scholarly journals assessment of Key factors of the foreign Exchange Rate formation in armenia

2018 ◽  
Vol 22 (5) ◽  
pp. 27-39
Author(s):  
E.  M. Sandoyan ◽  
M.  A.  Voskanyan ◽  
A.  G.  Galstyan
Keyword(s):  
Exchange Rate ◽  
Foreign Exchange ◽  
Transition Economy ◽  
Foreign Currency ◽  
Econometric Analysis ◽  
Exchange Rate Policy ◽  
Foreign Exchange Rate ◽  
Key Factors ◽  
Endogenous Factors ◽  
Regulation Policy

Usually, it is diffcult for developing countries to choose a currency regulation policy because of institutional inadequacy, including a signifcant level of concentration in commodity markets, and a high degree of dependence of the national market and fnancial system on exogenous factors and a huge external debt. This article is dedicated to the analysis and evaluation of key factors affecting the formation of the Armenian national currency (dram) exchange rate, as well as to the choice of the currency regulation policy in Armenia. The authors carried out a statistical and econometric analysis of the factors of the foreign exchange rate formation, taking into account the specifcs of the transition economy as a whole, as well as the features of the Armenian economy, in particular. The authors have identifed the exogenous and endogenous factors of the foreign exchange rate formation of the dram, depending on the inflow and outflow of foreign currency. Further, the authors specifed the influence of dominant factors on the choice of the currency regulation policy in the country. The authors carried out an econometric analysis of the factors identifed at the frst stage of the study using the VAR model. The results obtained from this model proved the hypothesis of the non-market nature of the dram’s exchange rate formation. The authors concluded that the dram’s exchange rate formation has non-market nature because of signifcant intervention on the currency market by the “monetary authorities”. The key conclusion of this study is the thesis about the need to change the approaches to currency regulation in Armenia in favour of the transition to a free-floating exchange rate policy in order to stimulate sustainable rates of economic growth in the long term.

Foreign Currency Derivatives and Foreign Exchange Rate Exposure Management of KOSDAQ Firms

2013 ◽  
Vol 21 (2) ◽  
pp. 223-254
Author(s):  
Taek Ho Kwon
Keyword(s):  
Exchange Rate ◽  
Foreign Exchange ◽  
Foreign Currency ◽  
Foreign Exchange Rate ◽  
Sufficient Evidence ◽  
Similar Data ◽  
Test Results ◽  
Crisis Period ◽  
Exchange Rate Exposure ◽  
Currency Derivatives

This study examines the foreign currency derivatives trading of KOSDAQ firms and analyses the relations of derivatives trading and foreign exchange rate exposure in the period 2005~2010. The amount of derivatives trading reaches 27.7% of total assets for the trading firms before global financial crisis period (2005~2007). While, the amount decreases to 17.6% of total assets during the crisis period (2008~2010). These amounts are much greater than those of KOSPI firms which are calculated using similar data specification and periods. The variables which are usually adopted as determinants of derivatives trading do not explain the usage of derivatives in the analysis of period 2005~2007. These results suggest that KOSDAQ firms use derivatives not only foreign exchange risk managements but also trading purposes during this period. Test results do not show sufficient evidence that KOSDAQ firms use derivatives trading in an effective manner to manage foreign exchange rate exposure. In sum, test results suggest that to achieve the goal of managing foreign exchange rate exposure firms should estimate their open position in foreign currency properly before conducting foreign currency derivatives trading.

scholarly journals An Intelligent Event-Sentiment-Based Daily Foreign Exchange Rate Forecasting System

2019 ◽  
Vol 9 (15) ◽  
pp. 2980 ◽  
Author(s):  
Muhammad Yasir ◽  
Mehr Yahya Durrani ◽  
Sitara Afzal ◽  
Muazzam Maqsood ◽  
Farhan Aadil ◽  
...  
Keyword(s):  
Deep Learning ◽  
Exchange Rate ◽  
Foreign Exchange ◽  
Foreign Currency ◽  
Foreign Exchange Rate ◽  
Exchange Rate Forecasting ◽  
Currency Exchange ◽  
Currency Exchange Rate ◽  
Us Dollar ◽  
The Exchange Rate

