We use the recently proposed duality approach to study the performance of static, myopic and generalized buy-and-hold (GBH) trading strategies. Our interest in static and GBH strategies is motivated by the fact that these strategies are intuitive and straightforward to implement in practice. The myopic strategy, while more difficult to implement, is often close to optimal and so we use it to ob...

While there are several existing agent-based systems addressing the crucial and difficult issues of automated negotiation and auction, this research has designed and engineered a society of trading agents with two distinguishing features: 1) a market-driven negotiation strategy and 2) a deal optimizing auction protocol. Unlike some of the existing systems where users manually select predefined ...

We reconsider the replication problem for contingent claims in a complete market under a general framework. Since there are various limitations in the Black–Scholes pricing formula, we propose a new method to obtain an explicit self–financing trading strategy expression for replications of claims in a general model. The main advantage of our method is that we propose using an orthogonal expansi...

In this paper, we first find out some good trading strategies from the historical series and apply them in the future. The profitable strategies are trained out by the gene expression programming (GEP), which involves some well-known stock technical indicators as features. Our data set collects the 100 stocks with the top capital from the listed companies in the Taiwan stock market. Accordingly...

Typical Double Auction (DA) models assume that trading agents are one-way traders. With this limitation, they cannot directly reflect the fact individual traders in financial markets (the most popular application of double auction) choose their trading directions dynamically. To address this issue, we introduce the Bi-directional Double Auction (BDA) market which is populated by two-way traders...

This paper evaluates the use of an artificial neural network within a stockmarket trading strategy. The neural network was previously developed by the same authors, and has been trained using fundamental, company specific data. This study sites the neural network within a trading context, and demonstrates it is capable of producing economically significant results after accounting for costs.

The weekend effect is described as the tendency for Monday security returns to be low (or negative) compared to other days of the week. The weekend effect may not be exploited by trading individual stocks because of transactions costs. However, the institutional characteristics of the US-based international open-end mutual funds may allow investors to exploit the weekend effect because mutual f...

In this work we are proposing a trading system where fuzzy logic is applied not only for defining the trading rules, but also for managing the capital to invest. In fact, two fuzzy decision support systems are developed. The first one uses fuzzy logic to design the trading rules and to apply the stock market technical indicators. The second one enhances this fuzzy trading system adding a fuzzy ...

We consider the problem of optimal position liquidation with the aim of maximizing the expected cash flow stream from the transaction in the presence of a temporary or permanent market impact. We use a stochastic programming approach to derive trading strategies that differentiate decisions with respect to different realizations of market conditions. The scenario set consists of a collection of...