Topic
Bidding
About: Bidding is a research topic. Over the lifetime, 15371 publications have been published within this topic receiving 294233 citations. The topic is also known as: competitive bidding.
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TL;DR: In this article, the authors consider an energy management system that controls a cluster of price-responsive demands and manages a wind-power plant and an energy storage facility, and propose a two-stage procedure based on robust optimization.
Abstract: We consider an energy management system that controls a cluster of price-responsive demands. Besides these demands, it also manages a wind-power plant and an energy storage facility. Demands, wind-power plant, and energy storage facility are interconnected within a small size electric energy system equipped with smart grid technology and constitute a virtual power plant that can strategically buy and sell energy in both the day-ahead and the real-time markets. To this end, we propose a two-stage procedure based on robust optimization. In the first stage, the bidding strategy in the day-ahead market is decided. In the second stage, and once the actual scheduling in the day-ahead market is known, we decide the bidding strategy in the real-time market for each hour of the day. We consider that the virtual power plant behaves as a price taker in these markets. Robust optimization is used to deal with uncertainties in wind-power production and market prices, which are represented through confidence bounds. Results of a realistic case study are provided to show the applicability of the proposed approach.
250 citations
TL;DR: This paper examined the effect of mergers on bidding firms' stock prices and found evidence of merger momentum: bidder stock prices are more likely to increase when a merger is announced if recent mergers by other firms have been received well (a "hot" merger market) or if the overall stock market is doing better.
Abstract: This paper examines the effects of mergers on bidding firms' stock prices. We find evidence of merger momentum: bidder stock prices are more likely to increase when a merger is announced if recent mergers by other firms have been received well (a "hot" merger market) or if the overall stock market is doing better. However, there is long run reversal. Long-run bidder stock returns are lower for mergers announced when the either merger or stock markets were hot at the time of the merger than for those announced at other times.
247 citations
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TL;DR: In this article, the authors review recent empirical research documenting offer premiums and bidding strategies in corporate takeovers, ranging from optimal auction bidding to the choice of deal payment form and premium effects of poison pills.
Abstract: I review recent empirical research documenting offer premiums and bidding strategies in corporate takeovers. The discussion ranges from optimal auction bidding to the choice of deal payment form and premium effects of poison pills. The evidence describes the takeover process at a detailed level, from initial premiums to bid jumps, entry of rival bidders, and toehold strategies. Cross-sectional tests illuminate whether bidders properly adjust for winner's curse, whether target stock price runups force offer price markups, and whether auctions of bankrupt firms result in reflect fire-sale discounts. The evidence is suggestive of rational strategic bidding behavior in specific contexts.
246 citations
TL;DR: In this article, the authors proposed an auction model in which very late bids have a positive probability of not being successfully submitted, and showed that late bidding in a fixed deadline auction can occur at equilibrium in auctions both with private values and with uncertain, dependent values.
246 citations
TL;DR: A new method is applied to get optimal management of IPLs in an uncertain environment and provide optimal bidding curves to take part in power market and demonstrate the effects of demand response program (DRP).
Abstract: In a near future, electric vehicles (EVs) will constitute considerable part of transportation systems due to their important aspects such as being environment friendly. To manage high number of EVs, developing hydrogen storage-based intelligent parking lots (IPLs) can help power system operators to overcome caused problems by high penetration of EVs. In this work, a new method is applied to get optimal management of IPLs in an uncertain environment and provide optimal bidding curves to take part in power market. The main purpose of this work is to get optimal bidding curves with considering power price uncertainty and optimal operation of IPLs. To model uncertainty of power price in the power market and develop optimal bidding curve, the opportunity, deterministic and robustness functions of the information gap decision theory (IGDT) technique has been developed. Obtained results has been presented in three strategies namely risk-taker, risk-neutral, and risk-averse corresponding to opportunity, deterministic, and robustness functions of the IGDT technique. In order to demonstrate the effects of demand response program (DRP), each strategy is optimized with and without DRP cases. The mixed-integer non-linear programming model is used to formulate the proposed problem which is solved using the GAMS optimization software under DICOPT solver.
244 citations