Designing and Evaluating a Recommender System within the Book Domain

Today the World Wide Web provides users with a vast array of information, and commercial activity on the Web has increased to the point where hundreds of new companies are adding web pages daily. This has led to the problem of information overload. Recommender systems have been developed to overcome this problem by providing recommendations that help individual users identify content of interest by using the opinions of a community of users

A novel approach for studying the high-frequency FOREX market

The Foreign Exchange (FOREX) market is the largest and most complex financial market in the world. With the advent of behavioural and micro-structural studies, many properties of the market have been revealed. However, previous studies contain only aggregate transaction data that do not distinguish between the activities of the different participants, formulating the market collective behavior.

Definitions of directional-change events

In the challenge of observing precious periodic patterns in the financial time series based on physical time changes, we propose intrinsic time as an alternative to physical time, where events of different magnitudes are the time-scale of the time series. This alternative approach, called directional-change events, defines the time series by the irregularity of time intervals between two sequential events. We believe directional-change events can enhance our study of the financial time series and improve the quality of time series analysis.

High frequency FOREX market transaction data handling

The foreign exchange market generates millions of daily tick data, often referred to as high frequency data (HFD), as a result of market participants decisions. By analyzing these data, one could reveal many of the market properties. However, HFD may possibly contain observations that are not reliable in terms of actual market activity. We manipulate a real dataset storing the full transaction history of more than 40,000 traders on an account level for 2.25 years.

Minimal agent-based model for the origin of trading activity in foreign exchange market

In this paper, we show that a minimal agent-based model for the Foreign Exchange (FX) market is capable of reproducing, to a certain extent, FX market trading activity. The model is minimal in that it has the advantage of having the minimum set of elements necessary for modelling the FX market in order to reproduce the FX market trading activity.

Modelling the trading behaviour in high-frequency markets

We use an agent-based approach to model trading behaviour in high-frequency markets. This study focuses on the Foreign Exchange (FX) market. The initial part of this study is to observe the micro-behaviour of traders to define the stylized facts of their trading activities. This is performed using a high-frequency dataset of anonymised individual traders' historical transactions on an account level, provided by OANDA Ltd.

Stylized facts of trading activity in the high frequency FX market: An Empirical Study

In this paper, we focus on studying the statistical properties (stylized facts) of the transactions data in the Foreign Exchange (FX) market which is the most liquid financial market in the world. We use a unique high-frequency dataset of anonymised individual traders' historical transactions on an account level provided by OANDA. To the best of our knowledge, this dataset can be considered to be the biggest available high-frequency dataset of the FX market individual traders' historical transactions.

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اشترك ب KSU Faculty آر.إس.إس