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Reservation price

About: Reservation price is a research topic. Over the lifetime, 4219 publications have been published within this topic receiving 112259 citations. The topic is also known as: reserve price.


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Journal ArticleDOI
TL;DR: In this article, the relationship between the variability of the daily price change and the daily volume of trading on the speculative markets was investigated and the results of the estimation can reconcile a conflict between the price variability-volume relationship for this market and the relationship obtained by previous investigators for other speculative markets.
Abstract: This paper concerns the relationship between the variability of the daily price change and the daily volume of trading on the speculative markets. Our work extends the theory of speculative markets in two ways. First, we derive from economic theory the joint probability distribution of the price change and the trading volume over any interval of time within the trading day. And second, we determine how this joint distribution changes as more traders enter (or exit from) the market. The model's parameters are estimated by FIML using daily data from the 90-day T-bills futures market. The results of the estimation can reconcile a conflict between the price variability-volume relationship for this market and the relationship obtained by previous investigators for other speculative markets. THIS PAPER CONCERNS the relationship between the variability of the daily price change and the volume of trading on speculative markets. Previous empirical studies [2, 3, 6, 12, 14, 16] of both futures and equity markets always find a positive association between price variability (as measured by the squared price change Ap2) and the trading volume.2 There are two explanations for the relationship. Clark's [2] explanation, which is secondary to his effort to explain why the probability distribution of the daily price change is leptokurtic, emphasizes randomness in the number of within-day transactions. In Clark's model the daily price change is the sum of a random number of within-day price changes. The variance of the daily price change is thus a random variable with a mean proportional to the mean number of daily transactions. Clark argues that the trading volume is related positively to the number of within-day transactions, and so the trading volume is related positively to the variability of the price change. The second explanation is due to Epps and Epps [6]. Their model examines the mechanics of within-day trading. The change in the market price on each within-day transaction or market clearing is the average of the changes in all of the traders' reservation prices. Epps and Epps assume there is a positive relationship between the extent to which traders disagree when they revise their reservation prices and the absolute value of the change in the market price. That is, an increase in the extent to which traders disagree is associated with a larger absolute price change. The price variability-volume relationship arises, then, because the volume of trading is positively related to the extent to which traders disagree when they revise their reservation prices.

1,558 citations

Book
01 Jan 1942

1,104 citations

Journal ArticleDOI
TL;DR: This article studied the second-price auctions run by eBay and Amazon and found that the fraction of bids submitted in the closing seconds of the auction is substantially larger in eBay than in Amazon, and more experience causes bidders to bid later on eBay but earlier on Amazon.
Abstract: Auctions on the Internet provide a new source of data on how bidding is in uenced by the detailed rules of the auction. Here we study the second-price auctions run by eBay and Amazon, in which a bidder submits a reservation price and has this (maximum) price used to bid for him by proxy. That is, a bidder can submit his reservation price (called a proxy bid) early in the auction and have the resulting bid register as the minimum increment above the previous high bid. As subsequent reservation prices are submitted, the bid rises by the minimum increment until the second-highest submitted reservation price is exceeded. Hence, an early bid with a reservation price higher than any other submitted during the auction will win the auction and pay only the minimum increment above the second-highest submitted reservation price. eBay and Amazon use different rules for ending an auction. Auctions on eBay have a Ž xed end time (a “hard close”), while auctions on Amazon, which operate under otherwise similar rules, are automatically extended if necessary past the scheduled end time until ten minutes have passed without a bid. These different rules give bidders more reason to bid late on eBay than on Amazon.We Ž nd that this is re ected in the auction data: the fraction of bids submitted in the closing seconds of the auction is substantially larger in eBay than in Amazon, and more experience causes bidders to bid later on eBay, but earlier on Amazon. Last-minute bidding, a practice called “sniping,” arises despite advice from both auctioneers and sellers in eBay that bidders should simply submit their maximum willingness to pay, once, early in the auction. For example, eBay instructs bidders on the simple economics of second-price auctions, using an example of a winning early bid. They discuss last-minute bids on a page explaining that they will not accept complaints about sniping, as follows:

1,040 citations

Journal ArticleDOI
TL;DR: In this paper, the authors characterize the solution to the problem of searching for the best outcome from alternative sources with different properties, and the optimal strategy is an elementary reservation price rule, where the reservation prices are easy to calculate and have an intuitive economic interpretation.
Abstract: This paper completely characterizes the solution to the problem of searching for the best outcome from alternative sources with different properties The optimal strategy is an elementary reservation price rule, where the reservation prices are easy to calculate and have an intuitive economic interpretation

1,034 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202219
202147
202062
201964
201859