Research articles for the 2020-01-12

A new approach for trading based on Long Short Term Memory technique
Zineb Lanbouri,Saaid Achchab

The stock market prediction has always been crucial for stakeholders, traders and investors. We developed an ensemble Long Short Term Memory (LSTM) model that includes two-time frequencies (annual and daily parameters) in order to predict the next-day Closing price (one step ahead). Based on a four-step approach, this methodology is a serial combination of two LSTM algorithms. The empirical experiment is applied to 417 NY stock exchange companies. Based on Open High Low Close metrics and other financial ratios, this approach proves that the stock market prediction can be improved.

Associating Ridesourcing with Road Safety Outcomes: Insights from Austin Texas
Eleftheria Kontou,Noreen C. McDonald

Improving road safety and setting targets for reducing traffic-related crashes and deaths are highlighted as part of the United Nation's sustainable development goals and vision zero efforts around the globe. The advent of transportation network companies, such as ridesourcing, expands mobility options in cities and may impact road safety outcomes. In this study, we analyze the effects of ridesourcing use on road crashes, injuries, fatalities, and driving while intoxicated (DWI) offenses in Travis County Texas. Our approach leverages real-time ridesourcing volume to explain variation in road safety outcomes. Spatial panel data models with fixed effects are deployed to examine whether the use of ridesourcing is significantly associated with road crashes and other safety metrics. Our results suggest that for a 10% increase in ridesourcing trips, we expect a 0.12% decrease in road crashes (p<0.05), a 0.25% decrease in road injuries (p<0.001), and a 0.36% decrease in DWI offenses (p<0.0001) in Travis County. Ridesourcing use is not associated with road fatalities at a 0.05 significance level. This study augments existing work because it moves beyond binary indicators of ridesourcing presence or absence and analyzes patterns within an urbanized area rather than metropolitan-level variation. Contributions include developing a data-rich approach for assessing the impacts of ridesourcing use on our transportation system's safety, which may serve as a template for future analyses of other US cities. Our findings provide feedback to policymakers by clarifying associations between ridesourcing use and traffic safety, while helping identify sets of actions to achieve safer and more efficient shared mobility systems.

Behavioral and Game-Theoretic Security Investments in Interdependent Systems Modeled by Attack Graphs
Mustafa Abdallah,Parinaz Naghizadeh,Ashish R. Hota,Timothy Cason,Saurabh Bagchi,Shreyas Sundaram

We consider a system consisting of multiple interdependent assets, and a set of defenders, each responsible for securing a subset of the assets against an attacker. The interdependencies between the assets are captured by an attack graph, where an edge from one asset to another indicates that if the former asset is compromised, an attack can be launched on the latter asset. Each edge has an associated probability of successful attack, which can be reduced via security investments by the defenders. In such scenarios, we investigate the security investments that arise under certain features of human decision-making that have been identified in behavioral economics. In particular, humans have been shown to perceive probabilities in a nonlinear manner, typically overweighting low probabilities and underweighting high probabilities. We show that suboptimal investments can arise under such weighting in certain network topologies. We also show that pure strategy Nash equilibria exist in settings with multiple (behavioral) defenders, and study the inefficiency of the equilibrium investments by behavioral defenders compared to a centralized socially optimal solution.

Bundling weather index-based crop insurance and credit: A Cautionary Tale against Misunderstood and Misinformed Take-Up
Syll, Mame Mor Anta,Weingärtner, Lena
The initial purpose of this study was to evaluate the effect of different bundling options of weather index-based crop insurance with agricultural credit on levels of insurance take-up. In a randomised controlled trial, 371 loan applicants were offered credit-linked insurance in three different ways: (1) mandatory bundling of products and incentivising insurance take-up by making it a partial supplement to loan collateral, (2) voluntary insurance with the same incentive and (3) voluntary insurance without incentive. However, we will quickly realize that the take-up of the bundle is mostly related to an issue of understanding, level of knowledge or information interpretation rather than to the way of bundling. Though the level of take-up appeared to be high, no matter the bundling option, results revealed that it was a misunderstood take-up based on the insufficient level of information or inappropriate interpretation of it. More effort is hence needed from development stakeholders to make sure the product value of insurance, namely a risk transfer instrument, is fully grabbed by farmers who purchase it.

