Price Exchange Research Articles

Analyzing and Measuring the Relationship between Public Spending and the Parallel Exchange Rate in the Iraqi Economy for the Period 2004-2022

Public spending represents the government’s financial leverage and has a significant impact on real and monetary economic variables, and one of these effects is the effect of public spending on the exchange rate as an important monetary variable for monetary policy, As we know that public spending in Iraq is financed from oil revenues sold in US dollars, and the Ministry of Finance converts the US dollar into Iraqi dinars to finance the government's need to spend within the requirements and obligations of the state's general budget, And converting the US dollar into Iraqi dinars has an impact on the parallel exchange market, even if there is a contractual exchange rate between the Ministry of Finance and the Central Bank of Iraq to convert the budget dollar into Iraqi dinars. However, the impact of public spending on reserves makes financial shocks have a significant impact on the exchange rate. The researcher believes that there is a reciprocal relationship between the effect of public spending on the exchange rate and the impact of the exchange rate on public spending because the conversion compass between the dollar and the dinar leaves great effects on public spending in the state’s general budget, and this is what the researcher achieved by using modern standard software to discover the nature of the relationship between public spending and the price of Exchange in the parallel market with realistic monthly data taken from the official website of the Central Bank of Iraq.

A STUDY OF DETERMINANTS OF FIRM VALUE OF INDIAN IT SECTOR: WITH SPECIAL REFERENCE TO EFFECT OF FOREIGN EXCHANGE RISK

Foreign currency risk is one of the most common types of risk that foreign businesses face, and risk management has become one of the most important aspects of comprehensive financial management in recent years. The exposure of a company to changes in foreign exchange prices is called foreign exchange risk, whilefirm value is an economic metric that reflects the market value of a company as a whole, i.e. the value that should be distributed among its shareholders and debt holders. The main objective of this study is to identify the effect of foreign exchange exposure on Firm Value for selected Indian IT companies. Five IT companies covering the tenyear data (2009 to 2018) have been selected for the study. Secondary data have been collected from their annual reports which have been analyzed through regression and analysis of variance with a view to predict the effect of foreign exchange risk. The study reveals that Foreign Exchange Risk is least consistent variable and there is a negative correlation between Foreign Exchange Risk on Firm Value.Result of Regression Analysis shows that there isinsignificant positive impact of Foreign Exchange Risk on Firm Value

The Accuracy of Relative Strength Index (RSI) Indicator in Forecasting Foreign Exchange Price Movement

This study aims to measure the accuracy of the Relative Strength Index (RSI) Indicator in predicting the direction of foreign exchange (forex) price movements. To achieve the research objectives, six foreign exchange currencies that fall into the major pair category were determined as samples. RSI data is collected from the Foreign Exchange Market which can be accessed via tradingview.com during the research period, January – September 2021. The data is analyzed using SPSS software with the Mann Whitney U Test which can prove statistically whether there is a significant difference between the predictions of forex price movements with the reality price movement. Thus, this study provides evidence of the accuracy of the Relative Strength Index (RSI) Indicator in predicting the direction of forex price movements. The findings of this study can be a reference for practitioners such as forex traders or business people who deal with foreign currencies in choosing technical analysis methods that can help make the right decisions.

Stock Price Forecasting: Machine Learning Models with K-fold and Repeated Cross Validation Approaches

Background: Stock exchange price prediction is one of the most researched topics, attracting interest from both academics and industry. Various algorithms have been developed since the introduction of Artificial Intelligence (AI) and have been used to forecast equities market movement. Despite all these researches, less attention has been paid to the use of cross validation (CV) approaches for better stock price prediction. Objective: The aim of this work is to predict Nigerian stock prices using machine learning models with K-fold and repeated K-fold CVs. Methods: In this work, we consider the prediction performance of machine learning models under two cross validation approaches, namely K-fold and repeated K-fold CVs and when no cross validation technique is used. The models consider here are simple linear regression model, random forest (RF), classification and regression tree (CART), and artificial neural network and the support Vector Machine model. Standard strategic indicators such as root mean square error and mean absolute error are used to evaluate the models. The financial data including real gross domestic product, inflation rate, exchange rate and interest rate are used as the input units in the model. Results: Predicting models with CVs technique exhibit superior performance to models with no CV technique involved. Conclusion: Modelling and forecasting stock exchange prices using RF model with CV are conducive to prediction for stock exchange price in Nigeria. Future research are warranted to consider other machine learning models with CVs approaches.

