# Research articles for the 2019-07-23

12 Pillarsâ€™ Framework for Successful Financial Inclusion in India
C, Viswanatha Reedy
SSRN
Financial inclusion has been accorded high importance by the GoI and RBI to aid the inclusive growth process of the economy but the impact of these did not yield agreeable results. There have been formidable challenges in this area such as bringing sections of society that are financially excluded within the ambit of the formal financial system, providing financial literacy and strengthening credit delivery mechanisms. As the majority of the rural population is still not included in the inclusive growth, the concept of financial inclusion becomes a challenge for the Indian economy. The present study made an attempt to study the effectiveness of the existing resources such as Network of Bank Branches, Business Correspondents (BCs), Basic Savings Bank Deposit Accounts with Overdraft facility, Financial Literacy and Credit Counselling, Credit Guarantee Fund, Micro Insurance, Unorganised Sector Pension Schemes, Payment Banks, Post Offices and Fair Price Shops Network, Information Technology, Banking Technologies, PMJDY and MUDRA Yojana, etc, towards financial inclusion. The study says that there is still lacuna which needs to be covered thereby making financial inclusion more efficient and user friendly for the financially untouchable rural population.

529 College Savings Plan under the TCJA: Evaluating Age-Based Portfolios
Riskin, Ross
SSRN
The enactment of the Tax Cuts and Jobs Act of 2017 (TCJA) introduces some of the most sweeping tax law changes in more than 30 years and enhances the flexibility investors have when using 529 college savings plans for more than just qualified higher education expenses. Investors can now use funds from these accounts to pay for qualified K-12 tuition expenses without being taxed or penalized on the earnings associated with the distributions at the federal level. While this new provision may make 529 college savings plans more attractive, investors may now need to re-evaluate their investment holdings in these plans especially if they are using age-based portfolios and are planning for pre-undergraduate education expenses, post-graduate education expenses, or are considering using a combination of in-state and out-of-state 529 college savings plans to achieve their education planning goals.

A Note on Universal Bilinear Portfolios
Alex Garivaltis
arXiv

This note provides a neat and enjoyable expansion and application of the magnificent Ordentlich-Cover theory of "universal portfolios." I generalize Cover's benchmark of the best constant-rebalanced portfolio (or 1-linear trading strategy) in hindsight by considering the best bilinear trading strategy determined in hindsight for the realized sequence of asset prices. A bilinear trading strategy is a mini two-period active strategy whose final capital growth factor is linear separately in each period's gross return vector for the asset market. I apply Cover's ingenious (1991) performance-weighted averaging technique to construct a universal bilinear portfolio that is guaranteed (uniformly for all possible market behavior) to compound its money at the same asymptotic rate as the best bilinear trading strategy in hindsight. Thus, the universal bilinear portfolio asymptotically dominates the original (1-linear) universal portfolio in the same technical sense that Cover's universal portfolios asymptotically dominate all constant-rebalanced portfolios and all buy-and-hold strategies. In fact, like so many Russian dolls, one can get carried away and use these ideas to construct an endless hierarchy of ever more dominant $H$-linear universal portfolios.

A note on Parisian ruin under a hybrid observation scheme
Mohamed Amine Lkabous
arXiv

In this paper, we study the concept of Parisian ruin under the hybrid observation scheme model introduced by Li et al. \cite{binetal2016}. Under this model, the process is observed at Poisson arrival times whenever the business is financially healthy and it is continuously observed when it goes below $0$. The Parisian ruin is then declared when the process stays below zero for a consecutive period of time greater than a fixed delay. We improve the result originally obtained in \cite{binetal2016} and we compute other fluctuation identities. All identities are given in terms of second-generation scale functions.

Accelerated Share Repurchase and other buyback programs: what neural networks can bring
Olivier Guéant,Iuliia Manziuk,Jiang Pu
arXiv

When firms want to buy back their own shares, they have a choice between several alternatives. If they often carry out open market repurchase, they also increasingly rely on banks through complex buyback contracts involving option components, e.g. accelerated share repurchase contracts, VWAP-minus profit-sharing contracts, etc. The entanglement between the execution problem and the option hedging problem makes the management of these contracts a difficult task that should not boil down to simple Greek-based risk hedging, contrary to what happens with classical books of options. In this paper, we propose a machine learning method to optimally manage several types of buyback contracts. In particular, we recover strategies similar to those obtained in the literature with partial differential equation and recombinant tree methods and show that our new method, which does not suffer from the curse of dimensionality, enables to address types of contract that could not be addressed with grid or tree methods.

