# Research articles for the 2021-02-21

Analyst Forecasts and Currency Markets
Mair, Florian
SSRN
I examine the forecasting performance, directional accuracy, rationality and economic value of analyst forecasts and characteristics of investment portfolios built from these forecasts for 30 currency pairs from 2006 to 2020. My results show that analyst forecasts perform worse than forecasts based on a random walk and forward rates and that they are biased and do not provide significant economic value to investors. Forecasts may strongly deviate from market expectations, while analyst forecast dispersion is positively associated with future currency returns. Portfolios built from analyst forecasts tend to strongly underperform the dollar factor, value, carry and momentum portfolios and are spanned by them. My findings indicate that expected returns extracted from analyst forecasts are negatively related to realized excess returns in FX markets and contribute to the literature on survey-based returns in asset pricing.

Auction Type Resolution on Smart Derivatives
Yusuke Ikeno,James Angel,Shin'ichiro Matsuo,Ryosuke Ushida
arXiv

This paper proposes an auction type resolution for smart derivatives. It has been discussed to migrate derivatives contracts to smart contracts (smart derivatives). Automation is often discussed in this context. It is also important to prepare to avoid disputes from practical perspectives. There are controversial issues to terminate the relationship at defaults. In OTC derivative markets, master agreements define a basic policy for the liquidation process but there happened some disputes over these processes. We propose to define an auction type resolution in smart derivatives, which each participant would find beneficial.

Co-movement of Price and Intrinsic Value - Does Accounting Information Matter?
Mehring, Oliver,Olsson, Per,Sievers, Soenke,Sofilkanitsch, Christian
SSRN
We investigate the co-movement of stock prices and intrinsic value estimates focusing on the estimation of risk. We apply risk measurements based on a) market and b) accounting data. We ï¬nd that price and value co-move from 1983 to 2014 on an index-level using accounting-based risk measurement in contrast to the market-based risk measurement. Our ï¬ndings have two vital implications. First, the lack of co-movement documented in prior research can alternatively be explained by the applied valuation model (market vs. accounting), rather than investors trading behavior (e.g., speculation). Second this result provides strong empirical evidence that accounting information is useful for equity investors. Finally, we analyze the role of accounting conservatism regarding co-movement. We document that on an index level conservative reporting harms the co-movement of price and value. However, conditioning on a co-movement of price and value, more conservatism is helpful for moving prices back to fundamentals.

Consolidation and Legacy of Foreign Currency Household Lending in Central and Eastern Europe: The Case of Hungary
SSRN
During the first decade of the 21st century, household FX loans spread in numerous countries in Central and Eastern Europe, where they caused serious macroeconomic and social problems with the spillover of the global financial crisis. Disregarding countries that joined the euro area, Hungary was the only state where household FX loans were completely phased out. The aim of the paper is to provide a structured presentation of the circumstances of the FX loan conversion in Hungary and to assess the potential risks related to the post FX loan period. The paper reviews the relevant international literature about the causes and the impact of unsecured FX lending in the household sector and analyses the phasing-out of the household FX loans in Hungary from the point of view of the legal considerations, the interest rate environment, the macroeconomic stability, the elbowroom in FX reserves and the timing of the process. The paper concludes that the conversion happened at the first date which was legally allowed and economically properly underpinned. The paper also presents that the central bank reacted to the new challenges of the phasing-out process with new macroprudential tools to prevent excessive indebtedness and over-lending, to reduce households' interest rate risks, and to ensure that customers have appropriate income reserves, in order to improve the quality and sustainability of lending to households in the future.

Equity Crowdfunding: New Evidence From Us and UK Markets
Rossi, Alice,Vanacker, Tom R.,Vismara, Silvio
SSRN
This paper offers insights into 3,576 initial equity crowdfunding offerings in the UK and US markets from 2012 to 2019. We investigate the factors influencing three outcomes: the success of the offering, the fundraising target, and matching between entrepreneurial ventures and crowdfunding platforms. In all markets, higher equity retention by original entrepreneurs positively affects the chances of success of the offerings and amount of capital raised. However, there are differences across platforms. Patents do not have a significant impact in entrepreneur-led platforms, while they matter in the UK investor-led platform SyndicateRoom. By separately observing the capital demand set by entrepreneurs and the capital supply by investors, we find that entrepreneurs in financial centers set higher targets in UK markets. There is no difference in the amount of capital raised by female and male entrepreneurs, conditional on female founders setting lower targets in UK markets.