COVID-19 INFLUENCE OVER BRAZILIAN AGRICULTURAL COMMODITIES AND DOLLAR–REAL EXCHANGE

This study evaluates the Brazilian agricultural commodities market and the dollar–real exchange price variation using the multifractal detrended fluctuations analysis methodology. We investigated the period from January 1, 2019 to September 25, 2019, outside the COVID-19 pandemic, and from January 1, 2020 to September 25, 2020, during the COVID-19 pandemic. We verified the fluctuations of commodities and dollar–real exchange prices during the pandemic caused by COVID-19 showed a record price. The results of Hurst exponent and multifractal parameters [Formula: see text], [Formula: see text], and [Formula: see text] indicate that during the COVID-19 pandemic, sugar was the most efficient commodity, while pork the less one. Compared to the identical months in 2019, the dollar–real exchange was the most efficient market, while ethanol was the least efficient.

The Inflation Effect of Exchange Rate and Price Stickiness in Turkey: NARDL Approach

Küreselleşme akımının etkisiyle birlikte ülkeler arasındaki sınırların ortadan kalkması uluslararası mal alışverişlerini hızlandırırken uluslararası alışverişler için gerekli döviz ihtiyacını da artırmaktadır. Bu durum döviz kurunda meydana gelen değişmelerin ekonomi üzerindeki etkisini artırmaktadır. Döviz kurlarında meydana gelen dalgalanmalar ithalata dayalı üretim ya da satış yapan endüstrilerde maliyet artışıyla birlikte yurtiçi fiyatları yükselterek bir enflasyonist sürecin yaşanmasına neden olmaktadır. Dolayısıyla bu çalışmada Türkiye’de 2013Q1-2021Q1 dönemi arasındaki enflasyon ile döviz kuru, ihracat ve ithalat arasındaki asimetrik ilişki NARDL yöntemi ile test edilmektedir. Çalışma sonucunda döviz kuru, ithalat ve ihracatın enflasyon üzerinde asimetrik etkisinin olduğu ve Türkiye’ de bu sürecin fiyat yapışkanlıklarına neden olduğu gözlemlenmiştir.

STOCK EXCHANGE MARKETING AS A FACTOR IN THE DEVELOPMENT OF INFORMATION PROVISION OF PRICE FORMATION MANAGEMENT IN GOODS EXCHANGING

It was researched the economic nature of the concept of “exchange marketing” and the levels of its management of exchange activities in this article. We analyzed the specifics of the exchange marketing, that conditioned due toexchange services. It was proved that exchange marketing is a factor in the development of information management of pricing in goods exchanging. The foreign experience of using exchange marketing as a method of management of exchange activity and as a method of research the market of exchange services was studied. The definition of «information support for the management of exchange pricing of commodities» was formulated. The conceptual model of balanced development of information support of pricing management in goods exchange includes: first of all it includes the conceptual basis that consist: 1) methodology: methods (costly, marketing and parametrical) and approaches (organizational, local, system (complex), functional, marketing, processing and resulting); 2) principles: systematicity, standardization, compatibility, data security, efficiency, reliability, adaptability, productivity, development, transparency and high standards of information disclosure; secondly, it includes tactical landmarks: 1) exchange system consolidation; 2) electronic securities and derivatives circulation streamlining; 3) the level of financial literacy awareness raising. It was proposed to use such a tool as Fillratio control to satisfy traders interests. It was turned out that the exchange gives the market makers a competitive advantage over traders by providing the last look system. It was determined that one of the goals of the exchange is to provide equal conditions for all market participants. It has been established if market makers given an opportunity to cancel any trader’s transaction, so they (market makers) will do that with the least market volatility and the least movement of the market price in a disadvantageous way for the market maker. It was substantiated that a large amount of turnover is occupied by algorithmic (automated) trading systems, the so-called trading robots of two types: arbitration and others among the investment-speculative operations.

About subsidizing socially significant exchange commodities

The article is devoted to the issues of subsidizing, which are very relevant in the light of recent discussions on improving the mechanisms of direct and implicit price subsidies. The paper discusses the issues of subsidizing of socially important goods, which include, for example, oil refinery products, liquefied gas and others, provides formulas for the amount of subsidies, determining the cost of subsidizing, the trader's margin from the exchange price. These calculations will contribute to the correct planning of regional budgets for subsidies.

