scholarly journals Are Foreign Currency Markets Interdependent? Evidence from Data Mining Technologies

2011 ◽  
Author(s):  
A. G. (Tassos) Malliaris ◽  
Mary Malliaris
Keyword(s):  
Data Mining ◽  
Foreign Currency ◽  
Currency Markets

Dual foreign currency markets and the role of expectations: Evidence from the Pacific Basin countries

2007 ◽  
Vol 21 (2) ◽  
pp. 238-259 ◽  
Author(s):  
Panayiotis F. Diamandis ◽  
Georgios P. Kouretas ◽  
Leonidas Zarangas
Keyword(s):  
Foreign Currency ◽  
Pacific Basin ◽  
Currency Markets ◽  
The Pacific

scholarly journals Predicting Material Weaknesses In Internal Control Systems After The Sarbanes-Oxley Act Using Multiple Criteria Linear Programming And Other Data Mining Approaches

2011 ◽  
Vol 25 (6) ◽  
Author(s):  
Wikil Kwak ◽  
Susan Eldridge ◽  
Yong Shi ◽  
Gang Kou
Keyword(s):  
Data Mining ◽  
Linear Programming ◽  
Internal Control ◽  
Foreign Currency ◽  
Predictive Ability ◽  
Cash Flows ◽  
Multiple Criteria ◽  
Font Size ◽  
Sarbanes Oxley ◽  
Material Weaknesses

<h1 style="TEXT-JUSTIFY: inter-ideograph; TEXT-ALIGN: justify; MARGIN: 0in 0.5in 0pt"><span style="font-family: Times New Roman;"><span style="COLOR: black; FONT-SIZE: 10pt">Our study proposes a multiple criteria linear programming (MCLP) </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">and other data mining </span><span style="COLOR: black; FONT-SIZE: 10pt">method</span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">s</span><span style="COLOR: black; FONT-SIZE: 10pt"> to predict </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">material weaknesses in a firm&rsquo;s internal control system after the Sarbanes-Oxley Act</span><span style="COLOR: black; FONT-SIZE: 10pt"> (SOX) using </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">2003-2004</span><span style="COLOR: black; FONT-SIZE: 10pt"> </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">U.S. </span><span style="COLOR: black; FONT-SIZE: 10pt">data.<span style="mso-spacerun: yes">&nbsp; </span>The results of the MCLP </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">and other data mining </span><span style="COLOR: black; FONT-SIZE: 10pt">approaches in </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">our</span><span style="COLOR: black; FONT-SIZE: 10pt"> </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">prediction </span><span style="COLOR: black; FONT-SIZE: 10pt">study show that the </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">MCLP</span><span style="COLOR: black; FONT-SIZE: 10pt"> method performs</span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO"> </span><span style="COLOR: black; FONT-SIZE: 10pt">better overall than the </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">other data mining approaches </span><span style="COLOR: black; FONT-SIZE: 10pt">using financial </span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO">and other </span><span style="COLOR: black; FONT-SIZE: 10pt">data from the Form 10-K report.</span><span style="COLOR: black; FONT-SIZE: 10pt; mso-fareast-language: KO"><span style="mso-spacerun: yes">&nbsp; </span>Consistent with prior research, firms that disclosed material weaknesses in their SOX Section 302 disclosures were more complex (based on the existence of foreign currency translations), more often used Big 4 auditors, and had lower operating cash flows-to-total assets ratios than the non-material weakness control firms.<span style="mso-spacerun: yes">&nbsp; </span>Because of mixed results on several profitability measures and marginal predictive ability for the MCLP and other methods used, more research is needed to identify firm characteristics that help investors, auditors, and others predict material weaknesses.</span></span></h1>

scholarly journals Traders Perception and Awareness on Financial Derivatives in Indian Stock Market

2020 ◽  
pp. 160-170
Author(s):  
Dr. N. Selvaraj
Keyword(s):  
Foreign Currency ◽  
Currency Markets ◽  
Minimum Risk ◽  
Healthy Development ◽  
Derivative Instruments ◽  
Reduce Risk ◽  
The Government ◽  
Indian Stock Market ◽  
Derivative Products ◽  
Independent Existence

