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This report attempts to look into the future of the global monetary system. The history and development of fiat currencies is reviewed, their strengths and weaknesses are presented, causing market stability or instability and recession, respectively. Attention is paid to the global processes affecting the traditional money markets and the accumulated experience of the institutions to deal with the crises. The increasing digitization in the industry, the economy and the daily life of every single person inevitably gives rise to the need for the use of digital currency to guarantee transactions between individual parties. The idea for these still unrealized needs was born nearly 40 years ago, and the first realization took place in 1996, when e-gold was born. Today, we have hundreds of cryptocurrencies that still operate in an unregulated market, and their legal status still varies from country to country. The desire of individual countries and banking institutions to start their legally regulated use by already developing and testing their own currencies is presented. [ABSTRACT FROM AUTHOR]

Objective/context: The boom-and-bust of New World slavery in the nineteenth century has always been a major topic of scholarship. In this essay, I suggest that the literature devoted to this theme, the so-called “capitalism and slavery debate,” has made capital invisible as a category of analysis due to its over-reliance on classical and neoclassical economics. As a result, slavery itself has been poorly historicized. My purpose is to put forth an alternative framework to restore the historicity of capital and slavery. Methodology: The article explores critical value theory to conceptualize capital and capitalism in historically meaningful terms. It argues that value creation is never confined to one country. It requires a historically transnational social formation that turns concrete labor into abstract labor and use-values into commodities through the multi-scale operatives of world money and world markets. The history of slavery should be narrated within this broader globalizing setting. Originality: The article’s claim is that the global value relations of industrial capital redetermined spatial relations between town and country, capital and labor, and production and consumption, engendering overlapping layers of a world geography of accumulation that both stimulated and challenged slavery. Conclusions: While most scholars present the relation between slavery and capitalism as constant for the period 1780-1880, I conclude that New World slavery went through two moments of boom-and-bust (c.1780-c.1820 and c.1830-1880), which were formed through, respectively, the global value relations of cotton production and coal-and-iron industrialism. [ABSTRACT FROM AUTHOR]

Hot money is generally associated with economic and financial turmoil in emerging economies. In this backdrop, a number of studies document the causal links between hot money and financial markets. Accordingly, the study examines the causal relationship among hot money, equities, and real estate assets in the small-scale economy of Pakistan. For this purpose, we employ various time series techniques such as the JJ Co-integration test, Granger causality tests, Impulse Response Functions (IRF), and Variance Decomposition Analysis (VDC). The findings validate the long-term association between speculative funds and underlying investment markets. The results uncover unidirectional causality from investment markets to hot money in Pakistan. However, the lack of a bi-directional relationship among the underlying variables indicates that hot money is not a major driver of soaring prices in equities and real estate assets. Alternatively, developing the underlying markets attracts speculative cash inflows into the economy. The findings of the study highlight some useful implications for investors and regulators. For instance, the study's findings present valuable insights for international investors seeking diversification opportunities in small-scale economies such as Pakistan. Also, the regulators in the underlying economy can utilize the study findings to formulate an optimal model to manage international capital flows. [ABSTRACT FROM AUTHOR]

In this paper, we present a robust predictive comparison of several continuous-time multi-factor models in the context of interbank rates. Recognizing the specific dynamics of the short-term segment of the yield curve, we examine the U.S. money market by extending two continuous-time frameworks with different factor structures, the Chan-Karolyi-Longstaff-Sanders (CKLS) model and the arbitrage-free dynamic Nelson-Siegel (AFDNS) model. A battery of formal forecasting accuracy tests is employed to select a subset of superior predictive models. Despite a better goodness-of-fit measure, additional factors improve the forecasting performance only for the CKLS family. With implications for monetary policy formulation, we found evidence of two separate maturity segments as the three-factor AFDNS and the five-factor CKLS models outperform parsimonious benchmarks in predicting the interbank rates for very short maturities. Our comparative forecasting results are re-confirmed with stronger out-of-sample performance for the five-factor CKLS model when the post global financial crisis sub-sample is analyzed. [ABSTRACT FROM AUTHOR]