Evaluating the Financial Performance by Considering the Effect of External Factors on Organization Cash Flow
Mohsin, Hussein Jalil,Ahmed, Sahbaa Abdulqader,Streimikiene, Dalia
SSRN
Financial performance is the measure of an organizationâ€™s productivity and effectiveness. It is used as an indicator of an organizationâ€™s ability to use available resources in generating returns and profits for its stakeholders. Determinants of financial performance include employee productivity, leadership in the organization and resource use. An organizationâ€™s financial performance defines its continuity. Stability in an organization is dependent on its financial accounting and management. In the world today, an organizationâ€™s corporate success is influenced by factors that are often out of its control. The external environment of an organization entails a variety of factors whose existence influences its performance and behaviors. The action of these factors directly or indirectly affects organizations. Organizations have to conform to these external factors for their survival. Organizations are environment-dependent and environment serving. An organization is impacted by the environment in which they operate and its success is solely dependent on its ability to adapt to its environment. Changes in external environment factors have a significant impact on the organizationâ€™s survival and success. The purpose of this research was to assess the effect of external factors on an organizationâ€™s cash flow. The aim of the study was to obtain data on these external factors and analyze them with the view of finding out their relationship with financial performance of organizations. Linear regression analysis was to find the correlation between the external factors and organizationâ€™s financial performance.

Exchange Rate Movements and Structural Break on China FDI Inflows
Lee, Jung Wan ,Brahmasrene, Tantatape
SSRN
The aim of the study is to explore the short-run and long-run dynamic relationships between exchange rate fluctuations and foreign direct investment (FDI) inflows in China. The justification is that the undertaken topic is preeminent for devising strategies to promote economic development, thus, a course that carries much at stake not only for China but also for other developing countries. Methodology used in the study consists of co-integration tests, vector error correction models, Wald tests and impulse responses. Monthly time series data from the National Bureau of Statistics of the Peopleâ€™s Republic of China are analyzed. The main empirical results indicate that a change in exchange rates negatively affects FDI inflows in the long run while there exists no evidence of short-run dynamics and reciprocal feedback between exchange rate fluctuations and FDI inflows. Furthermore, a structural break occurs during the 2007-2009 global financial crisis shock to FDI inflows in China. In conclusions, this research expands knowledge of factors that affect FDI inflows. To generalize the results obtained from this study, recommendations for future research include studies encompassing different economies where data are available. Such research will contribute towards improving our understanding of exchange rate systems and responses in each market.

Financial Development and Economic Growth in Selected Asian Economies: A Dynamic Panel ARDL Test
Sharma, Shravani,Sharma, Suparn Kumar
SSRN
The present endeavor measures the extent of the nexus between financial development and economic growth by utilizing annual macroeconomic panel data for selected 14 Asian economies. The study focuses on the link between the indicators of financial development and economic growth. The results of panel cointegration analysis suggest that there is two-way cointegration relationship from GDP to GCF and BM in short-run as well as in long-run however, the relationship is one-way, that is, from GDP to DCPS as well as from GDP to DCBS. The findings of the present study establish strong indications of the positive long-run relationship among all the selected indicators of financial development and economic growth. Moreover, the present attempt also indicates that gross capital formation and broad money are critical for economic growth and suggests that upliftment of economic growth of the economies improves the development of financial sector.

Firms, Jobs, and Gender Disparities in Top Incomes: Evidence from Brazil
Benguria, Felipe
SSRN
This paper studies the gender disparities among top incomes in Brazil during the period 1994-2013 using administrative data on the universe of formal-sector job spells and detailed information on educational attainment, employers, and occupations performed. Over these two decades, differences in pay and participation between genders have narrowed, yet the process has been slow and women are still severely underrepresented, especially within the very top percentiles of the earnings distribution. The following findings highlight the role of firms and occupations in explaining these patterns. At the start of the period, women in the top percentile of the distribution owe a larger fraction of their earnings to working at high-paying firms than do men, while menâ€™s top incomes are in excess of their firmsâ€™ average pay. In addition, belonging to the top percentile is initially much more persistent for men than for women. Both of these differences have vanished over time. I also document that the increase in the share in participation of women in top percentiles is primarily a within-firm and within-occupation phenomenon, which suggests that the evolution of cultural and institutional elements deserves further examination. Finally, I study the careers of female and male top earners, finding that the path to the top percentiles of the distribution is quite different across genders: Top-earning women work in larger firms from the start of their careers. Top-earning men earn large earnings premia above what their firm average pays throughout their career, and after their mid-30s switch employers at a higher frequency than women.

