weighed Support Vector Regression by using Grey Correlation Degree
Quanxi Wang

With the widespread engineering applications ranging from artificial intelligence and big data decision-making, originally a lot of tedious financial data processing, processing and analysis have become more and more convenient and effective. This paper aims to improve the accuracy of stock price forecasting. It improves the support vector machine regression algorithm by using grey correlation analysis (GCA) and improves the accuracy of stock prediction. This article first divides the factors affecting the stock price movement into behavioral factors and technical factors. The behavioral factors mainly include weather indicators and emotional indicators. The technical factors mainly include the daily closing data and the HS 300 Index, and then measure relation through the method of grey correlation analysis. The relationship between the stock price and its impact factors during the trading day, and this relationship is transformed into the characteristic weight of each impact factor. The weight of the impact factors of all trading days is weighted by the feature weight, and finally the support vector regression (SVR) is used. The forecast of the revised stock trading data was compared based on the forecast results of technical indicators (MSE, MAE, SCC, and DS) and unmodified transaction data, and it was found that the forecast results were significantly improved.