The article focuses on determining the impact of the consequences of the russian invasion of Ukraine on macroeconomic stability and the exchange rate of the national currency. The relevance of the ...chosen topic is substantiated. The problems of assessing the negative consequences of the russian invasion of Ukraine are outlined, including: violation of general macroeconomic stability, significant fluctuations in foreign exchange markets and destabilization of the national currency. The study considers the theoretical and methodological foundations of the study of foreign exchange markets and analyzes global trends in the development of the global currency market. The structure of world currency reserves is analyzed according to the assessment of the currency composition of the official currency reserve (COFER) of the IMF. The analysis of the dynamics of average spreads of purchase and sale of reserve currencies against the US dollar for traditional and non-traditional reserve currencies is carried out. As a result of studying world trends, the main factors that affect fluctuations in the exchange rate of currencies are identified. The main problems regarding the functioning of the national currency market in the context of the hostilities in Ukraine are outlined, in particular, the existing inflationary processes are analyzed. The dynamics of currency interventions of the NBU for 2021-2022 is considered. The features (advantages) of the application and the results of using the singular spectral analysis (SSA) method for predicting fluctuations in the US dollar and Euro in the national foreign exchange market are presented. The practical implementation of this method was carried out using the CaterpillarSSA software product. Evaluation of the accuracy of the forecast is performed using the MAPE method. The obtained forecast errors (less than 6%) suggest that the constructed models are adequate and can be used for further research and recommendations. Thus, it can be concluded that for Ukraine the most important factors affecting the exchange rate are seasonality and successful trade policy of the government, which, in turn, largely depends on resource prices. The carried out research allowed to highlight the features and main aspects of the functioning of the foreign exchange market of Ukraine during the period of ongoing military aggression.
RODOFEBISU – Trading Support System Tkachenko, Olexandr; Kutsenko, Mykyta; Fleshner, Hlib
Cifrova platforma: ìnformacìjnì tehnologìï v socìokulʹturnìj sferì,
12/2022, Volume:
5, Issue:
2
Journal Article
Peer reviewed
Open access
The purpose of the article is to study, analyze and consider the general problems and prospects of developing software for trading RodOfEbisu with the possibility of automated trading based on a ...recommendation algorithm.
The research methods are the basic methodologies and algorithms for successful trading. The article considers approaches to the development and operation of software for automated trading.
The novelty of the research is the analysis of modern trading methods in different markets, the results of which can be used in the development of its own trading automation product, which is an assistant and, possibly, can become an independent unit.
Conclusions. The paper investigates the existing views on the modern approach to decision-making and buying, which can be used to develop its own product – a trader’s assistant. Taking into account the results of the analysis, it was decided to develop software for trading RodOfEbisu, which can act as an advisor and executor, with the possibility of using different trading strategies.
This paper examines the short- and medium run dependence structures between oil and currency markets for MENA, other developing and developed countries, using a novel multiresolution decomposition ...method, namely the variational mode decomposition (VMD), along with a battery of time-invariant and time-varying symmetric and asymmetric copula functions. Further, we assess the downside and upside short- and medium-run risk spillovers from oil to U.S. exchange rate returns and vice versa by computing the conditional Value-at-Risk (CoVaR) risk measures. Before the copula estimations, we apply the spillover index of Diebold and Yilmaz (2012) and network diagrams to identify and select the currencies that are the most significant net contributors or net receivers of returns from/to the oil/currency markets. The copula results show strong evidence of time-varying and high average (tail) dependence between oil returns and the FX markets, which are net transmitters to oil, for the short and medium time horizons. On the other hand, we find average and relatively low dynamic dependence between oil and the net receiver currencies, regardless of the time horizons. Moreover, there is evidence of up and down risk asymmetric systemic risks from oil to currencies and vice versa for some countries in the short-and medium run horizons. Finally, the risk spillovers are asymmetric over time and investment horizons. These results have several important implications for hedging strategies and diversification benefits for oil and FX traders and institutional investors.
•The paper examines systemic risk and dependence structures between oil and 25 currency markets.•We employ the Diebold-Yilmaz index, multiresolution and copula approaches.•We quantify short- and medium-run up and down risk spillovers using the CoVaRs.•We find average and tail dependence between oil and currencies which varies under time horizons.•We provide evidence of higher risk spillovers in the medium- than short-run investment horizons.
