Research articles for the 2021-02-24

A Scaling Limit for Utility Indifference Prices in the Discretized Bachelier Model
Asaf Cohen,Yan Dolinsky

We consider the discretized Bachelier model where hedging is done on an equidistant set of times. Exponential utility indifference prices are studied for path-dependent European options and we compute their non-trivial scaling limit for a large number of trading times $n$ and when risk aversion is scaled like $n\ell$ for some constant $\ell>0$. Our analysis is purely probabilistic. We first use a duality argument to transform the problem into an optimal drift control problem with a penalty term. We further use martingale techniques and strong invariance principles and get that the limiting problem takes the form of a volatility control problem.

A Social Norm Nudge to Save More: A Field Experiment at a Retail Bank
Dur, Robert,Fleming, Dimitry,van Garderen, Marten,van Lent, Max
A large fraction of households have very little savings buffer and are therefore vulnerable to financial shocks. This paper examines whether a social norm nudge can induce such households to save more. We ran a large-scale field experiment at a retail bank in the Netherlands. We find that households who are exposed to the social norm nudge click more often on a link to a personal web page where they can start or adjust an automatic savings plan. However, analyzing detailed bank data, we find no treatment effect on actual savings, neither in the short run nor in the long run. Our null findings are quite precisely estimated. A complementary small-scale survey experiment suggests that people did notice the social norm nudge and also that it had an impact on savings intentions.

A learning scheme by sparse grids and Picard approximations for semilinear parabolic PDEs
Jean-François Chassagneux,Junchao Chen,Noufel Frikha,Chao Zhou

Relying on the classical connection between Backward Stochastic Differential Equations (BSDEs) and non-linear parabolic partial differential equations (PDEs), we propose a new probabilistic learning scheme for solving high-dimensional semi-linear parabolic PDEs. This scheme is inspired by the approach coming from machine learning and developed using deep neural networks in Han and al. [32]. Our algorithm is based on a Picard iteration scheme in which a sequence of linear-quadratic optimisation problem is solved by means of stochastic gradient descent (SGD) algorithm. In the framework of a linear specification of the approximation space, we manage to prove a convergence result for our scheme, under some smallness condition. In practice, in order to be able to treat high-dimensional examples, we employ sparse grid approximation spaces. In the case of periodic coefficients and using pre-wavelet basis functions, we obtain an upper bound on the global complexity of our method. It shows in particular that the curse of dimensionality is tamed in the sense that in order to achieve a root mean squared error of order ${\epsilon}$, for a prescribed precision ${\epsilon}$, the complexity of the Picard algorithm grows polynomially in ${\epsilon}^{-1}$ up to some logarithmic factor $ |log({\epsilon})| $ which grows linearly with respect to the PDE dimension. Various numerical results are presented to validate the performance of our method and to compare them with some recent machine learning schemes proposed in Han and al. [20] and Hur\'e and al. [37].

Equity Investing in the Age of Intangibles
Dugar, Amitabh,Pozharny, Jacob
Expenditures on creation of intangible capital have increased but accounting standards have not kept pace. We investigate whether this has affected the value relevance of book value and earnings. We construct a composite measure of intangible intensity based on intangible assets capitalized on the balance sheet, research and development expenditures, and sales, general & administrative expenditures to classify industries by intangible intensity. We show that the value relevance of book value and earnings has declined for high intangible intensity companies in USA and abroad, but for the low intangible intensity group it has remained stable in USA and increased internationally.

Fundamental Anomalies
Li, Erica X. N.,Ma, Guoliang,Wang, Shujing,Yu, Cindy
This paper examines to what extent stock market anomalies are driven by firm fundamentals under a production-based asset pricing framework. We estimate a two-capital q-model by matching the entire time series of firm-level stock returns using Bayesian Markov Chain Monte Carlo (MCMC), instead of matching the return moments at the portfolio level as prior studies do. Our paper addresses the critique on prior studies that the parameter values of the model are chosen to fit a specific set of anomalies and different values are required for different anomalies. We show that this simple q-model is able to generate large and significant size, momentum, profitability, investment, and intangibles premiums. Moreover, the model exhibits reliable out-of-sample forecasts on stock returns due to its economic structure.

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

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.

