Value Of Currency Research Articles

TRADITIONAL MANUFACTURING AND ARTISTIC WORK IN CHAD- REALITY AND CHALLENGES IN THE PERIOD FROM 2000 TO 2020

This study concerned “Traditional manufacturing and artistic work in Chad- reality and challenges in the period from 2000 to 2020”, the human’s geographical issue specifies this study, which considered the most important human activity since the beginning of the history to fulfill needs and ambitions, where the study had focused. The main importance of the subject where the human studies specially tourism had become of big interest in the regional and international fields as well as it became a local legacy which shows the cultural sides of every society. For this sake and that has been a result of thousands years of life interaction between local societies with habits, traditions and cultural values. Therefore this subject is considered as a new from it contains and discuss to enlighten touristic field in Chad. The study had focused on natural human geography with the reality of traditional manufacturing and valued touristic development field. The study had followed many disciplines like historical analysis with description which lay on history description and analyze the relation between them. And it has come with many results and some of the most important are: 1- Tourism is considered among the most important field in every country thus it contribute in boosting the economy and bringing the most valuable currency; 2- Traditional manufacturing and artistic work contribute on tourism’s marketing from traditional products’ show in forum and meeting to attract tourists. 3- Traditional manufacturing create jobs and reduce unemployment as well it contribute on sharing economical activities and boost the development beside it cultural legacy. The study had come out with many suggestions that we are going to presented to achieve a good future for traditional manufacturing and traditional work by presenting solutions to his handicaps that faced in many fields : a- In technology field: the state should give priority to the use of technology in traditional industries and artistic work so that would become modern and organized. b- In the intellectual field: the state must take the necessary measures to reduce and limit the negative effects that will be inflicted on the various traditional industries. c- The state should establish training centers for traditional craftsmen and research centers to develop traditional industry and ensure quality control of the products

Expected long-term rates of return when short-term returns are serially correlated

When short-term returns are serially uncorrelated, expected long-term and short-term returns are equal. However, we show that negative serial correlation among the short-term returns make the expected long-term returns lower than the short-term ones. Such serial correlation is likely to arise, for example, for an investor whose portfolio is invested abroad in assets denominated in foreign currencies, but who wants to make withdrawals in proportion to the fund's value in the domestic currency, and the exchange rate obeys long-term purchasing-power parity. Small-country sovereign wealth funds are leading examples of such investors. For the Norwegian GPFG, the expected annualized long-term rate of return in Norwegian kroner may be 0.7 to 1.8 percentage points lower than the expected short-term return. Negative contemporaneous correlation between global returns and changes in the real exchange rate may dampen and even reverse this result. Empirical evidence suggests that this may be the case for investors in USD-denominated assets domiciled in the United Kingdom, but not for investors domiciled in Norway or Germany. Empirically, we furthermore find that long-term annualized returns may fall short of short-term returns even when evaluated in real USD. Although negative serial correlation also shrinks the long-term variance, funds such as the GPFG should calibrate withdrawals to the expected long-term returns rather than the short-term ones.

COVID-19 Döneminde Türkiye Dış Ticaretinin Değerlendirilmesi

The value of the Turkish currency decreased by 44% in 2021. The trade balance was directly impacted by exchange rate fluctuation. Moreover, COVID-19 had a significant impact on the trade balance globally as well as in Turkey. In this study, we attempt to assess how COVID-19 has affected trade between Turkey and the EU27 counties. We employ the J-curve and S-curve approaches using various samples and sub-samples. Before examining how COVID-19 influences trade balances, we first looked at the long-term relationship of bilateral trade between Turkey and the EU27, including the impact of the real exchange rate on the trade balance. The findings indicate that, first; there is no indication of a J-curve or an S-curve in Turkey’s trade balance. Second, the Turkish trade balance benefited more from a real fall of the Turkish currency during the pandemic era. In comparison to pre-pandemic correlations, the pandemic cross-correlation coefficients are lower. Despite some delays, it turned out well. The Turkish trade balance is improved by the weakening of the Turkish Lira and the effects of COVID-19 during the pandemic, even if there is no indication of a J-curve or an S-curve.