Analysis of Liquidity, Profitability, Risk and Financial Distress: A Case Study of Dr.Reddyâ€™s Laboratories Ltd.
C, Viswanatha Reedy
SSRN
Liquidity is the ability of an organization to meet its financial obligations during the short-term and to maintain long-term debt-paying ability. The long-term survival depends on satisfactory income earned by it. A sound liquidity leads to better profitability, and in turn reduces the probability of default risk in future. Further, the risk and return are very important aspects to be considered while making any decisions regarding companyâ€™s finance. Predicting enterprise failures constitutes one of the most important activities in supervising enterprise risks and/or variables. The term enterprise failure is a definable phenomenon: for instance, failure to cover external debts, exceeding budget limits, failure to effect payment to suppliers, incurring losses, etc. Therefore, a study of liquidity, profitability, and their association with risk, assessing the financial position (financial distress/bankruptcy) is very much necessary to evaluate the financial strength of the company. Financial distress is a tight cash situation in which a business cannot pay the owed amounts on the due date. When a firm is under financial distress, the situation sharply reduces its market value and larger customers may cancel their orders. A firm in financial distress may face bankruptcy or liquidation leading to delay in meeting its liabilities. This paper attempts to study the association between liquidity, profitability and risk factor. The Altmanâ€™s Z-score model has been employed by the researcher to predict the risk of financial distress of Dr. Reddyâ€™s Laboratories Limited, from the year 2005-2011. The results indicated that the liquidity, and solvency position of the company has been satisfactory. The Z-score analysis revealed that the company is not suffering from financial distress and there are indications of turnaround activities already undertaken by the company.

Bankruptcy Prediction with Financial Systemic Risk
Jia, Zhehao,Shi, Yukun,Yan, Cheng,Duygun, Meryem
SSRN
Financial systemic risk â€" defined as the risk of collapse of an entire financial system vis-Ã -vis any one individual financial institution â€" is making inroads into academic research in the aftermath of the late 2000s Global Financial Crisis. We shed light on this new concept by investigating the value of various systemic financial risk measures in the corporate failure predictions of listed nonfinancial firms. Our sample includes 225,813 firm-quarter observations covering 8,604 US firms from 2000 Q1 to 2016 Q4. We find that financial systemic risk is incrementally useful in forecasting corporate failure over and above the predictions of the traditional accounting-based and market-based factors. Our results are stronger when the firm in consideration has higher equity volatility relative to financial sector volatility, the smaller size relative to the market, and more debts in current liabilities. The combined evidence suggests that systemic risk is a useful supplementary source of information in capital markets.

Bilateral Gamma distributions and processes in financial mathematics
Uwe Küchler,Stefan Tappe
arXiv

We present a class of L\'evy processes for modelling financial market fluctuations: Bilateral Gamma processes. Our starting point is to explore the properties of bilateral Gamma distributions, and then we turn to their associated L\'evy processes. We treat exponential L\'evy stock models with an underlying bilateral Gamma process as well as term structure models driven by bilateral Gamma processes and apply our results to a set of real financial data (DAX 1996-1998).

Bitcoin Speculation or Value Creation? Corporate Blockchain Investments and Stock Market Reactions
Autore, Don M.,Clarke, Nicholas,Jiang, Danling
SSRN
We study the stock price reaction to the first public news that a firm is investing in blockchain technology. The initial reaction averages close to +15% and is followed by a reversal over the next three months. However, reactions differ substantially based on the credibility of the investment and investorsâ€™ speculative tendencies. Investments associated with lottery-type stocks and higher investor attention and sentiment exhibit higher initial reactions but are followed by significant reversals. Blockchain investments that are at an advanced stage or confirmed in subsequent financial statements, however, are associated with higher initial reactions and little or no reversal.

Comparing the Effects of Behaviorally-Informed Interventions on Flood Insurance Demand: An Experimental Analysis of â€˜Boostsâ€™ and â€˜Nudgesâ€™
SSRN
This paper compares the effects of two types of behaviorally-informed policy, nudges and boosts, that are designed to increase consumer demand for insurance against low-probability, high-consequence (LPHC) events. Using previous findings in the behavioral sciences literature, this paper constructs and implements two nudges (an â€œinformationalâ€ and an â€œaffectiveâ€ nudge) and a statistical numeracy boost and then elicits individual risk beliefs and demand for flood insurance using a contingent valuation survey of 331 participants recruited from an online labor pool. Using a two-limit Tobit model to estimate willingness-to-pay (WTP) for flood insurance, this paper finds that the affective and informational nudges result in increases in WTP for flood insurance of roughly $21/month and$11/month relative to the boost, respectively. Taken together, the findings of this paper suggest that nudges are the more effective behaviorally-informed policy in this setting, particularly when the nudge design targets the affect and availability heuristics; however, additional research is necessary to establish sufficient conditions for this conclusion.

