Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Data Warehouse: From Architecture to Implementation
Data Warehouse: From Architecture to Implementation
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Using information retrieval techniques for supporting data mining
Data & Knowledge Engineering
Mining market data: a network approach
Computers and Operations Research
Mining stock category association and cluster on Taiwan stock market
Expert Systems with Applications: An International Journal
Flexible least squares for temporal data mining and statistical arbitrage
Expert Systems with Applications: An International Journal
The use of data mining and neural networks for forecasting stock market returns
Expert Systems with Applications: An International Journal
Dynamic adaptive ensemble case-based reasoning: application to stock market prediction
Expert Systems with Applications: An International Journal
Hybrid genetic algorithm and association rules for mining workflow best practices
Expert Systems with Applications: An International Journal
| Hi-index | 12.05 |
The foreign exchange market is one of the biggest markets in the global financial capital market. With current trends toward financial capital globalization, it is becoming more important to understand the hedge and arbitrage of foreign exchange markets. Thus, this study implements association rules as a data mining approach to explore the associations among 19 different pairs of foreign exchange rates. Transaction data, such as foreign exchange rates, were collected to construct a database; the Apriori algorithm was then used to generate the association rules. By doing so, this study proposes several possible portfolio alternatives in the Taiwan foreign exchange market, including foreign exchange hedge and arbitrage under different circumstances.