Currency Trading Research Articles

The Development of Private Digital Currency in China and Its Enlightenment to the Promotion of Legal Digital Currency

With the rapid development of global financial technology, legal digital currency will become an important form of currency in the future. At present, the central bank is committed to the development of legal digital currency in China, and has carried out experiments on relevant platforms. Legal digital currency is a new thing and lacks successful experience that can be used for reference. Therefore, the analysis and Research on the potential risks of private digital currency and a clear understanding of the shortcomings of China's current response to the risks of private digital currency are important prerequisites for the steady development of China's legal digital currency.
 Firstly, it expounds the concept and classification of digital currency, then analyzes the development and supervision status of private digital currency in China and other countries around the world, points out the shortcomings of China's response to the risk of private digital currency, and finally puts forward the enlightenment and suggestions for the issuance of legal digital currency in China.
 There are some problems in private digital currency, such as unclear legal attributes and tax policies, non-standard trading platforms, lack of consumer protection, and weak international cooperation. China should pay attention to the above problems when promoting the development of legal digital currency. Specifically, we should clarify the legal attribute of digital currency; Build a complete digital currency supervision system; Improve the digital currency tax policy; Standardize the digital currency trading platform; Building an anti-money laundering mechanism; Strengthen the protection of consumers' rights and interests; Strengthen international digital currency cooperation.

Construction of a volatility index from exchange-traded dollar–rupee options

PurposeThis paper aims to propose the implied volatility index for the US dollar–Indian rupee pair (INRVIX). The study seeks to examine whether INRVIX truly reflects future USDINR (US Dollar-Indian rupee) volatility and signals profitable currency trading strategies.Design/methodology/approachTwo measures of INRVIX are constructed and compared: a model-free version based on the methodology adopted by the Chicago Board of Options Exchange (CBOE) and a model-dependent version constructed from Black–Scholes–Merton-implied volatility. The proposed INRVIX is computed by tweaking some parameters of the CBOE methodology to ensure compatibility with the microstructure of the Indian currency derivatives market. The volatility forecasting ability of INRVIX is compared to that of a generalized autoregressive conditional heteroscedasticity (1,1) model. Ordinary least squares regression is used to examine the relationship between n-day-ahead USDINR returns and different quantiles of INRVIX.FindingsResults indicate that INRVIX based on the model-free approach reflects ex post volatility in a better manner than its model-dependent counterpart, although neither measure is found to be an unbiased and efficient forecast. Subsample analysis across tranquil and turbulent periods corroborates the results. The volatility forecasting performance of INRVIX is found to be better than that of forecasts based on historical time-series. These results are consistent with similar studies of developed market currencies. The study does not find any significant relationship between extreme levels of INRVIX and the profitability of trading strategies based on such levels, which is contrary to results from the equity options market.Practical implicationsForeign exchange volatility affects the costs of international trade and the external sector competitiveness of Indian multinationals. It is a significant risk factor for financial institutions and traders in the financial markets. An implied VIX for the USDINR could serve as an indicator of expected foreign exchange risk. It could thus provide a signal for a possible intervention in the forex market by the regulator. Regulators could introduce volatility derivative contracts based on the INRVIX. Such contracts would enable hedging of the pure volatility risk of dollar–rupee exposure. Thus, the study has practical implications for investors, hedgers, regulators and academicians alike.Originality/valueTo the author’s knowledge, this is one of a few studies to construct an implied VIX for an emerging currency like the rupee. The study is based on up-to-date sample data that includes the recent COVID-19 market crash. A novel contribution of this paper is that in addition to examining whether INRVIX contains information about future USDINR volatility, and it also examines the signalling power of INRVIX for currency trading strategies.

Volatility of Exchange Rate in Nigeria: An Investigation of Risk on Investment

The contribution of investment in currency trading in economic growth of a nation cannot be over emphasized. Hence, the examination of the risk involved in such trading because of volatility in foreign exchange rate. Time series data and model were used in this study. The monthly exchange rate of four major foreign currencies in Nigeria namely the US Dollars (USD), the Great Britain Pounds (GBP), the EURO and CFA Francs against Nigerian Naira (NGN) from January, 2004 to December, 2019 were extracted from website of Central Bank of Nigeria (CBN) with an open access to the public. Due to the volatile nature of the exchange rate, the Generalized Autoregressive Conditional Hetroscedastic (GARCH) model was a suitable model used at order 1 for parsimony to determine volatility used in computing Value at Risk (VaR). It was discovered that the maximum loss (risk), measured by VaR, that can occur at 95% confidence interval for twelve months forecast of trading with GBP was the highest, among the four currencies, with percentage loss of between 15.5% to 16.2%. While the CFA has the lowest risk with VaR between 0.02% to 0.03%. Based on the findings, the risk of investing in foreign exchange is the highest when trading in GBP with attendant high returns due to large fluctuations up and down of the exchange rate. This study will help investors to study the pattern of risk and returns and decide on the foreign currency to trade on. The government should put policies in place to encourage existing investors and new investors that want to invest on foreign exchange to create employment, since the risk involved can be determined as it is done in this study.