Inflation: Viewed in terms of Economic Structure, Aggregate Expenditure, Wages and Currency Value in a Review

Research objectives are to provide an overview of existing results from previous studies and provide conclusions by researchers. The research method used is a literature review that comes from existing scientific articles from various journals in the world related to variables.The results of the research in this study gave significant results with quantitative research methods and mostly used qualitative methods with the results of the researcher's perspective. Researchers highlight that the field of finance with variables written in research in this paper should use qualitative methods.

Metaverse Land Purchasing in Agreement Legal Perspective

In Indonesia, the term metaverse is widely discussed when many people buy metaverse land. On the Nextearth.io site, a number of virtual lands on a digital map of the location of a number of important areas or assets in Jogjakarta have also been sold for the value of crypto currency. This is a little different because the land purchased is not land in the real world but land that only exists in the virtual world. the research objective is the mechanism and validity of land sale and purchase agreements in the metaverse. This research is normative legal research using a normative juridical method using a law approach as a source of law and supporting literature. Purchase of land in Metaverse can be done by accessing the website which is a platform used for virtual property transactions. If reviewing the agreement on the purchase of metaverse land, the sale and purchase agreement is valid because it fulfills the legal requirements of the agreement.

The Valuation and Investment Risk of Cryptocurrency: Evidence from Bitcoin and Ethereum

From gold standard currencies to fiat money secured by government credit, to today's cryptocurrencies, the basic form of money and mankind's perception of its value has shifted dramatically. This paper will demonstrate the value and risk assessment of the two cryptocurrencies with the highest market share, i.e., Bitcoin and Ethereum. Although the current technology of cryptocurrencies is not perfect, it will improve over time and their value will increase due to the high demand for them. This aim of the study to give first-time investors an understanding of the valuation and risks of cryptocurrencies, rather than treating them as simple financial assets for investment. According to the analysis, the value and risk of Bitcoin depend deeply on many characteristics that were initially built into it. It also has an impact on the value of other virtual currencies at the same time. On the other hand, Ether is a much more open platform, so its value and risk depend more on the various applications and contracts built into a blockchain than Bitcoin. These results shed the light on guiding the further exploration of solving the safety problem of cryptocurrencies from different perspectives.

The Role of the United States in the Relation between Iran and China as Two Key Members of the Asian Global Supply Chain

With the birth of Fordism and the expansion of the markets beyond the states’ borders, national supply chains have evolved into international and global supply chains. Some countries fared much better than others in becoming an irreplaceable part of the said chain. For instance, one could mention Iran due to its rich oil reserves and geopolitical position on the globe, China with its cheap human capital and high-profit margins, and the US with its massive reach all around the world. This study examines the US’s mediatory effect on Iran-China’s relations. Consequently, a derivative of the gravity model has been devised to test the said hypothesis. The dependent variables to test this hypothesis are China’s imports from Iran and China’s exports to Iran. The model controls the two states’ currency value, their inflation rate, and the price of crude oil. Furthermore, the signing of the Joint Comprehensive Plan of Action in 2015 and the US’s Maximum Pressure Policy in 2017 are the main variables of interest in the model in form of two dummy variables. The study employs a novel multidisciplinary approach both on the methodology front by introducing an abstract conception of distance and on the epistemology front by combining international economics literature with that of the international relations. According to the results, the US’s foreign policy has a significant buffering effect on the trade between Iran and China. In other words, the United States acts as a distancing factor between the two states of Iran and China. This distancing effect, however, is stronger for China’s imports from Iran in comparison to China’s exports to Iran.

Modelling the dynamics of cryptocurrency prices for risk hedging: The case of Bitcoin, Ethereum, and Litecoin

Cryptocurrencies have, over the years, gained an unprecedented prominence in financial discourse, with the market fielding over 5,300 digital currencies and reaching over $2 trillion in market capitalisation in 2022. The surge in market values of digital currencies and their popularity in the world of e-commerce have remained unabated and equally received special attention from researchers focusing on identifying the underlying factors that drive changes in their market values. Thus, this study models the dynamics of the prices of cryptocurrencies alongside their interconnectedness, focusing on Bitcoin, Ethereum, and Litecoin along the time and frequency dimensions of monthly data from 1 March 2016 to 05/31/2022. Based on the ARDL model, results show that the volume of transactions of Bitcoin, Ethereum, and Litecoin, oil prices, and gold prices exert a more significant positive influence on their prices in the longrun than in the shortrun. However, the publicity of the selected cryptocurrencies (google search rates) does not significantly influence their prices. Interestingly, results from the Wavelet Granger causality tests show no causality between the raw series of Bitcoin, Ethereum, and Litecoin prices. However, a bi-directional causality exists between Bitcoin and Ethereum prices during the longrun in their low frequencies, a unidirectional causality running from Bitcoin to Litecoin prices during the longrun in their low frequencies, and a unidirectional causality running from Litecoin to Ethereum prices during the shortrun, medium run and longrun in their high, medium, and low frequencies. These findings have profound implications for the global financial market and investor decisions.

