Research articles for the 2019-07-25

A Re-Examination of Analysts’ Differential Target Price Forecasting Ability
Roger, Tristan,Fontaine, Patrice C.
We challenge the view that persistent differences in accuracy across analysts are proof that analysts differ in their ability to forecast stock prices. We show that these persistent differences in accuracy are driven instead by stock return volatility. Building upon option pricing theory, we construct a measure of forecast quality that controls for stock return volatility and forecast horizon. Contrary to previous studies, which failed to properly account for differences in stock return volatility, our empirical analysis reveals that analysts do not exhibit differences in their ability to forecast stock prices. We show that the accuracy of a target price strongly depends on the stock return volatility and the forecast horizon.

An Overview of the Regulatory Framework of FinTech in Nigeria
Phillips, Olayanju
Since the global financial crisis of 2007, several banking regulatory reforms have been instituted in a bid to increase trust in the Nigerian banking sector and maintain stability in the financial industry. These regulatory reforms, however, did not anticipate the intrusion of technology in the delivery of financial services.The absence of a direct and unified regulation on FinTech in Nigeria has engendered the erroneous notion that the Nigerian FinTech industry is uncharted territory. However, notwithstanding the inexistence of a cohesive FinTech regulation, the Central Bank of Nigeria (CBN) has issued several guidelines, which impacts various aspects of the FinTech industry, especially the digital payments sub-sector which has witnessed the highest amount of activity in recent times. These regulations seek to improve financial inclusion while allowing for continuous innovation. The purpose of this paper is to identify and examine the existing regulations in Nigeria’s FinTech industry and to canvass for a cohesive and comprehensive legislation for Fintech in Nigeria.

Analysts’ and Managers’ Use of Humor on Public Earnings Conference Calls
Call, Andrew C.,Flam, Rachel W.,Lee, Joshua A.,Sharp, Nathan Y.
We examine analysts’ and managers’ use of humor during public earnings conference calls. Using a sample of 85,793 conference calls from 2003-2016, we find that experienced analysts and analysts with positive views of the company are more likely than other analysts to use humor on conference calls. We also find that analysts tend to use humor when the tone of their question is unusually negative, and that analysts who use humor on conference calls are allowed to speak for a longer period of time and receive longer responses from managers. When managers use humor, abnormal returns surrounding the call are higher, and analysts’ stock recommendation revisions following the call are more positive. Our study provides new evidence on the use of humor in corporate disclosure events, and our findings indicate that humor has economically meaningful implications for public earnings conference calls.

Another Look at Cryptocurrency Bubbles
Gronwald, Marc
This paper deals with cryptocurrency bubbles. First, it points out that a number of recent papers on cryptocurrency bubbles are awed due to an insufficient consideration of the fundamental value of cryptocurrencies. As even fiat money is said to exhibit features of bubbles, the same applies to cryptocurrencies. Thus, any empirical investigation into either the presence of cryptocurrency bubbles or the fundamental value of cryptocurrencies is needless. Second, the paper conducts a short empirical analysis into the relationship of the prices of Etherum and Bitcoin. Evidence of explosive periods is found in the price of Etherum even if this price is expressed in terms of Bitcoin rather than US Dollars. These periods, however, are found to be in the first half of 2016 and 2017, respectively, but not during the price peak period of Bitcoin witnessed end of 2017 and beginning of 2018.

Bitcoin and Web Search Query Dynamics: Is the Price Driving the Hype or is the Hype Driving the Price?
Süssmuth, Bernd
Using a battery of timely multivariate time series techniques I study the Bitcoin cryptocurrency price series and web search queries with regard to their mutual predictability, Granger-causality and cause-effect delay structure. The Bitcoin is at first treated as a general currency, then as a generic asset. Google queries, although cointegrated, are found to be not helpful in predicting the USD exchange rate of Bitcoin as the speculative bubble in the latter antedates explosive behavior in the former. Chinese Baidu engine queries and compounded Baidu-Google queries predict Bitcoin price dynamics at relatively high frequencies ranging from two to five months. In the other direction, causality runs from the cryptocurrency price to queries statistics across nearly all frequencies. In both directions, the reaction time computed from a phase delay measure for the relevant frequency bands with significant causality ranges from slightly more than one month to about four months.