Conditional Correlations and Principal Regression Analysis for Futures
Armine Karami,Raphael Benichou,Michael Benzaquen,Jean-Philippe Bouchaud

We explore the effect of past market movements on the instantaneous correlations between assets within the futures market. Quantifying this effect is of interest to estimate and manage the risk associated to portfolios of futures in a non-stationary context. We apply and extend a previously reported method called the Principal Regression Analysis (PRA) to a universe of $84$ futures contracts between $2009$ and $2019$. We show that the past up (resp. down) 10 day trends of a novel predictor -- the eigen-factor -- tend to reduce (resp. increase) instantaneous correlations. We then carry out a multifactor PRA on sectorial predictors corresponding to the four futures sectors (indexes, commodities, bonds and currencies), and show that the effect of past market movements on the future variations of the instantaneous correlations can be decomposed into two significant components. The first component is due to the market movements within the index sector, while the second component is due to the market movements within the bonds sector.

Constructing a Social Accounting Matrix Framework to Analyse the Impact of Public Expenditure on Income Distribution in Malaysia
Mukaramah Harun,A.R. Zakariah,M. Azali

The use of the social accounting matrix (SAM) in income distribution analysis is a method recommended by economists. However, until now, there have only been a few SAM developed in Malaysia. The last SAM produced for Malaysia was developed in 1984 based upon data from 1970 and has not been updated since this time despite the significance changes in the structure of the Malaysian economy. The paper proposes a new Malaysian SAM framework to analyse public expenditure impact on income distribution in Malaysia. The SAM developed in the present paper is based on more recent data, providing an up-to date and coherent picture of the complexity of the Malaysian economy. The paper describes the structure of the SAM framework with a detailed aggregation and disaggregation of accounts related to public expenditure and income distribution issues. In the SAM utilized in the present study, the detailed framework of the different components of public expenditure in the production sectors and household groups is essential in the analysis of the different effects of the various public expenditure programmes on the incomes of households among different groups.

Debt Dynamics and Default Probabilities
Hackbarth, Dirk,Kitapbayev, Yerkin
We derive a simple integral equation for the default probability over a finite time horizon of a company that makes coupon payments on its debt and infrequently returns to its leverage target by increasing its debt unless it defaults on its debt. Compared to the conventional (constant default barrier) formula, our formula permits the default barrier to change dynamically (i.e., is ratcheted up) over time. Hence it addresses the misspecification problem stemming from existing default probability predictions that do not take into the account that firms alter (optimally) their capital structure. We quantify the importance of our solution by (i) comparing it to the correct formula for a static model and (ii) analyzing default probabilities for different dynamic models.

Diverse Risk Preferences and Heterogeneous Expectations in an Asset Pricing Model
Gomez, Thomas,Piccillo, Giulia
We propose a heuristic switching model of an asset market where the agents’ choice of heuristic is consistent with their individual risk aversion. They choose between a fundamentalist and a trend-following rule to form expectations about the price of a risky asset. Given their risk aversion, agents make a deterministic trade-off between mean and variance both in choosing a forecasting heuristic and determining the number of risky assets to buy. Heterogeneous risk preferences can lead to diverse choices of heuristic. Using empirical estimates for the distribution of risk aversion, simulations show that the resulting time-varying heterogeneity of expectations can give rise to chaotic dynamics: irregular booms and busts in the asset price without exogenous shocks. Small, stochastic price shocks lead to larger asset price bubbles, and can make stable solutions explosive. We prove that a representative agent cannot capture our model.

Does Non-Farm Income Improve The Poverty and Income Inequality Among Agricultural Household In Rural Kedah?
Siti Hadijah Che Mata,Ahmad Zafarullah Abdul Jalil,Mukaramah Harun

This paper used a primary data collected through a surveys among farmers in rural Kedah to examine the effect of non farm income on poverty and income inequality. This paper employed two method, for the first objective which is to examine the impact of non farm income to poverty, we used poverty decomposition techniques - Foster, greer and Thorbecke (FGT) as has been done by Adams (2004). For the second objective, which is to examine the impact of non farm income to income inequality, we used Gini decomposition techniques.

