# Research articles for the 2020-06-23

Are Characteristics Covariances or Characteristics?
Hornuf, Lars,Fieberg, Christian
SSRN
In this article, we shed more light on the covariances versus characteristics debate by investigating the explanatory power of the instrumented principal component analysis (IPCA), recently proposed by Kelly et al. (2019). They conclude that characteristics are covariances because there is no residual return predictability from characteristics above and beyond that in factor loadings. Our findings indicate that there is no residual return predictability from factor loadings above and beyond that in characteristics either. In particular, we find that stock returns are best explained by characteristics (characteristics are characteristics) and that a one-factor IPCA model is sufficient to explain stock risk (characteristics are covariances). We therefore conclude that characteristics are covariances or characteristics, depending on whether the goal is to explain stock returns or risk.

Bitcoin Returns and the Frequency of Daily Abnormal Returns
Caporale, Guglielmo Maria,Plastun, Oleksiy,Oliinyk, Viktor
SSRN
This paper investigates the relationship between Bitcoin returns and the frequency of daily abnormal returns over the period from June 2013 to February 2020 using a number of regression techniques and model specifications including standard OLS, weighted least squares (WLS), ARMA and ARMAX models, quantile regressions, Logit and Probit regressions, piecewise linear regressions and non-linear regressions. Both the in-sample and out-of-sample performance of the various models are compared by means of appropriate selection criteria and statistical tests. These suggest that on the whole the piecewise linear models are the best but in terms of forecasting accuracy they are outperformed by a model that combines the top five to produce â€œconsensusâ€ forecasts. The finding that there exist price patterns that can be exploited to predict future price movements and design profitable trading strategies is of interest both to academics (since it represents evidence against the EMH) and to practitioners (who can use this information for their investment decisions).

Compact Finite Difference Scheme with Hermite Interpolation for Pricing American Put Options Based on Regime Switching Model
Chinonso Nwankwo,Weizhong Dai,Ruihua Liu
arXiv

We consider a system of coupled free boundary problems for pricing American put options with regime-switching. To solve this system, we first employ the logarithmic transformation to map the free boundary for each regime to multi-fixed intervals and then eliminate the first-order derivative in the transformed model by taking derivatives to obtain a system of partial differential equations which we call the asset-delta-gamma-speed equations. As such, the fourth-order compact finite difference scheme can be used for solving this system. The influence of other asset, delta, gamma, and speed options in the present regime is estimated based on Hermite interpolations. Finally, the numerical method is tested with several examples. Our results show that the scheme provides an accurate solution that is fast in computation as compared with other existing numerical methods.

Controlling Shareholder Stock Pledge, Aggravated Expropriation and Corporate Acquisitions
Yan, Siyuan,Ling, Xiaoxu,Cheng, Louis T. W.
SSRN
This study examines the effect of controlling shareholder stock pledge on corporate acquisition decisions and associated performance. Using the sample of listed firms in China, we find that pledging firms, consistent with the aggravated expropriation hypothesis, initiate more takeovers, and further, acquisitions conducted by pledging firms obtain lower announcement returns. We address the endogenous concerns by using the instrumental variable and the difference in differences approaches. Moreover, our channel tests suggest that pledging acquirers overpay in the deals and are more likely to be involved in related party transactions. Cross-sectionally, we find that the relationship between the share pledge and returns is stronger for non-SOEs and firms with high-level free cash flow. Lastly, we find that pledging acquires under-perform in the long-run in terms of lower ROA and a greater likelihood of goodwill impairment. Overall, our findings indicate that controlling shareholders increasingly expropriate minority shareholdersâ€™ interest through self-serving corporate takeovers after the stock pledge.

Cross-Border Spillover Effects of Macroprudential Policies: A Conceptual Framework
SSRN
Due to the international dimension of the financial sector within the EU and beyond, domestically oriented macroprudential policies have the potential to create material cross-border spillover effects. This occasional paper provides a detailed overview of the academic and empirical literature on cross-border effects of macroprudential policies. It also summarises a stocktaking exercise, conducted by a task force of the ESCBâ€™s Financial Stability Committee (FSC), on existing national approaches within the EU for assessing and monitoring such cross-border spillover effects. The paper accompanies an FSC report presenting a framework to be used by macroprudential authorities when assessing cross-border spillover effects induced by enacted or planned policy measures.

Deep Learning for Portfolio Optimisation
Zhang, Zihao,Zohren, Stefan,Roberts, Stephen
SSRN
We adopt deep learning models to directly optimize the portfolio Sharpe ratio. The framework we present circumvents the requirements for forecasting expected returns and allows us to directly optimize portfolio weights by updating model parameters. Instead of selecting individual assets, we trade Exchange-Traded Funds (ETFs) of market indices to form a portfolio. Indices of different asset classes show robust correlations and trading them substantially reduces the spectrum of available assets to choose from. We compare our method with a wide range of algorithms with results showing that our model obtains the best performance over the testing period, from 2011 to the end of April 2020, including the financial instabilities of the first quarter of 2020. A sensitivity analysis is included to understand the relevance of input features and we further study the performance of our approach under different cost rates and different risk levels via volatility scaling.

