Research articles for the 2019-10-08
SSRN
Loans and Advance section of a bank is very important because the success of this department helps to increase its business. If this section does not properly work, the bank itself may become bankrupt. Bank makes loans and advances mostly to traders, businessmen, and industrialists. Although the nature of credit may differ in terms of security requirement, disbursement provision terms and conditions etc. To ensure secured banking Agrani Bank Limited works closely with its clients, the regulatory authorities, the shareholders, other banks and financial institutions. This bank recently achieved lots of milestones rather than other banks. The credit administration of this bank works very efficiently where loan documentation is performed by the experienced bankers. Presently the management is focusing on reducing Non-performing loans (NPLs) which is a big step of loan recovery. Apart from these, Agrani Bank Limited provides other services and some kinds of value added services for the welfare of the people. However, Loan and Advances is the most important asset as well as the primary sources of earning of a bank which help to improve financial health of a bank.
arXiv
The present paper is devoted to the study of a bank salvage model with finite time horizon and subjected to stochastic impulse controls. In our model, the bank's default time is a completely inaccessible random quantity generating its own filtration, then reflecting the unpredictability of the event itself. In this framework the main goal is to minimize the total cost of the central controller who can inject capital to save the bank from default. We address the latter task showing that the corresponding quasi-variational inequality (QVI) admits a unique viscosity solution, Lipschitz continuous in space and Holder continuous in time. Furthermore, under mild assumptions on the dynamics the smooth-fit $W^{(1,2),p}_{loc}$ property is achieved for any $1<p<+\infty$.
SSRN
Asset price bubbles have fascinated economists for decades. In consequence, the literature on bubbles and their detection is abundant, with many researchers taking very opposite positions on the topic, however. This survey gives a structured overview of the two branches of research that have received the most attention in bubble research. First, we describe the theoretical models that have been developed to model bubble phenomena. These can be divided into rational bubble models and behavioral bubble models. Second, we provide a structured overview of empirical methods for the detection of rational bubbles. We focus in particular on recently developed bubble detection methods, namely recursive unit root tests, fractional integration tests, and regime-switching tests. These tests are predominantly advanced stationarity and cointegration-based tests and as such are not based on the fundamental factors of the assets but rather focus on the time series of the asset prices. As a result, they avoid testing a joint hypothesis of the presence of rational bubbles and the validity of the model used to determine the assetâs value. Furthermore, they are capable of detecting multiple, periodically collapsing bubbles.While a consensus both on the appropriate theoretical bubble model as well as on the most applicable empirical bubble detection test has not been reached, especially empirical research has made significant progress. Different bubble detection tests now increasingly find overlapping evidence of rational bubbles when used to analyze the same time series. Nonetheless, many results are still inconclusive and bubbles remain an interesting avenue for further research.
SSRN
Over the past two decades, several corporates collapses and scandals led to track down any deficiencies of the traditional corporate governance mechanisms. These collapses and scandals include Enron (2001) and WorldCom (2002) in USA, Vivendi (2001) and Vinci (2006) in France, Parmalat (2003) in Italy, and most recently, Ecobank Transnational Incorporatedâs boardroom battle (2013) in West African Context. This chapter examines the relation between corporate governance mechanisms and operating performance and liquidity risk within the specific environment of West African Economic and Monetary Union (WAEMU) banks. The implementation of well-known western corporate governance mechanisms in emerging markets, which mostly focus on unsophisticated financial services, is likely to act more as operating constraints than value-creation factors. Based on a sample drawn from 100 commercial banks over the period 2006â"2010, we document the following four main findings: dual structure and board size are negatively and significantly associated with banksâ performance as proxied by Return on Assets (ROA) and Return on Equity (ROE), board size, board diversity and nature of ownership exhibit a negative and significant relation with banksâ liquidity risk, the presence of CEO in the directorsâ board appears to be the only corporate governance mechanism efficiently associated with banksâ liquidity risk, overall, the effects of the WAEMUâs banks corporate governance mechanisms on their operating performance and liquidity risk are significantly different if bank is in joint or single auditing setting (proxy for audit quality). This finding supports the view that audit quality is complementary to corporate governance mechanisms under the WAEMU context.