Interactions between social norms and incentive mechanisms in organizations
Ravshanbek Khodzhimatov,Stephan Leitner,Friederike Wall

We focus on how individual behavior that complies with social norms interferes with performance-based incentive mechanisms in organizations with multiple distributed decision-making agents. We model social norms to emerge from interactions between agents: agents observe other the agents' actions and, from these observations, induce what kind of behavior is socially acceptable. By complying with the induced socially accepted behavior, agents experience utility. Also, agents get utility from a pay-for-performance incentive mechanism. Thus, agents pursue two objectives. We place the interaction between social norms and performance-based incentive mechanisms in the complex environment of an organization with distributed decision-makers, in which a set of interdependent tasks is allocated to multiple agents. The results suggest that, unless the sets of assigned tasks are highly correlated, complying with emergent socially accepted behavior is detrimental to the organization's performance. However, we find that incentive schemes can help offset the performance loss by applying individual-based incentives in environments with lower task-complexity and team-based incentives in environments with higher task-complexity.

Investment, Idiosyncratic Risk, and Growth Options
Liu, Clark,Wang, Shujing
We provide evidence that growth options play an important role in determining the negative relation between corporate investment and idiosyncratic risk in the absence of agency problem. A simple real options model predicts that the negative relation between corporate investment and idiosyncratic risk is a U-shaped function of the level of idiosyncratic risk: investment responds the most when idiosyncratic risk is at the intermediate level. And the negative relation is stronger when firms possess more growth options. Our results are robust when we control for the effect of managerial risk aversion, supporting the view that firms' optimal response to uncertainty is an important driving force behind the negative investment-idiosyncratic risk relation.

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

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.

Mapping Organization Knowledge Network and Social Media Based Reputation Management
Andry Alamsyah,Maribella Syawiluna

Knowledge management is an important aspect of an organization, especially in the ICT industry. Having more control of it is essentials for the organization to stay competitive in the business. One way to assess the organization's knowledge capital is by measuring employee knowledge networks and their personal reputation in social media. Using this measurement, we see how employees build relationships around their peer networks or clients virtually. We are also able to see how knowledge networks support organizational performance. The research objective is to map knowledge network and reputation formulation in order to fully understand how knowledge flow and whether employee reputation has a higher degree of influence in the organization's knowledge network. We particularly develop formulas to measure knowledge networks and personal reputation based on their social media activities. As a case study, we pick an Indonesian ICT company that actively build their business around their employee peer knowledge outside the company. For the knowledge network, we perform data collection by conducting interviews. For reputation management, we collect data from several popular social media. We base our work on Social Network Analysis (SNA) methodology. The result shows that employees' knowledge is directly proportional to their reputation, but there are different reputations level on different social media observed in this research.

Measuring Marketing Communications Mix Effort Using Magnitude Of Influence And Influence Rank Metric
Andry Alamsyah,Endang Sofyan,Tsana Hasti Nabila

In the context of modern marketing, Twitter is considered a communication platform to spread information. Many companies create and acquire several Twitter accounts to support and perform varieties of marketing mix activities. Initially, each accounts used to capture a specific market profile. Together, the accounts create a network of information that provide consumer to the information they need depends on their contextual utilization. From many accounts available, we have the fundamental question on how to measure the influence of each account in the market based not only on their relations but also on the effects of their postings. The magnitude of Influence (MOI) metric is adapted together with Influence Rank (IR) measurement of accounts in their social network neighborhood. We use social network analysis approach to analyze 65 accounts in the social network of an Indonesian mobile phone network operator, Telkomsel which involved in marketing communications mix activities through series of related tweets. Using social network provide the idea of the activity in building and maintaining relationships with the target audience. This paper shows the results of the most potential accounts based on the network structure and engagement. Based on this research, the more number of followers one account has, the more responsibility it has to generate the interaction from their followers in order to achieve the expected effectiveness. The focus of this paper is to determine the most potential accounts in the application of marketing communications mix in Twitter.

Modeling Price Clustering in High-Frequency Prices
Vladimír Holý,Petra Tomanová

The price clustering phenomenon, i.e. an increased occurence of specific prices, is widely observed and well-documented for various financial instruments in various financial markets. In the literature, however, it is rarely incorporated into price models. We consider that there are several types of agents trading only in specific multiples of the tick size resulting in an increased occurrence of these multiples in prices. For example, stocks on the NYSE and NASDAQ exchanges are traded with precision to one cent but multiples of five cents and ten cents occur much more often in prices. To capture this behaviour, we propose a discrete price model based on a mixture of double Poisson distributions with dynamic volatility and dynamic proportions of agent types. The model is estimated by the maximum likelihood method. In an empirical study of DJIA stocks, we find that higher instantaneous volatility leads to weaker price clustering at the ultra-high frequency. This is in sharp contrast with results at low frequencies which show that daily realized volatility has positive impact on price clustering.