A Novel Bitcoin and Gold Prices Prediction Method Using an LSTM-P Neural Network Model.

As a result of the fast growth of financial technology and artificial intelligence around the world, quantitative algorithms are now being employed in many classic futures and stock trading, as well as hot digital currency trades, among other applications today. Using the historical price series of Bitcoin and gold from 9/11/2016 to 9/10/2021, we investigate an LSTM-P neural network model for predicting the values of Bitcoin and gold in this research. We first employ a noise reduction approach based on the wavelet transform to smooth the fluctuations of the price data, which has been shown to increase the accuracy of subsequent predictions. Second, we apply a wavelet transform to diminish the influence of high-frequency noise components on prices. Third, in the price prediction model, we develop an optimized LSTM prediction model (LSPM-P) and train it using historical price data for gold and Bitcoin to make accurate predictions. As a consequence of our model, we have a high degree of accuracy when projecting future pricing. In addition, our LSTM-P model outperforms both the conventional LSTM models and other time series forecasting models in terms of accuracy and precision.

The Threat of Financial Sanctions: What Safeguards Can Central Banks Build?

AbstractThe sanctions imposed by the G10 countries on financial institutions in Russia, including on its central bank, will come under scrutiny by emerging market central banks. This will help them build appropriate safeguards against disruptions to cross‐border transactions and revise their investment mandates to reduce the risk of reserve asset freezes. Building new financial market infrastructure and cross‐border payment systems, or strengthening existing ones, will become the priority of emerging global powers. The goal will be to build systems that support democratic governance mechanisms, have oversight arrangements involving the central banks of trusted countries, and promote fair and safe access to clearing and settlement under well‐defined policy guidelines. The use of alternatives to the US dollar as the invoicing currency in international trade will gather momentum. Markets for energy and other commodities will be the change drivers. China has an important role to play.

KONSEP HUKUM ISLAM TENTANG JUAL BELI MATA UANG (AL-SHARF)

International trade activities always require the transfer and conversion of currencies from one country to another. This is because every independent country in the world has the authority to determine the currency used and the exchange rate (the exchange rate of a country's currency with other countries). The purpose of this research is to analyze Islamic law regarding currency trading. The results of the study can be concluded that the legal concept in the implementation of the sharf in Indonesia is regulated through the Fatwa of the National Syari'ah Council of the Indonesian Ulema Council No: 28/DSN-MUI/III/2002 concerning the Sale and Purchase of Currency (Al-Sharf) which in general terms explain that currency buying and selling transactions are allowed in principle.

Withering COVID 19 Storm: Survival Strategies Employed by Informal Traders in Masvingo Urban, Zimbabwe

COVID 19 has shaken and destabilized the whole world and caused untold suffering of the human kind. It has caused serious business and social tremors that have resulted in several huge financial, materials, psychological and social losses throughout the world. The main thrust of this study was to explore the survival strategies that were employed by informal traders in Masvingo urban, Zimbabwe. A qualitative approach, which utilized a multiple case design, was utilized to carry out the study. The study population comprised all cross border traders in Masvingo urban. A sample of 15, 9 female and 6 Male, informal traders were selected using the snow balling sampling technique. All the selected participants were in the business of buying and selling clothes, electrical goods, groceries and foreign currency trading. A 13 item interview guide was used to solicit data from participants. Data was analysed using the thematic data analysis method. The study found out that flexibility and use online applications enabled informal traders to remain afloat during the COVID-19 disruptions. Traders sold their goods in foreign currency mainly the USD and South African rand, ICT aided trading systems. The other strategy adopted to survive included relocation of businesses to growth points and other business centres in rural areas and high density suburbs. Future studies should quantitatively assess the impact of COVID-19 disruptions on the informal sector.