Conditional inference on the asset with maximum Sharpe ratio
Steven E. Pav
arXiv

We apply the procedure of Lee et al. to the problem of performing inference on the signal noise ratio of the asset which displays maximum sample Sharpe ratio over a set of possibly correlated assets. We find a multivariate analogue of the commonly used approximate standard error of the Sharpe ratio to use in this conditional estimation procedure. We also consider the simple Bonferroni correction for multiple hypothesis testing, fixing it for the case of positive common correlation among assets.

Testing indicates the conditional inference procedure achieves nominal type I rate, and does not appear to suffer from non-normality of returns. The conditional estimation test has low power under the alternative where there is little spread in the signal noise ratios of the assets, and high power under the alternative where a single asset has high signal noise ratio.

Consumption smoothing in the working-class households of interwar Japan
Kota Ogasawara
arXiv

I analyze Osaka factory worker households in the early 1920s, whether idiosyncratic income shocks were shared efficiently, and which consumption categories were robust to shocks. While the null hypothesis of full risk-sharing of total expenditures was rejected, factory workers maintained their households, in that they paid for essential expenditures (rent, utilities, and commutation) during economic hardship. Additionally, children's education expenditures were possibly robust to idiosyncratic income shocks. The results suggest that temporary income is statistically significantly increased if disposable income drops due to idiosyncratic shocks. Historical documents suggest microfinancial lending and saving institutions helped mitigate risk-based vulnerabilities.

Credit Frictions, Selection into External Finance, and Gains from Trade
Unger, Florian
SSRN
This paper analyzes the effects of credit frictions in a trade model where heterogeneous firms select both into exporting and into two types of external finance. In our framework, small producers face stronger credit frictions, pay a higher borrowing rate and rely on bank finance, whereas large firms have access to cheaper bond finance. We show that an increase in credit frictions induces firms to select into bank finance, which attenuates the negative implications on product variety and welfare. In the open economy, the presence of effective financial intermediation increases the welfare gains from trade. In a counterfactual analysis, we exploit that our framework nests a model with credit frictions and one type of finance as a special case, and we show that endogenous selection into external finance is an important channel of adjustment.

Discrete dividend payments in continuous time
Jussi Keppo,Max Reppen,H. Mete Soner
arXiv

We propose a model in which dividend payments occur at regular, deterministic intervals in an otherwise continuous model. This contrasts traditional models where either the payment of continuous dividends is controlled or the dynamics are given by discrete time processes. Moreover, between two dividend payments, the structure allows for other types of control; we consider the possibility of equity issuance at any point in time. The value is characterized as the fixed point of an optimal control problem with periodic initial and terminal conditions. We prove the regularity and uniqueness of the corresponding dynamic programming equation, and the convergence of an efficient numerical algorithm that we use to study the problem. The model enables us to find the loss caused by infrequent dividend payments. We show that under realistic parameter values this loss varies from around 1% to 24% depending on the state of the system, and that using the optimal policy from the continuous problem further increases the loss.

Equilibrium Counterfactuals
Chemla, Gilles,Hennessy, Christopher
SSRN
We incorporate structural modellers into the economy they model. Using the traditional moment-matching method, they ignore policy feedback and estimate parameters using a structural model that treats policy changes as zero probability (or exogenous) "counterfactuals." Estimation bias occurs since the economy's actual agents, in contrast to model agents, understand policy changes are positive probability endogenous events guided by the modellers. We characterize equilibrium bias. Depending on technologies, downward, upward, or sign bias occurs. Potential bias magnitudes are illustrated by calibrating the Leland (1994) model to the Tax Cuts and Jobs Act of 2017. Regarding parameter identification, we show the traditional structural identifying assumption, constant moment partial derivative sign, is incorrect for economies with endogenous policy optimization: The correct identifying assumption is constant moment total derivative sign accounting for estimation-policy feedback. Under this assumption, model agent expectations can be updated iteratively until the modellers' policy advice converges to agent expectations, with bias vanishing.