Mortgage Lending in January-September 2020
Zubov, Sergey
On the back of the lending market interest rate cuts and implementation of the subsidized mortgage program (mortgage loans at the interest rate of 6.5% per annum for home buying on the primary housing market), real-estate market demand picked up. In Q1-Q3, 2020, banks increased substantially mortgage lending volumes, having surpassed the high outturns seen in 2018. The downside of the lending-based demand stimulation was the appreciation of prices both on the primary and secondary housing markets and high household debt load. This makes the money authorities point to the need of wrapping up the subsidized mortgage government program in the near future.

Optimal dynamic regulation of carbon emissions market: A variational approach
René Aïd,Sara Biagini

We consider the problem of reducing the carbon emissions of a set of firms over a finite horizon. A regulator dynamically allocates emission allowances to each firm. Firms face idiosyncratic as well as common economic shocks on emissions, and have linear quadratic abatement costs. Firms can trade allowances so to minimise total expected costs, from abatement and trading plus a quadratic terminal penalty. Using variational methods, we exhibit in closed-form the market equilibrium in function of regulator's dynamic allocation. We then solve the Stackelberg game between the regulator and the firms. Again, we obtain a closed-form expression of the dynamic allocation policies that allow a desired expected emission reduction. Optimal policies are not unique but share common properties. Surprisingly, all optimal policies induce a constant abatement effort and a constant price of allowances. Dynamic allocations outperform static ones because of adjustment costs and uncertainty, in particular given the presence of common shocks. Our results are robust to some extensions, like risk aversion of firms or different penalty functions.

PolicySpace2: modeling markets and endogenous housing policies
Bernardo Alves Furtado

Policymakers decide on alternative policies facing restricted budgets and uncertain, ever-changing future. Designing housing policies is further difficult giving the heterogeneous characteristics of properties themselves and the intricacy of housing markets and the spatial context of cities. We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks to integrate economic, spatial and transport literature. PS2 is applied to a comparison among three competing municipal housing policies aimed at alleviating poverty: (a) property acquisition and distribution, (b) rental vouchers and (c) monetary aid. Within the model context, the monetary aid, that is, a smaller amounts of help for a larger number of households, makes the economy perform better in terms of production, consumption, reduction of inequality and maintenance of financial duties. PS2 as such is also a framework that may be further adapted to a number of related research questions.

Price Discrimination in International Airline Markets
Gaurab Aryal,Charles Murry,Jonathan W. Williams

We develop a model of inter-temporal and intra-temporal price discrimination by monopoly airlines to study the ability of different discriminatory pricing mechanisms to increase efficiency and the associated distributional implications. To estimate the model, we use unique data from international airline markets with flight-level variation in prices across time, cabins, and markets, as well as information on passengers' reasons for travel and time of purchase. We find that the ability to screen passengers across cabins every period increases total surplus by 35% relative to choosing only one price per period, with both the airline and passengers benefiting. However, further discrimination based on passenger's reason to traveling improve airline surplus at the expense of total efficiency. We also find that the current pricing practice yields approximately 89% of the first-best welfare. The source of this inefficiency arises mostly from dynamic uncertainty about demand, not private information about passenger valuations.

Property Business Classification Model Based on Indonesia E-Commerce Data
Andry Alamsyah,Fariz Denada Sudrajat,Herry Irawan

Online property business or known as e-commerce is currently experiencing an increase in home sales. Indonesia's e-commerce property business has positive trending shown by the increasing sales of more than 500% from 2011 to 2015. A prediction of the property price is important to help investors or the public to have accurate information before buying property. One of the methods for prediction is a classification based on several distinctive property industry attributes, such as building size, land size, number of rooms, and location. Today, data is easily obtained, there are many open data from E-commerce sites. E-commerce contains information about homes and other properties advertised to sell. People also regularly visit the site to find the right property or to sell the property using price information which collectively available as open data. To predict the property sales, this research employed two different classification methods in Data Mining which are Decision Tree and k-NN classification. We compare which model classification is better to predict property price and their attributes. We use Indonesia's biggest property-based e-commerce site as our open data source, and choose location Bandung in our experiment. The accuracy result of the decision tree is 75% and KNN is 71%, other than that k-NN can explore more data patterns than the Decision Tree.