Volatility dependent smooth transitions and abrupt switches: why they are needed for better forecasting the FX rates

Exchange rate prediction is a problematic area. There still does not exist a structural exchange rate model that can consistently predict future exchange rates better than a driftless random walk model. This paper draws attention to two important points regarding this problem. First of all, many structural exchange rate models inherently depend on the uncovered interest parity (UIP) rule. However, empirical evidence almost universally rejects UIP. Therefore, this paper firstly questions whether it would be possible to improve the predictions of UIP by converting it into a nonlinear form since the workhorse UIP specification has traditionally been linear. Secondly, this paper also discusses that a nonlinear transformation is indeed a necessity given that exchange rates typically follow meandering time paths. Inspired by a Bank for International Settlements (BIS) report, UIP model is estimated by volatility-dependent Threshold autoregression (TAR) and Smooth transition regression (STR) specifications using a dataset on two popular carry trade currencies against the US dollar and the Japanese yen. Estimations clearly favor TAR and STR over a linear specification. Although random walk model remains as the champion, results are still indicative of the usefulness of a volatility-dependent regime switching framework for improving the prediction performances of various other structural models that are dependent on UIP.

Patterns of invoicing currency in global trade: New evidence

This paper presents the most comprehensive and up-to-date panel data set of invoicing currency patterns in global trade. It provides data on the shares of exports and imports invoiced in US dollars, euros, and other currencies for 115 countries since 1990. The evidence from these data confirms findings from earlier research regarding the strong persistence in invoicing currency patterns and the globally dominant role of the US dollar. It also points to several novel facts, such as the increase in the use of the dollar and the euro for invoicing, and the use of the euro as a vehicle currency in parts of Africa. Exchange rate pass-through and trade elasticity estimations with these data confirm that countries invoicing more in dollars (euros) tend to experience greater dollar (euro) exchange rate pass-through to their import prices and higher sensitivity of their trade volumes to fluctuations in these exchange rates.

Market Timing and Predictability in FX Markets

Abstract We study the economic value of market timing in foreign exchange (FX) markets, that is, using information about the conditional Sharpe ratio to adjust the notional value of a conditionally mean–variance efficient currency portfolio. Our strategy trades more (less) aggressively when the conditional risk-return trade-off is more (less) favorable. This leads to a significant improvement in the out-of-sample unconditional Sharpe ratio, skewness, and maximum drawdown per 1% expected excess return. The strategy’s market timing predicts returns, volatility, and skewness in FX markets. Popular currency pricing factors do not explain the strategy’s high average excess returns. Our findings suggest that it is costly to impose leverage or risk (i.e., conditional volatility) limits or other inferior market timing policies when constructing currency trading strategies.

A fuzzy ISM analysis of factors in growth of initial coin offerings (ICOs)

In the previous few years, the value of cryptocurrencies and their market capitalization have grown at an incredibly rapid pace. There are currently over 1500 distinct trading currencies with a total market valuation of over 384 billion US dollars. It is the purpose of this study to examine the elements that have helped the ICO industry flourish over the past several years. Findings from previous studies and recommendations from industry professionals lead to the selection of 16 variables. ISM (Interpretive Structural Modeling) analysis was utilised in order to better comprehend the influence and interrelationships across seven different Fuzzy levels of identified obstacles. Based on the drive and reliance power of the Fuzzy matrix utilising Fuzzy MICMAC, the factors are further divided into four primary groups. High reliance and driving power can be found in all but one of the selected fifteen criteria, except for no or low regulation. The storm’s expansion in the field is directly linked to the relationship between all factors. This revolutionary fundraising approach is changing and accepted by common investors because of “no or low regulation,” but it cannot be managed directly by the ICOs industry’s connected participants.

On the asymmetrical connectedness between cryptocurrencies and foreign exchange markets: Evidence from the nonparametric quantile on quantile approach

This study examines the relationship between cryptocurrencies and foreign exchange markets for three digital currencies and six fiat currencies using the quantile on quantile (QQ) regression approach of Sim and Zhou (2015). According to the QQ technique, we estimate how the quantiles of cryptocurrencies affect the foreign exchange market quantiles. It provides a broader view of the entire dependence structure between the forex markets and digital currencies than traditional methods. Our empirical analysis indicates a positive connection between foreign exchange currencies and cryptocurrencies for all nine currencies, particularly Bitcoin, at low, high, and middle tail quantiles. However, differences are present between economies and across quantiles of virtual currencies and fiat currencies for each economy. This heterogeneity is due to variations in economic structure, legal recognition by governments, associated risk, and monetary or macroeconomic policy changes that affect the trading of cryptocurrencies and fiat currencies.