At present, check transactions are one of the most common forms of money transfer in the market. The information for check exchange is printed using magnetic ink character recognition (MICR), widely used in the banking industry, primarily for processing check transactions. However, the magnetic ink card reader is specialized and expensive, resulting in general accounting departments or bookkeepers using manual data registration instead. An organization that deals with parts or corporate services might have to process 300 to 400 checks each day, which would require a considerable amount of labor to perform the registration process. The cost of a single-sided scanner is only 1/10 of the MICR; hence, using image recognition technology is an economical solution. In this study, we aim to use multiple features for character recognition of E13B, comprising ten numbers and four symbols. For the numeric part, we used statistical features such as image density features, geometric features, and simple decision trees for classification. The symbols of E13B are composed of three distinct rectangles, classified according to their size and relative position. Using the same sample set, MLP, LetNet-5, Alexnet, and hybrid CNN-SVM were used to train the numerical part of the artificial intelligence network as the experimental control group to verify the accuracy and speed of the proposed method. The results of this study were used to verify the performance and usability of the proposed method. Our proposed method obtained all test samples correctly, with a recognition rate close to 100%. A prediction time of less than one millisecond per character, with an average value of 0.03 ms, was achieved, over 50 times faster than state-of-the-art methods. The accuracy rate is also better than all comparative state-of-the-art methods. The proposed method was also applied to an embedded device to ensure the CPU would be used for verification instead of a high-end GPU. [ABSTRACT FROM AUTHOR]

This paper evaluates the roles of short- and long-term private and government interest rates and inside and outside money in the monetary transmission mechanism. With money and credit markets present, changes in monetary policy set off a chain of relative price and portfolio adjustments affecting output and prices. I study interest rate and money supply rules within this monetary transmission mechanism by estimating several Markov-switching Bayesian vector autoregressions (MS-BVARs) on a quarterly U.S. sample from 1960 to 2018. The best-fit MS-BVAR restricts MS to the impact and lag coefficients of the monetary policy and money demand regressions as well as to the stochastic volatilities (SVs) of the structural shocks. Estimates of this MS-BVAR yield evidence of a SV regime which coincides with NBER-dated recessions. This MS-BVAR also identifies a regime switch in the Fed's interest rate rule and banks' demand for outside money around the dot-com bust of 2000 and again from the 2007–2009 recession and financial crisis to the end of the sample. Counterfactual simulations show the 2007–2009 recession and financial crisis would have not been as deep and long-lasting if the fed funds rate had been as low as −8 % in 2009 and remained negative from 2010 through 2016. [ABSTRACT FROM AUTHOR]

Even markets that seem closer to the neoclassical ideal of the market like financial markets are organized by a combination of karpikian judgment devices and "mathematical-statistical models of calculation" (p. 149). Finally, the book shows that the aesthetization of social and economic life conduct almost all kinds of markets to face a problem of quality uncertainty and to be organized by karpikian market devices rather than mere prices like in theoretical standard markets. The fourth chapter goes beyond Karpik's definition of regimes of market coordination to explore the social mechanisms that lie behind market devices and market regimes. [Extracted from the article]

Purpose: The paper aims to examine whether the daily conventional money market overnight rate influences the monthly investment rate of Islamic deposits in Malaysia. The traditional approach, which averages the high-frequency data to match the low-frequency data, results in information loss for the high-frequency data. Design/methodology/approach: The paper uses the mixed data sampling (MIDAS) model to study the relationship between Islamic banking and conventional banking. The Malaysian data are used for the analysis as Malaysia has one of the most developed Islamic financial industries in the world, and it is well-known for its dual banking system. Findings: The evidence shows that the conventional overnight rate has a positive effect on the Islamic deposit rate. The results are consistent for Islamic deposit rates with different maturities. The positive aggregate effect holds when the lag length of the daily conventional overnight rate goes up to 90 days. Additional evidence shows that the daily conventional overnight rate has a similar effect on the conventional deposit rate. Originality/value: This paper documents that the relationship between Islamic banking and conventional banking is not monotonous. When high-frequency data is averaged with low-frequency data, the non-linear relationship will be masked. It highlights the importance of using high-frequency data to get a detailed picture. [ABSTRACT FROM AUTHOR]