Facebookâ€™s Project Libra: Will Libra Sputter Out or Spur Central Banks to Introduce Their Own Unique Cryptocurrency Projects?
SSRN
In the evolution of money, the advent of cryptocurrencies would have been an inevitable and a natural phenomenon, but the farfetched implications of the 2008 global credit mayhem only accelerated their arrival. Facebookâ€™s claim of the Libra Blockchain as a decentralized network is far from reality, in fact, it is a lie because Libra is designed to be launched in 2020 as a permissioned (centralized) system where billions of transactions will be governed by the 28 heavyweight validator-firms (nodes), each of which is a member of the Libra Association. Facebook has stated that the number of validators will reach 100, when this occurs, each validator including Facebook will have an equal share (i.e. 1%) of voting rights. This is an improvement over the Board of Governors of the Federal Reserve System, not all of the twelve Federal Reserve Banks have voting rights; besides the Fed Chairman and president of the Bank of New York (Vice-Chairman), four of the remaining eleven Reserve Bank presidents serve one-year terms on a rotating basis. Contrary to the huge hype filled with hopes, Bitcoin (as well as other existing 2,300 digital coins) on account of extreme volatility has failed to become a simple global crypto-currency for everyday life, enabling people to transfer money to individuals or businesses anywhere in the world and purchase desired products and services online within seconds without going through unnecessary hassle (i.e. limited or no access) and financial burden of high transactional costs. Facebookâ€™s Libra seems to possess all necessary elements to become a viable alternative to the U.S. dollar only if major central banks (particularly the Fed and ECB) and governments allow it.

Fair Value Measurement Discretion and Opportunistic Avoidance of Impairment Loss Recognition
Hodder, Leslie D.,Sheneman, Amy
SSRN
Prior studies find evidence that opportunistic reporting occurs in settings where fair value measurement is used. However, such research cannot determine whether the source of the opportunistic reporting is the estimate of fair value itself. Using detailed insurer investment holdings information, we separate the use of fair value measurement discretion from the application of non-measurement-related discretion in accounting for incurred losses of financial instruments. Our evidence contradicts the view that fair value measurement discretion plays a large role in opportunistic avoidance of loss recognition for financial instruments. Instead, managers appear to avoid loss recognition on investment securities by opportunistically applying subjective criteria related to perceived loss persistence and intent to hold.

Friends for the Benefits: The Effects of Political Ties on Sovereign Borrowing Conditions
Ambrocio, Gene,Hasan, Iftekhar
SSRN
Do closer political ties with a global superpower improve sovereign borrowing conditions? We use data on voting at the United Nations General Assembly along with foreign aid flows to construct an index of political ties and find evidence that suggests closer political ties leads to both better sovereign credit ratings and lower yields on sovereign bonds. We use heads-of-state official visits and coalition forces troop contributions as exogenous instruments to further strengthen the findings.

Impact of Corporate (Dividend) Action on Stocks in India
M, Nagendra,, Prof. M Suresh Babu
SSRN
The investment decision is influenced by many factors of which one such factor is return. The shareholders may get return in the form dividend which affects the share prices. The behavior of stock prices is unpredictable as price movement for different activities will move in different ways. The stock price movements can be divided into Economic and corporate activities. The impact of economic activities will be more or less same on all the stock prices while impact of corporate action varies from one stock to the other. Dividend payment is one of the important corporate actions that will have an impact on the behavior of stock prices. This research highlights the impact of dividend payment on the behavior of stock prices. To understand this behavior, ten stocks have been randomly picked which has paid the dividend in 2016. The researchers have used popular event window study and cumulative returns. In this regard, the researchers have picked two dates, namely dividend announcement date and the other is dividend effective date. The paired sample t-test is employed to compare cumulative returns before and after dividend announcement.

Large Retailers' Financial Services
Risso, Mario
SSRN
Over the last few years, large retailers offering financial services have considerably grown in the financial services sector. Retailers are increasing the wideness and complexity of their offer of financial services. Large retail companies provide financial services to their customers following different strategic ways. The provision of financial services in the retailers offer is implemented in several different ways related to the strategies, the structures and the degree of financial know-how of the large retailers involved.