Comparative Study of Forecasting Models for Forex Predictions with the Impact of Different Currencies

- Foreign Exchange (Forex) is the exchange / trading of currencies from different countries with the aim of making profit. Exchange rates on Forex markets are always changing and it is hard to predict. Many factors affect exchange rates of certain currency pairs like inflation rates, interest rates, government debt, term of trade, political stability of certain countries, recession and many more. Uncertainty in Forex prediction can be reduced with the help of technology by using machine learning. There are many machine learning methods that can be used when predicting Forex. The methods used in this paper are Long Short Term Memory (LSTM), Gated Recurrent Unit (GRU), Support Vector Regression (SVR). XGBOOST, and ARIMA. The outcome of this paper will be comparison results that show how other major currency pairs have influenced the performance and accuracy of different methods. From the results, it was proven that XGBoost outperformed other models by 0.36% compared to ARIMA model, 4.4% compared to GRU model, 8% compared to LSTM model, 9.74% compared to SVR model. Keywords— Forex Forecasting, Long Short Term Memory, Gated Recurrent Unit, Support Vector Regression, ARIMA, Extreme Gradient Boosting

Вопросы создания двухуровневой национальной валютной системы стран ЕАЭС

In the article the interaction of national currency system with world monetary system and reserve currencies is considered. The analysis of the world currency systems and substantiation of the need to change the world currency order is given. The concept of a two-level national currency system which based on the introduction of an additional gold national currency backed by gold is proposed. Such an innovation will significantly strengthen the savings function of the national currency and reduce the propensity of the population to dollarize their savings. It will also reduce the role of world currencies, which may become a new stage in the development of a new world monetary system. Ultimately, this may increase the role of national currencies in making payments in international trade and lead to a decline in the role of world reserve currencies. Gold national currency can be introduced in the form of banknotes, bank account and electronic money. The technical solution depends on the specifics and capabilities of each country, as well as on the preferences of the local population. With the growth of the gold national currency in savings and the use of national currencies in international trade, the two-tier national currency system will become more stable.

A Balance-of-Payments-Constrained Growth Model for a Small Commodity Exporting Country: Argentina Between 1971 and 2016

ABSTRACT We study the balance of payments (BOP) as a constraint on economic growth, focusing on Argentina’s economy between 1971 and 2016. The data show that Thirlwall’s balance-of-payments-constrained growth model cannot explain Argentina’s average growth during this period, which witnessed high growth in the terms of trade. We expand Thirlwall’s model based on recent empirical indications that exporters set their prices in foreign currencies. Thus, we show new ways in which the terms of trade and real exchange rate impact the growth rate compatible with the BOP equilibrium. While prices affect the growth rate compatible with the BOP equilibrium mainly through changes in the original model’s quantities, the proposed extension finds a stronger direct effect of the terms of trade. Through the extended model, we find that the weak and strong tests of Thirlwall’s Law are not rejected. Further, we show the consistency of the results regardless of the assumed country size or presence of structural economic breaks. Consequently, we argue that prior literature was inconclusive for Argentina as it did not consider invoicing of international trade in foreign currency, thus disregarding the full effect of the terms of trade and real exchange rate on growth compatible with the BOP equilibrium.

FEATURES OF FUNCTIONING AND SETTING OF THE SOFTWARE REGISTRAR OF SETTLEMENT TRANSACTIONSIN UKRAINE

Since August 1, 2020, in Ukraine, along with the traditional registrars of settlement transactions (RST) it is possible to use software RST, which is a technological and / or software solution used on any device in which the fiscal functions are realized through the fiscal server of the regulatory authority. Such a solution is designed to register settlement transactions for the sale of goods (provision of services), currency trading transactions in cash and / or register the number of sold goods (provided services), cash acceptance transactions for further transfer. Thus, software RST can be installed on any device (smartphone, tablet, laptop, etc.), which is certainly one of its advantages over traditional RST. It is more convenient to use a computer or notebook as a base of software RST on the premises, while for couriers, cab drivers, mobile points of sale for coffee, ice cream, etc. the most optimal is the use of a smartphone. Mandatory paper receipts will soon become an archaism. Along with them, entrepreneurs can now provide customers with electronic versions of receipts by email or in the form of a QR code. Thus, the introduction of a software registrar of settlement transactions is a step into the future in which more and more habitual activities in all spheres of life will be transferred online. The article gives an overview of the features of functioning of the program registrar of settlement operations. The advantages of its use for business, based on a comparison of its work with the hardware registrar of accounting transactions, are described. Describes the scenario by which checks are fiscalized in the office of the State Tax Service (STS) through the use of PRST. The development of the commercial PRST as a module that can be used for integration with the accounting software on the Windows operating system is carried out. An example of XML filter for receipts and their fiscalization is given. Describes the settings required for the correct operation of the commercial PRST according to the legislation of Ukraine, which allowed to simplify the process of settlement transactions in the field of trade and increase their automation.