As the reallocator of liquidity from banks with excess to banks with a deficit, the interbank money market (IMM) plays a fundamental role in the proper functioning of the banking system and the economy as a whole. The aggregate uncertainty derived from stochasticity of the overall level of the demand for short-term liquidity and the likelihood of domino failures of tightly connected competitors who lend themselves vast amounts of liquidity explains the complexity of decisions in this environment. To identify the most significant factors influencing actors' strategies, we first present the five underlying patterns discovered through a bibliometric analysis of 609 scientific documents in this field: contagion and systemic risk, stability, market structure, relationship and trust, and default and failure. Then, our detailed study findings on 160 recent works indicate elements that affect central banks' strategies in reducing systemic risk and preventing financial contagion, as well as managing the interbank network in a way that makes it more stable and resilient to shocks to conserve market confidence. Furthermore, they address factors that influence banks' strategies to maintain their lending relationships and mitigate default risk. In addition to summarizing potential research directions, this paper provides market participants with a strategy fact-sheet. [ABSTRACT FROM AUTHOR]

Copyright of Les Cahiers du CREAD is the property of Centre de Rrecherche en Economie Appliquee pour Developpement and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To test for arbitrage opportunities and market efficiency in the Hong Kong money, stock, and real estate markets, we find that the money market stochastically dominates both the stock and real estate markets. Furthermore, the real estate market dominates the stock market, the money market dominates nearly all the efficient frontier portfolios, none of the efficient portfolios dominates the money market, and the money market also dominates the equal-weighting portfolio. This infers that in some cases investors could achieve higher expected ex-ante utility by investing in an individual asset rather than a portfolio. Our conclusions drawn from the pre-COVID-19 period are the same as those drawn from the entire period and the conclusions drawn from the COVID-19 period are the same as those drawn from the entire period except that the money market only stochastically dominates some of the efficient frontier portfolios. Our findings question diversification benefits in the Hong Kong capital market during our sample period, including both the pre-COVID-19 and COVID-19 periods. [ABSTRACT FROM AUTHOR]

The corporate bond market has historically been one of the most highly invested capital markets in the world. A recent case has disrupted the corporate bond market by granting an untraditional remedy. This Note first discusses corporate bonds generally and their relevance in today's capital markets. Next, this Note discusses the recent case of Wilmington Savings Fund Society, FSB v. Cash America International, Inc. in the U.S. District Court for the Southern District of New York. This Note argues the court incorrectly decided Cash America and discusses what implications that incorrect decision has on bond issuers and the corporate bond market. Finally, this Note proposes three solutions that bond issuers can take to remedy the problems presented by Cash America. [ABSTRACT FROM AUTHOR]

The growth of so-called “shadow banking” was a significant contributor to the financial crisis of 2008, which had huge social costs that we still grapple with today. Our financial regulatory system still has not fully figured out how to address the risks of the derivatives, securitizations, and money market mutual funds that comprised Shadow Banking 1.0, but we are already facing the prospect of Shadow Banking 2.0 in the form of decentralized finance, or “DeFi.” DeFi’s proponents speak of a future where sending money is as easy as sending a photograph—but money is not the same as a photograph. The stakes are much higher when money is involved, and if DeFi is permitted to develop without any regulatory intervention, it will magnify the tendencies towards heightened complexity, leverage, rigidity, and runs that characterized Shadow Banking 1.0. Fortunately, though, there is still time to prevent DeFi from becoming Shadow Banking 2.0. This Article argues for precautionary regulation of DeFi, designed to limit its growth and to cordon off whatever remains from the established financial system and realworld economy. While proponents of DeFi will contend that such regulation will limit innovation, this Article argues that DeFi innovation has limited benefits for society. DeFi does not aspire to provide new financial products and services—it simply aspires to provide existing financial products and services in a decentralized way (meaning, without intermediaries). This Article will demonstrate that the DeFi ecosystem is, in fact, full of intermediaries and explain why full disintermediation of financial services is an entirely unrealistic aspiration. This Article will then proceed from that finding to argue that if DeFi cannot deliver on decentralization, regulators should feel emboldened to clamp down on DeFi in order to protect the stability of our financial system and broader economy. [ABSTRACT FROM AUTHOR]