Dynamic Interaction between Shared Autonomous Vehicles and Public Transit: A Competitive Perspective
Baichuan Mo,Zhejing Cao,Hongmou Zhang,Yu Shen,Jinhua Zhao

The emergence of autonomous vehicles (AVs) is anticipated to influence the public transportation (PT) system. Many possible relationships between AV and PT are proposed depending on the policy and institution, where competition and cooperation are two main categories. This paper focuses on the former in a hypothetical scenario-"if both AV and PT operators were only profit-oriented." We aim to quantitatively evaluate the system performance (e.g. level of service, operators' financial viability, transport efficiency) when AV and PT are profit-oriented competitors with dynamic adjustable supply strategies under certain policy constraints. We assume AV can adjust the fleetsize and PT can adjust the headway. Service fare and bus routes are fixed. The competition process is analyzed through an agent-based simulation platform, which incorporates a proposed heuristic dynamic supply updating algorithm (HDSUA). The first-mile scenario in Singapore Tampines area is selected as the case study, where only bus is considered for PT system. We found that when AV and bus operators are given the flexibility to adjust supply, both of them will re-distribute their supply spatially and temporally, leading to higher profits. In temporal dimension, both AV and bus will concentrate their supplies in morning and evening peak hours, and reduce the supplies in off-peak hours. The competition between AV and PT decreases passengers' travel time but increase their travel cost. The generalized travel cost is still reduced when counting the value of time. The bus supply adjustment can increase the bus average load and reduce total passenger car equivalent (PCE), which is good for transport efficiency and sustainability. But the AV supply adjustment shows the opposite effect. Overall, the competition does not necessarily bring out loss-gain results. A win-win outcome is also possible under certain policy interventions.

How does Soft Information Affect External Firm Financing? Evidence from Online Employee Ratings
Chemmanur, Thomas J.,Rajaiya, Harshit,Sheng, Jinfei
We analyze the effects of equity market investors having access to soft information, such as online employee ratings of firms, on their external financing and investment policies. We develop testable hypotheses using a theoretical framework in which the insiders of a firm have private information about its intrinsic value, but where outsiders have access to soft information signals imperfectly correlated with this intrinsic firm value. We test these hypotheses using a large sample of around 1.1 million employee ratings from the Glassdoor website covering a sample of 2842 public firms during 2008 to 2017. We find that firms with higher average online employee rating realizations are associated with algebraically greater abnormal stock returns upon an equity issue announcement; a greater propensity to have positive abnormal stock returns upon such an announcement; a greater propensity to issue equity rather than debt to raise external financing; higher annual investment expenditures; greater participation by institutional investors in their seasoned equity offerings (SEOs); and better long-run post-SEO operating performance. Our identification strategy makes use of a difference-in-differences (DID) methodology relying on the staggered implementation of laws protecting the First Amendment Rights of citizens (anti-SLAPP laws) across US states.

MUHASEBENIN TARIHINE KÃœRESEL KAPSAMDA ve TÃœRKÄ°YE KAPSAMINDA VERGÄ°SEL BlR BAKIÅž (A Taxational Overlook to the History of Accounting from a Global and Turkish Extent)
Kizil, Cevdet,Akman, Vedat,Zorkalkan, Tamer,Türkmen, Ramazan
Turkish Abstract: Bu çalışmada, muhasebenin tarihi küresel perspektif ve Türkiye perspektifinde vergiyle ilişkili olarak ayrıntılı şekilde incelenmiştir. Araştırmada, kronolojik olarak muhasebenin gelişim evresi ele alınarak, Dünya'da ve Türkiye'de muhasebe tarihinde dönüm noktası olarak tanımlanan olayları tetikleyen nedenler tartışılmıştır. Çalışmanın sonunda, genel bir değerlendirme yapılmıştır ve küresel kapsam ile Türkiye kapsamında karşılaştırmalara yer verilmiştir. Çalışmanın metodolojisi literatür taramasıdır. Araştırmanın sonuçlarına göre, Türkiye' de muhasebe anlayışı hem teorik hem de pratik olarak son yıllarda büyük aşama kaydetmiştir. Ancak, hala bir takım eksiklikler ve iyileştirilmesi gereken hususlar vardır.English Abstract: In this study, the history of accounting is analyzed in detail from a global and Turkish perspective related to taxation. The research mentions the development phases of accounting in a chronologic order. Also, reasons which have triggered the milestone incidents and events for the history of accounting in the world and Turkey are discussed. At the end of study, a general evaluation is made and comparisons are stated in a global and Turkish content. The methodology of research is literature review. According to the results of study, the accounting understanding and approach in Turkey have improved significantly in the recent years both theoretically and practically. However, some missing points andflaws still exist in addition to further potential issues, which should be improved.

Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility
Caporale, Guglielmo Maria,Karanasos, Menelaos,Yfanti, Stavroula
This paper estimates a bivariate HEAVY system including daily and intra-daily volatility equations and its macro-augmented asymmetric power extension. It focuses on economic factors that exacerbate stock market volatility and represent major threats to financial stability. In particular, it extends the HEAVY framework with powers, leverage, and macro effects that improve its forecasting accuracy significantly. Higher uncertainty is found to increase the leverage and macro effects from credit and commodity markets on stock market realized volatility. Specifically, Economic Policy Uncertainty is shown to be one of the main drivers of US and UK financial volatility alongside global credit and commodity factors.

Macroeconomic Instability And Fiscal Decentralization: An Empirical Analysis
Ahmad Zafarullah Abdul Jalil,Mukaramah Harun,Siti Hadijah Che Mat

The main objective of this paper is to fill a critical gap in the literature by analyzing the effects of decentralization on the macroeconomic stability. A survey of the voluminous literature on decentralization suggests that the question of the links between decentralization and macroeconomic stability has been relatively scantily analyzed. Even though there is still a lot of room for analysis as far as the effects of decentralization on other aspects of the economy are concerned, we believe that it is in this area that a more thorough analyses are mostly called for. Through this paper, we will try to shed more light on the issue notably by looking at other dimension of macroeconomic stability than the ones usually employed in previous studies as well as by examining other factors that might accentuate or diminish the effects of decentralization on macroeconomic stability. Our results found that decentralization appears to lead to a decrease in inflation rate. However, we do not find any correlation between decentralization with the level of fiscal deficit. Our results also show that the impact of decentralization on inflation is conditional on the level of perceived corruption and political institutions.

Noncooperative dynamics in election interference
David Rushing Dewhurst,Christopher M. Danforth,Peter Sheridan Dodds

Foreign power interference in domestic elections is an existential threat to societies. Manifested through myriad methods from war to words, such interference is a timely example of strategic interaction between economic and political agents. We model this interaction between rational game players as a continuous-time differential game, constructing an analytical model of this competition with a variety of payoff structures. All-or-nothing attitudes by only one player regarding the outcome of the game lead to an arms race in which both countries spend increasing amounts on interference and counter-interference operations. We then confront our model with data pertaining to the Russian interference in the 2016 United States presidential election contest. We introduce and estimate a Bayesian structural time series model of election polls and social media posts by Russian Twitter troll accounts. Our analytical model, while purposefully abstract and simple, adequately captures many temporal characteristics of the election and social media activity. We close with a discussion of our model's shortcomings and suggestions for future research.

QCNN: Quantile Convolutional Neural Network
Gábor Petneházi

Convolutional neural networks can do time series forecasting. They can learn local patterns in time, and they can be modified to learn only from the history (ignoring the future) and to use a long look-back window when doing so. A further simple modification enables them to forecast not the mean, but arbitrary quantiles of the distribution. And one last thing to make this all work: the CNN forecaster's complexity and flexibility requires much data, that is, preferably multiple time series. When this is met, the proposed QCNN framework can be competitive. It is demonstrated on a financial problem of huge practical importance: Value at Risk forecasting. By contributing to the stability of financial systems, deep learning may find one further way to improve our lives.

