scholarly journals Spatial-Temporal Analysis the Dynamics of Changes on the Foreign Exchange Market: an Empirical Estimates from Ukraine

2020 ◽  
Vol 1 (2) ◽  
pp. 1-6
Author(s):  
Oleg Vasiurenko ◽  
Vyacheslav Lyashenko ◽  
Valeria Baranova ◽  
Zhanna Deineko
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Emerging Economies ◽  
Foreign Exchange Market ◽  
Temporal Analysis ◽  
Wavelet Coherence ◽  
Exchange Market ◽  
Empirical Estimates ◽  
Market Trends ◽  
Spatial Temporal Analysis

The foreign exchange market plays an important role in the formation and development of financial markets. This market is of particular importance for emerging economies. To understand market trends (to understand and develop a strategy for its development), it is necessary to analyze historical data. It is also important to use different methods to carry out this analysis. Based on this, the paper analyzes the foreign exchange market in Ukraine for the period 2014-2018. For this analysis, the wavelet coherence methodology is used. This made it possible to assess the development of the foreign exchange market in Ukraine.

Global markets as global conversations

2007 ◽  
Vol 27 (5-6) ◽  
Author(s):  
Karin Knorr Cetina
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Global Market ◽  
Global Markets ◽  
Economic Aspects ◽  
Exchange Market ◽  
Conversational Interaction ◽  
Interaction System ◽  
Streaming Flow

AbstractFinancial markets are one of the most iconic and influential structures of our time. The foreign exchange market in particular is also the most genuinely global market—and the largest market worldwide, with an average daily turnover of 1.8 trillion US dollars. The foreign exchange market is also structurally like a massive conversational interaction system; many of its transactions are conducted through electronically mediated ‘conversations’. Transactions not conducted through conversations but through an electronic broker also display a sequential turn-taking structure. In this paper, I analyze the streaming ‘flow’ architecture of this market in terms of its sequential structures and their technological and economic aspects. I also specify and analyze several types of texted sequences that articulate and illustrate the response-based interaction system of this market. I argue that informational sequences are particularly important; the informational liquidity of this market sustains and supports the market's economic liquidity.

‘Indian Stock Market Volatility’: A Study of Inter-linkages and Spillover Effects

2019 ◽  
Vol 18 (2_suppl) ◽  
pp. S183-S212 ◽  
Author(s):  
Suparna Nandy (Pal) ◽  
Arup Kr. Chattopadhyay
Keyword(s):  
Stock Market ◽  
Financial Markets ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Volatility Spillover ◽  
Exchange Market ◽  
Causality Test ◽  
Asymmetric Volatility ◽  
Indian Stock Market ◽  
Domestic Stock

The article attempts to examine interdependence between Indian stock market and other domestic financial markets, namely, foreign exchange market, bullion market, money market, and also Foreign Institutional Investor (FII) trade and foreign stock markets comprising one regional stock market represented by Nikkei of Japan and other stock market for the rest of the world represented by Standard & Poor’s (S&P) 500 of the USA. Attempts are also made to examine asymmetric volatility spillover, first, between the Indian stock market and other domestic financial markets and second, between the Indian stock market and global stock markets (represented by Nikkei and S&P 500) along with the foreign exchange market. To measure linear interdependence among multiple time series of financial markets multivariate Vector Autoregression (VAR) analysis, Granger causality test, impulse response function and variance decomposition techniques are used. For estima-ting the volatility spillover among the aforesaid markets Dynamic Conditional Correlation-Multivriate-Threshold Autoregressive Condi-tional Heteroscedastic (DCC-MV-TARCH) (1, 1) model is applied on daily data for a quite long period of time from 01 April 1996 to 31 March 2012. The results of multi­variate VAR analysis, Granger causality test, variance decomposition analysis and impulse response function estimation establish significant interdependence between domestic stock market and different other financial markets in India and abroad. The results of DCC-MV-TARCH (1, 1) model estimation further show signi- ficant asymmetric volatility spillover between the domestic stock market and the foreign exchange market and also from the domestic stock market to bullion market and changes in gross volume of FII trade. We also find (a) both way asymmetric volatility spillover between the domestic stock market and the Asian stock market and (b) its unidirectional movement from the world stock market to the domestic stock market. The results of the study may help market regulators in setting regulatory policies considering the inter-linkages and pattern of volatility spillovers across different financial markets. JEL Classification: G15, G17

scholarly journals COMPUTATION INTELLIGENCE BASED DAILY ALGORITHMIC STRATEGIES FOR TRADING IN THE FOREIGN EXCHANGE MARKET