Development of the Model for the Creditworthiness Analysis in Russian Metallurgy
Doroshevskiy, Dmitry,Markovskaya, Elizaveta
SSRN
To minimize credit risks, banks must first analyze the financial condition of a potential borrower and evaluate their creditworthiness. The technique used for this purposes should be comprehensive, accurate and reliable. However, criticism of existing approaches to assessing creditworthiness is often associated with their lack of flexibility and absence of industry-specific approach.The metallurgical industry is very important for the Russian economy. Many organizations operating in related industries consume the metallurgical production, and the products themselves have a significant share in national exports. Russian metallurgical organizations are leaders not only in the domestic, but also in the global market.The concepts of credit risk, insolvency and creditworthiness were studied. The milestones of assessing the creditworthiness of organizations were considered, the evolution of approaches to valuation was presented during the second half of the last century and to the present moment. A brief overview of existing banking practices is provided.The financial performance of Russian metallurgic enterprises were analyzed. Particular attention is paid to the review of industry leaders as examples of the most sustainable organizations. Based on the reporting data, the characteristics of financial indicators and capital structure inherent in the industry were identified.The process of creating the methodology for assessing creditworthiness, which would take into account the characteristics of metallurgical organizations, is presented. A compilation of financial ratios for analysis was selected, the probability of bankruptcy was estimated for each company in the sample. Based on panel data on 35 companies for 2014-2018, through using a logistic regression, a scoring model was built to assess the creditworthiness of metallurgical organizations.The result of the work was an express methodology that allows to assess the creditworthiness of a metallurgical organization quickly and transparently, and at the same time, with sufficient accuracy, taking into account industry specifics.

Do Firms Adjust Corporate Governance in Response to Economic Policy Uncertainty? Evidence From Board Size
Ongsakul, Viput,Treepongkaruna, Sirimon,Jiraporn, Pornsit,Uyar, Ali
SSRN
Prior research shows that board size has a significant effect on firm performance. Therefore, board size is a crucial aspect of the board of directors. We investigate how firms adjust board size in response to economic policy uncertainty (EPU). We find that firms reduce board size in the presence of EPU. In particular, a rise in EPU by one standard deviation reduces board size by 21.61% on average. Our results are consistent with the notion that agency conflicts are more severe in the presence of EPU. Accordingly, firms strengthen their corporate governance by reducing board size.

Agrawal, Anup,Lim, Yuree
SSRN
We examine whether Title II of the JOBS Act increases small firmsâ€™ access to capital. Title II allows firms to sell securities via general solicitations to accredited investors. We find that firms that offer securities via general solicitation tend to be of lower quality. After accounting for selection, we find that general solicitation offerings are less likely to succeed, and they raise lower amounts of capital than other offerings. Moreover, general solicitation offerings incur substantial brokerage costs to verify that investors are accredited under the Act. Our results imply the need to craft policies that induce better ways of signaling firm quality or more transparent approaches to reducing information asymmetry.

Does Covered Interest Parity Hold in Long-Dated Securities?
SSRN
This paper investigates the validity of Covered Interest Rate Parity (CIP) in long-dated fixed income securities. I show that common measures of CIP in securities of longer maturities rely on trading strategies subject to rollover risk and credit risk, or fail to fully account for the trading costs. Hence, round-trip CIP profit is generally not possible to reap when the trade is risk-free and all costs are taken into account. In particular, short-selling costs (haircuts and lending fees) and differences in funding spreads across currencies allow for substantial deviations from CIP without implying arbitrage opportunities. In contrast to recent research, my results suggest that CIP holds well and lend little support to the view that stricter banking regulations have led to persistent arbitrage opportunities in long-dated fixed income and currency markets.

Domestic-Political Risk, Global Economic Policy Uncertainty, and Banksâ€™ Profitability: Evidence from Ukrainian Banks
Athari, Seyed Alireza
SSRN
This study specifically examines the effects of domestic-political risk and global economic policy uncertainty factors on the profitability of Ukrainian banks during the 2005-2015 period. The empirical results underscore that the domestic-political stability and global economic policy uncertainty have significant positive and negative effect on Ukrainian banks' profitability, respectively. Results suggest that a rise of Ukrainian banksâ€™ profitability depends significantly on decreasing domestic-political and global risk levels. Likewise, the results of traditional determinants indicate that the profitability of Ukrainian banks is shaped by the bank and industry-specific determinants. The results are robust and consistent when alternative model specifications are conducted. The findings of this study have important policy implications for policymakers, banks' managers, and analysts.

Examining the Relationships between Land Values and Credit Availability
Sant' Anna, Ana Claudia,Cowley, Cortney,Katchova, Ani
SSRN
Given the changes made to the agricultural lending system since the 1980s farm crisis, we investigate the current effects of credit availability on land values. Using data from Federal Reserve Agricultural Credit Surveys, we measure credit availability and perform county-level panel fixed effects estimations controlling for land value determinants, credit availability factors, and county and macroeconomic factors. We build an indicator of increased credit availability and find that estimating farmland values with different factors of credit availability separately could mask combined effects. When conditions for credit availability increase or remain unchanged from the previous year, land values may increase by up to 25%. While higher credit availability may facilitate land acquisition, it can also put upward pressure on land values.

Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincar\'e Embeddings
Lucia Larise Stavarache,Donatas Narbutis,Toyotaro Suzumura,Ray Harishankar,Augustas Žaltauskas
arXiv

In the recent years money laundering schemes have grown in complexity and speed of realization, affecting financial institutions and millions of customers globally. Strengthened privacy policies, along with in-country regulations, make it hard for banks to inner- and cross-share, and report suspicious activities for the AML (Anti-Money Laundering) measures. Existing topologies and models for AML analysis and information sharing are subject to major limitations, such as compliance with regulatory constraints, extended infrastructure to run high-computation algorithms, data quality and span, proving cumbersome and costly to execute, federate, and interpret. This paper proposes a new topology for exploring multi-banking customer social relations in AML context -- customer-to-customer, customer-to-transaction, and transaction-to-transaction -- using a 3D modeling topological algebra formulated through Poincar\'e embeddings.

Financial Instruments Entail Liabilities: Ether, Bitcoin, and Litecoin Do Not
Callens, Evariest
SSRN
The financial assets that are subject to major European financial legislation (i.e. (designated types of) financial instruments) have traditionally been defined in a largely exemplary and circular manner. The recent proliferation of â€˜non-traditionalâ€™ financial assets, such as cryptocurrencies and stablecoins, is increasingly challenging the viability of these pragmatic financial asset definitions. Through the analysis of the technologies and functionalities underpinning non-traditional financial assets, legal scholarship has aimed to categorize novel assets within the existing framework of financial asset definitions. Although a solid understanding of e.g. distributed ledger applications and cryptography appears a prerequisite for future policy and legislative interventions, contemporary European financial legislation is mostly indifferent to the technologies on which financial assets may be wired. Categorizations based on the purposes that non-traditional assets may serve (i.e. payment, utility, and investment) are more relevant to financial law, but suffer from subjectivity because they depend on the asset usage by the asset holder. Against this backdrop, this paper proposes a novel systematization of non-traditional assets that is based upon the conceptual substructure of the assets within scope of European financial legislation. More specifically, this paper submits that, irrespective of underlying technologies and functionalities, all assets that are subject to major European financial legislation have a conceptual common denominator: they entail the liability of an entity and, hence, have intrinsic value. The proposed categorization singles out a well-defined group of novel financial assets that is not subject to European financial law (i.e. assets that only have extrinsic value). Different from functionality- and technology-based categorizations, the suggested approach allows to eradicate ambiguities and potential overinclusiveness of functionality-based categorizations of non-traditional assets. By exploring the conceptual common denominator of the financial assets that are subject to European financial legislation, this paper aims to foster debate on the circular and exemplary character of financial asset definitions in European financial legislation in general and the relation of these definitions to novel types of financial assets in particular.

Forecast Disagreement about Long-run Macroeconomic Relationships
Kuang, Pei,Tang, Li,Zhang, Renbin,Zhang, Tongbin
SSRN
Using survey forecast data, we study if professional forecasters utilize long-run co-integration relationships among macroeconomic variables to forecast future as postulated in workhorse stochastic growth models. There exists a significant heterogeneity among forecasters, the majority of whom do not use these long-run relationships and generally make more accurate forecasts (comparing with those who use). Simple parsimonious recursive forecasting models are fitted to the data as one way to approximate the expectation formation process of the forecasters who utilize (or do not utilize) the long-run relationships.

Goldilocks and the Three WACCs
Tham, Joseph
SSRN
This paper presents three different approaches for calculating the levered annual values for a finite cash flow profile. In the first approach, we use KU, the return to unlevered equity to calculate the annual tax savings and use KU to calculate the (present) value of the tax savings. In the second approach, we use KD, the cost of debt to calculate the annual tax savings and use KU to calculate the (present) value of the tax savings. In the third approach, we use KD, the cost of debt to calculate the annual tax savings and the (present) value of the tax savings.

Hedge Fund Activists: Value Creators or Good Stock Pickers?
Cremers, Martijn,Giambona, Erasmo,Sepe, Simone M.,Wang, Ye
SSRN
We show that hedge fund activism is associated with positive abnormal stock returns in both the short term and the long term. Using matching procedures to mitigate selection effects, we find that activistsâ€™ targets do not outperform ex ante similar control firms; this suggests that activists are good stock pickers, not value creators. Activists also exhibit strong timing skills, generally selling (buying) stocks in targeted firms during periods in which these stocks outperform (under-perform) and ahead of negative (positive) abnormal returns. These selection skills do not seem to benefit the buy-and-hold shareholders of the targeted firms.

Interest Received by Banks During the Financial Crisis: LIBOR vs Hypothetical SOFR Loans
Jermann, Urban J.
SSRN
The cumulative additional interest from LIBOR during the crisis is estimated to be between 1% to 2% of the notional amount of outstanding loans, depending on the tenor and type of SOFR rate used. The amount of LIBOR business loans owned by banks could have been as high as about 2trn, and the overall additional interest income banks received thanks to LIBOR could have been as high as 30bn dollars. The analysis also shows that a compounded SOFR reduces insurance relative to a term SOFR.