Local Public Corruption and Bank Lending Activity in the United States
Bermpei, Theodora,Kalyvas, Antonios Nikolaos,Leonida, Leone
SSRN
Using a conviction-based measure, we find that local (state-level) public corruption exerts a negative effect on the lending activity of US banks. Our baseline estimations show that the difference in public corruption between, e.g., Alabama, where corruption is high, and Minnesota, where corruption is low, implies that banks headquartered in the former state grant 0.56% less credit (or $3.57 million for the average bank) ceteris paribus. Using proxies for relationship lending and monitoring, we also find that these bank characteristics weaken the negative effect of public corruption on lending. In further analysis, we show that these effects are more evident for smaller banks and banks operating in a single state. These results are robust to tests that address endogeneity, to the use of perception-based measures of corruption and after controlling for credit demand conditions. These findings provide evidence that public corruption could facilitate information asymmetry in the lending market and, thus, could hinder local development by reducing bank credit. Macroprudential Policy at the ECB: Institutional Framework, Strategy, Analytical Tools and Policies ConstÃ¢ncio, Vitor,Cabral, InÃªs,Detken, Carsten,Fell, John,Henry, JÃ©rÃ´me,Hiebert, Paul,Kapadia, Sujit,Altimar, Sergio Nicoletti,Pires, Fatima,Salleo, Carmelo SSRN This occasional paper describes how the financial stability and macroprudential policy functions are organised at the ECB. Financial stability has been a key policy function of the ECB since its inception. Macroprudential policy tasks were later conferred on the ECB by the Single Supervisory Mechanism (SSM) Regulation. The paper describes the ECBâ€™s macroprudential governance framework in the new institutional set-up. After reviewing the concept and origins of systemic risk, it reflects on the emergence of macroprudential policy in the aftermath of the financial crisis, its objectives and instruments, as well as specific aspects of this policy area in a monetary union such as the euro area. The ECBâ€™s responsibilities required new tools to be developed to measure systemic risk at financial institution, country and system-wide level. The paper discusses selected analytical tools supporting financial stability surveillance and assessment work, as well as macroprudential policy analysis at the ECB. The tools are grouped into three broad areas: (i) methods to gauge the state of financial instability or prospects of near-term systemic stress, (ii) measures to capture the build-up of systemic risk focused on country-level financial cycle measurement and early warning methods, and (iii) the ECB stress testing framework for macroprudential purposes. Managerial Overconfidence Assessment Model: An Emerging Market Context Nikravesh, Mehdi SSRN Managerial Overconfidence is an important behavioral bias in finance and accounting literature. Despite of wide-variety researches on the bias, there are challenges to assess overconfidence for researchers and other interested groups. By using a mixed approach including literature review, interviews with experts and Screening Fuzzy Delphi, The paper develops a model to assess the bias. The results show the managerial overconfidence assessment model has two dimensions called internal and external that both have three aspects including â€œbetter than average effectâ€, â€œoptimismâ€ and â€œillusion of controlâ€. Moreover, the results show the Delphi panelâ€™s experts believe overconfidence indices used by recent Iranian studies including over-investment and optimism management earnings forecasts proxies are not valid proxies to assess managerial overconfidence in Tehran Securities Exchange as an emerging market. The paperâ€™s developed model represents valid indices to assess managersâ€™ overconfidence can be used by the research findingsâ€™ users. Network Hypes and Asset Prices of Cryptocurrencies: Empirical Evidence Based on Google-Attention Approach Ling, Aifan,Zhu, Zhikai SSRN The rapid expansion of cryptocurrency market attracts us to think what factorsdrive the prices of cryptocurrencies. Using google attentions to measure the networkhype, this paper checks the effect of network hypes in the cryptocurrency market andfurther proposes a three-factor asset pricing model consisting of market factor, sizefactor and network hype factor. Empirical results show: (1) There is a positive andsignificant effect of network hype in cryptocurrency market and the network hype canplay an important role in rising prices of cryptocurrencies. (2) The average excessreturns of cryptocurrencies are negatively correlated with their sizes and have a sig-nificant positive correlation with the change of google attentions. (3) Our three-factormodel has a strong explanatory power for the excess returns of cryptocurrencies, andcan explain the momentum factor, reversal factor and liquidity factor in the cryptocur-rency market. On occupation times in the red of L\'evy risk models David Landriault,Bin Li,Mohamed Amine Lkabous arXiv In this paper, we obtain analytical expression for the distribution of the occupation time in the red (below level$0$) up to an (independent) exponential horizon for spectrally negative L\'{e}vy risk processes and refracted spectrally negative L\'{e}vy risk processes. This result improves the existing literature in which only the Laplace transforms are known. Due to the close connection between occupation time and many other quantities, we provide a few applications of our results including future drawdown, inverse occupation time, Parisian ruin with exponential delay, and the last time at running maximum. By a further Laplace inversion to our results, we obtain the distribution of the occupation time up to a finite time horizon for refracted Brownian motion risk process and refracted Cram\'{e}r-Lundberg risk model with exponential claims. Option pricing in bilateral Gamma stock models Uwe Küchler,Stefan Tappe arXiv In the framework of bilateral Gamma stock models we seek for adequate option pricing measures, which have an economic interpretation and allow numerical calculations of option prices. Our investigations encompass Esscher transforms, minimal entropy martingale measures,$p$-optimal martingale measures, bilateral Esscher transforms and the minimal martingale measure. We illustrate our theory by a numerical example. Poissonian occupation times of spectrally negative L\'evy processes with applications Mohamed Amine Lkabous arXiv In this paper, we introduce the concept of \emph{Poissonian occupation times} below level$0\$ of spectrally negative L\'evy processes. In this case, occupation time is accumulated only when the process is observed to be negative at arrival epochs of an independent Poisson process. Our results extend some well known continuously observed quantities involving occupation times of spectrally negative L\'evy processes. As an application, we establish a link between Poissonian occupation times and insurance risk models with Parisian implementation delays.