The Government of India has introduced Economic Policy in 1991 to implement structural reforms for reduce the imbalances. In India, Traders want maximum gain with minimum risk, so is the case with derivatives. Derivatives are among the forefront of the innovations in the financial markets and aim to increase returns and reduce risk. A derivative is a financial product which has been derived from another financial product or commodity. The derivatives do not have independent existence without underlying product and market. Derivatives are contracts which are written between two parties for easily marketable assets. Derivatives are gaining importance due to increased volatility in capital and foreign currency markets. RBI finds ways for healthy development of market and takes steps to popularise the use of derivative instruments, but still awareness about the derivative instruments and its uses are quite low. Hence, it is necessary to find out the level of awareness among investing public and if found low, how to create adequate awareness to encourage the use of derivative products as hedge tools. This study can be used by the regulating authorities and broker houses to increase awareness among the traders about derivatives. One should invest in secured and risk-free investments rather than high-risk, highly profitable investments. Tracking the market environment better with sound knowledge about a particular stock would result in better returns. Since many of the entities in this study are independent of each other, there is need to analyse on a buying decision specifically for respective stocks. People with less experience can also be high profit makers when decisions are based on intricate fundamental and technical analyses.

scholarly journals Clustering Clustering Data Eskspor Buah-Buahan Berdasarkan Negera Tujuan Menggunakan Algoritma K-Means

2021 ◽  
Vol 8 (1) ◽  
pp. 73
Author(s):  
Haviz Atma Negara ◽  
Achmad Rizaldi Putra ◽  
Ultach Enri
Keyword(s):  
Data Mining ◽  
United Arab Emirates ◽  
Economic Activity ◽  
Foreign Currency ◽  
Clustering Method ◽  
Maximum Profit ◽  
The Government ◽  
Clustering Data ◽  
Food Commodities ◽  
Level Cluster

Abstrak: Ekspor merupakan kegiatan ekonomi dalam memasarkan dan jual barang, baik industry, pangan, serta kebutuhan lainnya kepada negara lainnya yang memiliki kurs atau nilai mata uang asing yang lebih besar, tujuannya ialah untuk mencari keuntungan yang sebesar-besarnya. Penelitian ini bertujuan untuk menerapkan data mining dengan metode k-means clustering data ekspor buah-buahan menurut negara tujuannya yang merupakan salah satu komoditas pangan. Penelitian ini menggunakan data pada tahun 2012 sampai 2019 yang diambil melalui situs https://www.bps.go.id. Data diolah dengan mengklasterkan data ekspor kedalam 3 kelompok yaitu tinggi, sedang dan rendah. Didapatkan hasil Centroid data untuk cluster tingkat ekspor tinggi sebesar 2054519.3, centroid data untuk cluster tingkat ekspor sedang sebesar 489020.3, centroid data untuk cluster tingkat ekspor rendah sebesar 20.2. Sehingga diperoleh hasil cluster negara tujuan ekspor yaitu 2 negara cluster tingkat ekspor tinggi yakni negara Tiongkok & Malaysia, 2 negara cluster tingkat ekspor rendah yakni Vietnam & Thailand, dan 6 negara cluster tingkat ekspor rendah yakni Hongkong, Singapura, Nigeria, India, Jepang, Uni Emirat Arab. Informasi pengklasteran data ekspor buah-buahan ini dapat menjadi saran serta masukan bagi pemerintah maupun perusahaan-perusahaan swasta maupun negeri dalam menentukan strategi ekspor buah-buahan dimasa depan.   Kata kunci: buah-buahan, data mining, ekspor, k-means, rapid miner.   Abstract Export is an economic activity in marketing and selling goods, both industrial, food, and other needs to other countries that have a higher exchange rate or foreign currency value, the aim is to seek the maximum profit. This study discusses the application of data mining using the k-means clustering method on fruit export data based on destination countries. This study uses export data from one of Indonesia's food commodities, namely fruits based on the main destination countries in 2012 to 2019 which was taken through the https://www.bps.go.id site. The data is processed by clustering the export data into 3 groups, namely high, medium and low. The data centroid for the high export level cluster is 2054519.3, the data centroid for the medium export level cluster is 489020.3, the data centroid for the low export level cluster is 20.2. So that an assessment is obtained based on the fruit export index with 2 cluster countries with high export levels, namely China & Malaysia, 2 cluster countries with low export levels, namely Vietnam & Thailand, and 6 cluster countries with low export levels, namely Hong Kong, Singapore, Nigeria, India, Japan, United Arab Emirates. This information on clustering fruit export data can be a suggestion and input for the government and private and state companies in determining fruit export strategies in the future.   Keywords: fruits, data mining, exports, k-means, rapid miner.

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