How Decentralized is the Governance of Blockchain-based Finance: Empirical Evidence from four Governance Token Distributions
Johannes Rude Jesnen,Victor von Wachter,Omri Ross
arXiv

Novel blockchain technology provides the infrastructure layer for the creation of decentralized appli-cations. A rapidly growing ecosystem of applications is built around financial services, commonly referred to as decentralized finance. Whereas the intangible concept of decentralization is presented as a key driver for the applications, defining and measuring decentralization is multifaceted. This pa-per provides a framework to quantify decentralization of governance power among blockchain appli-cations. Governance of the applications is increasingly important and requires striking a balance be-tween broad distribution, fostering user activity, and financial incentives. Therefore, we aggregate, parse, and analyze empirical data of four finance applications calculating coefficients for the statistical dispersion of the governance token distribution. The gauges potentially support IS scholars for an objective evaluation of the capabilities and limitations of token governance and for fast iteration in design-driven governance mechanisms.

In and out of lockdown: Propagation of supply and demand shocks in a dynamic input-output model
Anton Pichler,Marco Pangallo,R. Maria del Rio-Chanona,François Lafond,J. Doyne Farmer
arXiv

Economic shocks due to Covid-19 were exceptional in their severity, suddenness and heterogeneity across industries. To study the upstream and downstream propagation of these industry-specific demand and supply shocks, we build a dynamic input-output model inspired by previous work on the economic response to natural disasters. We argue that standard production functions, at least in their most parsimonious parametrizations, are not adequate to model input substitutability in the context of Covid-19 shocks. We use a survey of industry analysts to evaluate, for each industry, which inputs were absolutely necessary for production over a short time period. We calibrate our model on the UK economy and study the economic effects of the lockdown that was imposed at the end of March and gradually released in May. Looking back at predictions that we released in May, we show that the model predicted aggregate dynamics very well, and sectoral dynamics to a large extent. We discuss the relative extent to which the model's dynamics and performance was due to the choice of the production function or the choice of an exogenous shock scenario. To further explore the behavior of the model, we use simpler scenarios with only demand or supply shocks, and find that popular metrics used to predict a priori the impact of shocks, such as output multipliers, are only mildly useful.

Internal hydro- and wind portfolio optimisation in real-time market operations
Hans Ole Riddervold,Ellen Krohn Aasgård,Lisa Haukaas,Magnus Korpås
arXiv

In this paper aspects related to handling of intraday imbalances for hydro and wind power are addressed. The definition of imbalance cost is established and used to describe the potential benefits of shifting from plant-specific schedules to a common load requirement for wind and hydropower units in the same price area. The Nordpool intraday pay-as-bid market has been the basis for evaluation of imbalances, and some main characteristics for this market has been described. We consider how internal handling of complementary imbalances within the same river system with high inflow uncertainty and constrained reservoirs can reduce volatility in short-term marginal cost and risk compared to trading in the intraday market. We have also shown the the imbalance cost for a power producer with both wind and hydropower assets can be reduced by internal balancing in combination with sales and purchase in a pay-as-bid intraday market

Linear-quadratic stochastic delayed control and deep learning resolution
William Lefebvre,Enzo Miller
arXiv

We consider a class of stochastic control problems with a delayed control, both in drift and diffusion, of the type dX t = $\alpha$ t--d (bdt + $\sigma$dW t). We provide a new characterization of the solution in terms of a set of Riccati partial differential equations. Existence and uniqueness are obtained under a sufficient condition expressed directly as a relation between the horizon T and the quantity d(b/$\sigma$) 2. Furthermore, a deep learning scheme is designed and used to illustrate the effect of delay on the Markowitz portfolio allocation problem with execution delay.

Liquidity Constraint of Banks and Non-Neutrality of Monetary Policy
Wang, Tianxi
SSRN
This paper studies non-neutrality of monetary policy incorporating three facts: The majority of media of exchange is not fiat money but bank liability; fiat money is largely used by banks to meet liquidity demand; and banks extensively use government bonds for liquidity management. It finds that monetary policy produces real effects by changing the tightness of banks' liquidity constraint; its effect for liquidity unconstrained banks is the opposite of that for the maximally constrained; expansion of digital ways of payment increases price levels by reducing the withdrawal probability; and if this probability becomes zero fiat money stops circulation.