The Conundrum of Stock Market Performance and Gross Domestic Product: An Empirical Evidence from Kenya

The main objective of this study was to establish is the difficult question among researchers on the direction of relationship between the stock market performance and the gross domestic product using an empirical evidence from Kenya. Both theoretical and empirical reviews have presented a puzzle especially in the long run relationship between the two variables and empirical investigations in various country contexts , time varying longitudinal periods and other settings have continued to provide conflicting results. The study employed quarterly statistics of the Nairobi All Share Index (NASI) obtained from the Capital Markets Authority Bulletins and quarterly Gross Domestic Product rates from 2012-2019 obtained from Kenya National Bureau of Statistics and applied the Engle granger causality test and establish the link between stock market performance and economic growth in the long run (i.e. whether stock market performance causes economic growth or itself is a consequence of increased economic activity). The statistical techniques used included the unit root Augmented Dickey Fuller (ADF) test in order to test the stationarity for all the time series in their levels and first differences. The Johansen co-integration test to investigate whether the variables are cointegrated of the same order taking into account the trace statistics and the maximum eigen-value tests. The data was transformed into natural logarithms and normalized for further analysis. Both GDP and NASI were found to be stationery at level and upon first difference after ADF tests. The findings were that there was none directional/No causal relationship between the two variables after conducting a pairwise granger causality test, however there was a significant cointergrating equation on the variables, signifying the long run relationship between the two variables. From the results, it was inferred that the movement of stock prices in the Nairobi stock exchange reflect the macroeconomic condition in the long run of the country and can therefore be used to predict the future path of economic growth however the puzzle continues on causality.

Multiperiod Portfolio of Energy Purchasing Strategies including Climate Scenarios

Because electricity retailers must ensure that energy supply matches end-user demand, electricity that is not traded through bilateral contracts is typically traded in power exchanges which are subject to great price volatility. In Colombia, the spot price is a reflection of climate variability because approximately 70% of the country’s electricity is generated by large hydropower stations. In this study, we forecast 2018′s prices and calculated its corresponding purchase margins using the 2015 to 2017 bilateral contract prices for electricity plus power exchange price information and climate information. Our forecasts included climate uncertainty and evaluated two multi-period portfolio methods for deciding among three purchasing strategies: bilateral contracts in the regulated market, bilateral contracts in the non-regulated markets, and purchases in the power exchange. The results indicate that retailers should follow a middle course that is neither conservative nor risky. Creation of portfolios independent of the multi-period method can balance purchases through bilateral contracts and in the power exchange in a way that considers climatic uncertainty. This type of balanced portfolio could control medium-term risks of price volatility and result in good levels of purchase margins.

The purchasing power parity and exchange‐rate economics half a century on

AbstractThe value of a country's currency is often considered as the most important price in the economy. Exchange‐rate changes can significantly affect the profitability of exporters, the prices paid by consumers, as well as complicating the comparison of the economies of different countries. In this article, we illustrate the workings of the purchasing power parity (PPP) and demonstrate its practical use with cross‐country data covering the 50 years since the collapse of the Bretton Woods monetary system. We find that despite the prolonged gyrations of currency values and the multitude of trade barriers, the forces of arbitrage and resource re‐allocation are sufficient to overcome many of these distortions in the longer term. We also provide a broad survey of other prominent themes, both extant and emerging, in international economics that highlight the importance of the relationship between exchange rates and prices.

Stock Price Prediction Using Random Forest Method and Twitter Sentiment Analysis

Stock price forecasting could be a vital and thriving topic in financial engineering especially since new techniques and approaches on this matter are gaining ground constantly. Within the contemporary era, the ceaseless use of social media has reached unprecedented levels, which has led to the belief that the expressed public sentiment could be correlated with the behaviour of stock prices. The concept is to acknowledge patterns which confirm this correlation and use them to predict the future behaviour of the assorted stock prices. With little doubt, though uninteresting individually, tweets can provide a satisfactory reflection of public sentiment when taken in aggregate. We develop a system which collects past tweets, processes them further, and examines the effectiveness of varied machine learning techniques like Naive Bayes Bernoulli classification and Support Vector Machine (SVM), for providing a positive or negative sentiment on the tweet corpus. Subsequently, we employ the identical machine learning algorithms to research how tweets correlate with exchange price behaviour. Finally, we examine our prediction's error by comparing our algorithm's outcome with next day's actual close price. Overall, the final word goal of this project is to forecast how the market will behave within the future via sentiment analysis on a collection of tweets over the past few days, also on examine if the idea of contrarian investing is applicable. the ultimate results seem to be promising as we found correlation between sentiment of tweets and stock prices.