Semimartingale price systems in models with transaction costs beyond efficient friction
Christoph Kühn,Alexander Molitor

A standing assumption in the literature on proportional transaction costs is efficient friction. Together with robust no free lunch with vanishing risk, it rules out strategies of infinite variation, as they usually appear in frictionless markets. In this paper, we show how the models with and without transaction costs can be unified.

The bid and the ask price of a risky asset are given by c\'adl\'ag processes which are locally bounded from below and may coincide at some points. In a first step, we show that if the bid-ask model satisfies "no unbounded profit with bounded risk" for simple strategies, then there exists a semimartingale lying between the bid and the ask price process.

In a second step, under the additional assumption that the zeros of the bid-ask spread are either starting points of an excursion away from zero or inner points from the right, we show that for every bounded predictable strategy specifying the amount of risky assets, the semimartingale can be used to construct the corresponding self-financing risk-free position in a consistent way.

Text as Data: Real-time Measurement of Economic Welfare
Rickard Nyman,Paul Ormerod

Economists are showing increasing interest in the use of text as an input to economic research. Here, we analyse online text to construct a real time metric of welfare. For purposes of description, we call it the Feel Good Factor (FGF). The particular example used to illustrate the concept is confined to data from the London area, but the methodology is readily generalisable to other geographical areas. The FGF illustrates the use of online data to create a measure of welfare which is not based, as GDP is, on value added in a market-oriented economy. There is already a large literature which measures wellbeing/happiness. But this relies on conventional survey approaches, and hence on the stated preferences of respondents. In unstructured online media text, users reveal their emotions in ways analogous to the principle of revealed preference in consumer demand theory. The analysis of online media offers further advantages over conventional survey-based measures of sentiment or well-being. It can be carried out in real time rather than with the lags which are involved in survey approaches. In addition, it is very much cheaper.

The Logic of Strategic Assets: From Oil to Artificial Intelligence
Jeffrey Ding,Allan Dafoe

What resources and technologies are strategic? This question is often the focus of policy and theoretical debates, where the label "strategic" designates those assets that warrant the attention of the highest levels of the state. But these conversations are plagued by analytical confusion, flawed heuristics, and the rhetorical use of "strategic" to advance particular agendas. We aim to improve these conversations through conceptual clarification, introducing a theory based on important rivalrous externalities for which socially optimal behavior will not be produced alone by markets or individual national security entities. We distill and theorize the most important three forms of these externalities, which involve cumulative-, infrastructure-, and dependency-strategic logics. We then employ these logics to clarify three important cases: the Avon 2 engine in the 1950s, the U.S.-Japan technology rivalry in the late 1980s, and contemporary conversations about artificial intelligence.

The Role Of Cross Selling In SME Banking: An Analysis from Turkey
Karadag, Hande,Akman, Vedat
Non-lending activities in SME financing is a phenomenon whose significance has recently been recognized. Provision of different products and services to companies is becoming an important profit center for banks serving SMEs and the supply side of SME financing has been experiencing a shift towards fee-based products and services, mainly due to the risks and challenges associated with SME lending. Despite these important developments in the industry, there are a limited number of studies that focus on the bank activities related with cross-selling to SMEs. This paper aims to address this gap in the literature, by investigating the role of cross selling in SME banking by analyzing the major business models and strategies both at international and local contexts. The study targets to make important contributions to SME finance and in particular SME banking literature, as it highlights the changing market structure in the supply-side of SME banking and pinpoints how best practices in international banking system can form examples for banks that prioritize growth in SME segment.

Tournament Incentives and Reserve Management
Nart, Ahmet,Lai, Gene C.,Ho, Chia-Ling
This paper examines the relation between tournament incentives and reserve management. We find a positive relation between internal tournament incentives and reserve errors, implying that a larger pay gap as a tournament prize induces vice presidents (VPs) to overestimate loss reserves. In other words, a higher tournament prize is associated with conservative loss reserve management. Unlike the literature, we do not find a positive relation between tournament incentive and profits (risk taking behavior). Taken together, the evidence indicates that VPs focus on strong financial health of the firm instead of its profitability. In addition, we find the impact of internal tournament incentives on the reserve error is more pronounced for larger, financially weak and more geographically focused firms, and is mitigated for the firms with higher percentage of claim loss reserve over total liability and paying relatively higher tax rates. Our results also suggest that SOX mitigates the conservative reserve behavior. Finally, we also find that as board independence enhances, VPs induced by promotion-based tournaments become more likely to have conservative reserve behavior.