Bond Risk Premiums at the Zero Lower Bound
Andreasen, Martin,Jørgensen, Kasper,Meldrum, Andrew
This paper documents a significantly stronger relationship between the slope of the yield curve and future excess bond returns on Treasuries from 2008-2015 than before 2008. This new predictability result is not matched by the standard shadow rate model with Gaussian factor dynamics, but extending the model with regime-switching in the (physical) dynamics of the factors at the lower bound resolves this shortcoming. The model is also consistent with the downwards trend in surveys on short rate expectations at long horizons, but requires a break in the level of its factors to closely fit the low level of these surveys since 2015.

Business Tax Policy Under Default Risk
Comincioli, Nicola,Vergalli, Sergio,Panteghini, Paolo M.
In this article we use a stochastic model with one representative firm to study business tax policy under default risk. We will show that, for a given tax rate, the government has an incentive to reduce (increase) financial instability and default costs if its objective function is welfare (tax revenue).

Changes in Analysts’ Stock Recommendations Following Regulatory Action Against Their Brokerage
Call, Andrew C.,Sharp, Nathan Y.,Wong, Paul A.
Despite the importance of sell-side analysts in the capital markets, we know little about the effectiveness of routine monitoring of the sell-side industry. We examine the attributes of sell-side research issued by analysts before and after their brokerage faces regulatory sanctions. We find that after a sanction, analysts at sanctioned brokerages lower their stock recommendations, both in absolute terms and relative to the recommendations of other analysts following the same firms. These analysts are also more likely than analysts at other brokerages to downgrade a company’s stock after the receipt of unfavorable information about the firm. Importantly, we document that analysts at nonsanctioned brokerages also reduce the optimism of their stock recommendations when a peer analyst’s brokerage is sanctioned, consistent with spillovers as a result of routine regulatory monitoring. Our study provides evidence that regulatory action against sell-side brokerages is associated with a reduction in sell-side analysts’ positive bias.

Common Ownership Does Not Have Anti-Competitive Effects in the Airline Industry
Dennis, Patrick J.,Gerardi, Kristopher,Schenone, Carola
Institutional investors often own significant equity in firms that compete in the same product market. These "common owners" may have an incentive to coordinate the actions of firms that would otherwise be competing rivals, leading to anti-competitive pricing. This paper uses data on airline ticket prices to test whether common owners induce anti-competitive pricing behavior. We find little evidence to support such a hypothesis, and show that the positive relationship between average ticket prices and a commonly used measure of common ownership previously documented in the literature is generated by the endogenous market share component, rather than the ownership component, of the measure.

Deep Reinforcement Learning in Financial Markets
Souradeep Chakraborty

In this paper we explore the usage of deep reinforcement learning algorithms to automatically generate consistently profitable, robust, uncorrelated trading signals in any general financial market. In order to do this, we present a novel Markov decision process (MDP) model to capture the financial trading markets. We review and propose various modifications to existing approaches and explore different techniques to succinctly capture the market dynamics to model the markets. We then go on to use deep reinforcement learning to enable the agent (the algorithm) to learn how to take profitable trades in any market on its own, while suggesting various methodology changes and leveraging the unique representation of the FMDP (financial MDP) to tackle the primary challenges faced in similar works. Through our experimentation results, we go on to show that our model could be easily extended to two very different financial markets and generates a positively robust performance in all conducted experiments.

Does the short-term boost of renewable energies guarantee their stable long-term growth? Assessment of the dynamics of feed-in tariff policy
Milad Mousavian H.,Hamed Shakouri G.,Alinaghi Mashayekhi,Aliyeh Kazemi