SSRN
This paper examines customer satisfaction in Islamic banks in Qatar in comparison with their conventional counterpart. It is an attempt to investigate whether Islamic banks have overcome the obstacle of being relatively new; whether they have started providing satisfying services to their customers or whether they act as taking advantage of their customersâ needs for Islamic finance products and treat them as captive clients who resort to Islamic banks for religious reasons. The research queries needed to be answered by the bankâs customers themselves to test their view of the services they get. A comprehensive comparative questionnaire was formulated. Responses from the questionnaire and other data collected from banksâ websites, personal interviews, etc., were analyzed. The paper conducted cross-sector comparisons of Islamic and conventional banking as well as individual comparisons between banks. Analysis of these results, computing averages and comparing them at the level of each bank as well as at the sectoral level between Islamic banks and conventional banks, was conducted. Through this, the paper attempts to uncover banksâ performance and find out all areas of improvements that the Islamic and conventional banks need to work on.
arXiv
Recognizing subtle historical patterns is central to modeling and forecasting problems in time series analysis. Here we introduce and develop a new approach to quantify deviations in the underlying hidden generators of observed data streams, resulting in a new efficiently computable universal metric for time series. The proposed metric is in the sense that we can compare and contrast data streams regardless of where and how they are generated and without any feature engineering step. The approach proposed in this paper is conceptually distinct from our previous work on data smashing, and vastly improves discrimination performance and computing speed. The core idea here is the generalization of the notion of KL divergence often used to compare probability distributions to a notion of divergence in time series. We call this the sequence likelihood (SL) divergence, which may be used to measure deviations within a well-defined class of discrete-valued stochastic processes. We devise efficient estimators of SL divergence from finite sample paths and subsequently formulate a universal metric useful for computing distance between time series produced by hidden stochastic generators.
SSRN
The rise of the gig economy has become an important trend in the labour market, and economists have recently started examining its macroeconomic impacts. Based on the aggregate time-series data from American Time Use Survey, this paper explores whether the gig economy has led to more flexible work arrangement and work-time allocation in three dimensions: (1) part-time/full-time; (2) work at home/in the workplace; (3) wage-salary work/self-employed. It suggests that there is a shift toward work-flexibility in terms of location in the United States over the past decade, i.e. people tend to work more at home versus at workplace, a trend mostly obvious among women, a full-time job and wage-salary workers. In contrast, the evidence for a shift toward part-time job and self-employment are less conclusive.
arXiv
Exchanges implement intentional trade delays to limit the harmful impact of low-latency trading. Do such "speed bumps" curb investment in fast trading technology? Data is scarce since trading technologies are proprietary. We build an experimental trading platform where participants face speed bumps and can invest in fast trading technology. We find that asymmetric speed bumps, on average, reduce investment in speed by only 20%. Increasing the magnitude of the speed bump by one standard deviation further reduces low-latency investment by 8.33%. Finally, introducing a symmetric speed bump leads to the same investment level as no speed bump at all.
SSRN
This study seeks to determine the effect of presidential elections on the stock market in Kenya. The methodology used is event study methodology and the study looks at the 2017 election period, specifically the August initial elections and the October re-election. The key variables are NSE20 and the stock prices of every listed stock during the specified event windows. The study analyses the market as a whole and further subdivides it into its various sectors in order to analyse how different sectors are affected differently. The study finds that in the chosen event windows, the market as a whole is affected positively by the announcement of the results of the elections. Some sectors such as the commercial & services, energy & petroleum, manufacturing & allied sector and the telecommunication & technology sectors are affected positively by the announcement of the results of the elections. The agricultural sector is the only sector that is affected negatively by the announcement of the election results in both event windows.
SSRN
The spread of distributed ledger technology (DLT) in finance could help to improve the efficiency and quality of supervision. This paper makes the case for embedded supervision, ie a regulatory framework that provides for compliance in tokenised markets to be automatically monitored by reading the market's ledger, thus reducing the need for firms to actively collect, verify and deliver data. After sketching out a design for such schemes, the paper explores the conditions under which distributed ledger data might be used to monitor compliance. To this end, a decentralised market is modelled that replaces today's intermediary-based verification of legal data with blockchain-enabled data credibility based on economic consensus. The key results set out the conditions under which the market's economic consensus would be strong enough to guarantee that transactions are economically final, so that supervisors can trust the distributed ledger's data. The paper concludes with a discussion of the legislative and operational requirements that would promote low-cost supervision and a level playing field for small and large firms.