Competition of the world leading currencies: Features of the current stage

Subject. The article analyzes the competition of the world leading currencies in the global economy, specifics of the current stage, trends in the role of particular currencies in the global market. Objectives. The purpose is to review the current positions of the U.S. Dollar, Euro and Yuan in the global financial markets, assess prospects for maintaining the leading role of the U.S. Dollar, development trends in the position of Euro and Yuan. Methods. I applied the content analysis of available sources, provide a historical overview of issues under consideration, scrutinized the estimates of financial analysts. Results. The paper unveils reasons for increased competition of the leading currencies (U.S. Dollar, Euro, Yuan) in the global foreign exchange market, which include an increase in the scale of payment transactions in the global financial and commodity markets. It also reveals trends in the use of particular currencies in foreign trade and financial transactions, evaluates prospects for the use of specific world currencies in the global economy. Conclusions. At present, U.S. Dollar maintains its leading positions. However, in the future, an increase in the use of Euro- and Yuan-denominated transactions should be expected in the commodity and financial markets due to enlarged presence of Chinese companies in the global economy. Further development of European integration can ensure the expansion of the single European currency in the global financial market. The share of Yuan in foreign exchange reserves of central banks tends to increase. Private investors' demand for Yuan is also expected to grow.

The BitcoinHeist: Classifications of Ransomware Crime Families

Ransomware attacks are on the rise and attackers are hijacking valuable information from different critical infrastructures and businesses requiring ransom payments to release the encrypted files. Payments in cryptocurrencies are designed to evade tracing the transactions and the recipients. With anonymity being paramount, tracing cryptocurrencies payments due to malicious activity and criminal transactions is a complicated process. Therefore, the need to identify these transactions and label them is crucial to categorize them as legitimate digital currency trade and exchange or malicious activity operations. Machine learning techniques are utilized to train the machine to recognize specific transactions and trace them back to malicious transactions or benign ones. I propose to work on the Bitcoin Heist data set to classify the different malicious transactions. The different transactions features are analyzed to predict a classifier label among the classifiers that have been identified as ransomware or associated with malicious activity. I use decision tree classifiers and ensemble learning to implement a random forest classifier. Results are assessed to evaluate accuracy, precision, and recall. I limit the study design to known ransomware identified previously and made available under the Bitcoin transaction graph from January 2009 to December 2018.

Google Search in Exchange Rate Models: Hype or Hope?

This paper studies the power of online search intensity metrics, measured by Google, for examining and forecasting exchange rates. We use panel data consisting of quarterly time series from 2004 to 2018 and ten international countries with the highest currency trading volume. Newly, we include various Google search intensity metrics to our panel data. We find that online search improves the overall econometric models and fits. First, four out of ten search variables are robustly significant at one percent and enhance the macroeconomic exchange rate models. Second, country regressions corroborate the panel results, yet the predictive power of search intensity with regard to exchange rates vary by country. Third, we find higher prediction performance for our exchange rate models with search intensity, particularly in regard to the direction of the exchange rate. Overall, our approach reveals a value-added of search intensity in exchange rate models.

Effects of exchange rates and invoiced currencies on trade: Evidence from South Korea

AbstractThis study examines the relationship between exchange rates and South Korea's trade flows considering invoicing currencies in line with the dominant currency paradigm. We use the trade weight data of South Korea's total and bilateral trade with its major trading partners. Our analysis of the elasticities of South Korea's trade with respect to bilateral exchange rates shows that a strong US dollar—the dominant invoiced currency—is associated with a decline in South Korea's imports, regardless of the country of origin. We also show that the Japanese yen, as the other dominant invoicing currency in bilateral trade between South Korea and Japan, has a similar effect to that of the US dollar. In addition, fluctuations in the invoicing share of dominant currencies improve the statistical significance of the effect of exchange rate changes. We also report the results at the sectoral level. Overall, our results are consistent with the dominant currency paradigm. Finally, according to the South Korea pass‐through results, which show that US dollar rate fluctuations affect both import and consumer prices immediately, South Korean importers seem to react quickly by changing trade quantities and domestic sales prices.