Feed in tariff (FiT) is one of the most efficient ways that many governments throughout the world use to stimulate investment in renewable energies (REs) technology. For governments, financial management of the policy is very challenging as that it needs a considerable amount of budget to support RE producers during the long remuneration period. In this paper, we illuminate that the early growth of REs capacity could be a temporary boost and the system elements would backlash the policy if financial circumstances are not handled well. To show this, we chose Iran as the case, which is in the infancy period of FiT implementation. Iran started the implementation of FiT policy in 2015 aiming to achieve 5 GW of renewable capacity until 2021. Analyses show that the probable financial crisis will not only lead to inefficient REs development after the target time (2021), but may also cause the existing plants to fail. Social tolerance for paying REs tax and potential investors trust emanated from budget related mechanisms are taken into consideration in the system dynamics model developed in this research to reflect those financial effects, which have rarely been considered in the previous researches. To prevent the financial crisis of the FiT funding and to maintain the stable growth in long term, three policy scenarios are analyzed: continuation of the current program with higher FiT rates, adjusting the FiT rates based on the budget status, and adjusting the tax on electricity consumption for the development of REs based on the budget status. The results demonstrate that adjusting the tax on electricity consumption for the development of REs based on budget status leads to the best policy result for a desired installed capacity development without any negative social effects and financial crises.

Five Facts About Beliefs and Portfolios
Giglio, Stefano,Maggiori, Matteo,Stroebel, Johannes,Utkus, Stephen P.
We administer a newly-designed survey to a large panel of retail investors who have substantial wealth invested in financial markets. The survey elicits beliefs that are crucial for macroeconomics and finance, and matches respondents with administrative data on their portfolio composition and their trading activity. We establish five facts in this data: (1) Beliefs are reflected in portfolio allocations. The sensitivity of portfolios to beliefs is small on average, but varies significantly with investor wealth, attention, trading frequency, and confidence. (2) It is hard to predict when investors trade, but conditional on trading, belief changes affect both the direction and the magnitude of trades. (3) Beliefs are mostly characterized by large and persistent individual heterogeneity; demographic characteristics explain only a small part of why some individuals are optimistic and some are pessimistic. (4) Investors who expect higher cash flow growth also expect higher returns and lower long-term price-dividend ratios. (5) Expected returns and the subjective probability of rare disasters are negatively related, both within and across investors. These five facts challenge the rational expectation framework for macro-finance, and provide important guidance for the design of behavioral models.

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.

Hedging Climate Change News
Engle, Robert F.,Giglio, Stefano,Lee, Heebum,Kelly, Bryan T.,Stroebel, Johannes
We propose and implement a procedure to dynamically hedge climate change risk. We extract innovations from climate news series that we construct through textual analysis of newspapers. We then use a mimicking portfolio approach to build climate change hedge portfolios. We discipline the exercise by using third-party ESG scores of firms to model their climate risk exposures. We show that this approach yields parsimonious and industry-balanced portfolios that perform well in hedging innovations in climate news both in sample and out of sample. We discuss multiple directions for future research on financial approaches to managing climate risk.

How Does the Interaction of Macroprudential and Monetary Policies Affect Cross-Border Bank Lending?
Takáts, ElÅ'd,Temesvary, Judit
We combine a rarely accessed BIS database on bilateral cross-border lending flows with cross-country data on macroprudential regulations. We study the interaction between the monetary policy of major international currency issuers (USD, EUR and JPY) and macroprudential policies enacted in source (home) lending banking systems. We find significant interactions. Tighter macroprudential policy in a home country mitigates the impact on lending of monetary policy of a currency issuer. For instance, macroprudential tightening in the UK mitigates the negative impact of US monetary tightening on USD-denominated cross-border bank lending outflows from UK banks. Vice-versa, easier macroprudential policy amplifies impacts. The results are economically significant.

Leveraged Bank Loan Versus High Yield Bond Mutual Funds
Banegas, Ayelen,Goldenring, Jessica
Since the financial crisis, the markets for Bank Loan (BL) and High Yield Bond (HYB) mutual funds (MFs) have grown significantly, with assets under management increasing from $19 billion and $75 billion to close to $117 billion and $225 billion, respectively, as of December 2018. This short paper characterizes the universe of BL MFs and compare it against that of HYB MFs on several dimensions. We document that BL and HYB MFs' respective market share of leverage loans (LL) and high yield (HY) corporate bonds outstanding increased since the mid-2000s. We also show that in terms of portfolio allocations, HYB and BL MFs hold around 60 percent of B, BB and BBB-rated assets and that exposure to foreign fixed-income markets is relatively small for both types of MFs. Finally, we document that net flows as a share of assets were larger and more volatile for BL MFs than for their HYB counterparts and that HYB MFs significantly outperformed BL MFs since early 2000.