Financial time series analysis is an important research area that can predict various economic indicators such as the foreign currency exchange rate. In this paper, a deep-learning-based model is proposed to forecast the foreign exchange rate. Since the currency market is volatile and susceptible to ongoing social and political events, the proposed model incorporates event sentiments to accurately predict the exchange rate. Moreover, as the currency market is heavily dependent upon highly volatile factors such as gold and crude oil prices, we considered these sensitive factors for exchange rate forecasting. The validity of the model is tested over three currency exchange rates, which are Pak Rupee to US dollar (PKR/USD), British pound sterling to US dollar (GBP/USD), and Hong Kong Dollar to US dollar (HKD/USD). The study also shows the importance of incorporating investor sentiment of local and foreign macro-level events for accurate forecasting of the exchange rate. We processed approximately 5.9 million tweets to extract major events’ sentiment. The results show that this deep-learning-based model is a better predictor of foreign currency exchange rate in comparison with statistical techniques normally employed for prediction. The results present evidence that the exchange rate of all the three countries is more exposed to events happening in the US.

scholarly journals Forecasting INR Exchange Rate Against USD, GBP, JPY, SGD, EUR, AED Using Machine Learning

2021 ◽  
pp. 684-689
Author(s):  
Sumith Pevekar
Keyword(s):  
Machine Learning ◽  
Exchange Rate ◽  
Random Forest ◽  
Foreign Exchange ◽  
Foreign Currency ◽  
Foreign Exchange Rate ◽  
Random Forest Algorithm ◽  
Currency Exchange ◽  
Predicting Performance ◽  
Machine Learning Model

The price of a native currency expressed in terms of another currency is known as a foreign exchange rate. In other terms, a foreign exchange rate compares the value of one currency to that of another. The value of standardized currencies varies with demand, supply, and consumer confidence around the world due to which their values fluctuate over time. To forecast the exchange rate of INR, I have developed a machine learning model. The model was trained to estimate six foreign currency exchange rates against the Indian Rupee using historical data. This model uses Random Forest algorithm to train and predict the values. The suggested system’s predicting performance is assessed and contrasted using statistical metrics. According to the findings, the Random Forest algorithm-based model predicts well and achieves an accuracy of 93.61%. KEYWORDS: Regression, Random Forest, Exchange Rate, INR

scholarly journals FDI Inflow, Stock Market Performance and Exchange Rate: Indian Scenario

2017 ◽  
Vol 7 (2) ◽  
pp. 148
Author(s):  
Kunal Kunal ◽  
B V Phani
Keyword(s):  
Exchange Rate ◽  
Stock Market ◽  
Foreign Exchange ◽  
Foreign Currency ◽  
Market Performance ◽  
Foreign Exchange Rate ◽  
Policy Implications ◽  
Sensitivity Index ◽  
Indian Economy ◽  
Stock Market Performance

In this research work, macro level analysis has been conducted to assess impact of foreign direct investment (FDI) capital inflow in Indian economy. This study is focused on causality relationship between FDI inflow, stock market performance and foreign exchange rate. This framework is used for policy implications of relationship between three variables. These macro-economic variables are linked with different policies. Causality tests performed on these variables are further used for policy implications. Impact of change in exchange rate on changes in FDI inflow is the least significant followed by impact of changes in FDI inflow on changes in sensitivity index of stock exchange (SENSEX). The third least significant relationship is observed between changes in FDI inflow on change in exchange rate. These relationships are implied to ‘Impossible Trinity’ framework to assess preference for monetary, fiscal and foreign exchange rate policies. It is observed that improving performance of stock market (SENSEX) should be on priority followed by exchange rate. These finding have implications on fiscal policy, monetary policy and exchange rate. The increase in return of stock market and favourable exchange rate will help in increasing FDI inflow in Indian economy. Stock market performance depends on daily transactions by investors and they are regulated only, not controlled. Supply of foreign currency in India is controlled by the Reserve Bank of India (RBI), who assesses the supply conditions of the market and attempts to manage exchange rate in favour of Indian economy. In other words, the exchange rate can be controlled by having control on supply of foreign currency in domestic market. Hence, there is possibility of having fixed exchange rate and target band of exchange rate.