Wage Structure of Artisans and Labourers: Western Rajasthan (17th-18th Century)

Our study examines the wages of artisans and labourers during the medieval period of India with special reference to 17th-18th century Western Rajasthan. During the study period, the artisans were paid in the form of naqd (cash), jinsi (kind), and hawalgi (advance). The study under review also reveals the value of currency. Our research compares the purchasing power of wages by showing the prices of basic commodities.

RETRACTED ARTICLE: Analysis of the impact of the trade war between China and America on the RMB exchange rate under the R-vine copula model from the perspective of the global value chain

AbstractChanges in the RMB exchange rate (ExRate) impact major strategic directions, such as China’s rise, the “Belt and Road” initiative, and RMB internationalization. Studying the impact of the trade war between China and America on the RMB ExRate is significant. This paper constructs an R-vine copula model and studies the influencing factors of the ExRate and the mechanism of the trade war between China and America on the RMB ExRate. The impact of the Trade war between China and America on the RMB ExRate is analyzed in detail. Besides, the R-vine copula model is used to analyze the fluctuations of the ExRate returns of the Association of Southeast Asian Nations (ASEAN). The R-vine copula model is employed to study the volatility of the ExRate return series of ASEAN countries, and the mean of the ExRate dependence coefficients of ASEAN and the estimation results of R-vine copula parameters are analyzed. Finally, the results are obtained. There is a relation between the RMB ExRate and Chinese tariffs in analyzing the impact of the trade war between China and America on the RMB ExRate. There is a negative correlation between tariffs and the RMB ExRate. There is a positive correlation between the value of the RMB and China’s trade surplus without considering the monetary policy. The value of the Chinese currency has risen as China’s trade surplus has grown. Stable foreign exchange reserves can stabilize the RMB ExRate. It is concluded that the economic and trade cooperation between China and ASEAN has become increasingly frequent under the influence of the trade war between China and America through the R-vine copula model analysis. The ExRate risk further increases and the ExRate yield sequence fluctuates significantly. The lower tail dependency coefficient for market tail dependencies is slightly larger than the upper tail dependency coefficient. The impact of bad news on the currency ExRate market is clear. In the context of the current trade war between China and America intensifying, the sharp fluctuations in the RMB ExRate caused by the trade war between China and America have promoted the transformation of economic growth. The shift from commodity export to capital export is realized. The reasons for RMB ExRate changes need to be explored. It is recommended to continuously deepen the reform of the RMB ExRate system and maintain the stable development of the ExRate.

Impact of Select National and International Incidents on Gold and Silver Prices in India

In this paper an attempt is made to know the impact of select national and international incidents such as Russia and Ukraine War, Afghanistan War, 1st Lockdown in India, US and Iraq Civil war and Surgical Strike in India on gold and silver prices from 2019 to 2022. The study used t-test: Paired Two Sample for Means and correlation to know the volatility and relationship between gold, silver prices with the value of Indian currency. The study finds the significance difference between gold prices, silver prices and value of Indian currency before and after the incidents. The study also finds whether there is any relationship between the gold prices, silver prices with Indian currency and how they are related to each other.

Factor investing and currency portfolio management

Currency-specific pricing factors are pervasive in international asset pricing. However, portfolio and risk management based on forex factors, instead of individual currencies, are rarely discussed. This paper tries to fill this gap by modelling dynamic correlations and non-normality among forex factors. By considering the four most popular forex factors: the dollar risk factor, the carry trade factor, the currency momentum factor, and the currency value factor, we find that a dynamic conditional correlation copula (DCC-copula) model with skewed-t kernel fits the joint distribution well. We show that, for risk-averse investors who focus on factor investing or employ the forex factors to resize the specific risk exposure, ignoring the tail dependence structure of forex factors brings significant costs.