In this paper we show that the Chilean exchange rate has the ability to predict the returns of oil and of three additional oil-related products: gasoline, propane and heating oil. We show this using ...both in- and out-of sample exercises at multiple horizons. Natural explanations for our findings rely on the well know “dollar effect” and on the present-value theory for exchange rate determination in combination with the strong co-movement displayed by fuel and metal prices. Given that the Chilean economy is heavily influenced by copper, which represents nearly 50% of total national exports, the floating Chilean Peso is importantly affected by price fluctuations in this metal. As oil-related products display an important co-movement with base metal prices, it is reasonable to expect evidence of Granger causality from the Chilean peso to these oil-related products. Interestingly, we provide sound evidence indicating that the predictive ability of the Chilean Peso goes beyond these natural explanations. In particular, we show another plausible predictive channel: volatility in combination with a negative contemporaneous leverage effect in fuel returns. Finally, we compare the Chilean peso with other commodity-currencies in their ability to predict fuel returns. The Chilean peso fares extremely well in this competition, especially at short horizons of one, three and six months.
•The Chilean exchange rate has the ability to predict fuel returns at several horizons.•This predictability goes beyond the Commodity Currency Hypothesis.•The Chilean peso outperforms other commodity currencies in their ability to predict fuel returns.•The Chilean peso has the ability to predict WTI realized volatility.•We introduce a volatility channel to the commodity-currency forecasting literature.
Introduction
Time series models on financial data often have problems with the stationary assumption of variance on the residuals. It is well known as the heteroscedasticity effect. The ...heteroscedasticity is represented by a nonconstant value that varies over time.
Methods
The heteroscedasticity effect contained in the basic classical time series model of Autoregressive Integrated Moving Average (ARIMA) can adjust its residuals as the variance model by using Generalized Autoregressive Conditional Heteroscedasticity (GARCH). In improving the model accuracy and overcoming the heteroscedasticity problems, it is proposed a combination model of ARIMA and Feed-Forward Neural Network (FFNN), namely ARIMA-FFNN. The model is built by applying the soft computing method of FFNN to replace the variance model. This soft computing approach is one of the numerical methods that can not be only applied in the theoretical subject but also in the data processing.
Results
In this research, the accuracy of the time series model using the case study of the exchange rate United States dollar-Indonesia rupiah with a monthly period from January 2001 to May 2021 shows that the best accuracy of the possible models is the model of ARIMA-FFNN, which applies soft computing to obtain the optimal fitted parameters precisely.
Discussion
This result indicates that the ARIMA-FFNN model is better used to approach this exchange rate than the rest model of ARIMA-GARCH and ARIMA-GARCH-FFNN.
In 1962, surgeons at two hospitals in Bombay used heart-lung machines to perform open-heart surgery. The devices that made this work possible had been developed in Minneapolis in 1955 and ...commercialized by 1957. However, restrictions on currency exchange and foreign imports made it difficult for surgeons in India to acquire this new technology. The two surgeons, Kersi Dastur and PK Sen, pursued different strategies to acquire the ideas, equipment, and tacit knowledge needed to make open-heart surgery work. While Dastur tapped Parsi networks that linked him to local manufacturing expertise, Sen took advantage of opportunities offered by the Rockefeller Foundation to access international training and medical device companies. Each experienced steep learning curves as they pursued the know-how needed to use the machines successfully in dogs and then patients. The establishment of open-heart surgery in India required the investment of substantial labor and resources. Specific local, national, and transnational interests motivated the efforts. Heart-lung machines, for instance, took on new meanings amid the nationalist politics of independent India: Even as surgeons sought imported machines, they and their allies assigned considerable value to ‘indigenous’ innovation. The confluence of the many interests that made Sen and Dastur’s work possible facilitated the uneasy co-existence of conflicting judgments about the success or failure of this medical innovation.
This paper establishes a hybridized intelligent machine learning based currency exchange forecasting model using Extreme Learning Machines (ELMs) and the Jaya optimization technique. This model can ...very well forecast the exchange price of USD (US Dollar) to INR (Indian Rupee) and USD to EURO based on statistical measures, technical indicators and combination of both measures over a time frame varying from 1day to 1month ahead. The proposed ELM-Jaya model has been compared with existing optimized Neural Network and Functional Link Artificial Neural Network based predictive models. Finally, the model has been validated using various performance measures such as; MAPE, Theil'sU, ARV and MAE. The comparison of different features demonstrates that the technical indicators outperform both the statistical measures and a combination of statistical measures and technical indicators in ELM-Jaya forecasting model.