Prosumage of solar electricity: tariff design, capacity investments, and power system effects
Claudia Günther,Wolf-Peter Schill,Alexander Zerrahn
arXiv

We analyze how tariff design incentivizes households to invest in residential photovoltaic and battery systems, and explore selected power sector effects. To this end, we apply an open-source power system model featuring prosumage agents to German 2030 scenarios. Results show that lower feed-in tariffs substantially reduce investments in photovoltaics, yet optimal battery sizing and self-generation are relatively robust. With increasing fixed parts of retail tariffs, optimal battery capacities and self-generation are smaller, and households contribute more to non-energy power sector costs. When choosing tariff designs, policy makers should not aim to (dis-)incentivize prosumage as such, but balance effects on renewable capacity expansion and system cost contribution.

Protecting the Downside of Trend When It's Not Your Friend
Yang, Kun,Qian, Edward E.,Belton, Bryan
SSRN
Simple trend-following strategies have been documented as cost-effective, transparent alternatives to the hedge-fund style Managed Futures strategies. While largely capturing the returns of the Managed Futures industry, those simple strategies may periodically suffer significant losses due to over-simplified trend signals and under-diversified portfolio construction. In this article, the authors show that trend-following strategies with moderate sophistication and better diversification can significantly reduce the downside risk of simple trend-following strategies without sacrificing much upside potential. The authors therefore recommend investors who seek the benefits of cost-effective trend-following strategies to consider adding reasonable complexity to the strategies.

Regulation, Financial Crises, and Liberalization Traps
Marchionne, Francesco,Pisicoli, Beniamino,Fratianni, Michele U.
SSRN
To reconcile the mixed empirical results, we develop a theoretical model whose main implication is a concave impact of regulation on the probability of a crisis. We test this relationship by applying a Probit model of a non-linear specification to annual data from 1999 to 2011 drawn from 132 countries. The probability of a financial crisis fits an inverted U-shaped curve: it rises as regulation stringency moves from low to medium levels and falls from medium to high levels. Countries located at the intermediate level of regulatory stringency face more instability than countries that are either loosely or severely regulated. We identify the latter two groups as falling in "liberalization traps" Institutional quality interacts significantly with the regulatory environment.

Risk Factor Disclosures and Stock Price Crash Risk
Li, Leye,Peng, Zihang Ryan
SSRN
This paper studies the association between a firmâ€™s risk factor disclosures (RFDs) and its future stock price crash risk. By analyzing a stylized model that features short-selling constraints and investors with differential information processing abilities, we show that the amount of information disclosed in RFDs increases the divergence of opinion among investors, leading to higher crash risk. Consistent with this prediction, we empirically document that the length of a firmâ€™s RFD is positively associated with its future crash risk, and this association is more pronounced for RFDs of higher informativeness and RFDs with more emphasis on firm-specific risk topics. We further find that short selling trading constraints and information uncertainty that adds to arbitrage risk aggravate this positive relation. Overall, our findings suggest that in the presence of differential investorsâ€™ information processing abilities and short-selling constraints, mandating more downside disclosure alone cannot pre-empt stock price crash risk.

Sales Compensation and Recommendations As the Fund of the Month
Oh, Yoonhae
SSRN
This study analyzes whether mutual fund distributors are more likely to recommend products with higher sales compensation to maximize their profit. The lists of the â€˜fund of the monthâ€™ on their webpages are utilized from April of 2015 to August of 2015. A simple comparative analysis shows that the average sales fees and the average front-end load are significantly higher in the recommended funds among the A share class of domestic equity funds. The results of a regression analysis confirm that funds with high sales compensation levels are more likely to be recommended. This holds true for both domestic equity funds and hybrid bond funds even after controlling for fund age, fund size, and past returns.