I investigate whether bank exposures to sovereign debt during the European debt crisis affected the real economy. I show that a shock to the marked-to-market (MTM) value of bank exposures to sovereign debt led to credit tightening in 2010–2011 that had negative real effects on small and young firms. Because banks do not usually mark their holdings of sovereign bonds to market, I explore the transmission channels of the unrealized losses on credit supply. I show that a shock to MTM exposures reduced short-term bank funding from U.S. money market funds rather than affecting equity or working through alternative channels. [ABSTRACT FROM AUTHOR]

A review of periodical literature for 2021 is presented, with topics that include money market instruments during the first globalization, private-order institution in global trade, and wage differentials in the English and Welsh railway industry.

Stock market forecast improves the economic development of the country. People invest in the stock market at high risk without performing the appropriate analysis. So, it is essential to identify the stock market value prediction through existing stock market datasets. This analysis can be made through machine learning algorithms. Machine Learning is defined as the process through which only investors will gain the profit when investing the money into the stock market. Many prediction models have been contributed by the existing investigators to estimate the stock value. The contribution by Hybrid Heuristic algorithm is that it provides a coherent future prediction of stock market prices and investors will also get the insights about how to sell and buy a specific stock to get more profit. Gann square technique is used to forecast a price maneuver dependent on value, pattern analysis and period which is also used for intraday online trading without prior knowledge. [ABSTRACT FROM AUTHOR]

Banking is an indispensable sector in our modern society and it forms the core area of money market among the advanced countries. Financial access to all sections of society is inevitable for the overall development of a nation. But the society should have timely and adequate availability of financial services to ensure access at affordable cost. The present study is intended to analyze the usage of banking products and services of commercial banks in Villupuram district. [ABSTRACT FROM AUTHOR]

The rise of non-fungible tokens (NFTs) has been astonishing, in particular for the arts and creative industries. The dominant discourse both in mainstream media and in academia today focuses predominantly on what this new technology can do for the art market rather than art itself. However, framing NFTs in art in the context of money and markets draws attention away from the more subtle and creative role of NFTs. Consequently, this article asks: What is the role of NFTs in art, beyond the market? This research complements existing empirical work, by conducting a case study and interviews with members of DADA, a historic NFT art project which is particularly critical towards the role of the art market. The findings foregrounded five roles that NFTs play in art: as (1) a tool for systemic change, (2) a new way to community, (3) a ritual artefact, (4) a means for preservation and (5) a new medium. [ABSTRACT FROM AUTHOR]

Does Indian sovereign yield volatility reflect economic fundamentals, or whether it is a self-generated force flowing through markets with little connection to such fundamentals? To answer the question, this research explores the volatility dynamics and measures the persistence of shocks to the sovereign bond yield volatility in India from 1 January 2016, to 18 May 2022, using a family of GARCH models. The empirical results indicate the high volatility persistence across the maturity spectrum in the sample period. However, upon decomposing the markets into bull and bear phases, our results support the existence of weak volatility persistence and rapid mean reversion in the bear market. This shows that the economic response policies implemented by the government during the pandemic, including fiscal measures, have a restraining effect on sovereign yield volatility. For a positive γ, the results suggest the possibility of a "leverage effect" that is markedly different from that frequently seen in stock markets. Results further indicate that the fluctuations in Indian sovereign yields cannot be dissociated from inflation and money market volatility. Our findings herein provide valuable information and implications for policymakers and financial investors worldwide. [ABSTRACT FROM AUTHOR]