Is Blockholder Diversity Detrimental?
Schwartz-Ziv, Miriam,Volkova, Ekaterina
SSRN
We find, in three settings in which an exogenous event affects (the revelation of) block diversity, that block diversity is detrimental to firm performance: (1) Disclosure of an increase in block diversity around an exogenously predetermined date is followed by a negative market reaction; in contrast (2) an individualâ€™s death or retirement that leads to a decrease in block diversity is followed by an improvement in firm performance; and, similarly, (3) dissolution of blocks due to the 2003 mutual fund scandal that led to a decrease in block diversity was followed by an improvement in firm performance. We also show that firms held by a heterogeneous blockholder base consistently perform worse than firms held by a homogeneous blockholder base, as firms of the former type are more likely to be sued by shareholders and to experience disagreements at shareholder meetings.

Keeping Some Skin in the Game: How to Start a Capital Market in Longevity Risk Transfers
Biffis, Enrico,Blake, David P.
SSRN
The recent activity in pension buy-outs and bespoke longevity swaps suggests that a significant process of aggregation of longevity exposures is under way, led by major investment banks and buy-out firms with the support of leading reinsurers. As regulatory capital charges and limited reinsurance capacity constrain the scope for market growth, there is now an opportunity for institutions that are pooling longevity exposures to issue securities that appeal to capital market investors, thereby broadening the sharing of longevity risk and increasing market capacity. For this to happen, longevity exposures need to be suitably pooled and tranched to maximize diversification benefits offered to investors and to address asymmetric information issues. We argue that a natural way for longevity risk to be transferred is through suitably designed principal-at-risk bonds.

Low-Risk Effect: Evidence, Explanations and Approaches to Enhancing the Performance of Low-Risk Investment Strategies
Joshipura, Mayank,Joshipura, Nehal
SSRN
The authors offer evidence for low-risk effect from the Indian stock market using the top-500 liquid stocks listed on the National Stock Exchange (NSE) of India for the period from January 2004 to December 2018. Finance theory predicts a positive risk-return relationship. However, empirical studies show that low-risk stocks outperform high-risk stocks on a risk-adjusted basis, and it is called low-risk anomaly or low-risk effect. Persistence of such an anomaly is one of the biggest mysteries in modern finance. The authors find strong evidence in favor of a low-risk effect with a flat (negative) risk-return relationship based on the simple average (compounded) returns. It is documented that low-risk effect is independent of size, value, and momentum effects, and it is robust after controlling for variables like liquidity and ticket-size of stocks. It is further documented that low-risk effect is a combination of stock and sector level effects, and it cannot be captured fully by concentrated sector exposure. By integrating the momentum effect with the low-volatility effect, the performance of a low-risk investment strategy can be improved both in absolute and risk-adjusted terms. The paper contributed to the body of knowledge by offering evidence for: a) robustness of low-risk effect for liquidity and ticket-size of stocks and sector exposure, b) how one can benefit from combining momentum and low-volatility effects to create a long-only investment strategy that offers higher risk-adjusted and absolute returns than plain vanilla, long-only, low-risk investment strategy.

Lumpy Investment and Expected Stock Returns
Im, Hyun Joong,Park, Heungju
SSRN
This study investigates the predictability of stock market returns using a novel corporate investment measure that captures the lumpy characteristic of firm-level investment. We find that the proportion of firms with investment spikes ("spike") is a strong predictor of excess stock returns. Specifically, an increase in "spike" significantly lowers future excess stock returns. The predictability of "spike" is consistently observed in both in-sample and out-of-sample tests. Furthermore, "spike" shows strong predictability at a business cycle frequency, suggesting that the predictability of "spike" is driven by time-varying risk premium associated with business cycles rather than temporary mis-pricing.

Modelling Longevity Bonds: Analysing the Swiss Re Kortis Bond
Hunt, Andrew,Blake, David P.
SSRN
A key contribution to the development of the traded market for longevity risk was the issuance of the Kortis bond, the worldâ€™s first longevity trend bond, by Swiss Re in 2010. We analyse the design of the Kortis bond, develop suitable mortality models to analyse its payoff and discuss the key risk factors for the bond. We also investigate how the design of the Kortis bond can be adapted and extended to further develop the market for longevity risk.

Multi-population Mortality Projection: The Augmented Common Factor Model with Structural Breaks
WANG, PENGJIE,Pantelous, Athanasios A.,Vahid, Farshid
SSRN
Multi-population mortality forecasting has become an increasingly important area in actuarial science and demography, as a means to avoid long-run divergence in mortality projection. This paper aims to establish a unified state-space Bayesian framework to model, estimate and forecast mortality rates in a multi-population context. In this regard, we reformulate the augmented common factor model to account for structural breaks in the mortality indexes. Further, we conduct a Bayesian analysis to make inferences and generate forecasts so that process, parameter and model uncertainties can be considered simultaneously and appropriately. The square-root-form of the Kalman Filter is exploited to improve robustness when sampling latent states. We illustrate the efficiency of our methodology through two distinctive case studies. The first uses Australian two-gender mortality data. The second projects mortality for a list of selected Eurozone countries, where the hierarchical clustering approach on principal components is utilised to group countries with similar mortality characteristics together. Both point and probabilistic forecast evaluations are considered in the empirical analysis. The derived results support the fact that the incorporation of stochastic drifts mitigates the impact of the structural change in the time indexes on mortality projection.