Dynamic pricing of electricity: Enabling demand response in domestic households

Fluctuations in retail energy prices may incentivize domestic households to adapt their load pattern in order to minimize the cost of electricity. This paper determines the price volatility necessary for automatic load shifting to cover the cost of the associated smart metering within a household. This study shows that current price volatility does not allow sufficient savings to compensate for additional metering costs. However, results indicate that a change towards an ‘ad-valorem’ electricity taxation dependent on exchange prices could make residential demand-side management profitable. At the same time, the potential price risk for consumers that do not react to pricing signals because of a lack of smart devices, is almost negligible. As consumption patterns suggest, these households consume in times of both high and low prices, thereby almost canceling out higher payments at peak times even without any load shifts. With these results, policymakers can anticipate the effects of dynamic retail prices on electricity and derive the implications of different taxation settings.

Monetary Policy Performance under Control of exchange rate and consumer price index

Central Reserve announced the Monetary Policy Rate from 1955 to 2021 in different ways, and the central bank should be equally interested in the output of exchange rate and price stability. Besides having a stabilizing effect on the price level and trend of exchange rate stabilized the countries outputs. We find that monetary policy control; the price level does not affect production and exchange rate. Monetary policy is the only thing that can change the trend of exchange rate and Consumer Price Index. The actual policy was fixed exchange rate, and currency devaluations like Japan were quite successful for stability. The results indicate that the central bank can stabilize much of the macroeconomic indicators and disturbances under a monetary exchange rate and consumer price index system.

Decentralized bi-level stochastic optimization approach for multi-agent multi-energy networked micro-grids with multi-energy storage technologies

This paper presents a novel decentralized bi-level stochastic optimization approach based on the progressive hedging algorithm for multi-agent systems (MAS) in multi-energy microgrids (MEMGs) to enhance network flexibility. In the proposed model, suppliers and consumers of three energy carrier of power, heat, and hydrogen are considered. This system further consists of multi-energy storage systems such as plug-in electric vehicle aggregators, thermal energy storage, and hydrogen energy storage with the application of power-to-hydrogen and hydrogen-to-power technologies. Furthermore, the Latin Hypercube Sampling method has been utilized to manage the uncertainties. In addition, a penalty function and a power exchange pricing model are evaluated by the electrical marginal price of each microgrid to determine the agreed power exchange among the MEMGs. The suggested work performs over a MAS with three MEMGs. The total profit of each microgrid is maximized over a 24-h scheduling in three diverse case studies. Ultimately, the proposed decentralized bi-level optimization approach, by converging through seven iterations, indicates an effective performance as a promising solution to a MAS-based framework. Besides, the optimal scheduling of the MEMGs were converged in the same profit for the diverse network topologies. Implementing multi-energy storage systems plays a major role in increasing total profit of MEMGs and improving the reliability performance of MAS-based structure.

Exchange Rate Fluctuations and Economic Growth in Nigeria (1981 – 2020)

This study examined the relationship between exchange rate and economic growth in Nigeria between 1981 and 2020. The specific objectives are to determine the effects of exchange rate, inflation and interest rate on gross domestic product (GDP). The data on the variables were obtained from the Central Bank of Nigeria (CBN) Statistical Bulletin and World Development Indicators, and analyzed using descriptive statistics, unit root as well as bounds cointegration tests and ARDL model. The unit root test results showed that the variables are mixed integrated. While inflation is stationary at levels, the other variables in the model were stationary at first difference. The bounds cointegration test showed that long run relationship exists between GDP growth and the underlying explanatory variables. The findings showed that exchange rate and inflation negatively impacted on economic growth. This finding indicates that increase in exchange rate and price level is detrimental to the growth of the Nigerian economy. There is evidence of a significant positive effect of interest rate on GDP growth. This finding explains the reality in Nigeria, where businesses and households tend to borrow even as interest rate increases, but tend to cut corners by reducing the quality of their products and services or pass-on the increased costs of borrowing to consumers by increasing prices. Given the findings, this study recommends amongst others that the federal government through the CBN should ensure that exchange rate policy should is consistent to provide opportunity for a realistic and stable exchange rate capable of driving economic growth in Nigeria.

