# Research articles for the 2020-09-02

#Fail: Social Media, Firm Distress, and Going Concern Opinions
Condie, Eric,Moon, James
SSRN
Research identifies a number of settings in which the opinions of social media users reflect information useful to capital market participants, including investors and analysts. We extend this research by examining whether social media could be useful for auditors. Specifically, we investigate whether the opinions of users on the social media platform StockTwits are useful for evaluating firms in financial distress. We find that social media sentiment, measured using message bearishness and probability of failure derived from a machine-learning algorithm, relates positively to both the likelihood of firm failure and the likelihood a firmâ€™s auditor issues a going-concern opinion. However, we find minimal evidence that the presence of a going-concern opinion mediates the association between social media sentiment and failure, suggesting auditors do not fully incorporate this publicly available information. We also provide evidence that naÃ¯ve consideration of social media sentiment reduces Type II errors at a faster rate than the corresponding increase in Type I errors. Our evidence should be informative to regulators and audit firms, both of whom are currently evaluating how the proliferation of data on social media can be useful to auditors.

A Critical Review on Investorâ€™s Awareness and Perceptions of Mutual Fund Investments
Venkatesan, Ranganathan
SSRN
Mutual fund is a collective investment scheme. This scheme is professionally managed by financial executives. The aim of the present study is measure the level of awareness investorâ€™s towards mutual funds. The next objective is analyzing the factors influencing the mutual fund investment decision. The present research instrument is developed through literature review, some investorâ€™s opinion and other secondary data sources. The snowball sampling procedure was followed to select the sample. The sample size of the present study is 127. The data collected from the respondents residing at Tiruvannamalai District. The collected data were analyzed using the software excel and SPSS. The result of the present study is used to various investment offer firms like banks, financial institutions and investors.

A New Approach to Estimating Loss-Given-Default Distribution
Masahiko Egami,Rusudan Kevkhishvili
arXiv

We propose a new approach to estimating the loss-given-default distribution. More precisely, we obtain the default-time distribution of the leverage ratio (defined as the ratio of a firm's assets over its debt) by examining its last passage time to a certain level. In fact, the use of the last passage time is particularly relevant because it is not a stopping time: this corresponds to the fact that the timing and extent of severe firm-value deterioration, when default approaching, is neither observed nor easily estimated. We calibrate the model parameters to the credit market, so that we can illustrate the loss-given-default distribution implied in the quoted CDS spreads.

A Stochastic Control Approach to Defined Contribution Plan Decumulation: 'The Nastiest, Hardest Problem in Finance'
Forsyth, Peter
SSRN
We pose the decumulation strategy for a Defined Contribution (DC) pension plan as a problem in optimal stochastic control. The controls are the withdrawal amounts and the asset allocation strategy. We impose maximum and minimum constraints on the withdrawal amounts, and impose no-shorting no-leverage constraints on the asset allocation strategy. Our objective function measures reward as the expected total withdrawals over the decumulation horizon, and risk is measured by Expected Shortfall (ES) at the end of the decumulation period. We solve the stochastic control problem numerically, based on a parametric model of market stochastic processes. We find that, compared to a fixed constant withdrawal strategy, with minimum withdrawal set to the constant withdrawal amount, the optimal strategy has a significantly higher expected average withdrawal, at the cost of a very small increase in ES risk. Tests on bootstrapped resampled historical market data indicate that this strategy is robust to parametric model mis-specification.

Adaptive Market Hypothesis: Evidence From Three Centuries of UK Data
SSRN
We examine the evolving efficiency of UK stock market and currency (British Pound) during the last three centuries. Using both Automatic Variance Ratio (AVR) and Automatic Portmanteau (AQ) tests, we find evidence of time-varying degree of efficiency which supports the Adaptive Markets Hypothesis (AMH).

An approximate solution for options market-making in high dimension
Bastien Baldacci,Joffrey Derchu,Iuliia Manziuk
arXiv

Managing a book of options on several underlying involves controlling positions of several thousands of financial assets. It is one of the most challenging financial problems involving both pricing and microstructural modeling. An options market maker has to manage both long- and short-dated options having very different dynamics. In particular, short-dated options inventories cannot be managed as a part of an aggregated inventory, which prevents the use of dimensionality reduction techniques such as a factorial approach or first-order Greeks approximation. In this paper, we show that a simple analytical approximation of the solution of the market maker's problem provides significantly higher flexibility than the existing algorithms designing options market making strategies.