New Risk Measure VAR Squared (VAR (2)) and its Calculation Part Ii: Case of the General Law of Allocation of Damages. Comparison of VAR (2) and Es
Minasyan, Vigen Babkenovich
SSRN
The work introduces the concept of a new risk measure VaR in a square (VaR(2)) and displays the formula for calculating it. It turns out that to calculate the VaR (2), it is sufficient to calculate a normal measure of risk VaR , with a certain changed confidence probability.The ratio of risk estimates by risk measures VaR(2) and ES was investigated.

New Stochastic Dominance Theory for Investors With Risk-Averse and Risk-Seeking Utilities With Applications Including Solutions for the Friedman-Savage Paradox and the Diversification Puzzle
Wong, Wing-Keung
SSRN
In this paper, we first state some well-known problems including the Friedman-Savage paradox raised by Friedman and Savage (1948) who wonder why individuals would like to buy insurance as well as buy lottery tickets. To provide solutions to the problems, we first use the idea from Fishburn and Kochenberger (1979), Thon and Thorlund-Petersen (1988), and Chew and Tan (2005) to use two-way stochastic dominance to define the $j$-order risk-averse and risk-seeking utility that consists of both risk-averse and risk-seeking components and we call the utility AD utility and call investors with AD utility AD investors. Thereafter, we develop a new stochastic dominance theory for AD investors and we call the theory ADSD theory. We then develop some properties for the ADSD theory, including properties of expected-utility maximization, hierarchy, transitivity, and diversification, and properties under the additional condition of equal mean so that we can use the theory to get the solutions for all the problems and hypotheses we set in this paper. Applying the ADSD theory, we first get a new solution for the Friedman-Savage paradox. In addition, we find that AD investors could invest in both completely diversified portfolio and individual assets and, in general, buy any pair of both less-risky and more-risky assets. For example, AD investors could invest in both bonds and stocks, both bonds and futures, and both stocks and futures to get higher expected utility.

Numerical aspects of integration in semi-closed option pricing formulas for stochastic volatility jump diffusion models
Josef Daněk,J. Pospíšil
arXiv

In mathematical finance, a process of calibrating stochastic volatility (SV) option pricing models to real market data involves a numerical calculation of integrals that depend on several model parameters. This optimization task consists of large number of integral evaluations with high precision and low computational time requirements. However, for some model parameters, many numerical quadrature algorithms fail to meet these requirements. We can observe an enormous increase in function evaluations, serious precision problems and a significant increase of computational time. In this paper we numerically analyse these problems and show that they are especially caused by inaccurately evaluated integrands. We propose a fast regime switching algorithm that tells if it is sufficient to evaluate the integrand in standard double arithmetic or if a higher precision arithmetic has to be used. We compare and recommend numerical quadratures for typical SV models and different parameter values, especially for problematic cases.

On the Disclosure of the Costs of Investment Management
Blake, David P.
SSRN
This paper argues that no good reasons have been put forward for why all the costs of investment management, both visible and hidden, should not ultimately be fully disclosed. They are after all genuine costs borne by the investor. Furthermore, recent studies have shown that hidden costs are at least as high as visible costs, if not much higher. Full transparency could be introduced in stages.

On the Inflation Risks Embedded in Sovereign Bond Yields
SSRN
The purpose of this paper is to study the compensation for inflation risks priced in sovereign bond yields. And we do so by modelling the time-varying dynamics of asset returns and inflation, and then estimating the cost of hedging inflation risks from the perspective of a well diversified portfolio. This allows to disentangle the time-varying compensation for expected and unexpected inflation shocks embedded in sovereign bond yields; and provides estimates of the real risk-free rate. We show that nominal sovereign bond yields for Germany, France, Japan and the United States, reflect, over the more recent years, a low real risk-free rate, as well as low levels of compensation for both expected and unexpected inflation. The simultaneous occurrence of these low contributions is novel, and not encountered previously in our sample. We also find that inflation risks are not necessarily reduced with the inclusion of real estate assets in the minimum variance portfolio. Our analysis also prompts us to suggest that the financial advantage of issuing inflation-linked sovereign debt, and namely saving on the embedded inflation risk premium of issuing nominal debt, appears to be eroded by the liquidity premium charged by investors for holding the less attractive inflation-linked debt asset.

Optimal Hedging in Incomplete Markets
George Bouzianis,Lane P. Hughston
arXiv

We consider the problem of optimal hedging in an incomplete market with an established pricing kernel. In such a market, prices are uniquely determined, but perfect hedges are usually not available. We work in the rather general setting of a L\'evy-Ito market, where assets are driven jointly by an $n$-dimensional Brownian motion and an independent Poisson random measure on an $n$-dimensional state space. Given a position in need of hedging and the instruments available as hedges, we demonstrate the existence of an optimal hedge portfolio, where optimality is defined by use of an expected least squared-error criterion over a specified time frame, and where the numeraire with respect to which the hedge is optimized is taken to be the benchmark process associated with the designated pricing kernel.