Copyright of Brazilian Journal of Law & International Relations / Relações Internacionais no Mundo is the property of Relacoes Internacionais no Mundo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Bank lending is at the stage of financial intermediation in most countries with a poorly diversified money market. The credit market in Romania has been growing steadily since 2005 as a result of banks opening up to the public. After the advent of the first mortgages, credit took off and the volume of consumer credit reached a peak. The unexpected Covid 19 pandemic has brought minor changes to the structure and volume of bank lending in Romania. The study reveals changes and trends in bank lending in Romania. Due to the fact that bank credit is the main form of financing in Romania, the study presented is important and relevant for analysts and the public. [ABSTRACT FROM AUTHOR]

We investigate the time‐varying relationship of funding liquidity (FL) and market liquidity (ML) in a Markov regime‐switching model. By using a comprehensive U.S. TRACE dataset, we provide strong evidence that FL and corporate bond ML are interlinked, and their impact on each other is highly regime‐dependent. We find that FL and ML exhibit a large‐and‐positive mutual impact when money market is tight and equity market is volatile. But in normal regimes, FL is found to have a negative impact on ML with a much smaller magnitude than those in stressed regimes. Furthermore, FL is more stable than ML with less regime changes. Our article offers insight on the important mechanism by which central banks can improve ML through the funding market. [ABSTRACT FROM AUTHOR]

In other words, weak NGDP before the Lehman failure, owing to the mistakes of the Fed, caused the financial and economic crisis; not the financial crisis causing weak NGDP as the standard story has it. I Money Illusion i by Scott Sumner is a comprehensive and timely exposition of Sumner's vision of "market monetarism" as a guide for monetary policy. Market monetarism argues that monetary policy makers should use their instruments to keep nominal GDP (NGDP) on a moderate growth path. [Extracted from the article]

We use unique individual bank-to-bank repo transaction data to empirically assess the efficiency of the existing Swiss financial market infrastructure (FMI) for executing delivery versus payment transactions. This approach enables us to identify its current benefits and drawbacks as well as where new technologies, such as distributed ledger technology, could provide a remedy. We find that the fastest settlement time for repo transactions is 12 s, but that settlements are often delayed by more than 10 min due to the lack of collateral availability. We conclude that the cross-border availability of securities needs to be addressed by either improving interoperability of existing infrastructures or using new technologies. [ABSTRACT FROM AUTHOR]

Predicting stock market movements is a well-known problem of interest. Financial markets employ a staggering amount of sophisticated and complex technologies for getting efficient results while trading. Algorithmic trading (AT) is one of the major steps in this direction as it is gaining wide acceptance in the global market. There are various Computational intelligence models that have produced a significant number of results over a period of time. Some of them are neuro fuzzy models, systems based on genetic algorithm and support vector machines (SVM). Every day a huge volume of data is produced from Dotex International Limited which is also known as NSE Data Analytics Ltd. This data contains all the factors which more or less directly affect the movement of the market. A stock market is a complicated system which attract a lot of people everyday but there have been many instances where people have lost their entire life savings within a day specially while trading in options. Hence, it requires a lot of knowledge and one should be able to control his emotions while trading. Usually, newbies consider stock market as a money vending machine and jump into it directly without even knowing the basics of it. Every one knows that one who can predict the momentum of market is the real king of this game and thus we have made an attempt for predicting the trend of the stock market. Two models are built, one for daily forecast and one for monthly forecast. [ABSTRACT FROM AUTHOR]

When the Great Depression struck the United States, O.M.W. Sprague was America's foremost expert on financial crises. His History of Crises under the National Banking System is a frequently cited classic. Had he diagnosed a banking panic and called for an aggressive response by the Federal Reserve, it might have made a difference; but he did neither. Sprague's misdiagnosis had, I argue, two causes. First, the crisis lacked the symptoms of a panic, such as high interest rates in the New York money market, which Sprague had identified from his studies of previous crises. Second, Sprague's macro-economic ideas led him to conclude that increasing the stock of money would be of little help once a depression was underway. Sprague's main concern was that abandoning the gold standard would intensify the crisis, a concern that led him to resign his position as advisor to the U.S. Treasury to protest Roosevelt's gold policy. [ABSTRACT FROM AUTHOR]