Türkiye’de Referans (Gösterge) Faiz Oluşturulması: Türk Lirası Gecelik Referans Faiz Oranı (TLREF) Üzerine Bir İnceleme [Launching Reference (Benchmark) Interest Rate in Turkey: A Conceptual Examination upon Turkish Lira Overnight Reference Interest Rate (TLREF)]
Kartal, Mustafa Tevfik
Turkish Abstract: Makroekonomik göstergeler, ekonomilerin genel durumunu yansıtan önemli araçlardır. Büyüme, enflasyon ve işsizlik gibi göstergeler farklı değişkenlerden etkilenmektedir. Buna karşın, faiz oranları tüm makroekonomik göstergeleri pozitif veya negatif etkileyen en önemli değişkenlerden biridir. Faiz oranlarındaki değişimler tüm finansal piyasaları ve ekonomik aktörleri derinden etkilemektedir. 13 Eylül 2019 tarihi itibarıyla Türkiye’de politika faizi %16,5, ortalama ticari kredi faizi %20,39, ortalama mevduat faizi ise %16,63 seviyesindedir. 2021 yılsonunda LIBOR son bulacağı için ülkeler ulusal referans faiz oranlarını ilan etmeye yönelik çalışmalar yapmaklardır. Türkiye’de ise TRLIBOR, politika faizi, kredi faizi, mevduat faizi, tahvil-bono faizi gibi birçok farklı faiz türü bulunmakla birlikte piyasada gerçekleşen işlemlere dayalı olarak hesaplanan bir referans faiz oranı bulunmamaktadır. Bu eksikliğin giderilmesi ve LIBOR sonrası dönem için Borsa İstanbul (BİST) tarafından 17.06.2019 tarihinde TLREF ilan edilmeye başlanmıştır. İlk TLREF %24,82 olarak yayınlanmış olup 13.09.2019 tarihinde ise %16,19 olarak gerçekleşmiştir. Türkiye’de politika faizinin, ticari kredi faizinin ve diğer faiz türlerinin gerçekleşme seviyesi dikkate alındığında TLREF piyasa koşullarını yansıtan ve derinliğe sahip bir referans faiz oranıdır. Önümüzdeki dönemde finansal kuruluşların TLREF’e dayalı finansal ürünler sunmasıyla birlikte TLREF’in ulusal referans faiz oranı niteliği daha da güçlenecektir.English Abstract: Macroeconomic indicators are important tools that reflect the general condition of economies. Indicators such as growth, inflation and unemployment are affected by different variables. On the other hand, interest rates are one of the most important variables affecting all macroeconomic indicators positively or negatively. Changes in interest rates deeply affect all financial markets and economic actors. Policy rate is at the level of 16.5%, average interest rate of commercial loans is at the level of 20.39%, and average deposit interest rate is at the level of 16.63% in Turkey as of 13 September 2019. As LIBOR will be terminated in 2021 year end, countries have been conducting efforts to launch national reference interest rates. In Turkey, although there are a variety of interest rate types such as TRLIBOR, policy rate, loan interest, deposit interest, bonds-bill interest, there is not a reference interest rate to be calculated based on transactions made in market. In order to eliminate this deficiency and preparation for the period after LIBOR, TLREF has been started to be announced by Borsa Istanbul (BIST) on 06.17.2019. The first TLREF was launched as 24.82% and TLREF has become 16.19% on 09.13.2019. TLREF is a reference interest rate which reflects market conditions and has depth when taking into consideration the level of policy rate, commercial credits interest rate and other interest rates types. In the forthcoming period, national reference interest rate characteristic of TLREF will be strengthened with the introduction of TLREF-based financial products by financial institutions.