Liquid Speed: On-Demand Fast Trading at Distributed Exchanges
Michael Brolley,Marius Zoican

Exchanges acquire excess processing capacity to accommodate trading activity surges associated with zero-sum high-frequency trader (HFT) "duels." The idle capacity's opportunity cost is an externality of low-latency trading. We build a model of decentralized exchanges (DEX) with flexible capacity. On DEX, HFTs acquire speed in real-time from peer-to-peer networks. The price of speed surges during activity bursts, as HFTs simultaneously race to market. Relative to centralized exchanges, HFTs acquire more speed on DEX, but for shorter timespans. Low-latency "sprints" speed up price discovery without harming liquidity. Overall, speed rents decrease and fewer resources are locked-in to support zero-sum HFT trades.

Machine Learning Optimization Algorithms & Portfolio Allocation
Perrin, Sarah,Roncalli, Thierry
Portfolio optimization emerged with the seminal paper of Markowitz (1952). The original mean-variance framework is appealing because it is very efficient from a computational point of view. However, it also has one well-established failing since it can lead to portfolios that are not optimal from a financial point of view (Michaud, 1989). Nevertheless, very few models have succeeded in providing a real alternative solution to the Markowitz model. The main reason lies in the fact that most academic portfolio optimization models are intractable in real life although they present solid theoretical properties. By intractable we mean that they can be implemented for an investment universe with a small number of assets using a lot of computational resources and skills, but they are unable to manage a universe with dozens or hundreds of assets. However, the emergence and the rapid development of robo-advisors means that we need to rethink portfolio optimization and go beyond the traditional mean-variance optimization approach.Another industry and branch of science has faced similar issues concerning large-scale optimization problems. Machine learning and applied statistics have long been associated with linear and logistic regression models. Again, the reason was the inability of optimization algorithms to solve high-dimensional industrial problems. Nevertheless, the end of the 1990s marked an important turning point with the development and the rediscovery of several methods that have since produced impressive results. The goal of this paper is to show how portfolio allocation can benefit from the development of these large-scale optimization algorithms. Not all of these algorithms are useful in our case, but four of them are essential when solving complex portfolio optimization problems. These four algorithms are the coordinate descent, the alternating direction method of multipliers, the proximal gradient method and the Dykstra's algorithm. This paper reviews them and shows how they can be implemented in portfolio allocation.

Modeling Flash Crash Behavior in a Stock Market Using Multivariate Hawkes Processes
Shi, Feng,Broussard, John Paul,Booth, G. Geoffrey
This paper uses multivariate Hawkes processes to model the transactions behavior of the U.S. stock market as proxied by the 30 Dow Jones Industrial Average stocks before, during and after the May 6, 2010 flash crash, which lasted 36 minutes. The basis for our analysis is the excitation matrix, which we use to describe the network of interactions among the stocks Using high-frequency transactions data for individual stocks, we find, among other things, strong evidence of contagion that is self- and asymmetrically cross-induced. Our descriptive findings have implications for stock trading and corresponding risk management strategies as well as stock market microstructure design.

Monetary Policy Transmission to Consumer Financial Stress and Durable Consumption
Georgarakos, Dimitris,Tatsiramos, Konstantinos
We examine the effects of monetary policy on household self-assessed financial stress and durable consumption using panel data from eighteen annual waves of the British Household Panel Survey. For identification, we exploit random variation in household exposure to interest rates generated by the random timing of household interview dates with respect to policy rate changes. After accounting for household and month-year-of-interview fixed effects, we uncover significant heterogeneities in the way monetary policy affects household groups that differ in housing and saving status. In particular, an increase in the interest rate induces financial stress among mortgagors and renters, while it lessens financial stress of savers. We find symmetric effects on durable consumption, mainly driven by mortgagors with high debt burden or limited access to liquidity and younger renters who are prospective home buyers.

On the Statistical Differences between Binary Forecasts and Real World Payoffs
Nassim Nicholas Taleb

What do binary (or probabilistic) forecasting abilities have to do with overall performance? We map the difference between (univariate) binary predictions, bets and "beliefs" (expressed as a specific "event" will happen/will not happen) and real-world continuous payoffs (numerical benefits or harm from an event) and show the effect of their conflation and mischaracterization in the decision-science literature. We also examine the differences under thin and fat tails. The effects are:

A- Spuriousness of many psychological results particularly those documenting that humans overestimate tail probabilities and rare events, or that they overreact to fears of market crashes, ecological calamities, etc. Many perceived "biases" are just mischaracterizations by psychologists. There is also a misuse of Hayekian arguments in promoting prediction markets.