We consider a non-consuming agent investing in a stock and a money market interested in the portfolio market price far in the future. We derive a strategy which is almost log-optimal in the long run in the presence of small proportional transaction costs for the case when the rate of return and the volatility of the stock market price are bounded Ito processes with bounded coefficients and when the volatility is bounded away from zero. [ABSTRACT FROM AUTHOR]

This paper reconceptualizes the impact of US finance on European banking as a process of 'extroverted financialisation'. This impact is commonly associated with the rise of 'market-based banking' (MBB). While MBB exposes how commercial banking has been deeply transformed by disintermediation and borrowing from wholesale markets, the concept struggles to capture the distinct imperatives of this process, and its uneven nature. By contrast, the concept of extroverted financialization captures the problems European banks have faced while adapting to US-led financialization. More specifically, the concept portrays the financialization of European banking as an outcome of new funding practices, called liability management (LM), developed in US money markets from the 1960s onwards. I show how this put pressures on European lenders because it allowed US banks to leverage extensively. To catch up, European banks had to improve their access to liquid USD, which forced them to find a way into the Eurodollar markets and into the US money markets. To operate in these markets, they had to gradually implement the practices of LM. This process of extroversion made their own banking models highly fragile and dependent on US money market funding. Despite adopting LM, they could not reduce their structural disadvantages vis-à-vis US banks. [ABSTRACT FROM AUTHOR]

Islamic banking for the Indonesian people is a concept that has been developed since 1992 but is still relatively new for the Indonesian people, including the Muslim community itself. Based on the fact that the practice of Islamic banking is only at an early stage, it is only natural that the Islamic banking system is still poorly understood by the public, in the end, even though the customers of Islamic banks are not sure about bank management, they still use Islamic banking services. In the view of sharia, money is not a commodity but a tool to achieve added economic value. Without the added economic value, money cannot create prosperity. This is in contrast to interest-based banking where money breeds money, regardless of whether it is used in productive activities or not. Time is the main factor. Meanwhile, in the view of sharia, money will only grow if it is invested in real economic activities. In operational activities, Islamic banking is faced with problems that can become obstacles in achieving its goals, including problems related to a crisis. Basically, Islamic banking has similarities with conventional banking in dealing with risks in business process activities. These risks can be caused by natural disasters, human error and pandemic risks. This research is a literature review which is expected to produce a robust model Islamic money market to enhance quality of Islamic banking in facing and deal with the crisis due to the pandemic. [ABSTRACT FROM AUTHOR]

This paper looks into the role of announcement effect and liquidity effect in monetary transmission in Indian money market. It first looks into the impact of these two effects on the operational target that is, overnight call money market and then applies the same framework on other short term money market rates. The time period considered is from May 2011, when the new monetary policy framework was introduced till Feb 2021. The results show the presence of both the effects on the overnight call money rate and also on other short term rates. In addition to this, there is a presence of asymmetry in monetary transmission which is more prominent after fine-tuning of RBI's monetary operations. [ABSTRACT FROM AUTHOR]

Deutsche Bank was once an acclaimed US-style investment bank but is now struggling. The rise of US finance is often explained as an outcome of financial liberalization that motivated other banks to abandon their traditional industrial support to chase profit opportunities within global securities markets. This story, however, underestimates how the transition to US-led financialization was deeply entangled with managerial struggles and the contradictions of adopting US financial innovations from a peripheral position. By contrast, I use the concept of extroverted financialization to portray Deutsche Bank's transformation as an outcome of its attempts to integrate new funding practices connected to US money markets, called liability management. I argue that this process generated a difficult-to-manage business model and, ultimately, Deutsche's decline. Because of these extroverted strategies, the bank is now caught between opposing logics of banking, within neither of which it can regain its previous powerful position. [ABSTRACT FROM AUTHOR]

