Search results

This study aims to investigate – theoretically and empirically – if call auctions incorporate asymmetric information into prices.

First, this study introduces a new model of price formation in a call auction with insider information. In this call auction model, insider trading gives rise to an asymmetric information component of transaction costs. Next, this study estimates the model using 20 stocks from Euronext Paris and investigates if the asymmetric information component is present.

The theoretical analysis reveals that call auctions incorporate asymmetric information into prices. The empirical analysis finds strong evidence for the asymmetric information component. Testable implications provide further support for the model.

Call auctions have recently been proposed as an alternative to continuous limit order book markets to overcome problems associated with high-frequency trading. However, it is still an open question whether call auctions efficiently aggregate asymmetric information. The findings of this study imply that call auctions facilitate price discovery and, therefore, are a viable alternative to continuous limit order book markets.

There is no generally accepted measure of trading costs for call auctions. Therefore, the measure introduced in this study is of great value to anyone who wants to quantify trading costs in call auctions, understand the determinants of trading costs in call auctions or compare trading costs and their components between continuous markets and call auctions. This study also contributes to the literature devoted to estimating the probability of information-based trading.

The purpose of this paper is to empirically examine the impact of closing mechanism changes on market quality, investor trading behavior and market manipulation in the Shanghai stock market.

A dummy variable is constructed indicating whether the closing mechanism is call auction or continuous auction. Market quality is measured from aspects of liquidity, volatility and price continuity; investor trading behavior is scaled by order timing and order aggressiveness, and a price deviation indicator is the proxy of manipulation. Using panel regression, this study examines the impact of closing mechanism changes based on intraday transaction data from the Shanghai stock market.

The conclusions are as follows: First, market quality improves after the closing mechanism is reformed in terms of liquidity, volatility and price continuity. Second, order strategy changes significantly in the closing call market, and investors trade more aggressively in the continuous trading period before closing. Third, the closing call mechanism restrains the closing price manipulation and thus prompts an efficient closing price.

This paper examines the policy effects of closing mechanism changes from aspects of market quality, trading behavior and price manipulation, providing pieces of evidence for trading mechanism design and market supervision in emerging markets.

The purpose of this paper is to study price discovery and price convergence in securities trading within a fragmented market environment where stocks are traded on multiple venues. The results provide novel empirical insights questioning the generalizability of the current literature and aim to expand the understanding of price determination in a fragmented market microstructure.

This paper provides an empirical data analysis based on an event study methodology. The authors applied Thomson Reuters Tick History data covering German blue chip stocks listed on multiple venues in 2009 and 2013. Different time aggregations up to one second are applied to provide an in-depth analysis.

The paper empirically discovers a persistent price leader-follower relationship not only during intraday auctions but also in subsequent continuous trading. The authors found that trading on alternative venues instantly dries out in case the dominant market switches to a call auction. In these situations, alternative markets await and adopt the official price signal of the dominant market although prices on alternative venues still indicate a certain extent of price discovery. This phenomenon remains persistent at different levels of market fragmentation, indicating that alternative trading venues fully accept the price leadership role of the dominant market, no matter their own market share.

This paper provides an innovative empirical setup to analyze price co-movement and convergence based on high-frequent data. Further, the results provide novel and robust insights into the price determination process in fragmented markets that clarify the role of price follower and price leader.

The main aim of this paper is to review some of the newest and most promising advances in auction theory with an eye to applications to procurement practice. Here we focus in particular on four topics related to multidimensional auctions: 1) how to define a proper scoring rule when the awarding bodies lack the necessary information regarding its own preferences and suppliers’ technology; 2) how to cope with the information disclosure policy regarding the discretional evaluation of some aspects of each contractual proposal; 3) how to use contractors’ reputations based on their past performance in the awarding process; 4) how to control the risk of collusion and corruption in the awarding phase.

The purpose of this paper is to quantitatively assess wood pallet suppliers' reaction to online reverse auctions and its impact on their business policies and practices.