We quantify such conflations with a metric for "pseudo-overestimation".

B- Being a "good forecaster" in binary space doesn't lead to having a good actual performance}, and vice versa, especially under nonlinearities. A binary forecasting record is likely to be a reverse indicator under some classes of distributions. Deeper uncertainty or more complicated and realistic probability distribution worsen the conflation .

C- Machine Learning: Some nonlinear payoff functions, while not lending themselves to verbalistic expressions and "forecasts", are well captured by ML or expressed in option contracts.

D- Fattailedness: The difference is exacerbated in the power law classes of probability distributions.

Operational and Fianncial Performance of Andhra Pradesh State Financial Corporation â€" An Overview
C, Viswanatha Reedy
Andhra Pradesh State Financial Corporation [APSFC] is a term lending Institution established in 1956 by merger of Andhra State Financial Corporation and Hyderabad State Financial Corporation for promoting small and medium scale industries (SMEs) in Andhra Pradesh under the provisions of the Sate Financial Corporations Act, 1951. The APSFC as premier state level financial institution and as an integral part of the development financing system in the country has gained prominence for playing its role in the achievement of rapid and high quality industrial growth in Andhra Pradesh. It offers a package of assistance to the entrepreneurs to enable them to translate their project ideas into reality. The corporation has launched many entrepreneur-friendly schemes to provide term loans, working capital term loans, and special and seed capital assistance to suit the needs of various categories of entrepreneurs. The Corporation has completed five and half decades of dedicated service in industrial financing of tiny, small and medium scale sector units and contributing to the balanced regional development of the state. It has been continuously doing its best in every possible area of its operations to retain its premier position among the SFCs in the country. In order to provide an instant picture of the performance of the APSFC during the last 10 years, the researcher has under taken the present study entitled “Operational and Financial Performance of Andhra Pradesh State Financial Corporation â€" An Overview”. In this paper the researcher has made an attempt to examine the no. of applications sanctioned with applied amount, flow of assistance in terms of sanctions and disbursements, flow of assistance to small-scale sector, Recovery performance of the Corporation, Income and expenditure, Operating and net profit, Growth in net worth, Capital adequacy ratio, Asset quality and reduction of NPAs, Cost of borrowings and return on average assets. At the end of the analysis some viable and useful suggestions are offered to tone up the overall performance of the Corporation for industrial development in Andhra Pradesh.

Optimal make take fees in a multi market maker environment
Bastien Baldacci,Dylan Possamaï,Mathieu Rosenbaum

Following the recent literature on make take fees policies, we consider an exchange wishing to set a suitable contract with several market makers in order to improve trading quality on its platform. To do so, we use a principal-agent approach, where the agents (the market makers) optimise their quotes in a Nash equilibrium fashion, providing best response to the contract proposed by the principal (the exchange). This contract aims at attracting liquidity on the platform. This is because the wealth of the exchange depends on the arrival of market orders, which is driven by the spread of market makers. We compute the optimal contract in quasi explicit form and also derive the optimal spread policies for the market makers. Several new phenomena appears in this multi market maker setting. In particular we show that it is not necessarily optimal to have a large number of market makers in the presence of a contracting scheme.

Options Trading and Voluntary Corporate Disclosure
Chen, Yangyang,Ng, Jeffrey,Yang, Xin
Motivated by the close relation between stock options and the underlying stock and the informed trading taking place in the options market, we examine the effect of options trading on voluntary corporate disclosure. We find that options trading is negatively and significantly related to the likelihood and frequency of management earnings forecasts, suggesting that firms with an active options market make less voluntary disclosure. This finding suggests that information spillover from the options market to the stock market can increase stock price informativeness, in turn, reducing the need for firms to engage in voluntary disclosure to guide investor expectations. We further document that the negative relation between options trading and management forecasts is more pronounced for firms with a poorer information environment, a finding that highlights that information transfer from other markets, especially those with informed trading, is more important for more opaque firms. Consistent with information transfer reducing the need for voluntary disclosure, we also find that the negative relation is more pronounced for firms with stock market conditions that facilitate more price discovery. Lastly, we find that options trading reduces the specificity and informativeness of management forecasts. Our paper offers new insight into how cross-market information transfer can affect voluntary disclosure.