Cryptococcal meningitis is a major cause of mortality and morbidity in countries with high HIV prevalence, primarily affecting patients whose CD4 are < = 100 cells/μl. Routine Cryptococcal Antigen ...(CrAg) screening is thus recommended in the South African HIV treatment guidelines for all patients with CD4 counts < = 100 cells/μl, followed by pre-emptive anti-fungal therapy where CrAg results are positive. A laboratory-based reflexed CrAg screening approach, using a Lateral Flow Assay (LFA) on remnant EDTA CD4 blood samples, was piloted at three CD4 laboratories.
This study aimed to assess the cost-per-result of laboratory-based reflexed CrAg screening at one pilot CD4 referral laboratory.
CD4 test volumes from 2014 were extracted to estimate percentage of CD4 < = 100 cells/μl. Daily average volumes were derived, assuming 12 months per/year and 21.73 working days per/month. Costing analyses were undertaken using Microsoft Excel and Stata with a provider prospective. The cost-per-result was estimated using a bottom-up method, inclusive of test kits and consumables (reagents), laboratory equipment and technical effort costs. The ZAR/$ exchange of 14.696/$1 was used, where applicable. One-way sensitivity analyses on the cost-per-result were conducted for possible error rates (3%- 8%, reductions or increases in reagent costs as well as test volumes (ranging from -60% to +60%).
The pilot CD4 laboratory performed 267000 CD4 tests in 2014; ~ 9.3% (27500) reported CD4< = 100 cells/μl, equivalent to 106 CrAg tests performed daily. A batch of 30-tests could be performed in 1.6 hours, including preparation and analysis time. A cost-per-result of $4.28 was reported, with reagents contributing $3.11 (72.8%), while technical effort and laboratory equipment overheads contributed $1.17 (27.2%) and $0.03 (<1%) respectively. One-way sensitivity analyses including increasing or decreasing test volumes by 60% revealed a cost-per-result range of $3.84 to $6.03.
A cost-per-result of $4.28 was established in a typical CD4 service laboratory to enable local budgetary cost projections and programmatic cost-effectiveness modelling. Varying reagent costs linked to currency exchange and varying test volumes in different levels of service can lead to varying cost-per-test and technical effort to manage workload, with an inverse relationship of higher costs expected at lower volumes of tests.
This paper investigates the impact of foreign fund’ flow on the Indonesian stock index incorporating other variables, namely the international stock market, gold price, foreign exchange rate, and the ...oil price. GJR-GARCH (1,1) model is used to analyze daily time-series data on IDX, foreign fund flows, the S&P 500, and gold, currency, and oil prices from 2014 to 2019. There is an evidence of leverage effect. It means that there is an asymmetric news impact on the conditional variances. Currency and oil prices are the only variables to have an impact on the Indonesian stock market index, while the rest of the variables do not influence the index. The government may provide infrastructures to attract foreign investors. At the same time, the government has to issue the policy that will protect the economy from stock market shocks. Finally, investors may include gold in their portfolio to diversify their investments.
JEL Classification: G120, G10, G40
Financial markets are seen as one of the most important markets in economic terms. The activities of investors in the financial markets consist in predicting how best to invest the accumulated ...capital, using all kinds of analyzes and forecasts. In the literature on the subject, apart from fundamental analysis, technical analysis is distinguished. While the first one is to help you choose a specific asset with profitable potential, technical analysis is designed to help the investor find a specific moment that is most suitable for buying or selling. The aim of the article is to demonstrate the potential benefits associated with modifying the default settings of technical analysis indicators on the example of the EUR/USD currency pair using the MetaTrader4 investment platform. Analizing was carried out on the basis of the most popular currency pair in terms of turnover on the Forex market - EUR/USD. The research used an investment strategy based on Parabolic SAR and Relative Strength Index RSI technical analysis indicators, whose indications were verified both in the context of default settings and after the author‘s modification. The results of the conducted research indicate significant differences, depending on the adopted parameters of the above-mentioned indicators.
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