Back-testing Expected Shortfall: Evidence From European Securitized Real Estate
SSRN
Events such as the European sovereign debt crisis, terrorism and Brexit cause more uncertainty and volatility in capital markets. This encourages us to use both conditional and unconditional forecasts (back-tests) for expected shortfall (ES) in 8 indices of listed European real estate securities and Real estate investment trusts (REITs). Using the method proposed by Du and Escanciano, we find that ES is generally superior to Value-at-Risk in describing and capturing risk during extreme events such as the financial crisis. Our results are important to regulators, risk managers and investors.

Finance, Inequality and Inclusive Education in Sub-Saharan Africa
Asongu, Simplice,Nnanna, Joseph,Acha-Anyi, Paul N.
SSRN
This research complements the extant literature by establishing inequality critical masses that should not be exceeded in order for financial access to promote gender parity inclusive education in Sub-Saharan Africa. The focus is on 42 countries in the sub-region and the data is for the period 2004-2014. The estimation approach is the Generalized Method of Moments. When remittances are involved in the conditioning information set, the Palma ratio should not exceed 6.000 in order for financial access to promote gender parity inclusive â€œprimary and secondary educationâ€ and the Atkinson index should not exceed 0.695 in order for financial access to promote inclusive tertiary education. However, when the internet is involved in the conditioning information set, it is established that in order for financial access to promote inclusive primary and secondary education, the: (i) Gini coefficient should not exceed 0.571; (ii) Atkinson index should not be above 0.750 and (iii) Palma ratio should be maintained below 8.000. Irrespective of variable in the conditioning information set, what is apparent is that inequality decreases the incidence of financial access on inclusive education. Hence, a common policy measure is to reduce inequality in order to promote inclusive education using the financial access mechanism. Policy implications are discussed in the light of Sustainable Development Goals.

Friends Donâ€™t Lie: Monitoring and Communication With Risky Investments
Banerjee, Snehal,Szydlowski, Martin
SSRN
Venture capital (VC) investors have been criticized for lax monitoring and for being too â€œfounder-friendly.â€ We identify an overlooked benefit of such behavior: entrepreneurs lie less to friendly VCs. The entrepreneur is privately informed about project success, enjoys private benefits of control, and recommends a project to the VC. The VC chooses the project and can intervene in the interim. The equilibrium features a â€œmonitoring trapâ€: possible intervention leads the entrepreneur to lie, which prompts further intervention. However, both are better off if the VC commits to intervene less. We characterize implications for information acquisition, control rights, and staged financing.

Infinite horizon utility maximisation from inter-temporal wealth
Michael Monoyios
arXiv

We develop a duality theory for the problem of maximising expected lifetime utility from inter-temporal wealth over an infinite horizon, under the minimal no-arbitrage assumption of No Unbounded Profit with Bounded Risk (NUPBR). We use only deflators, with no arguments involving equivalent martingale measures, so do not require the stronger condition of No Free Lunch with Vanishing Risk (NFLVR). Our formalism also works without alteration for the finite horizon version of the problem. As well as extending work of Bouchard and Pham to any horizon and to a weaker no-arbitrage setting, we obtain a stronger duality statement, because we do not assume by definition that the dual domain is the polar set of the primal space. Instead, we adopt a method akin to that used for inter-temporal consumption problems, developing a supermartingale property of the deflated wealth and its path that yields an infinite horizon budget constraint and serves to define the correct dual variables. The structure of our dual space allows us to show that it is convex, without forcing this property by assumption. We proceed to enlarge the primal and dual domains to confer solidity to them, and use supermartingale convergence results which exploit Fatou convergence, to establish that the enlarged dual domain is the bipolar of the original dual space. The resulting duality theorem shows that all the classical tenets of convex duality hold. Moreover, at the optimum, the deflated wealth process is a potential converging to zero. We work out examples, including a case with a stock whose market price of risk is a three-dimensional Bessel process, so satisfying NUPBR but not NFLVR.