2018 ◽  
Author(s):  
Nijolė Maknickienė ◽  
Ieva Kekytė ◽  
Algirdas Maknickas
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Processing Unit ◽  
Exchange Market ◽  
Data Prediction ◽  
Open Source Framework ◽  
Market State ◽  
Port Systems ◽  
Graphical Processing

Successful trading in financial markets is not possible without a support system that manages the preparation of the data, prediction system, and risk management and evaluates the trading efficien-cy. Selected orthogonal data was used to predict exchange rates by applying recurrent neural network (RNN) software based on the open source framework Keras and the graphical processing unit (GPU) NVIDIA GTX1070 to accelerate RNN learning. The newly developed software on the GPU predicted ten high-low distributions in approximately 90 minutes. This paper compares different daily algorith-mic trading strategies based on four methods of portfolio creation: split equally, optimisation, orthogonality, and maximal expectations. Each investigated portfolio has opportunities and limita-tions dependent on market state and behaviour of investors, and the efficiencies of the trading sup-port systems for investors in foreign exchange market were tested in a demo FOREX market in real time and compared with similar results obtained for risk-free rates.

scholarly journals Applications of Financial Technology in Foreign Exchange Market

2021 ◽  
Vol 233 ◽  
pp. 01160
Author(s):  
Wei Li
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Service Industry ◽  
Advanced Technology ◽  
Exchange Market ◽  
Financial Industry ◽  
Block Chain ◽  
Exchange Management ◽  
Financial Technology

Financial technology (Fintech), including a series of advanced technologies such as big data, artificial intelligence and block-chain, has been gradually applied to various industries after years of development and will become the major driver of the future financial industry. As one of the largest financial markets in the world, the traditional foreign exchange service industry is gradually entering the era of fintech, bringing new vitality to the foreign exchange market through advanced technology and improving the efficiency of foreign exchange management. However, while enjoying the opportunities brought by fintech to the foreign exchange field, practitioners in both fintech and the foreign exchange industry should also actively face the challenges and try to build a safe and efficient foreign exchange market environment.

scholarly journals The Efficiency of Foreign Exchange Markets in Pakistan: An Empirical Analysis

2014 ◽  
Vol 19 (1) ◽  
pp. 133-149 ◽  
Author(s):  
Rizwana Bashir ◽  
Rabia Shakir ◽  
Badar Ashfaq ◽  
Atif Hassan
Keyword(s):  
Exchange Rate ◽  
Foreign Exchange ◽  
Emerging Economies ◽  
Foreign Exchange Market ◽  
Empirical Relationship ◽  
Exchange Market ◽  
Monthly Data ◽  
Market Inefficiency ◽  
Policy Work ◽  
Exchange Markets

This study investigates the empirical relationship between spot and forward exchange rate efficiency with reference to Pakistan and the efficiency of its foreign exchange market. We use monthly data from the State Bank of Pakistan and KIBOR rates for the period July 2006 to December 2013. Our results indicate that the forward exchange rate does not fully reflect all the information available. Market players may gain the benefits of volatility speculation due to market inefficiency. Pakistan’s foreign exchange market is still small compared to those of other emerging economies, implying that substantial policy work is required.

Product, Money, and Foreign Exchange Market Disequilibria and Inflation in Uzbekistan During the Period 1994-2000

2003 ◽  
Vol 53 (4) ◽  
pp. 363-384
Author(s):  
T. Ranaweera
Keyword(s):  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Exchange Market ◽  
Inflation Dynamics ◽  
Quarterly Data ◽  
Empirical Estimates ◽  
Market Rate ◽  
Long Run ◽  
Short Run ◽  
Import Restrictions

In this study a macroeconomic framework is developed and applied ascertaining the influence of domestic disequilibria and external shocks on inflation dynamics in Uzbekistan. Using quarterly data for the period 1994:Q1 to 2000:Q3, several long-run relationships are estimated for goods, money, and foreign exchange markets of Uzbekistan, which are characterised by multiple exchange rates, import restrictions, and other domestic administrative controls. The empirical estimates, which use error-correction mechanisms for different markets, show that domestic monetary and output developments, and changes in the official exchange rate vis-à-vis the parallel market rate have had a significant influence on the short-run behaviour of the foreign exchange market in Uzbekistan. Furthermore, disequilibria in the product and money markets are the major forces driving short-run inflation dynamics. It should be noted that the study has been constrained by both the quantity and the quality of quarterly data available on the Uzbek economy.

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