Semi-Parametric Hierarchical Bayes Estimates of New Yorkers' Willingness to Pay for Features of Shared Automated Vehicle Services
Rico Krueger,Taha H. Rashidi,Akshay Vij
arXiv

In this paper, we contrast parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian multinomial logit models and leverage these methods to infer distributions of willingness to pay for features of shared automated vehicle (SAV) services. Specifically, we compare the multivariate normal (MVN), finite mixture of normals (F-MON) and Dirichlet process mixture of normals (DP-MON) mixing distributions. The latter promises to be particularly flexible in respect to the shapes it can assume and unlike other semi-parametric approaches does not require that its complexity is fixed prior to estimation. However, its properties relative to simpler mixing distributions are not well understood. In this paper, we evaluate the performance of the MVN, F-MON and DP-MON mixing distributions using simulated data and real data sourced from a stated choice study on preferences for SAV services in New York City. Our analysis shows that the DP-MON mixing distribution provides superior fit to the data and performs at least as well as the competing methods at out-of-sample prediction. The DP-MON mixing distribution also offers substantive behavioural insights into the adoption of SAVs. We find that preferences for in-vehicle travel time by SAV with ride-splitting are strongly polarised. Whereas one third of the sample is willing to pay between 10 and 80 USD/h to avoid sharing a vehicle with strangers, the remainder of the sample is either indifferent to ride-splitting or even desires it. Moreover, we estimate that new technologies such as vehicle automation and electrification are relatively unimportant to travellers. This suggests that travellers may primarily derive indirect, rather than immediate benefits from these new technologies through increases in operational efficiency and lower operating costs.

Size matters for OTC market makers: viscosity approach and dimensionality reduction technique
Philippe Bergault,Olivier Guéant
arXiv

In most OTC markets, a small number of market makers provide liquidity to clients from the buy side. More precisely, they set prices at which they agree to buy and sell the assets they cover. Market makers face therefore an interesting optimization problem: they need to choose bid and ask prices for making money out of their bid-ask spread while mitigating the risk associated with holding inventory in a volatile market. Many market making models have been proposed in the academic literature, most of them dealing with single-asset market making whereas market makers are usually in charge of a long list of assets. The rare models tackling multi-asset market making suffer however from the curse of dimensionality when it comes to the numerical approximation of the optimal quotes. The goal of this paper is to propose a dimensionality reduction technique to address multi-asset market making with grid methods. Moreover, we generalize existing market making models by the addition of an important feature for OTC markets: the variability of transaction sizes and the possibility for the market maker to answer different prices to requests with different sizes.

Technical Appendix of: Stochastic Bounds for Portfolio Analysis
Anyfantaki, Sofia,Arvanitis, Stelios,Post, Thierry,Topaloglou, Nikolas
SSRN
This supplementary Technical Appendix contains formal proofs of the propositions which are stated in Anyfantaki, S., S. Arvanitis, S., Th. Post, Th. and N. Topaloglou, 2019, 'Stochastic Bounds for Portfolio Analysis', available at SSRN:https://ssrn.com/abstract=3181869 or http://dx.doi.org/10.2139/ssrn.3181869, together with additional results and references.

Term structure modeling for multiple curves with stochastic discontinuities
Claudio Fontana,Zorana Grbac,Sandrine Gümbel,Thorsten Schmidt
arXiv

The goal of the paper is twofold. On the one hand, we develop the first term structure framework which takes stochastic discontinuities explicitly into account. Stochastic discontinuities are a key feature in interest rate markets, as for example the jumps of the term structures in correspondence to monetary policy meetings of the ECB show. On the other hand, we provide a general analysis of multiple curve markets under minimal assumptions in an extended HJM framework. In this setting, we characterize absence of arbitrage by means of NAFLVR and provide a fundamental theorem of asset pricing for multiple curve markets. The approach with stochastic discontinuities permits to embed market models directly, thus unifying seemingly different modeling philosophies. We also develop a new tractable class of models, based on affine semimartingales, going beyond the classical requirement of stochastic continuity. Due to the generality of the setting, the existing approaches in the literature can be embedded as special cases.