The main purpose of this research study is to describe the early warning method for extreme risk in financial markets. The research study depends upon secondary data analysis. The data was collected from websites, including Google Scholar, and annual financial reports related to extreme risk and financial markets. Excessive risk is the main independent variable, and the financial market includes the bonds, capital, and money markets. These are dependent variables for measuring the research study using E-views software and generating informative results. The descriptive statistic, total equality analysis, significant analysis, correlation coefficient analysis, and histogram and state values are related to the early warning method for extreme risk in financial markets. The overall result found significant links between early warning methods for unnecessary risk in financial markets. [ABSTRACT FROM AUTHOR]

Mobile payments will become increasingly common in the future since they reduce transaction time, and they have already replaced interactions with physical money in some markets. Yet in Nepal, consumers' adoption of mobile payment services remains very low as compared to other traditional forms of payments, such as cash and credit cards. Thus, this study aimed to investigate the factors influencing consumers' behavioral intention to adopt Mobile Payment Services in Kathmandu Valley, the area surrounding the capital of Nepal. The Unified Theory of Acceptance and Use of Technology was integrated with Privacy Calculus Theory and used in this study. Structural equation modeling results from 455 respondents revealed that facilitating conditions such as necessary knowledge and other technologies had a positive and the strongest influence on consumers' actual use of such payments. Effort expectancy had a high and positive influence on consumers' behavior intention towards mobile payment services. Consumers' behavior intention was also positively influenced by performance expectancy and social influence. Mobile payment service providers could use these factors to effectively address consumers' needs and try to exceed the expectations of their target consumers. [ABSTRACT FROM AUTHOR]

Financial inclusion efforts have resulted in a rapid increase in access to financial services. However, the usage of these financial services has not expanded at the same pace, especially in rural areas. The paper explores the factors that have caused usage to lag behind access using a qualitative approach. Data is collected from two predominantly rural provinces in South Africa using focus group discussions. While supply-side factors of distance and transaction costs are important, demand-side factors, including lack of employment, low and irregular incomes, financial illiteracy, and risk and trust perceptions, play a more significant role. We suggest that creating an enabling environment for the development of mobile money could overcome proximity barriers and result in better inclusion of rural communities. There is a need to invest in technology to improve network and Internet reception in rural areas. In addition, the government needs to reconsider the exclusive issuance of e-money by banks. Partnerships with supermarket money markets also have the potential to expand financial inclusion. Moreover, post-adoption financial education should complement efforts to expand financial inclusion. Simplified and transparent cost structures could help resolve the mistrust of banks. [ABSTRACT FROM AUTHOR]

We discuss the impacts of the COVID-19 pandemic on Indonesia's financial markets and monetary policy dynamics. We explore five types of financial markets in Indonesia: (1) the Rupiah (IDR) interbank money market; (2) the US Dollar (USD) interbank money market; (3) government conventional bond (SUN) markets; (4) the stock market; and (5) the USD/IDR spot market. We examine Bank Indonesia's (BI)'s three monetary policy instruments: (1) BI 7-day Reverse Repo Rate (the policy rate); (2) minimum reserve requirement ratios for banks (GWM); and (3) BI's monetary operations. We find that several policy instruments have significant impacts on specific financial markets before and during the pandemic, i.e., the policy rate on the IDR and USD interbank money market, the IDR GWM on the medium-term SUN market, and the foreign exchange (FX) GWM on the FX market. We also find that the COVID-19 pandemic strengthened the impacts of BI's policy instruments on particular financial markets during the pandemic than the pre-pandemic period. We suggest BI continues to maintain the stability of financial markets to support the government efforts to restore the economy from the fiscal side. [ABSTRACT FROM AUTHOR]