Issues in the Use of the Balance Sheet Tool
Carlson, Mark A.,D'Amico, Stefania,Fuentes-Albero, Cristina,Schlusche, Bernd,Wood, Paul R.
SSRN
This paper considers various ways of using balance sheet policy (BSP) to provide monetary policy stimulus, including the BSPs put in place by the Federal Reserve in the wake of the Global Financial Crisis, the choice between fixed-size and flow-based asset purchase programs, policies targeting interest rate levels rather than the quantity of asset purchases, and programs aimed at increasing more direct lending to households and firms. For each of these BSP options, we evaluate benefits and costs. We conclude by observing that BSPsâ€™ relative effectiveness and thus optimal configuration will depend on the shocks affecting the economy. Consequently, it would be valuable for the Federal Reserve to keep a variety of tools at its disposal and employ the ones that best fit the situation that it faces.

Joint and Survivor Annuity Valuation with a Bivariate Reinforced Urn Process
Souto Arias, Luis,Cirillo, Pasquale
SSRN
Using a Bi-variate Reinforced Urn Process (B-RUP), a novel way of modeling the dependence of coupled lifetimes is introduced, with application to the pricing of joint and survivor annuities. In line with the machine learning paradigm, the model is able to improve its performances over time, but it also allows for the use of a priori information, like for example expertsâ€™ judgement, to complement the empirical data. Using a well-known Canadian data set, the performances of the B-RUP are studied and compared with the existing literature.

Market Impact in a Latent Order Book
arXiv

The latent order book of \cite{donier2015fully} is one of the most promising agent-based models for market impact. This work extends the minimal model by allowing agents to exhibit mean-reversion, a commonly observed pattern in real markets. This modification leads to new order book dynamics, which we explicitly study and analyze. Underlying our analysis is a mean-field assumption that views the order book through its \textit{average} density. We show how price impact develops in this new model, providing a flexible family of solutions that can potentially improve calibration to real data. While no closed-form solution is provided, we complement our theoretical investigation with extensive numerical results, including a simulation scheme for the entire order book.

Market Timing in Precious Metals Is Detrimental to Value Creation
SSRN
Few number of days accounts for most of the returns delivered by precious metals (gold, silver, platinum and palladium). A passive buy and hold investment strategy in precious metals outperforms market timers who miss the best 5, 10 and 50 days by 51%, 71% and 98%, respectively. Likewise, long-term performance of precious metals is largely determined by the return of few outliers (black swans). Thus, investors should reconsider trying to predict when to be in and out of the precious metals markets and support investing in precious metals ETFs.

Monetary Policy Strategies and Tools: Financial Stability Considerations
Goldberg, Jonathan E.,Klee, Elizabeth,Prescott, Edward S.,Wood, Paul R.
SSRN
This paper examines potential interactions between financial stability and the monetary policy strategies and tools considered in the Federal Reserveâ€™s review of monetary policy strategy, tools, and communication practices. Achieving the Federal Reserveâ€™s goals of full employment and price stability promotes financial stability. A key concern, however, is that with a low equilibrium real interest rate, a low policy rate will be necessary, and in turn, these low rates may contribute to an increase in financial system vulnerabilities. Our analysis suggests that there are typically significant macroeconomic and financial stability benefits of using these tools and strategies, but there are plausible situations in which financial vulnerabilities are such that it would be desirable to limit their use. A clear communications strategy can help minimize financial vulnerabilities. Should vulnerabilities arise, they are often best addressed with macroprudential tools.

Neural Networks Predictive Modeling for Football Betting
Sibony, John,Tlemsani, Abdelfatah,Hamchi, Youssef ,Gjergji, Monika,Shurmanov, Evgueny,Frunza, Marius
SSRN
The aim of this paper is to explore neural network-based modelling strategies for football betting. A neural network model and a challenger model based on a traditional econometric approach introduced by Dixon were estimated on data from five national leagues results including France, Spain, Italy, Germany, England) Our results show that the Neural network-based model has better predictive accuracy compared with the traditional econometric models. Betting strategies were implemented using prediction outputs generated with both econometric and neural networks models. The latter provides with a better return over investment. Nevertheless, both approaches lead to losses in the long run.