The Decrease in Life Insurance Ownership: Implications for Financial Planning
Kim, Kyoung Tae,Mountain, Travis,Hanna, Sherman D.,Kim, Namhoon
SSRN
Based on our analyses of Survey of Consumer Finances datasets, the proportion of households owning a life insurance policy decreased from 72% in 1992 to 60% in 2016. We estimated logistic regressions on the likelihood of ownership of any, term, and cash value life insurance. We conclude that changes in household characteristics accounted for the decrease in term life insurance ownership, but not for the decreases in any and in cash value life insurance ownership. We also found a positive association between use of a financial planner and life insurance ownership. We discuss implications for financial planning.

Naftali Cohen,Tucker Balch,Manuela Veloso
arXiv

Financial companies continuously analyze the state of the markets to rethink and adjust their investment strategies. While the analysis is done on the digital form of data, decisions are often made based on graphical representations in white papers or presentation slides. In this study, we examine whether binary decisions are better to be decided based on the numeric or the visual representation of the same data. Using two data sets, a matrix of numerical data with spatial dependencies and financial data describing the state of the S&P index, we compare the results of supervised classification based on the original numerical representation and the visual transformation of the same data. We show that, for these data sets, the visual transformation results in higher predictability skill compared to the original form of the data. We suggest thinking of the visual representation of numeric data, effectively, as a combination of dimensional reduction and feature engineering techniques. In particular, if the visual layout encapsulates the full complexity of the data. In this view, thoughtful visual design can guard against overfitting, or introduce new features -- all of which benefit the learning process, and effectively lead to better recognition of meaningful patterns.

The Extended Friday the 13th Effect in the US Stock Returns
Dumitriu, Ramona,Stefanescu, Razvan
SSRN

The Use of Price-to-Revenue Ratios in Valuing Sports Franchises
Rascher, Daniel A.
SSRN
For reasons described, the use of Price-to-Revenue ratios is the generally accepted approach to valuing sports franchises.

Naftali Cohen,Tucker Balch,Manuela Veloso
arXiv

The art of systematic financial trading evolved with an array of approaches, ranging from simple strategies to complex algorithms all relying, primary, on aspects of time-series analysis. Recently, after visiting the trading floor of a leading financial institution, we noticed that traders always execute their trade orders while observing images of financial time-series on their screens. In this work, we built upon the success in image recognition and examine the value in transforming the traditional time-series analysis to that of image classification. We create a large sample of financial time-series images encoded as candlestick (Box and Whisker) charts and label the samples following three algebraically-defined binary trade strategies. Using the images, we train over a dozen machine-learning classification models and find that the algorithms are very efficient in recovering the complicated, multiscale label-generating rules when the data is represented visually. We suggest that the transformation of continuous numeric time-series classification problem to a vision problem is useful for recovering signals typical of technical analysis.

Who is Liable if a Public Cryptocurrency Protocol Fails?
Ã˜stbye, Peder
SSRN
Cryptocurrencies have entered the economy as alternative money, speculation objects, and utility tokens for digital platforms. Cryptocurrencies are based on cryptography-based asset disposals broadcasted peer-to-peer to be validated in a decentralized way according to consented protocols. In a public (permissionless) cryptocurrency, the protocol development itself is also decentralized. There several risks associated with the protocols, which may eventually result in the failure of a cryptocurrency. The question is who, if anyone, can be held liable for such a failure. Such liability is important for both victim compensation as well as the promotion of robust protocols. Protocol developers are obvious candidates to be held liable for the failure of a cryptocurrency protocol. Participants at the network level, such as validators, may also be candidates to be held liable for certain failures, especially those intentionally caused by such participants by abusing the features of a protocol. Finally, for some failures, participants in the wider ecosystem, such as trading platforms and wallet providers, are candidates to be held liable if a public cryptocurrency protocol fails.

Yield Uncertainty and Strategic Formation of Supply Chain Networks
Victor Amelkin,Rakesh Vohra
arXiv

How does supply uncertainty affect the structure of supply chain networks? To answer this question we consider a setting where retailers and suppliers must establish a costly relationship with each other prior to engaging in trade. Suppliers, with uncertain yield, announce wholesale prices, while retailers must decide which suppliers to link to based on their wholesale prices. Subsequently, retailers compete with each other in Cournot fashion to sell the acquired supply to consumers. We find that in equilibrium retailers concentrate their links among too few suppliers, i.e., there is insufficient diversification of the supply base. We find that either reduction of supply variance or increase of mean supply, increases a supplier's profit. However, these two ways of improving service have qualitatively different effects on welfare: improvement of the expected supply by a supplier makes everyone better off, whereas improvement of supply variance lowers consumer surplus.