Mechanistic Framework of Global Value Chains
Sourish Dutta
arXiv

Indeed, the global production (as a system of creating values) is eventually forming like a gigantic and complex network/web of value chains that explains the transitional structures of global trade and development of the global economy. It's truly a new wave of globalisation, and we term it as the global value chains (GVCs), creating the nexus among firms, workers and consumers around the globe. The emergence of this new scenario asks: how an economy's firms, producers and workers connect in the global economy. And how are they capturing the gains out of it in terms of different dimensions of economic development? This GVC approach is very crucial for understanding the organisation of the global industries and firms. It requires the statics and dynamics of diverse players involved in this complex global production network. Its broad notion deals with different global issues (including regional value chains also) from the top down to the bottom up, founding a scope for policy analysis (Gereffi & Fernandez-Stark 2011). But it is true that, as Feenstra (1998) points out, any single computational framework is not sufficient to quantification this whole range of economic activities. We should adopt an integrative framework for accurate projection of this dynamic multidimensional phenomenon.

Multi-class Models for Assessing the Financial Condition of Manufacturing Enterprises
Tomczak, Sebastian Klaudiusz
SSRN
Since 2007, the operating conditions of companies have changed significantly and can be described as more unpredictable. Insolvency of one company may, by the domino effect, have negative impacts on other operators. In extreme cases, these impacts can lead to their bankruptcy. Therefore, it is important to constantly monitor both the financial condition of a company and the financial condition of its business partners. In order to evaluate the financial standing of a company different types of methods can be employed. The aim of the paper was to build two models that specify more than two states of financial standing of manufacturing businesses. The use of the models enables recognition of the deteriorating financial condition of manufacturing companies a few years before insolvency is declared. The traditional discriminant model and Bayesian model were constructed. Cluster analysis was used to select classes of financial standing of the analyzed companies. The models were tested on two sets of samples. A small sample consisted of 224 (112 + 112) companies and a large sample consisted of more than 10,600 companies. The results showed that the traditional discriminant model performs better than the Bayesian model for classifying companies.

REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu,Weiqing Liu,Chang Xu,Jiang Bian,Jian Yin,Tie-Yan Liu
arXiv

Stock trend forecasting, aiming at predicting the stock future trends, is crucial for investors to seek maximized profits from the stock market. Many event-driven methods utilized the events extracted from news, social media, and discussion board to forecast the stock trend in recent years. However, existing event-driven methods have two main shortcomings: 1) overlooking the influence of event information differentiated by the stock-dependent properties; 2) neglecting the effect of event information from other related stocks. In this paper, we propose a relational event-driven stock trend forecasting (REST) framework, which can address the shortcoming of existing methods. To remedy the first shortcoming, we propose to model the stock context and learn the effect of event information on the stocks under different contexts. To address the second shortcoming, we construct a stock graph and design a new propagation layer to propagate the effect of event information from related stocks. The experimental studies on the real-world data demonstrate the efficiency of our REST framework. The results of investment simulation show that our framework can achieve a higher return of investment than baselines.

Supporting Financial Inclusion with Graph Machine Learning and Super-App Alternative Data
Luisa Roa,Andrés Rodríguez-Rey,Alejandro Correa-Bahnsen,Carlos Valencia
arXiv

The presence of Super-Apps have changed the way we think about the interactions between users and commerce. It then comes as no surprise that it is also redefining the way banking is done. The paper investigates how different interactions between users within a Super-App provide a new source of information to predict borrower behavior. To this end, two experiments with different graph-based methodologies are proposed, the first uses graph based features as input in a classification model and the second uses graph neural networks. Our results show that variables of centrality, behavior of neighboring users and transactionality of a user constituted new forms of knowledge that enhance statistical and financial performance of credit risk models. Furthermore, opportunities are identified for Super-Apps to redefine the definition of credit risk by contemplating all the environment that their platforms entail, leading to a more inclusive financial system.

The Effectiveness of Hedge Fund Investment Strategies under Various Market Conditions
Falkowski, MichaÅ‚,SierpiÅ„ska-Sawicz, Agata,Szczepankowski, Piotr
SSRN
The main purpose of the article was to analyze the effectiveness of the basic investment strategies used by hedge funds in the long term (years 1994-2015) and during the global financial crisis (years 2007-2009). Using information from commercial databases we attempted to verify the hypothesis that alternative hedge funds, regardless of the type of strategy they use, are capable of achieving better outcomes than other capital allocation options, at any time and under a variety of market conditions. We analyzed hedge funds effectiveness in two stages. For stage one, we performed a profitability analysis for the whole hedge funds sector in the two periods and compared the results with the stock rates of return achieved by investors in the global market for the same period and with the risk-free rate. At stage two we calculated ratios that included rate of return and risk, though only for specific strategies. We used traditional portfolio performance measures (Sharpe, Treynor, Jensen ratios) as well as the newer ones (the Sortino ratio, downside deviation). The results show no confirmation that investments carried out by hedge funds are more risky than traditional capital investment methods. Risk associated with investments by the analyzed entities was lower not only in times of prosperity, but also during crisis, providing a clear indication of the higher effectiveness of entities operating in the alternative investment sector and regardless of the changes taking place in the financial market, the length of the capital investment period or the investment strategy being pursued.