Impact of Exchange Rate, and Foreign Direct Investment on External Debt: Evidence from Pakistan Using ARDL Cointegration Approach

Using time series data from Pakistan 1973 to 2021, this research examines the effect of exchange-rate, fiscal deficits, foreign direct investment and economic expansion on foreign debt. The auto regressive distributed lag model is used in the research to look into the co-integration analysis of variables and their existence. The study confirms the positive and significant relationship exist among the rate of exchange, foreign direct investment, the fiscal deficit, economic growth, and external debt in the long run. However, in the short run, the real effective exchange rate and fiscal deficit are negatively related to the external debt, whereas the economic growth is positively related to the external debt. The policy maker recommended that rises the exchange rate, the value of a domestic currency falls to some extent, which improves the foreign exchange in which loans must be returned.

The effects of currency devaluation on Ethiopia’s major export commodities: The case of coffee and khat: Evidence from the vector error correction model and the Johansen co-integration test

Devaluation of the currency has been stipulated and utilized increasingly as a stabilization device in developing countries. The Ethiopian government employed a devaluation policy to improve the export performance of the country. However, various literature demonstrates that the devaluation of the Ethiopian Birr (ETB) has an ambiguous effect on the country’s export performance. Therefore, the prime objective of the study was to investigate the effect of domestic currency devaluation on Ethiopian major primary export commodities by employing time series data for the period 1987 to 2020. With the help of Johansen’s co-integration and vector error correction modelling, the impact of the devaluation of the real effective exchange rate on major export commodities was assessed in the long run as well as in the short run. The study found that the devaluation of the real effective exchange rate has a positive and significant relationship with the values of major export commodities in the long run. This implies that the decrease in the value of the domestic currency promotes exports in the long run. Other variables like foreign direct investment, with an expected positive sign, and real gross domestic product (with a negative sign), are also found to be statistically significant in explaining exports in the long run. The findings of this paper suggest that policy intervention in the form of devaluing the domestic currency could be effective in improving export performance given that the effect of inflation on output is controlled.

Long term currency forecast with multiple trend corrected exponential smoothing with shifting lags

In the current global economy, exchange rate forecasting is critical for investors and businesses seeking to make informed investment decisions and manage risk. While many short-term exchange rate forecasting methods exist, long-term forecasting methods are limited and often fail to account for the complex macroeconomic factors that influence exchange rate trends. However, investors need to have an analytically examined basis for deciding to invest, which requires knowing more about the future values of the related market currency. This paper proposes a new Multiple Trend Corrected Exponential Smoothing with Shifting Lags model to forecast long-term exchange rates, which incorporates multiple trend corrections and shifting lags to provide more accurate predictions of future currency values. We apply the proposed method to six currency pairs (USD/EUR, USD/NOK, USD/TRY, USD/CNY, USD/XOF, and USD/MGF) from 2006 to 2018 and compare its performance to existing methods, such as moving average, weighted moving average, and exponential smoothing. Our results show that the proposed model provides more accurate long-term exchange rate forecasts for developed countries than existing methods. Our findings have important implications for investors and businesses seeking to manage currency risk and make informed investment decisions in the global economy.

Predictions of the Outcomes for League of Legends and Diamond Price Using Regression Method

Intensified worldwide inflation has added panic to the public about confidence of monetary currency value. People devote themselves to searching for relative constant measurement on country or world economic level evaluation frequently. Under economic uncertainty and on account of precious metal being a great hedge against inflation, gold or diamond are usually applied into economic analysis or prediction. ​The Diamond, as an equivalent to currency, has extensive acceptance worldwide. Hence, predicting diamond price has the same function compared to economic future forecasting through financial fluctuation. Advances in information technology have facilitated the development of video games and provided opportunities for video game competitions. More and more international tournaments are recognized by sports and sports organizations, and some competitive sports have become official events of the Asian Games. As a sport, fairness is essential, and League of Legends as a 5V5 combat game, fairness on both sides is the basis to maintain the game environment, which means that the winning rate of both sides will be close to 50%. This paper intends to predict diamond price by using simple linear regression. Besides, the forecasting of outcome for League of Legends will be also displayed in this paper, based on the platform R as analysis tool and standard indication. These results shed light on two practical applications of regression models in statistics and the corresponding explanations of their causes will be discussed.