The overshooting theorem as pioneered by Rudiger Dornbusch has facilitated the creation of effective monetary policies in the past years. This paper re-examined the validity of the overshooting phenomenon based on the autoregressive distributed lag (ARDL) bound test approach. To achieve the main objective the paper firstly examined if the United States/Malawi Kwacha (USD-MWK) exchange rate overshoots or undershoots its long run exchange rate. In addition, the research paper has prior tested if there exist any significant fundamental macroeconomic fluctuations that may dictate spot exchange rate movements. In a theoretically derived price-flex model. The study has used a forty-one-year span of yearly nominal (USD-MWK) exchange rate data and that of monetary fundamentals data. Furthermore, empirically it has been found that only the inflation rate differential is economically significant in triggering spot rate rapid movements in the Price-Flex model. Conclusively, exchange rate overshooting has tested to be evident in Malawi. Solely attributed by the significant inflation rate differential where the other fundamentals are not statistically significant at 5% level of significance. This has been accounted to the constrained workability of the specified Price-Flex mathematical model in our economic environment. The study also discovered and concluded that inflationary pressures (irdif) emanating from the money market might be the key contribution of currency instability, fluctuations, and extreme exchange rate overshooting in Malawi. The limitation of this theoretical examination was that the overshooting theorem was tested on a single significant macroeconomic fundamental. The reason can be that the Price-Flex mathematical model has constrained full workability in our economic environment in explaining spot-exchange rate fluctuations. Further studies may want to improve on this. [ABSTRACT FROM AUTHOR]

This paper analyzes the dynamic capital structure choices with model uncertainty. We find that robustness concerns from shareholders and creditors have distinct implications. Creditor ambiguity aversion allows a firm to take advantage of the debt tax shield in no-commitment equilibrium because ambiguity aversion serves as a commitment device that disciplines the leverage ratchet effect and even results in debt buybacks. In contrast, shareholder ambiguity aversion mitigates overborrowing incentives only when the default option is out-of-the-money. If the default option is sufficiently in-the-money, ambiguity-averse shareholders are tempted to adopt a more aggressive debt policy because they can transfer model uncertainty to creditors upon default. Interestingly, we show that the commitment against future debt dilution could be suboptimal because of inefficient ambiguity sharing. Finally, we highlight that model uncertainty and volatility have distinct impacts on target leverage, default, and debt capacity. [ABSTRACT FROM AUTHOR]

Forecasting the risk factor of the financial frontier markets has always been a very challenging task. Unlike an emerging market, a frontier market has a missing parameter named "volatility", which indicates the market's risk and as a result of the absence of this missing parameter and the lack of proper prediction, it has almost become difficult for direct customers to invest money in frontier markets. However, the noises, seasonality, random spikes and trends of the time-series datasets make it even more complicated to predict stock prices with high accuracy. In this work, we have developed a novel stacking ensemble of the neural network model that performs best on multiple data patterns. We have compared our model's performance with the performance results obtained by using some traditional machine learning ensemble models such as Random Forest, AdaBoost, Gradient Boosting Machine and Stacking Ensemble, along with some traditional deep learning models such as Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term (BiLSTM). We have calculated the missing parameter named "volatility" using stock price (Close price) for 20 different companies of the frontier market and then made predictions using the aforementioned machine learning ensemble models, deep learning models and our proposed stacking ensemble of the neural network model. The statistical evaluation metrics RMSE and MAE have been used to evaluate the performance of the models. It has been found that our proposed stacking ensemble neural network model outperforms all other traditional machine learning and deep learning models which have been used for comparison in this paper. The lowest RMSE and MAE values we have received using our proposed model are 0.3626 and 0.3682 percent, respectively, and the highest RMSE and MAE values are 2.5696 and 2.444 percent, respectively. The traditional ensemble learning models give the highest RMSE and MAE error rate of 20.4852 and 20.4260 percent, while the deep learning models give 15.2332 and 15.1668 percent, respectively, which clearly states that our proposed model provides a very low error value compared with the traditional models. [ABSTRACT FROM AUTHOR]