The Expediting Effect of Monitoring on Infrastructural Works. A Regression-Discontinuity Approach with Multiple Assignment Variables
Giuseppe Francesco Gori,Patrizia Lattarulo,Marco Mariani
arXiv

Decentralised government levels are often entrusted with the management of public works and required to ensure well-timed infrastructure delivery to their communities. We investigate whether monitoring the activity of local procuring authorities during the execution phase of the works they manage may expedite the infrastructure delivery process. Focussing on an Italian regional law which imposes monitoring by the regional government on "strategic" works carried out by local buyers, we draw causal claims using a regression-discontinuity approach, made unusual by the presence of multiple assignment variables. Estimation is performed through discrete-time survival analysis techniques. Results show that monitoring does expedite infrastructure delivery.

The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?
Anthony Strittmatter,Conny Wunsch
arXiv

The vast majority of existing studies that estimate the average unexplained gender pay gap use unnecessarily restrictive linear versions of the Blinder-Oaxaca decomposition. Using a notably rich and large data set of 1.7 million employees in Switzerland, we investigate how the methodological improvements made possible by such big data affect estimates of the unexplained gender pay gap. We study the sensitivity of the estimates with regard to i) the availability of observationally comparable men and women, ii) model flexibility when controlling for wage determinants, and iii) the choice of different parametric and semi-parametric estimators, including variants that make use of machine learning methods. We find that these three factors matter greatly. Blinder-Oaxaca estimates of the unexplained gender pay gap decline by up to 39% when we enforce comparability between men and women and use a more flexible specification of the wage equation. Semi-parametric matching yields estimates that when compared with the Blinder-Oaxaca estimates, are up to 50% smaller and also less sensitive to the way wage determinants are included.

The Impact of Corona Populism: Empirical Evidence from Austria and Theory
Patrick Mellacher
arXiv

I study the impact of corona populism -- politics aimed at denying or downplaying the danger posed by COVID-19 for strategic reasons -- on the evolution of the pandemic using regional data from Austria. The right-wing FPOE first vocalized strong support for strict lockdown measures, but made a corona populist turn at the end of the first wave of infections. Using panel regression analysis, I show that the vote share of the FPOE at the last national parliamentary elections is a strong predictor for the number of COVID-19 deaths per capita after the FPOE switched their policy stance, while there is no correlation before the policy switch. Interestingly, I do not find a statistically significant correlation between the FPOE vote share and the reported number of infections. I hypothesize that this can be traced back to a self-selection bias in testing. To explore this hypothesis, I extend the classical SIRD model to incorporate conditional quarantine and two groups of agents: the majority and the corona sceptics, where the latter are less inclined to get tested and engage in social distancing. Such a model can explain the puzzling empirics: if mixing is sufficiently homophilic, an increase in the share of corona sceptics can cause an increase in the number of deaths without increasing the number of reported infections. I finally discuss the partly non-trivial implications of the interplay between group sizes, behavioral differences and the degree of homophily on public health outcomes within the theoretical model.

The equivalent constant-elasticity-of-variance (CEV) volatility of the stochastic-alpha-beta-rho (SABR) model
Jaehyuk Choi,Lixin Wu
arXiv

This study presents new analytic approximations of the stochastic-alpha-beta-rho (SABR) model. Unlike existing studies that focus on the equivalent Black-Scholes (BS) volatility, we instead derive the equivalent constant-elasticity-of-variance (CEV) volatility. Our approach effectively reduces the approximation error in a way similar to the control variate method because the CEV model is the zero vol-of-vol limit of the SABR model. Moreover, the CEV volatility approximation yields a finite value at a zero strike and thus conveniently leads to a small-time asymptotics for the mass at zero. The numerical results compare favorably with the BS volatility approximations in terms of the approximation accuracy, small-strike volatility asymptotics, and no-arbitrage region.

Thiele's Differential Equation Based on Markov Jump Processes with Non-countable State Space
Emmanuel Coffie,Sindre Duedahl,Frank Proske
arXiv

In modern life insurance, Markov processes in continuous time on a finite or at least countable state space have been over the years an important tool for the modelling of the states of an insured. Motivated by applications in disability insurance, we propose in this paper a model for insurance states based on Markov jump processes with more general state spaces. We use this model to derive a new type of Thiele's differential equation which e.g. allows for a consistent calculation of reserves in disability insurance based on two-parameter continuous time rehabilitation rates.