arXiv
Recently (Assani et al. 2018) introduced the concept of the most productive scale size (MPSS) for multi-stage data envelopment analysis (DEA) systems which are connected in series. However, some real-life applications may have different structures. This paper investigates the MPSS measurements for systems consisting of multiple subsystems connected in parallel. New models for determining the MPSS of the system and the subsystems are proposed. It is proved that the MPSS of the system can be decomposed as the weighted sum of MPSS of the individual subsystems. The main result is that the system is overall MPSS if and only if it is MPSS in each subsystem. MPSS decomposition allows policymakers to target the non-MPSS subsystems of the production process in order to the subsequent improvements. An application of China Five-Year Plans (FYPs) is used to show the applicability of the proposed methods for estimating and decomposing MPSS in parallel network DEA. Industry and Agriculture sectors with shared inputs are considered as two subsystems in the FYPs. Interesting findings have been noticed. First, for an equal ratio of shared inputs (50 Industry: 50 Agriculture), the Industry sector achieved MPSS in 22 years compared to 17 years in Agriculture. In other words, using the same resources of population, GDP, and general government final consumption, the Industry sector is more stable and productive than the Agriculture sector. Second, the last two FYPs, 11th and 12th, were the perfect two FYPs among the others.
SSRN
In this paper, we investigate investors' expectations on economic growth and uncertainty risk implied by derivative securities. Empirical evidence on investors' expectations implied by derivative securities has been intensively studied in the U.S. and other developed markets, however, such evidence still seems to be rare for emerging markets. Using high frequency data of the Taiwan Stock Exchange (TAIEX) weighted index and its derivatives from Jan-02-2003 to Dec-31-2014, we construct time series of implied dividends, variance risk premium and higher risk-neutral moments. We find that term structure of the implied dividend yield and variance risk premium have some abilities on predicting the excess return of the TAIEX weighted index and growth of industrial production index of Taiwan. We also demonstrate that there is a strong and positive relation between the risk-neutral skewness and options slope, which is in line with what previous literature found in the U.S. stock market.
SSRN
The many regulatory reforms following the Great Financial Crisis of 2007-09 have most often been designed and adopted through an international cooperative process. As such, actions have tended to harmonise national approaches and diminish inconsistencies. Nevertheless, some market participants and policymakers have recently raised concerns over an unwanted and unnecessary degree of fragmentation in financial markets globally, with possibly adverse effects for financial stability. This paper reviews the degree of fragmentation in various markets and classifies its possible causes. It then reviews whether fragmentation is necessarily detrimental to financial stability, suggesting that, as is more likely, various trade-offs exist. To identify and assess the scope for Pareto improvements, it concludes by outlining areas for further analysis.
SSRN
Given the accelerating global popularity of the social enterprise concept as a response to the growing failings of neoliberal capitalism, there are increasing calls for deeper analysis of some of the leading social enterprises. One of the highest profile examples of a social enterprise is the microcredit institution AMK based in Cambodia. Using data and insights gathered during fieldwork in Cambodia in late 2017 and again in early 2019, as well as secondary data obtained elsewhere, this paper shows how AMK was willing and able to use professional marketing, friendly academics, and a supportive international development community in order to create a seductive narrative that it was âdoing well by doing goodâ. In fact, the impact of AMK, as in the case of the many other microcredit institutions in Cambodia and around the world, has been negative not just for its poor clients but for the wider community as well. Reckless lending leading to rising over-indebtedness and gradual land-loss are just two of the negative outcomes associated with the operation of the microcredit sector in Cambodia, and with AMK in particular. Until such problematic examples of a social enterprise are explicitly recognised for what they are and confronted by those promoting the concept with good intentions, the potential for the social enterprise format to be deployed as a genuine force for social impact will remain strictly limited.
SSRN
The use of contractual engineering to create channels of credit intermediation outside of the realm of banking regulation has been a recurring activity in Western financial systems over the last 50 years. After the financial crisis of 2007 and 2008, this phenomenon, at that time commonly referred to as âshadow bankingâ, evoked a large-scale regulatory backlash, including several specific regulatory constraints being placed on non-bank financial institutions (NBFI). This paper proposes a different avenue for regulators to keep regulatory arbitrage under control and preserve sufficient space for efficient financial innovation. Rather than engaging in the proverbial race between hare and hedgehog that is emerging with increasingly specific regulation of particular contractual arrangements, this paper argues for a normative approach to supervision. We outline this approach in detail by showing that regulators should primarily analyse the allocation of tail risk inherent in the respective contractual arrangements. Our paper proposes to assign regulatory burdens equivalent to prudential banking regulation, in case these arrangements become only viable through indirect or direct access to an (ad hoc) public backstop. In order to make the pivotal assessment, regulators will need information about recent contractual innovations and their risk-allocating characteristics. According to the scholarship on regulatory networks serving as communities of interpretation, we suggest in particular how regulators should structure their relationships with semi-public gatekeepers such as lawyers, auditors and consultants to keep abreast of the real-world implications of evolving transactional structures. This paper then uses the rise of credit funds as a non-bank entities economically engaged in credit intermediation to apply this normative framework, pointing to recent contractual innovations that call for more regulatory scrutiny in a multipolar regulatory dialogue.