Optimal Risk-Taking in Corporate Defined Benefit Plans under Risk-Shifting
Kitamura, Tomoki,Omori, Kozo
SSRN
Purpose: The purpose of this paper is to theoretically examine the risk-taking decision of corporate defined benefits (DB) plans. The equity holdersâ€™ investment problem that is represented by the position of a vulnerable option is solved. Design/methodology/approach: The simple traditional contingent claim approach is applied, which considers only the distributions of corporate cash flow, without the model expansions, such as market imperfections, needed to explain the firmsâ€™ behavior for DB plans in previous studies. Findings: The authors find that the optimal solution to the equity holdersâ€™ DB investment problem is not an extreme corner solution such as 100 percent investment in equity funds as in the literature. Rather, the solution lies in the middle range, as is commonly observed in real-world economies.Originality/value: The major value of this study is that it develops a clear mechanism for obtaining an internal solution for the equity holdersâ€™ DB investment problem and it provides the understanding that the base for corporate investment behavior for DB plans should incorporate the fact that in some cases the optimal solution is in the middle range. Therefore, the corporate risk-taking behavior of DB plans is harder to identify than the results of the empirical literature have predicted.

Post-M&A Performance and Failure: Implications of Time Until Deal Completion
Thompson, Ephraim Kwashie,Kim, Changki
SSRN
Firm values change substantially between deal announcement and closing, risking renegotiation or termination. For deals that eventually close, does waiting longer to close benefit the acquirer post-M&A? We investigate whether the time that elapses until deal completion is an indicator of post-M&A performance and failure. We find that deals taking an optimum time to implement perform better, supporting the due diligence hypothesis, while taking too long to close is an indication of poor post-M&A performance and subsequent failure, supporting the overdue hypothesis.

Post-Merger and Acquisition Performance, Probability of Default and Delisting: An International Study
Thompson, Ephraim Kwashie,Kim, Changki
SSRN
After the completion of an M&A, a number of factors may affect the performance, probability of default and actual delisting of the acquirer. In this paper, we identify and investigate the factors which affect the performance and survival of the acquirer or newly merged firm after a deal is closed. We find that the volatility of the currency exchange rate between the two countries, the target countryâ€™s inflation rate volatility, stock method of payment, and different industries of the target and acquiring firms pose a risk of poor post-merger stock performance. In addition, the time until deal completion and differences in culture are associated with an increased probability of default after a deal is closed. Finally, we find that none of the variables significantly explains the likelihood of post-completion delisting.

ResTech: Innovative Technologies for Crisis Resolution
Loiacono, Giuseppe,Mazzullo, Alessandro,Rulli, Edoardo
SSRN
The increasing use of financial technologies (FinTech) by market participants fostered the discussion among public authorities on the use of similar technologies for regulatory (RegTech) and supervisory (SupTech) purposes. In a similar vein, innovative technologies could be applied in the context of financial firmsâ€™ crisis resolution. The resolution context is, however, peculiar: since resolution is not a profit-making activity, there is little market incentive for the private sector to foster innovation in this area. Therefore, resolution authorities may decide to drive the innovation by developing big data technologies and solutions to resolve financial crisis. This paper sets the definition of Resolution Technology (ResTech), and outlines its areas of application. ResTech is built on innovative technologies, which could support the work of resolution authorities in developing resolution plans and in resolving financial firms. Also, ResTech could guide firmsâ€™ compliance functions. This paper identifies four main areas of ResTech: resolution planning, resolution execution, cross-border exchange of information and automatised compliance for banks and financial firms. The adoption of big data architectures could transform resolution planning in a dynamic activity; in the same vein, machine learning algorithms could boost the application of existing resolution tools and support the determination of the resolution strategy. This paper concludes that the benefits of ResTech need to be measured against the increased risks taken by technology adopters. In a technology-driven environment, resilient IT infrastructures and e-governance processes are essential to prevent operational, reputational and legal risks.

Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
arXiv

We introduce a novel framework to account for sensitivity to rewards uncertainty in sequential decision-making problems. While risk-sensitive formulations for Markov decision processes studied so far focus on the distribution of the cumulative reward as a whole, we aim at learning policies sensitive to the uncertain/stochastic nature of the rewards, which has the advantage of being conceptually more meaningful in some cases. To this end, we present a new decomposition of the randomness contained in the cumulative reward based on the Doob decomposition of a stochastic process, and introduce a new conceptual tool - the \textit{chaotic variation} - which can rigorously be interpreted as the risk measure of the martingale component associated to the cumulative reward process. We innovate on the reinforcement learning side by incorporating this new risk-sensitive approach into model-free algorithms, both policy gradient and value function based, and illustrate its relevance on grid world and portfolio optimization problems.