One-factor Hull-White Model Calibration for CVA - Part I: Instrument Selection With a Kink
Puetter, Christoph M,Renzitti, Stefano
SSRN
This paper is the first of a multi-part series on the calibration of the one-factor Hull-White short rate model for the purpose of computing CVAs (and xVAs) with an xVA system. It introduces an atypical bootstrapping scheme for the calibration of the short rate volatility. The second part focuses on the selection of the mean reversion parameter. In both expositions we present long-term time series results for EUR, JPY, and USD, covering the period from the beginning of 2009 (at the earliest) to spring 2020.

One-factor Hull-White Model Calibration for CVA - Part II: Optimizing the Mean Reversion Parameter
Puetter, Christoph M,Renzitti, Stefano
SSRN
This paper is the second of a multi-part series on the calibration of the one-factor Hull-White short rate model for the purpose of computing CVAs (and xVAs) with an xVA system. The first part introduces an atypical bootstrapping scheme for the calibration of the short rate volatility. The present second part focuses on the selection of the mean reversion parameter. In both expositions we present long-term time series results for EUR, JPY, and USD, covering the period from the beginning of 2009 (at the earliest) to spring 2020.

Pricing Efficiency of Bitcoin Trusts
SSRN
This article examines the pricing efficiency of Bitcoin Investment Trust. We investigate the deviation between prices and net asset values and find that there is a significant and persistent premium with an average of 44%. Such evidence points to pricing inefficiency of the currently available trust and encourages practitioners to introduce better instruments such as Exchange Traded Funds as alternatives to investors interested in having exposure to bitcoins and the digital currencies market.

Luis Escauriaza,Daniel C. Schwarz,Hao Xing
arXiv

Motivated by an equilibrium problem, we establish the existence of a solution for a family of Markovian backward stochastic differential equations with quadratic nonlinearity and discontinuity in $Z$. Using unique continuation and backward uniqueness, we show that the set of discontinuity has measure zero. In a continuous-time stochastic model of an endowment economy, we prove the existence of an incomplete Radner equilibrium with nondegenerate endogenous volatility.

Speculative Bubbles and Irrational Exuberance in African Stock Markets
SSRN
We apply the sequential unit root tests of Phillips et al. (2015) for mildly explosive processes to identify and date-stamp bubbles in the emerging and frontier African stock markets. We find periods of explosive behavior in the priceâ€"dividend ratio in several markets which is indicative of irrational exuberance. We find strong evidence of multiple speculative bubbles in Botswana, Egypt, Ghana, Kenya, Nigeria and Tunisia. Results of our study are important to individual investors, emerging markets fund managers, and policy makers.

Structured Products II: Insurance-Linked Products and Hybrid Securities
Garay, Urbi
SSRN
Many structured products are relatively new and their participation in institutional portfolios is expected to continue to grow in the future. The first part of the chapter explores insurance-linked securities (ILS), a relatively new asset class, where we discuss catastrophe bonds and longevity risk related products.The second part of the chapter discusses ways to invest in insurance risk. The important concept of mortality risk is analyzed, and the mechanics and investment attributes of life insurance settlements are discussed. Finally, the third part of the chapter covers mezzanine finance products. Here we discuss the following investment vehicles available to access mezzanine finance: subordinated debt with step-up rates, subordinated debt with PIK interest, subordinated debt with profit participation, subordinated debt with warrants, and convertible loans. We also comment on the use of these hybrid securities in project finance.

Syncing Innovation to Avoid Sinking: Supplier Response to Customer Covenant Violations
Selvam, Srinivasan,Tan, Kelvin Jui Keng
SSRN
When customers face financing frictions, they are incentivized to retain suppliers through nonmonetary incentives, such as by sharing technology with suppliers, thereby fostering supplier innovation. Using customer-supplier pairs in the U.S., we find that suppliers of customers that violate covenants become more innovative, specialize in narrow areas, and exhibit greater tendencies to cite and coordinate with customer innovation. Additionally, supplier innovation increases more when suppliers have greater financing flexibility, customers are highly specialized, and both trading partners are more trustworthy. Such innovation positively influences customer relationships, supplier performance, and supplier-firm survival. Overall, our findings illustrate nonmonetary channels that motivate relationship-specific investments.