Overcoming the Matthew Effect in Status Dominated Environments â€" a Configurational Analysis of Venture Capital Investments
Berger, Elisabeth S.C.,Kuckertz, Andreas
Entering status dominated environments as new entrant is a difficult endeavor. Accumulated advantages go along with the tendency of incumbents to succeed, whereas entrants are likely to lose (Matthew effect). This study examines what combination of deal resources accumulated by venture capital partners lead to high deal performance in order to analyze if new entrants can nonetheless overcome the burden of being new, i.e. having a low status position and only weak ties with current actors in status dominated environments. Our configurational analysis of 333 venture capital investments reveals opportunities for entrants to succeed that go beyond joining forces with established actors. Our findings contribute to research on interorganizational network formation and the strategic actions new entrants on the VC market may take to be successful. Furthermore, the study sheds light on the effect of syndicated opposed to single venture capitalist deals and suggests that successful syndicates require a certain degree of homogeneity among the investors.

Preventing Bank Panics with Fees and Gates
Voellmy, Lukas
I study whether a bank can prevent runs by augmenting its demandable debt contracts with 'fees and gates' -clauses as intended by the 2014 money market mutual fund reform. I focus on purely self-fulfilling runs; the bank's investments do not exhibit fundamental risk and aggregate liquidity needs of depositors are known. The bank holds assets with different maturities and premature liquidations lead to losses. If the bank never puts restrictions on withdrawals, it will be susceptible to runs à-la Diamond and Dybvig (1983) since early redemptions impose liquidation losses on depositors who do not withdraw. Gates (suspension) eliminate run equilibria whenever depositors' liquidity preference is not too strong; if liquidity preference is strong, gates give rise to deposit-access panics à-la Engineer (1989). Fees are more effective in preventing runs compared to gates if and only if liquidation losses are low. If liquidation losses are high and liquidity preference is strong, fees and gates need to be combined in the right manner in order to prevent runs.

Pricing Poseidon: Extreme Weather Uncertainty and Firm Return Dynamics
Kruttli, Mathias,Roth Tran, Brigitte,Watugala, Sumudu W.
We investigate the uncertainty dynamics surrounding extreme weather events through the lens of option and stock markets by identifying market responses to the uncertainty regarding both potential hurricane landfall and subsequent economic impact. Stock options on firms with establishments exposed to the landfall region exhibit increases in implied volatility of 5-10 percent, reflecting impact uncertainty. Using hurricane forecasts, we show that landfall uncertainty and potential impact uncertainty are reflected in prices before landfall. We find no evidence that markets incorporate better hurricane forecasts than those from NOAA. Improvements to hurricane forecasts could have economically significant effects in financial markets.

Resolution of the St. Petersburg paradox using Von Mises axiom of randomness
Andrea Berdondini

In this article we will propose a completely new point of view for solving one of the most important paradoxes concerning game theory. The solution develop shifts the focus from the result to the strategy s ability to operate in a cognitive way by exploiting useful information about the system. In order to determine from a mathematical point of view if a strategy is cognitive, we use Von Mises' axiom of randomness. Based on this axiom, the knowledge of useful information consequently generates results that cannot be reproduced randomly. Useful information in this case may be seen as a significant datum for the recipient, for their present or future decision-making process. Finally, by resolving the paradox from this new point of view, we will demonstrate that an expected gain that tends toward infinity is not always a consequence of a cognitive and non-random strategy. Therefore, this result leads us to define a hierarchy of values in decision-making, where the cognitive aspect, whose statistical consequence is a divergence from random behaviour, turns out to be more important than the expected gain.