Warehouse load-out queues and aluminum prices

Long load-out queues emerged in two LME exchange warehouses as the consequence of the serious stock overhang in the years following the Global Financial Crisis. The warehouse operators chose to operate a restrictive rule on load-outs causing long load-out queues (over 2 years at their peak). These queues raised the premiums over the exchange price paid by consumers and received by producers. Contrary to some claims, the exchange price did not fall to offset higher premiums with the result that transactions prices were also raised. The episode points to problems with mutual exchanges and raises questions about UK regulatory oversight.

Power Theory of Exchange and Money

Modern exchange theories model a large market, but do not explain single exchanges. This paper considers the phenomenon of single exchange and formulates the general exchange problem in the form of a system of two equations, subjective and objective. Subjective equilibrium is given by the Walras–Jevons marginal utility equation. Objective equilibrium equations by Walras and Jevons are averaged over all transactions in the market and can only give a rough general picture without explaining the specific price of an individual exchange. An exchange micro-condition must be found that, when averaged, will give the Walras market equilibrium macro-condition. The study of the internal structure of exchange leads to the need to consider power. The concept of generalized power is introduced. It is generalized power that serves as the primary comparable and measurable objective basis of exchange. The power theory of exchange provides the objective price-equation. It is demonstrated that money is a measure of generalized power in exchange and a certification of generalized power in subsequent exchanges. This methodology is based on an interdisciplinary analysis of an abstract exchange model in the form of a system of equations. The proposed theory is able to uniformly explain any exchange, including a single one, which is impossible with the existing theories of exchange.

Stock Price Prediction Using Optimal Network Based Twitter Sentiment Analysis

In recent times, stock price prediction helps to determine the future stock prices of any financial exchange. Accurate forecasting of stock prices can result in huge profits to the investors. The prediction of stock market is a tedious process which involves different factors such as politics, economic growth, interest rate, etc. The recent development of social networking sites enables the investors to discuss the stock market details such as profit, future stock prices, etc. The proper identification of sentiments posted by the investors in social media can be utilized for predicting the upcoming stock prices. With this motivation, this paper focuses on the design of effective stock price prediction using dragonfly algorithm (DFA) based deep belief network (DBN) model. The DFA-DBN technique aims to properly determine the sentiments of the investors from Twitter data and forecast future stock prices. From Twitter data, the DFA-DBN technique attempts to accurately determine the sentiments of investors, as well as predict future stock prices. For accurate stock price prediction, the proposed DFA-DBN model includes the development of a DBN model. The proposed DFA-DBN model involves the design of DBN model for accurate prediction of stock prices. Besides, the hyperparameter tuning of the DBN technique is performed by utilize of DFA and thereby boosts the overall prediction performance. For validating the supremacy of the DFA-DBN model, a comprehensive experimental analysis takes place and the results demonstrate the accurate prediction of stock prices. A predicted DFA-DBN algorithm with a higher accuracy of 94.97 percent is available. On the basis of the data in the tables and figures above, the DFA-DBN approach has been demonstrated to be an effective instrument for anticipating stock price fluctuations.

Do Oil Price Shocks Affect Exchange Rates in Oil-importing Countries: A Case of the Zambian Economy using the SVAR Approach

Oil price shocks have been argued to impact Real Effective Exchange Rates (REERs) in net oil importing countries, mostly through the wealth-transfer effect, which involves the transfer of wealth from net oil-importers to net oil-exporters, and the Terms of Trade Channel. Since this analysis had not been done for the Zambian case by decomposing oil price shocks, a Structural Vector Autoregressive Model (SVAR) was used to measure the contemporaneous impact of oil price shocks on REERs, and was complemented by Impulse Response Functions (IRFs), Granger Causality Tests and Forecast Error Variance Decomposition (FEVD). The long-run impact was analyzed by the Vector Error Correction Model (VECM) after satisfaction of cointegration requirements. The findings revealed that decomposed oil price shocks had no short-run contemporaneous impact on REERs at the 5% level. Similarly, it was found that decomposed oil price shocks and the combined effect of all the variables in the system did not granger-cause Zambia’s REERs, while FEVD results showed that oil price shocks were attributed for a minute proportion of the variation in REERs. These findings were attributed to Zambia’s profile as a predominantly copper and cobalt exporter, historic exchange rate controls, fuel subsidies, and price controls. Johansen’s cointegration test revealed the existence of at least one cointegrated equation in the system, so the subsequent VECM which was constructed revealed that decomposed oil price shocks had no long-run impact on REERs in Zambia, but that the Error Correction Term (ECT) which measures the speed to adjustment back to equilibrium after a short-run disturbance, was significant.