scholarly journals Efficiency of the Black Foreign Exchange Market

2019 ◽  
Vol 11 (2) ◽  
pp. 165
Author(s):  
Ali Farhan Chaudhry ◽  
Mian Muhammd Hanif ◽  
Sameera Hassan ◽  
Muhammad Irfan Chani
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Weak Form ◽  
Exchange Rate Policy ◽  
Foreign Exchange Rate ◽  
Ratio Test ◽  
Exchange Market ◽  
Policy Makers

This empirical study is first of its nature to examine the weak-form of efficiency for unofficial foreign exchange market of Pakistan proxied by Japanese Yen (JPY/PKR), Swiss Franc (CHF/PKR), British Pound (GBP/PKR), and US Dollar (USD/PKR) exchange rates. For this we have employed Ljung Box Q-test, unit root tests including Dickey-Fuller (Dickey 1979), Augmented Dickey-Fuller (Dickey 1981) tests and Phillips and Perron (1988) test, Durbin Watson test, Runs-test, and Variance ratio test by using unofficial foreign exchange rate time series of Yen/PKR, CHF/PKR, GBP/PKR and USD/PKR from 1994M07 to 2001M06. Empirical results lead to the conclusion that the unofficial foreign exchange market of Pakistan is weak-form efficiency. The implications of this empirical research are of great importance for designing foreign exchange policy i.e. policy makers (be it accounting, export/import or public policy makers) are to consider fluctuations in unofficial foreign exchange rates while designing official foreign exchange rate policy of developing country like Pakistan. Further, policymakers can enhance the efficiency of official foreign exchange market by intervention subject to a widening of unofficial foreign exchange premium beyond a certain limit in developing countries like Pakistan.

scholarly journals The microstructure of foreign exchange rate and foreign exchange rate formation

2005 ◽  
Vol 50 (164) ◽  
pp. 63-79
Author(s):  
Vladimir Vuckovic
Keyword(s):  
Exchange Rate ◽  
Foreign Exchange ◽  
Market Microstructure ◽  
Foreign Exchange Market ◽  
Foreign Currency ◽  
Stock Exchange ◽  
Foreign Exchange Rate ◽  
Exchange Market ◽  
Market Participants ◽  
Essential Question

The subject matter of market microstructure analysis are processes through which investor activities are transferred to quantities and prices. This direction indicates the fact that has been unjustifiably neglected in fundamental theories ? foreign exchange rate results from the interactions between market participants. Spot foreign exchange market can best be described as a decentralised market with a number of dealers. There is no organised physical place (stock exchange) where dealers meet their clients nor is there an electronic system which enables quotations of all dealers in a currency market to be simultaneously shown on the screen. The theory of order flows has resulted from the answer to the essential question of market microstructure: do trading mechanisms affect the price formation process of the trading subject, and how do they affect it. Information is scattered and not available to all subjects in an aggregate form, which is the consequence of a decentralised structure, lack of regulations and nontransparent trading on the foreign exchange market. In such a setting, market participants are incessantly aggregating signals based on scattered information, and no sooner than collective orders for foreign currency sales and purchases are formed do they build into the foreign exchange rate in the process of new information trading. are a good explanation for changes in the foreign exchange rate. Several studies have shown that order flows.

Sign in / Sign up

Export Citation Format

Share Document