Risk-dependent centrality in economic and financial networks
Paolo Bartesaghi,Michele Benzi,Gian Paolo Clemente,Rosanna Grassi,Ernesto Estrada

Node centrality is one of the most important and widely used concepts in the study of complex networks. Here, we extend the paradigm of node centrality in financial and economic networks to consider the changes of node "importance" produced not only by the variation of the topology of the system but also as a consequence of the external levels of risk to which the network as a whole is submitted. Starting from the "Susceptible-Infected" (SI) model of epidemics and its relation to the communicability functions of networks we develop a series of risk-dependent centralities for nodes in (financial and economic) networks. We analyze here some of the most important mathematical properties of these risk-dependent centrality measures. In particular, we study the newly observed phenomenon of ranking interlacement, by means of which two entities may interlace their ranking positions in terms of risk in the network as a consequence of the change in the external conditions only, i.e., without any change in the topology. We test the risk-dependent centralities by studying two real-world systems: the network generated by collecting assets of the S\&P 100 and the corporate board network of the US top companies, according to Forbes in 1999. We found that a high position in the ranking of the analyzed financial companies according to their risk-dependent centrality corresponds to companies more sensitive to the external market variations during the periods of crisis.

Safe Asset Carry Trade
Ballensiefen, Benedikt,Ranaldo, Angelo
We provide an asset pricing analysis of one of the main categories of near-money or safe assets, the repurchase agreement (repo). Heterogeneity in repo rates allows for a remunerative carry trade. The return on this carry trade, our carry factor, together with a market factor explain the temporal and cross-sectional variation in repo rates within a no-arbitrage framework: While the market factor determines the level of short-term interest rates, the carry factor accounts for the cross-sectional dispersion. Consistent with the safe asset literature, the carry factor reflects heterogeneity in convenience premia and is explained by the safety premium, the liquidity premium, and the opportunity cost of holding money.

Shock Transmission Through Cross-Border Bank Lending: Credit and Real Effects
Hale, Galina,Kapan, Tumer,Minoiu, Camelia
We study the transmission of financial shocks across borders through international bank connections. Using data on cross-border interbank loans among 6,000 banks during 1997-2012, we estimate the effect of asset-side exposures to banks in countries experiencing systemic banking crises on profitability, credit, and the performance of borrower firms. Crisis exposures reduce bank returns and tighten credit conditions for borrowers, constraining investment and growth. The effects are larger for foreign borrowers, including in countries not experiencing banking crises. Our results document the extent of cross-border crisis transmission, but also highlight the resilience of financial networks to idiosyncratic shocks.

Special Drawing Rights in a New Decentralized Century
Andreas Veneris,Andreas Park

Unfulfilled expectations from macro-economic initiatives during the Great Recession and the massive shift into globalization echo today with political upheaval, anti-establishment propaganda, and looming trade/currency wars that threaten domestic and international value chains. Once stable entities like the EU now look fragile and political instability in the US presents unprecedented challenges to an International Monetary System (IMS) that predominantly relies on the USD and EUR as reserve currencies. In this environment, it is critical for an international organization mandated to ensure stability to plan and act ahead. This paper argues that Decentralized Ledger-based technology (DLT) is key for the International Monetary Fund (IMF) to mitigate some of those risks, promote stability and safeguard world prosperity. Over the last two years, DLT has made headline news globally and created a worldwide excitement not seen since the internet entered the mainstream. The rapid adoption and open-to-all philosophy of DLT has already redefined global socioeconomics, promises to shake up the world of commerce/finance and challenges the workings of central governments/regulators. This paper examines DLT core premises and proposes a two-step approach for the IMF to expand Special Drawing Rights (SDR) into that sphere so as to become the originally envisioned numeraire and reserve currency for cross-border transactions in this new decentralized century.

Taxing the Disposition Effect: The Impact of Tax Awareness on Investor Behavior
Bazley, William J.,Moore, Jordan,Murren Vosse, Melina
Canonical portfolio choice models suggest that investors should consider the tax implications of trading. Using field data, we show that individual trading behavior is sensitive to effective capital gains tax rates when rates are likely salient, such as during regime changes. In an experimental market setting, increasing the salience of tax consequences reduces the disposition effect by more than 40%, leading to higher portfolio balances with no significant change in total trading activity. We demonstrate that increasing tax awareness, particularly through visual cues, can impact individuals' portfolio choices, which implies potential for policy to improve financial decision-making.