arXiv
In the context of a randomized experiment with non-compliance, I identify treatment effects without exclusion restrictions. Instead of relying on specific experimental designs, I exploit a baseline survey which is commonly available in randomized control trials. I show the identification of the average treatment effect on the treated (ATT) as well as the local average treatment effect (LATE) assuming that a baseline variable maintains similar rank orders as the control outcome. I then apply this strategy to a microcredit experiment with one-sided non-compliance to identify the ATT. In microcredit studies, a direct effect of the treatment assignment has been a threat to identification of the ATT based on an IV strategy. I find the IV estimate of log revenue for the ATT is 2.3 times larger than my preferred estimate of log revenue. R package ptse is available for this analysis.
arXiv
We analyze the optimal control of disease prevention and treatment in a basic SIS model. We develop a simple macroeconomic setup in which the social planner determines how to optimally intervene, through income taxation, in order to minimize the social cost, inclusive of infection and economic costs, of the spread of an epidemic disease. The disease lowers economic production and thus income by reducing the size of the labor force employed in productive activities, tightening thus the economy's overall resources constraint. We consider a framework in which the planner uses the collected tax revenue to intervene in either prevention (aimed at reducing the rate of infection) or treatment (aimed at increasing the speed of recovery). Both optimal prevention and treatment policies allow the economy to achieve a disease-free equilibrium in the long run but their associated costs are substantially different along the transitional dynamic path. By quantifying the social costs associated with prevention and treatment we determine which policy is most cost-effective under different circumstances, showing that prevention (treatment) is desirable whenever the infectivity rate is low (high).
SSRN
We show that managers can significantly lower corporate borrowing costs by adjusting effective tax rates. While prior research suggests a positive linear relation between tax avoidance and cost of debt, we document a U-shaped relationship in which bondholders reward âundershelteringâ firms with a decreasing cost of debt for increasing their tax avoidance until a point at which the relationship reverses. As firms move toward the most aggressive tax avoidance levels, their cost of debt increases. Our study is the first we are aware of to provide evidence of a non-linear, U-shaped relation between tax avoidance and cost of debt. Additionally, we provide evidence suggesting that managers benefit with lower costs of debt (average yield savings of 1.37%) by benchmarking their firmâs tax avoidance relative to their industry peers.
arXiv
In Chinese societies, superstition is of paramount importance, and vehicle license plates with desirable numbers can fetch very high prices in auctions. Unlike other valuable items, license plates are not allocated an estimated price before auction. I propose that the task of predicting plate prices can be viewed as a natural language processing (NLP) task, as the value depends on the meaning of each individual character on the plate and its semantics. I construct a deep recurrent neural network (RNN) to predict the prices of vehicle license plates in Hong Kong, based on the characters on a plate. I demonstrate the importance of having a deep network and of retraining. Evaluated on 13 years of historical auction prices, the deep RNN's predictions can explain over 80 percent of price variations, outperforming previous models by a significant margin. I also demonstrate how the model can be extended to become a search engine for plates and to provide estimates of the expected price distribution.
SSRN
Given capital market imperfections, an entrepreneur can alleviate financial frictions by creating a pyramidal business group in which a parent firm offers its subsidiary firm internal finance. This endogenous creation of pyramidal business groups can beget asymmetric financial frictions between business-group firms and stand-alone firms. I build a model to show that these asymmetric financial frictions can have sizable effects on resource allocation. On one hand, the financial advantage of pyramidal business groups can foster productive firms by incorporating them as subsidiaries. On the other hand, the asymmetrically large amount of external capital controlled by pyramidal business groups can be expended by unproductive business-group firms and push up the equilibrium price of capital. The model suggests that with fine investor protection or low financial frictions, the benefits of pyramidal business groups can be dominated by their costs because the probability of fostering productive subsidiaries diminishes as the efficiency of external capital markets improves, while the prevalence of pyramidal business groups is not attenuated due to their continuing asymmetric financial advantage.