Survey method was used to determine how pallet suppliers react to online reverse auctions.

Determines that pallet suppliers do not realize the benefits claimed by online reverse auction service providers. Identifies new sources of costs which accrue to buyers and are not accounted for in so‐called “total cost” request for quotes including: retaliatory pricing practices, less cooperative relationships, and sourcing work back to the original supplier. The qualitative benefits identified for suppliers by third‐party online reverse auction service providers are overstated or false.

The present work can be extended to other commodity categories to identify similarities and differences in how suppliers react to online reverse auctions, understand the domain of successful and unsuccessful application of the online reverse auction tool, and provide further insight into the evolution of buyer‐seller relationships, including embedded organizational routines such as power‐based bargaining.

Findings mirror the results found in a previous study that examined aerospace parts suppliers' reaction to online reverse auctions, and indicates that market makers have consistently overstated the benefits of online reverse auctions to both sellers and buyers, and the use of this tool will typically result in unfavorable outcomes for both buyers and sellers.

This paper will be of interest to buyers, sellers, and market makers, as it identifies important problems with online reverse auctions, and suggests questions that buyers should ask market makers to ensure better sourcing decisions.

This study aims to explore how a microlending digital platform connects social investors in developed countries and micro-entrepreneurs in Africa. However, additional research is necessary to discuss how online auction models are designed and implemented and how existing theories can explain their use in the so-called developing countries.

The research is based on a single case study: an online auction model for microlending named AfricaMC. Two main methods collected empirical data, namely, online participant observation, i.e. real-time participation in the online auction market and in the forum of discussions, where the authors observed the processes of microlending transactions as registered members; analysis of online documents, by reviewing forum discussions, analyzing reports, blogs, chats and other materials.

The results suggest that using sociological and information systems theoretical lenses in a complementary manner could provide greater value than using economics.

The study makes two main contributions. First, it mobilizes a pluralist theoretical approach based on economic, sociological and information systems perspectives to improve the understanding of microlending digital platforms using online auction models. Second, it uses the understanding produced from data analysis of one particular African case to validate propositions derived from these three theoretical approaches that might be applied to other cases.

As the demand for online auctions increases, the process of monitoring multiple auction houses, deciding which auction to participate in and making the right bids, become challenging tasks for consumers. Hence, knowing the closing price of a given auction would be an advantage, since this information will ensure a win in a given auction. However, predicting a closing price for an auction is not easy, since it is dependent on many factors. The purpose of this paper is to report on a predictor agent that utilises grey system theory to predict the closing price for a given auction.

The focus of the research is on grey system agent. This paper reports on the development of a predictor agent that attempts to predict the online auction closing price in order to maximise the bidder's profit. The performance of this predictor agent is compared with two well‐known techniques, the Simple Exponential Function and the Time Series, in a simulated auction environment and in the eBay auction.

The grey theory agent gives a better result when less input data are made, while the Time Series Agent can be used with the availability of a lot of information. Although the Simple Exponential Function Agent is able to predict well with less input data, it is not an appropriate method to be applied in the prediction model since its formula is not realistic and applicable in predicting the online auction closing price. The experimental results also showed that using moving historical data produces a higher accuracy rate than using fixed historical data for all three agents.

Grey system theory prediction model, GM(1, 1) has not been applied in online auction prediction. In this paper the authors have applied grey theory into an agent to predict the closing price of an online auction, in order to increase the profit of bidders in the bidding stage. The experimental results show that the accuracy of the grey prediction model is more then 90 per cent, with less then eight historical data inputs.

While significant efforts have been made to study auction and logistics theories in the context of perishable supply chain trading (PSCT) over the last few years, the consensus has not yet been reached on how best to examine the impact of physical-internet-enabled auction logistics (AL) decisions and processes on dynamic perishable products transactions. The purpose of this paper is to address this gap by investigating the existing situations and identifying future opportunities for both academic and industrial communities.