The Costs and Benefits of Liquidity Regulations: Lessons from an Idle Monetary Policy Tool
Curfman, Christopher J,Kandrac, John
We investigate how liquidity regulations affect banks by examining a dormant monetary policy tool that functions as a liquidity regulation. Our identification strategy uses a regression kink design that relies on the variation in a marginal high-quality liquid asset (HQLA) requirement around an exogenous threshold. We show that mandated increases in HQLA cause banks to reduce credit supply. Liquidity requirements also depress banks' profitability, though some of the regulatory costs are passed on to liability holders. We document a prudential benefit of liquidity requirements by showing that banks subject to a higher requirement before the financial crisis had lower odds of failure.

The Role of U.S. Monetary Policy in Global Banking Crises
Durdu, Ceyhun Bora,Martin, Alex,Zer, Ilknur
We examine the role of U.S. monetary policy in global financial stability by using a cross-country database spanning the period from 1870-2010 across 69 countries. U.S. monetary policy tightening increases the probability of banking crises for those countries with direct linkages to the U.S., either in the form of trade links or significant share of USD-denominated liabilities. Conversely, if a country is integrated globally, rather than having a direct exposure, the effect is ambiguous. One possible channel we identify is capital flows: If the correction in capital flows is disorderly (e.g., sudden stops), the probability of banking crises increases. These findings suggest that the effect of U.S. monetary policy in global banking crises is not uniform and largely dependent on the nature of linkages with the U.S.

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, and for Standard & Poor 400 Mid-Cap and 600 Small-Cap. 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, weak for individual stocks). No conclusive evidence about dependence of excess return (alpha) on size, or international markets.

To Regulate or Not to Regulate? A Comparison of Government Responses to Peer-to-Peer Lending among the United States, China, and Taiwan
Tsai, Chang-hsien
With the worldwide revolution in financial technology (“FinTech”), Peer-to-Peer (“P2P”) lending, an alternative funding channel, has grown rapidly over the past decade. P2P lending benefits digital financial inclusion by providing an online platform to facilitate direct trades between borrowers and lenders with limited intermediation by traditional financial institutions. During P2P lending transactions, a significant amount of transaction records are accumulated, thus creating a FinTech-driven credit assessment mechanism to help underserved borrowers, who are often turned down by traditional financial intermediaries, obtain credit. P2P lending business models as well as government responses to those models differ. For example, the United States has been reactive, requiring platforms to fully comply with the extant securities regulation, while China, though initially hands-off, has also become reactive, limiting P2P platforms to the information intermediation model due to a series of P2P failures. Taiwan’s regulatory response to P2P lending, led by its Financial Supervisory Commission (“FSC”), the sole financial market watchdog in Taiwan, started as reactive, warning that the P2P lending industry should not cross four major red lines drawn under existing regulatory and business structures. The Taiwanese government, however, has become more proactive â€" at least in form, introducing the Financial Technology Development and Innovative Experimentation Act (the “FinTech Sandbox Act”) to permit cautious regulatory experimentation. Though a positive effort, this act may, in substance, be an ineffective means to address the regulatory dilemma between prudential regulation and financial competition and innovation. This is because the government lacks the institutional incentive to replace the existing regulatory regime with something truly proactive. We propose a structural change in the current institutional design that could reallocate the authority of financial competition and innovation to a more motivated financial agency, separate from and independent of the FSC, that would be better positioned to safeguard financial competition and innovation enabled by FinTech.

Unbiased deep solvers for parametric PDEs
Marc Sabate Vidales,David Siska,Lukasz Szpruch

We develop several deep learning algorithms for approximating families of parametric PDE solutions. The proposed algorithms approximate solutions together with their gradients, which in the context of mathematical finance means that the derivative prices and hedging strategies are computed simulatenously. Having approximated the gradient of the solution one can combine it with a Monte-Carlo simulation to remove the bias in the deep network approximation of the PDE solution (derivative price). This is achieved by leveraging the Martingale Representation Theorem and combining the Monte Carlo simulation with the neural network. The resulting algorithm is robust with respect to quality of the neural network approximation and consequently can be used as a black-box in case only limited a priori information about the underlying problem is available. We believe this is important as neural network based algorithms often require fair amount of tuning to produce satisfactory results. The methods are empirically shown to work for high-dimensional problems (e.g. 100 dimensions). We provide diagnostics that shed light on appropriate network architectures.