Robo-Advice and the Future of Delegated Investment
Merkle, Christoph
SSRN
Robo-advisors can replace financial advisors and asset managers at low costs. However, human managers and advisors will survive for a number of reasons: First, robo-advisors primarily appeal to a clientele of already financially sophisticated investors, they lack some of the qualities people look for in a â€œmoney doctorâ€, and their business model still stands to the test of time. While a general algorithm aversion is absent in the financial domain, even tech-savvy millennials do not particularly favor robo-advisors. As new survey data shows, investors view algorithms as an aid to human managers rather than competitors. A hybrid model with humans and robos working together, as already implemented by some financial institutions, might be the future of delegated investment.

Kuang, Pei,Tang, Li
SSRN
The paper develops and estimates a stock pricing model with sentiment shocks to stock price forecasts and learning about stock prices by investors which replicates several survey evidence on stock price forecasts along with a standard set of asset pricing facts for the United States. A unique feature is that stock price forecasts in the model are not anchored by (or not co-integrated with) forecasts of fundamentals as in survey data. The model suggests about two-thirds of the fluctuations of stock price-dividend ratios are driven by shifting investorsâ€™ expectations as a result of the dynamic interaction between the sentiment shocks and investorsâ€™ learning.

Simplified Stochastic Calculus via Semimartingale Representations
ÄŒernÃ½, AleÅ¡,Ruf, Johannes
SSRN
We develop a stochastic calculus that makes it easy to capture a variety of predictable transformations of semimartingales such as changes of variables, stochastic integrals, and their compositions. The framework offers a unified treatment of real-valued and complex-valued semimartingales. The proposed calculus is a blueprint for the derivation of new relationships among stochastic processes with specific examples provided in the paper.

Simplified Stochastic Calculus: Multiplicative Compensators and Changes of Measure
ÄŒernÃ½, AleÅ¡,Ruf, Johannes
SSRN
The paper develops multiplicative compensation for complex-valued semimartingales and studies some of its consequences. It is shown that the stochastic exponential of any complex-valued semimartingale with independent increments becomes a true martingale after multiplicative compensation, where such compensation is meaningful. This generalization of the LÃ©vy-Khintchin formula fills an existing gap in the literature. We further report Girsanov-type results based on non-negative multiplicatively compensated semimartingales. In particular, we obtain a simplified expression for the multiplicative compensator under the new measure.

Simplified calculus for semimartingales: Multiplicative compensators and changes of measure
Aleš Černý,Johannes Ruf
arXiv

The paper develops multiplicative compensation for complex-valued semimartingales and studies some of its consequences. It is shown that the stochastic exponential of any complex-valued semimartingale with independent increments becomes a true martingale after multiplicative compensation, where such compensation is meaningful. This generalization of the L\'evy-Khintchin formula fills an existing gap in the literature. We further report Girsanov-type results based on non-negative multiplicatively compensated semimartingales. In particular, we obtain a simplified expression for the multiplicative compensator under the new measure.

Socially Responsible Hedge Funds
Liang, Hao,Sun, Lin,Teo, Melvyn
SSRN
Hedge funds whose management companies endorse the United Nations Principles for Responsible Investment (PRI) underperform other hedge funds after adjusting for risk but attract larger flows, harvest greater fee revenues, and accumulate more capital. Consonant with an agency explanation, the underperformance is driven by PRI signatories with low ESG exposures. By exploiting quasi-natural experiments, we provide causal evidence that relate agency problems to signatory underperformance. Low-ESG signatories that do not walk the talk trigger more regulatory, investment, and severe infractions, and report more suspicious returns. The results suggest that some signatories strategically embrace responsible investment to pander to investor preferences.

Solution of option pricing equations using orthogonal polynomial expansion
Falko Baustian,Kateřina Filipová,Jan Pospíšil
arXiv

In this paper we study both analytic and numerical solutions of option pricing equations using systems of orthogonal polynomials. Using a Galerkin-based method, we solve the parabolic partial diferential equation for the Black-Scholes model using Hermite polynomials and for the Heston model using Hermite and Laguerre polynomials. We compare obtained solutions to existing semi-closed pricing formulas. Special attention is paid to the solution of Heston model at the boundary with vanishing volatility.

Stock Picking with Machine Learning
Wolff, Dominik,Echterling, Fabian
SSRN
We combine insights from machine learning and finance research to build machine learning algorithms for stock selection. Our study builds on weekly data for the historical constituents of the S&P 500 over the period from 1999 to 2019 and includes typical equity factors as well as additional fundamental data, technical indicators, and historical returns. Deep Neural Networks (DNN), Long Short-Term Neural Networks (LSTM), Random Forest, Boosting, and Regularized Logistic Regression models are trained on stock characteristics to predict whether a specific stock outperforms the market over the subsequent week. We analyze a trading strategy that picks stocks with the highest probability predictions to outperform the market. Our empirical results show a substantial and significant outperformance of machine learning based stock selection models compared to a simple equally weighted benchmark. Moreover, we find non-linear machine learning models such as neural networks and tree-based models to outperform more simple regularized logistic regression approaches. The results are robust when applied to the STOXX Europe 600 as alternative asset universe. However, all analyzed machine learning strategies demonstrate a substantial portfolio turnover and transaction costs have to be marginal to capitalize on the strategies.