The relevant literature was sort out along with three dimensions, namely auction mechanism, level of decision and coordination. The methods of field investigation and focus group discussion were also used to explore the factors influencing AL performance.

A number of key findings presented. First, there is an emerging paradigm shift from offline auction to online auction. Robust and resilient AL are needed to fulfill the massive number of orders from different channels while considering dynamic decisions. Second, three-level decisions in AL have been explicitly classified and defined. Various mathematical techniques used in literature vis-à-vis the contexts of AL were mapped. Third, a coordination mechanism that dynamically balances trade-off between logistics efficiency and transaction price was discussed. Lastly, several opportunities for future research were distinguished with coherent connection of research domains and open questions.

This paper not only summaries key themes of current research dimensions, but also indicates existing deficiencies and potential research directions. The findings can be used as the basis for future research in PSCT and related topics.

The purpose of this paper is twofold. The first is to estimate the correlation between market activity and volatility on an exchange that does not use continuous auctions to find prices. The second is to estimate the sensitivity of that relationship to differences in opinions across traders regarding asset value.

Both objectives are accomplished by using seven years of trader‐level data from the Tokyo Grain Exchange, which uses rapid sequences of Walrasian tâtonnement auctions to discover prices. On the TGE, only one futures contract trades at any given time and all of a commodity's futures contracts are auctioned in a rapid sequence, with only seconds between a sequence's auctions. The results are interpreted under the hypothesis that this design causes traders' beliefs to become more accurate and more uniform as a sequence progresses.

Intraday volume is u‐shaped while intraday volatility is downward sloping. The volume–volatility link is positive and stays constant or strengthens as traders' beliefs about value become more precise. The link is driven by trades originating from small futures commission merchants, especially those trades entered on behalf of customers.

Evidence that accounting for cross‐correlations when estimating volatility can have an important effect on estimates is presented. Researchers are encouraged to further explore the implications of cross‐correlations.

The paper includes implications for existing theory, the measurement of volatility, and the design of central exchanges.

This paper uses the TGE as a natural laboratory to test theory. It is the first such study to use data from an exchange that does not use continuous auctions, and the first to document the simultaneous existence of u‐shape volume and downward‐sloping volatility.

In this paper, the main focus is on supply and demand auction systems with resource pooling in modern supply chain from a theoretical modeling perspective. The supply and demand auction systems in modern supply chains among manufacturers and suppliers serve as information sharing mechanisms. The purpose of this paper is to match the supply and demand such that a modern supply chain can achieve incentive compatibility and economic efficiency. The authors design such a supply and demand auction system that can integrate resources to efficiently match the supply and demand.

The authors propose three theoretic models of modern supply chain auctions with resource pooling according to the Vickrey auction principle. They are supply auction model with demand resource pooling, demand auction model with supply resource pooling, and double auction model with demand and supply resource pooling. For the proposed auction models, the authors present three corresponding algorithms to allocate resources in the auction process by linear programming, and study the incentive compatibility and define the Walrasian equilibriums for the proposed auction models. The authors show that the solutions of the proposed algorithms are Walrasian equilibriums.

By introducing the auction mechanism, the authors aim to realize the following three functions. First is price mining: auction is an open mechanism with multiple participants. Everyone has his own utility and purchasing ability. So, the final price reflects the market value of the auction. Second is dynamic modern supply chain construction: through auction, firm can find appropriate partner efficiently. Third is resources integration: in business practices, especially in modern supply chain auctions, auctioneers can integrate resources and ally buyers or sellers to gain more efficiency in auctions.

In the paper, the authors propose three theoretic models and corresponding algorithms of modern supply chain auctions with resource pooling according using the Vickrey auction principle, which achieves three functions: price mining, dynamic modern supply chain construction and resources integrating. Besides, these proposed models are much closer to practical settings and may have potential applications in modern supply chain management.