A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of...

We analyze the effects of better algorithmic demand forecasting on collusive profits. We show that the comparative statics crucially depend on the whether actions are observable. Thus, the optimal antitrust policy needs to take into account the institutional settings of the industry in question....

Stock market forecasting provides challenging and interesting task to both investors and academic researchers because trading decision at an appropriate time makes more profit for investors. In present study, a new approach has been proposed to integrate Adaptive Neuro-Fuzzy Inference System...

The explosion of algorithmic trading has been one of the most prominent recent trends in the financial industry. Algorithmic trading consists of automated trading strategies that attempt to minimize transaction costs by optimally placing orders. The key ingredient of many of these strategies are...

Even when human point forecasts are less accurate than data-based algorithm predictions, they can still help boost performance by being used as algorithm inputs. Assuming one uses human judgment indirectly in this manner, we propose changing the elicitation question from the traditional direct...

This paper presents a framework capable of accurately forecasting future sales in the retail industry and classifying the product portfolio according to the expected level of forecasting reliability. The proposed framework, that would be of great use for any company operating in the retail...

Borrowing information from populations with similar structural mortality patterns and trajectories has been well recognized as a useful strategy for the mortality forecasting of a target population. This paper presents a flexible framework for the selection of populations from a given candidate...

Accurate forecasting of inter-urban traffic flow has been one of most important issues globally in the research on road traffic congestion. The information of inter-urban traffic with a cyclic data pattern presents a more challenging situation. This investigation presents a short-term traffic...