Regional and Sectoral Structures and Their Dynamics of Chinese Economy: A Network Perspective from Multi-Regional Input-Output Tables
Tao Wang,Shiying Xiao,Jun Yan,Panpan Zhang

A multi-regional input-output table (MRIOT) containing the transactions among the region-sectors in an economy defines a weighted and directed network. Using network analysis tools, we analyze the regional and sectoral structure of the Chinese economy and their temporal dynamics from 2007 to 2012 via the MRIOTs of China. Global analyses are done with network topology measures. Growth-driving province-sector clusters are identified with community detection methods. Influential province-sectors are ranked by weighted PageRank scores. The results revealed a few interesting and telling insights. The level of inter-province-sector activities increased with the rapid growth of the national economy, but not as fast as that of intra-province economic activities. Regional community structures were deeply associated with geographical factors. The community heterogeneity across the regions was high and the regional fragmentation increased during the study period. Quantified metrics assessing the relative importance of the province-sectors in the national economy echo the national and regional economic development policies to a certain extent.

Selective Attention in Exchange Rate Forecasting
Kapounek, Svatopluk,Kučerová, Zuzana,Kočenda, Evžen
We analyze the exchange rate forecasting performance under the assumption of selective attention. Although currency markets react to a variety of different information, we hypothesize that market participants process only a limited amount of information. Our analysis includes more than 100,000 news articles relevant to the six most-traded foreign exchange currency pairs for the period of 1979â€"2016. We employ a dynamic model averaging approach to reduce model selection uncertainty and to identify time-varying probability to include regressors in our models. Our results show that smaller sizes models accounting for the presence of selective attention offer improved fitting and forecasting results. Specifically, we document a growing impact of foreign trade and monetary policy news on the euro/dollar exchange rate following the global financial crisis. Overall, our results point to the existence of selective attention in the case of most currency pairs.

Summarizing Online Conversation of Indonesia Tourism Industry using Network Text Analysis
Andry Alamsyah,Sheila Shafira,Muhamad Alfin Yudhistira

The tourism industry is one of the potential revenues and has an important role in economics in Indonesia. The tourism Industry brings job and business opportunities, foreign exchange earnings, and infrastructure development, tourism also plays the role of one of the main drivers in socio-economic progress in Indonesia. The number of foreign tourists visiting Indonesia increase cumulatively and has reached 10.41 million visits or an increase of 10.46 percent from the same period in the previous year. Government trying to increase the number of tourists to visit Indonesia by promoting many Indonesian tourist attractions.

Fernández-Villaverde, Jesús,Mandelman, Federico,Yu, Yang,Zanetti, Francesco
This paper develops a dynamic general equilibrium model with heterogeneous firms that face search complementarities in the formation of vendor contracts. Search complementarities amplify small differences in productivity among firms. Market concentration fosters monopsony power in the labor market, magnifying profits and further enhancing high-productivity firms’ output share. Firms want to get bigger and hire more workers, in stark contrast with the classic monopsony model, where a firm aims to reduce the amount of labor it hires. The combination of search complementarities and monopsony power induces a strong “Matthew effect” that endogenously generates superstar firms out of uniform idiosyncratic productivity distributions. Reductions in search costs increase market concentration, lower the labor income share, and increase wage inequality.

The COVID-19 Insolvency Gap: First-Round Effects of Policy Responses on SMEs
Dörr, Julian Oliver,Murmann, Simona,Licht, Georg
COVID-19 placed a special role to fiscal policy in rescuing companies short of liquidity from insolvency. In the first months of the crisis, SMEs as the backbone of Europe’s real economy benefited from large and mainly indiscriminate aid measures. Avoiding business failures in a whatever it takes fashion contrasts, however, with the cleansing mechanism of economic crises: a mechanism which forces unviable firms out of the market, thereby reallocating resources efficiently. By focusing on firms’ pre-crisis financial standing, we estimate the extent to which the policy response induced an insolvency gap and analyze whether the gap is characterized by firms which had already struggled before the pandemic. With the policy measures being focused on smaller firms, we also examine whether this insolvency gap differs with respect to firm size. Based on credit rating and insolvency data for the near universe of actively rated German firms, our results suggest that the policy response to COVID-19 has triggered a backlog of insolvencies in Germany that is particularly pronounced among financially weak, small firms, having potential long term implications on economic recovery.

The COVID-19 outbreak and stock market reactions: Evidence from Australia
Rahman, Md Lutfur,Amin, Abu S.,Al Mamun, Mohammed Abdullah
We examine how the Australian stock market responded to the uncertainties created by the COVID-19 pandemic and whether the stimulus package offered by the Government helped restore confidence in the market. This study finds a negative stock market reaction to the pandemic announcement, however, among two stimulus packages related announcements, the market reacted positively only to “JobKeeper” package. The cross-sectional results suggest that the smallest, least profitable and value portfolios suffered more during the pandemic. Finally, size and liquidity are found to be the significant drivers of abnormal returns.

