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 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.

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

2021 ◽  
Vol 20 (11) ◽  
pp. 2074-2088
Author(s):  
Vladimir K. BURLACHKOV
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Global Economy ◽  
Foreign Exchange Market ◽  
Global Market ◽  
Leading Role ◽  
The World ◽  
Current Stage ◽  
The U.S

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.

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 Sovereign Credit Rating Announcements and Liquidity Shocks in the Lebanese Daily Foreign Exchange Market

2020 ◽  
Vol 5 (1) ◽  
pp. 66-83
Author(s):  
Samih Antoine Azar
Keyword(s):  
Financial Markets ◽  
Foreign Exchange ◽  
Foreign Exchange Market ◽  
Credit Rating ◽  
Jel Classification ◽  
Exchange Market ◽  
Sovereign Credit ◽  
Long Run ◽  
The Impact ◽  
Sovereign Credit Rating

Sovereign credit rating announcements are usually unexpected events that can affect local financial markets either favorably or detrimentally. In Lebanon, the credit outlook witnessed a deteriorating trend since the mid of the year 2016. The major hypothesis of this paper is that the reaction to the bad credit rating announcements is statistically significant, although ephemeral, delimited to just a few days. It is through the liquidity channel that these announcements create uncertainty and affect the economy. There are two related hypotheses: (1) illiquidity shocks impact undesirably the financial markets, and (2) credit rating announcements are accompanied by a surge in illiquidity. Since the impact of these announcements is ephemeral it should be assessed by high-frequency data, or at most by daily financial data. The domestic foreign exchange market is an ideal place to study this impact. Fortunately, the central bank of Lebanon has lately made available daily foreign exchange rates for six major currencies beginning in 2010. This defines six multiple regressions that are constructed to differentiate between the short-run and the long-run responses to illiquidity. The empirical results show that the above two hypotheses are strongly supported. Moreover, it matters little whether the event window is 3, 4 or 5 days. JEL Classification: G14, F31, C58, C38.

A Study On Technical Analysis With Reference To International Forex

Think India ◽  
2019 ◽  
Vol 22 (3) ◽  
pp. 1129-1144
Author(s):  
Bichith C. Sekhar ◽  
A. Umamaheswari
Keyword(s):  
Foreign Exchange ◽  
Abnormal Return ◽  
Foreign Exchange Market ◽  
Relative Strength ◽  
Exchange Market ◽  
Strength Index ◽  
Technical Tool ◽  
Alpha Beta ◽  
Decentralized Market ◽  
Currency Conversion

The foreign exchange market (Forex, FX, or currency market) is a global decentralized market for the trading of currencies. The foreign exchange market assists international trade and investments by enabling currency conversion. Our study is to test the technical tools to analyze about the technical impact and its return in the market.  For this purpose 13 cross currency pairs were taken as sample size and Jensen’s Alpha, Beta, Relative Strength Index, and Buy and Hold Abnormal Return were used as technical tool for analysis and the conclusion is that it’s not preferred to invest in JPY pairs as the volatility and the return are not up to the mark and its preferred to invest in EURCAD as the return was high when compared to other scripts and the market was moving accordingly to its cross currency pair.

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