Artificial neural network (ANN)-based estimation of the influence of COVID-19 pandemic on dynamic and emerging financial markets

The COVID-19 pandemic is a serious global issue destroying financial markets awfully. The proper estimation effect of COVID-19 pandemic on dynamic emerging financial markets is a big challenge due to a complex multidimensional data. However, the present study proposes a Deep Neural Network (DNN)-based multivariate regression approach with backpropagation algorithm and structural learning-based Bayesian network with constraint-based algorithm to investigate the influence of COVID-19 pandemic on the currency and derivatives markets of an emerging economy. The output shows that the COVID-19 pandemic has negatively influenced the financial markets as indicated by sharply depreciating currency value around 10 % to 12 % and reducing short-position of futures derivatives around 3 % to 5 % for currency risk hedging. The robustness estimation shows that there have probabilistic distributed between Traded Futures Derivatives Contracts (TFDC), Currency Exchange Rate (CER), and Daily Covid Cases (DCC) and Daily Covid Deaths (DCD). Moreover, the output represents that the futures derivatives market conditionally depends on the currency market volatility given percentage of COVID-19 pandemic. This study may help to policymakers of financial markets in decision-making to control CER volatility that may promote currency market stability to enhance currency market activities and boost confidence of foreign investors in extreme financial crisis circumstances.

Trading Strategies for Cryptocurrencies Based on Machine Learning Scenarios

A Cryptocurrency is a peer-to-peer digital exchange system in which cryptography is used to generate and distribute currency units. Bitcoin as the foremost digital currency, using asymmetric cryptographic algorithms, blockchain technology, was conceptualized by Satoshi Nakamoto in 2008 and born in 2009. In 14 years, digital currency has gone from being initially controversial and worthless to rapid increase in value. The huge fluctuations in its price have attracted worldwide attention, and more people have begun to pay attention to the investment strategy of digital currency. Starting from the attributes of Bitcoin, this paper objectively compares the application effect of arbitrage strategy and trend strategy in machine learning on Bitcoin, analyzes and summarizes and predicts the future of Bitcoin's investment. To be specific, the arbitrage strategy involves three methods, i. e. , cash arbitrage, cross-exchange arbitrage and related variety arbitrage; trend strategy involves two methods, i. e. , the timing method and the multi-factor method. These results shed light on guiding further exploration of potential of investing digital currencies, which provides an in-depth summary analysis of risk-free arbitrage and digital currency value forecasts.

Transition of Countries to Currency and Trade Sustainable International Cooperation on the BRICS Platform

The transition to monetary and trade sustainable cooperation within the BRICS can be carried out on the basis of the energy economic equivalent of the national currencies of sovereign states. The International Monetary Index will link the existing commodity masses of states with national currencies. The creation of two-circuit national monetary and financial systems will create conditions for the evolutionary transition of budget formation. Double-circuit monetary and financial systems will bind national currencies to energy economic equivalents and goods. An interim measure of the national currency due to the energy economic equivalent and a group of goods with both commodity and monetary properties creates their currency value. This makes it possible to estimate their value in the energy economic equivalent. The energy economic equivalent can become a meter of the intrinsic value of any payment means. The economic reserve base, expanded at the expense of groups of goods, makes it possible to create a stable basis for strengthening national currencies in the system of domestic, regional and international settlements, maintaining their stability. It is possible to connect the financial and real sectors of the international economy of sovereign states through the BRICS investment international bank. This will allow the generation of long and cheap financial resources by issuing securities and digital financial assets secured by a group of goods with foreign exchange value. National currencies will become full-fledged, tied to the amount of those resources that are in the provision of the BRICS investment international bank.

IoT-Based Banknotes Saving Automation System

Many problems occur with traditional savings, such as users not knowing the nominal amount that has been saved later, and the authenticity of the money saved. To overcome this problem, the "Savings Storage Automation System with IoT-Based Banknotes" tool was created, this tool aims to help users save money easily and safely. The system design is based on Arduino Mega. The inputs on the Arduino Mega consist of a GY-33 TCS34725 as a color sensor and a keypad to perform functions. The output produced is in the form of nominal data of banknotes that can be seen by the user through an LCD and sent to a database, checking the authenticity of the money is done manually by using ultraviolet. The method used to identify the nominal banknotes is based on the reading of each RGB value and color temperature on each nominal banknote. The average accuracy of reading currency values on real banknotes reaches 88%, while in testing counterfeit banknotes it is 14%. Testing execution time when entering money into savings is 3.57 seconds and data to the database is 6.57 seconds.