The Shift from Active to Passive Investing: Risks to Financial Stability?
Anadu, Kenechukwu,Kruttli, Mathias S.,McCabe, Patrick E.,Osambela, Emilio
SSRN
The past couple of decades have seen a significant shift from active to passive investment strategies. We examine how this shift affects financial stability through its impacts on: (i) fundsâ€™ liquidity and redemption risks, (ii) asset-market volatility, (iii) asset-management industry concentration, and (iv) comovement of asset returns and liquidity. Overall, the shift appears to be increasing some risks and reducing others. Some passive strategies amplify market volatility, and the shift has increased industry concentration, but it has diminished some liquidity and redemption risks. Finally, evidence is mixed on the links between indexing and comovement of asset returns and liquidity.

Trends, Reversion, and Critical Phenomena in Financial Markets
Christof Schmidhuber
arXiv

Financial markets across all asset classes are known to exhibit trends. These trends have been exploited by traders for decades. Here, we empirically measure when trends revert, based on 30 years of daily futures prices for equity indices, interest rates, currencies and commodities. We find that trends tend to revert once they reach a critical level of statistical significance. Based on polynomial regression, we carefully measure this critical level. We find that it is universal across asset classes and has a universal scaling behavior, as the trend's time horizon runs from a few days to several years. The corresponding regression coefficients are small, but statistically highly significant, as confirmed by bootstrapping and out-of-sample testing. Our results signal to investors when to exit a trend. They also reveal how markets have become more efficient over the decades. Moreover, they point towards a potential deep analogy between financial markets and critical phenomena: our analysis supports the conjecture that financial markets can be modeled as statistical mechanical ensembles of Buy/Sell orders near critical points. In this analogy, the trend strength plays the role of an order parameter, whose dynamcis is described by a Langevin equation.

Weak error rates for option pricing under the rough Bergomi model
Christian Bayer,Eric Joseph Hall,Raúl Tempone
arXiv

In quantitative finance, modeling the volatility structure of underlying assets is a key component in the pricing of options. Rough stochastic volatility models, such as the rough Bergomi model [Bayer, Friz, Gatheral, Quantitative Finance 16(6), 887-904, 2016], seek to fit observed market data based on the observation that the log-realized variance behaves like a fractional Brownian motion with small Hurst parameter, $H < 1/2$, over reasonable timescales. Both time series data of asset prices and option derived price data indicate that $H$ often takes values close to $0.1$ or smaller, i.e. rougher than Brownian Motion. This change greatly improves the fit to time series data of underlying asset prices as well as to option prices while maintaining parsimoniousness. However, the non-Markovian nature of the driving fractional Brownian motion in the rough Bergomi model poses severe challenges for theoretical and numerical analyses as well as for computational practice. While the explicit Euler method is known to converge to the solution of the rough Bergomi model, the strong rate of convergence is only $H$. We prove rate $H + 1/2$ for the weak convergence of the Euler method and, surprisingly, in the case of quadratic payoff functions we obtain rate one. Indeed, the problem of weak convergence for rough Bergomi is very subtle; we provide examples demonstrating that the rate of convergence for payoff functions well approximated by second-order polynomials, as weighted by the law of the fractional Brownian motion, may be hard to distinguish from rate one empirically. Our proof relies on Taylor expansions and an affine Markovian representation of the underlying and is further supported by numerical experiments.

What Matters for Organizing M&As Successfully?
Schmitz, Alexander,Sievers, Soenke
SSRN
How is merger and acquisition (M&A) success associated with firm internal M&A process organization? The literature so far acknowledges that un-observable internal firm characteristics are at least as important as observable firm- and deal-specific characteristics to explain M&A success. Thus, this paper directly asks M&A experts around the globe to shed more light on this important issue. We investigate three indices, capturing the degree of M&A:1) process standardization, 2) process duration, and 3) process attention. Next, we analyze the process participation among four organizational layers, i.e., the functional involvement of the:a) top management team, b) headquarter, c) business unit management, and d) business unit functions. We predict and find that all three indices are positively associated with M&A success, while process standardization and attention to deal strategy are of particular importance. Turning to the four organizational layers, a textured analysis shows that, for instance, target valuation should be performed by the headquarter functions, but not by the top management team nor the business unit. Overall, our findings are important to better understand unexplored M&A success drivers and provide directions for future research. Finally, our results might help practitioners to adjust their M&A process organization to further improve their M&A success.

When Does Board Diversity Benefit Shareholders? Strategic Deadlock as a Commitment to Monitor