Actionable trading strategies for trading agents determine the potential of the simulated models in real-life markets. The development of actionable strategies is a non-trivial task, which needs to consider real-life constraints and organizational factors in the market. In this paper, we first analyze such constraints on developing actionable trading strategies. Further we propose an actionable...

T recent financial crisis highlights the importance of market crashes and the subsequent market illiquidity for optimal portfolio selection. We propose a tractable and flexible portfolio choice model where market crashes can trigger switching into another regime with a different investment opportunity set. We characterize the optimal trading strategy in terms of coupled integro-differential equ...

We design and deploy a trading strategy that mirrors the Exchange Traded Fund (ETF) arbitrage technique for sector trading. Artificial Neural Networks (ANNs) are used to capture pricing relationships within a sector using intra-day trade data. The fair price of a target security is learnt by the ANN. Significant deviations of the true price from the computed price (ANN predicted price) are expl...

The presumed source of the volatility is a trading strategy called “programmed trading.”2 This strategy, which essentially involves trading on small and shortlived price differences for the same group of stocks in the spot, futures and options markets, is not new. The introduction of stock jnde~futures around 1982 and the application of computer techniques to monitor price differences and trigg...

In this paper, we propose an agent-based spectrum trading mechanism, where secondary users (SUs) can access the spectrum through the Secondary Network Operator (SNO). Buying spectrum from primary users(PUs) and reselling them to secondary users(SU), SNO plays an agent-like role in the spectrum trading process. The most significant challenge for SNO is how to make most profitable strategy. We ad...