The Effect of Mergers and Acquisitions on Bank Performance in Egypt
Badreldin, Ahmed Mohamed,Kalhöfer, Christian
Recent economic reforms in Egypt have significantly improved its macroeconomic indicators and financial sector. Banks have witnessed significant merger and acquisition activity as a result of these reforms in attempts to privatize and strengthen the banking sector. This study measures the performance of Egyptian banks that have undergone mergers or acquisitions during the period 2002-2007. This is done by calculating their return on equity using the Basic ROE Scheme in order to determine the degree of success of banking reforms in strengthening and consolidating the Egyptian banking sector. Our findings indicate that not all banks that have undergone deals of mergers or acquisitions have shown significant improvements in performance and return on equity when compared to their performance before the deals. Furthermore, extensive analysis was performed yielding the same results. It was concluded that mergers and acquisitions have not had a clear effect on the profitability of banks in the Egyptian banking sector. They were only found to have minor positive effects on the credit risk position. These findings do not support the current process of financial consolidation and banking reforms observed in Egypt, and provide weak evidence to support their constructive role in improved bank profitability and economic restructure.

The option value of vacant land: Don't build when demand for housing is booming
Lange, Rutger-Jan,Teulings, Coen N.
Urban structures and urban growth rates are highly persistent. This has far-reaching implications for the optimal size and timing of new construction. We prove that rational developers postpone construction not because prospects are gloomy, but because they are bright. The slow mean reversion in urban growth rates for the Netherlands and the United States (estimated at 0.07 per annum) implies that a substantial share of cities should optimally postpone construction due to high growth. Observed heterogeneity in floorspace density across cities can be explained not by differences in population levels, but in growth rates.

Understanding the Farmers, Environmental Citizenship Behaviors Towards Climate Change. The Moderating Mediating Role of Environmental Knowledge and Ascribed Responsibility
Immaculate Maumoh,Emmanuel H. Yindi

Knowledge is known to be a pre-condition for an individuals behavior. For the most efficient informational strategies for education, it is essential that we identify the types of knowledge that promote behavior effectively and investigate their structure. The purpose of this paper is therefore to examine the factors that affect Kenyan farmers, environmental citizenship behavior (ECB) in the context of Adaptation and mitigation (Climate smart agriculture). To achieve this objective, a theoretical framework has been developed based on value belief norm (VBN) theory. Design/methodology/approach, Data were obtained from 350 farmers using a survey method. Partial lease square structural equation modelling (PLS-SEM) was used to examine the hypothetical model. The results of PLS analysis confirm the direct and mediating effect of the causal sequences of the variables in the VBN model. The moderating role of Environmental knowledge has been seen to be impactful in Climate Smart Agriculture.

Was treibt die Renditen von Hedgefonds? Eine empirische Untersuchung ausgewählter Hedgefonds Strategien (What Drives Hedge Fund Returns? An Empirical Investigation Of Selected Hedge Fund Strategies)
Lehrbass, Frank,Woerndl, Fabian
German Abstract:Nach einer kurzen Übersicht über ausgewählte Hedge Fond Strategien untersuchen wir ökonometrisch, wie bestimmte, publizierte Marktrisikofaktoren die Rendite von ausgewählten Hedge Fond Strategien beeinflussen. Die Modelle erreichen fast alle R² oberhalb 40%.English Abstract:After a short overview on hedge fund strategies we analyze which market risk factors drive hedge fund returns per strategy. The models' explanatory power as measured by R² is above 40 percent in nearly all cases.

When Pro-Poor Microcredit Institutions Favor Richer Borrowers - A Moral Hazard Story
Biancini, Sara,Venet, Baptiste,Ettinger, David
We suggest an explanation for the existence of “mission drift”, the tendency for Microfinance Institutions (MFIs) to lend money to wealthier borrowers rather than to the very poor. We focus on the relationship between MFIs and external funding institutions. We assume that both the MFIs and the funding institutions are pro-poor and agree on the optimal proportion of funds to be granted to the poorer borrower. However, asymmetric information on the effort chosen by the MFI to identify higher quality projects may increase the share of loans attributed to wealthier borrowers. This occurs because funding institutions have to build incentives for MFIs, creating a trade off between the quality of the funded projects and the attribution of loans to poorer borrowers.