SSRN
This paper examines how ownership characteristics affect the performance of small and medium technology startups in Russia. We focus on how different types of owners (e.g. founders, state, venture capital and corporate firms) contribute to startup performance. Using an unbalanced panel of startups from Skolkovo, the largest Russian innovation cluster, from 2010 to 2016, we found evidence of a negative relationship between a support from government-related organisations and chosen indicators of startup performance. Our findings confirmed the positive impact of venture capital on ROA, especially for the Space cluster startups. While family members as owners were not found to have a significant impact on startups, we identified a positive contribution from managerial ownership to ROA. The study highlights the importance of other ownership characteristics, which were found to be significant in previous studies of emerged markets. We discuss potential interpretations of the findings and provide strategic management insights for startup owners and investors.
SSRN
Supervisory governance is believed to affect financial stability. While the literature has identified pros and cons of having a central bank or a separate agency responsible for microprudential banking supervision, the advantages of having this task shared by both institutions have received considerably less attention in the literature. Shared supervision has however inherent benefits for the stability of the banking system, as it increases the costs of supervisory capture: capturing a single supervisor, be it the central bank or an agency, has in fact lower costs than capturing two. Nevertheless, while this argument has been proposed theoretically, it has never been tested empirically. This paper fills this void introducing a new dataset on the supervisory governance of 116 countries from 1970 to 2016. It finds that, while nonperforming loans are not significantly affected by supervisory governance per se, they are significantly lower in countries where supervision is shared and the risk of capture is high. This last result, which is robust to a number of controls and robustness checks, proves new evidence in support of the detrimental impact of shared supervision on supervisory capture.
arXiv
In economics literature, it is accepted that all people are rational and they try to maximize their utilities as possible as they can. In addition, economic theories are formed with the assumptions not suitable to real life. For instance, indifference curves are drawn with the assumptions that there are two goods, people are rational, more is preferred to less and so on. Hence, the consumer behaviors are guessed according to this analysis. Nevertheless, these are invalid in real life. And this inconsistencey are examined by behavioral economics and neuroeconomics. Behavioral economics claims that people can behave what they are not expected since people can be irrational, their willpower is limited and altruistic behaviors can be seen and they can give more value to what they own. As a result of these, consumer behaviors become more different than that of economic theory. In addition to behavioral economics, neuroeconomics also examines consumer behaviors more differently than mainstream economic theory. It emphasizes the people using prefrontial cortex of the brain are more rational than the people using hippocampus of the brain. Therefore, people can make illogical choices compared to economic theory. In these cases, levying taxes such as personal income tax or value added tax can be ineffective or effective. In other words, the effect becomes ambigious. Hence,the hypothesis that if government desires to levy personal income tax or value added tax, it makes a detailed research in terms of productivity of taxes forms the fundamental of this study.
SSRN
This paper examines whether monetary policy reaction function matters for financial stability. We measure how responsive the Federal Reserve's policy appears to be to imbalances in the equity, housing and credit markets. We find that changes in these policy sensitivities predict the later development of financial imbalances. When monetary policy appears to respond more countercyclically to market overheating, imbalances tend to decline over time. This effect is distinct from that of current and anticipated interest rate levels - the risk-taking channel. The evidence highlights the importance of a "policy reaction function" channel of monetary policy in shaping the financial cycle.
SSRN
Prior research shows that firms tend to recruit directors from the geographically-proximate area. Due to a limited supply of qualified individuals in a given area, firms located in close proximity have to share a limited pool of talented individuals. As a result, the larger the number of firms in the same area, the fewer directors each firm in the area is able to obtain on average. Consistent with this notion, our results show that firms located in a zip code with a larger number of other firms exhibit significantly smaller board size. We then exploit the variation in the numbers of firms across the zip codes and estimate the effects of board size on various corporate outcomes. Our results show that larger board size leads to lower firm value, lower accounting profitability, higher leverage, higher dividend payouts, and a stronger propensity to be an acquirer.
arXiv
We extend the scope of the vol-of-vol expansion given in [27] from finite dimensional stochastic volatility models to infinite dimensional (rough) forward variance models and provide new explicit representations of the push-down Malliavin weights that simplifies the computations and provides new insights into their structure. This will validate the Bergomi-Guyon expansion for a large class of forward variance models.