The Dollar and Corporate Borrowing Costs
Meisenzahl, Ralf,Niepmann, Friederike,Schmidt-Eisenlohr, Tim
SSRN
We show that U.S. dollar movements affect syndicated loan terms for U.S. borrowers, even for those without trade exposure. We identify the effect of dollar movements using spread and loan amount adjustments during the syndication process. Using this high-frequency, within loan variation, we find that a one standard deviation increase in the dollar index increases spreads by up to 15 basis points and reduces loan amounts and underpricing by up to 2 percent and 7 basis points, respectively. These effects are concentrated in dollar appreciations. Our results suggest that global factors reflected in the dollar determine U.S. borrowing costs.

The Real Lessons of the Global Banking Crisis
Blake, David P.
SSRN
This article examines the causes of the Global Banking Crisis (GBC) and finds a number of important issues that still need to be addressed, some of which have not been discussed in the previous major studies of the GBC. We offer solutions for dealing with these issues. These include: a proper definition of risk that clearly differentiates between idiosyncratic, systematic and systemic risks; proper measurement of risk; better corporate governance of risk appetite and risk profile in individual banks; better risk management capabilities within the banking system and a greater understanding of risk management by the regulator; a proper definition of capital, i.e., economic rather than regulatory capital, and a proper assessment of economic capital adequacy; and simpler products!

The Social Welfare Implications of the Zenga Index
Francesca Greselin,Simone Pellegrino,Achille Vernizzi
arXiv

We introduce the social welfare implications of the Zenga index, a recently proposed index of inequality. Our proposal is derived by following the seminal book by Son (2011) and the recent working paper by Kakwani and Son (2019). We compare the Zenga based approach with the classical one, based on the Lorenz curve and the Gini coefficient, as well as the Bonferroni index. We show that the social welfare specification based on the Zenga uniformity curve presents some peculiarities that distinguish it from the other considered indexes. The social welfare specification presented here provides a deeper understanding of how the Zenga index evaluates the inequality in a distribution.

The unbearable lightness of equilibria in a low interest rate environment
Guido Ascari,Sophocles Mavroeidis
arXiv

Structural models with no solution are incoherent, and those with multiple solutions are incomplete. We develop a method to study coherency and completeness conditions for linear dynamic forward-looking rational expectations models under an occasionally binding constraint. In the context of the simple New Keynesian model with a zero lower bound, this method shows that the coherency and completeness condition generally violates the Taylor principle. Rational expectations require time-varying and correlated support restrictions on the distribution of the structural shocks. With appropriate restrictions, a very large number of equilibria can be supported.

V-, U-, L-, or W-shaped recovery after COVID? Insights from an Agent Based Model
Dhruv Sharma,Jean-Philippe Bouchaud,Stanislao Gualdi,Marco Tarzia,Francesco Zamponi
arXiv

We discuss the impact of a Covid-like shock on a simple toy economy, described by the Mark-0 Agent-Based Model that we developed and discussed in a series of previous papers. We consider a mixed supply and demand shock, and show that depending on the shock parameters (amplitude and duration), our toy economy can display V-shaped, U-shaped or W-shaped recoveries, and even an L-shaped output curve with permanent output loss. This is due to the existence of a self-sustained "bad" state of the economy. We then discuss two policies that attempt to moderate the impact of the shock: giving easy credit to firms, and the so-called helicopter money, i.e. injecting new money into the households savings. We find that both policies are effective if strong enough, and we highlight the potential danger of terminating these policies too early. While we only discuss a limited number of scenarios, our model is flexible and versatile enough to allow for a much wider exploration, thus serving as a useful tool for the qualitative understanding of post-Covid recovery. We provide an on-line version of the code at https://gitlab.com/sharma.dhruv/markovid .

Vocational Training Programs and Youth Labor Market Outcomes: Evidence from Nepal
S. Chakravarty,M. Lundberg,P. Nikolov,J. Zenker
arXiv

Lack of skills is arguably one of the most important determinants of high levels of unemployment and poverty. In response, policymakers often initiate vocational training programs in effort to enhance skill formation among the youth. Using a regression-discontinuity design, we examine a large youth training intervention in Nepal. We find, twelve months after the start of the training program, that the intervention generated an increase in non-farm employment of 10 percentage points (ITT estimates) and up to 31 percentage points for program compliers (LATE estimates). We also detect sizeable gains in monthly earnings. Women who start self-employment activities inside their homes largely drive these impacts. We argue that low baseline educational levels and non-farm employment levels and Nepal's social and cultural norms towards women drive our large program impacts. Our results suggest that the program enables otherwise underemployed women to earn an income while staying at home - close to household errands and in line with the socio-cultural norms that prevent them from taking up employment outside the house.

Ð­ÐºÐ¾Ð½Ð¾Ð¼Ð¸Ñ‡ÐµÑÐºÐ¸Ðµ Ð¸Ð·Ð¼ÐµÑ€ÐµÐ½Ð¸Ñ ÑÐµÐ³Ð¾Ð´Ð½Ñ (ÑƒÑ‡ÐµÐ±Ð½Ð¾Ðµ Ð¿Ð¾ÑÐ¾Ð±Ð¸Ðµ) (Economic Measurements Today: A Textbook)
Artemenkov, Andrey Igorevich
SSRN
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