scholarly journals Price Discovery and Learning during the German 5G Auction

2021 ◽  
Vol 14 (6) ◽  
pp. 274
Author(s):  
Thomas Dimpfl ◽  
Alexander Reining
Keyword(s):  
Price Discovery ◽  
Price Formation ◽  
Bidding Behavior ◽  
Efficient Process ◽  
Formation Efficiency

The auctioning of frequency has to comply with a multitude of requirements in order to guarantee a transparent and efficient process. The German Federal Network Agency (Bundesnetzagentur) has opted for a design that provides participants with information on the highest bid after each round for every band along with information on the bidder. We evaluate the price formation efficiency in this setup to see how fast prices become informative about the final auction value. We find that prices are partially informative right from the beginning which allows us to conclude that participants were able to learn fast from their competitors’ bidding behavior and validates the choice of the agency to implement the auction in the present format.

scholarly journals Price Discovery in Cryptocurrency Markets

2019 ◽  
Vol 109 ◽  
pp. 97-99
Author(s):  
Igor Makarov ◽  
Antoinette Schoar
Keyword(s):  
United States ◽  
Price Discovery ◽  
The United States ◽  
Price Formation ◽  
Significant Heterogeneity ◽  
Local Markets ◽  
The Us ◽  
It Impact

We ask which markets drive bitcoin prices and how price discovery happens across different exchanges. Does the greater exuberance for cryptocurrencies outside the United States affect prices only on local markets or does it impact price formation on global cryptocurrency markets? We document significant heterogeneity in which price formation happens across exchanges and time. When markets are more integrated, shocks to prices on all exchanges contribute to price discovery. However, when markets become segmented, those exchanges that have large arbitrage spreads relative to the US price, i.e. where investors are more exuberant become much less important for price discovery.

scholarly journals UNDERSTANDING INDONESIA’S CITY-LEVEL CONSUMER PRICE FORMATION: IMPLICATIONS FOR PRICE STABILITY

2019 ◽  
Vol 22 (4) ◽  
pp. 405-422
Author(s):  
Paresh Kumar Narayan
Keyword(s):  
Price Index ◽  
Price Discovery ◽  
Consumer Price Index ◽  
Price Formation ◽  
Price Stability ◽  
Price Changes ◽  
Monthly Data

Using the Consumer Price Index (CPI) data of 82 Indonesian cities, we propose thehypothesis of heterogeneity in the cities’ contribution to the aggregate IndonesianCPI. Using a price discovery model fitted to monthly data, we discover that (1) of the23 cities in the province of Sumatera, five contribute 44% and nine contribute 66.7%to price changes, and (2) of the 26 cities in Java, four alone contribute 41.6% to pricechanges. Even in smaller provinces, such as Bali and Nusa Tenggara, one city alonedominates the change in aggregate CPI. From these results, we draw implications formaintaining price stability.

scholarly journals Call Market Experiments: Efficiency and Price Discovery through Multiple Calls and Emergent Newton Adjustments

2017 ◽  
Vol 9 (4) ◽  
pp. 1-41 ◽  
Author(s):  
Charles R. Plott ◽  
Kirill Pogorelskiy
Keyword(s):  
Price Discovery ◽  
Competitive Equilibrium ◽  
Market Price ◽  
Price Formation ◽  
Order Book ◽  
Call Markets ◽  
Multiple Unit ◽  
Market Experiments ◽  
Raphson Method ◽  
Call Market

We study multiple-unit, laboratory experimental call markets in which orders are cleared by a single price at a scheduled “call.” The markets are independent trading “days” with two calls each day preceded by a continuous and public order flow. Markets approach the competitive equilibrium over time. The price formation dynamics operate through the flow of bids and asks configured as the “jaws” of the order book with contract execution featuring elements of an underlying mathematical principle, the Newton-Raphson method for solving systems of equations. Both excess demand and its slope play a systematic role in call market price discovery. (JEL C92, D41, D44, G14)

scholarly journals Experiencing Market Dynamics with TraderEx: A Trading Decision-Making Simulation

2021 ◽  
pp. 87-100
Author(s):  
Deniz Ozenbas ◽  
Michael S. Pagano ◽  
Robert A. Schwartz ◽  
Bruce W. Weber
Keyword(s):  
Decision Making ◽  
At Risk ◽  
Dynamic Process ◽  
Business School ◽  
Price Discovery ◽  
School Curriculum ◽  
Price Formation ◽  
Institutional Trading ◽  
Financial Industry ◽  
Real Money

AbstractTrading education is vital for success in the securities and investments industry. Are apprenticeships and time on an institutional trading desk the only way to learn how to trade? Do you need to work with real orders and have real money at risk to gain experience interacting with the dynamic process of price formation? The answers are no and no. Trading simulations that are well-designed can create experiences with price discovery and impose the challenges of illiquidity in ways that replicate the learning accomplished (and pressures felt) on a real trading desk. With TraderEx, you will appreciate the complexity of trading and understand it as a distinct profession within the financial industry, even if it is not always thought of as such in business school curriculum.

Market Efficiencies and Drift: A Computational Model

2009 ◽  
Vol 84 (6) ◽  
pp. 1805-1831 ◽  
Author(s):  
John Dickhaut ◽  
Baohua Xin
Keyword(s):  
Computational Model ◽  
Price Discovery ◽  
Strong Form ◽  
Price Formation ◽  
Double Auction ◽  
Security Prices ◽  
Individual Decisions ◽  
Work Done

ABSTRACT: Accounting and finance researchers show semi-strong form efficiency or lack thereof by using sequences of prices from Center for Research in Security Prices (CRSP) and Compustat data for which there is no model for how these prices arise from individual decisions. One needs a setting in which prices (including bids and asks) as well as information about individuals making the choices are both available. To begin to bridge the gap between theory and data, we extend work done by experimental economists on the double auction and model price formation that is or is not semi-strong efficient. Agents in the model uncover prices in a manner consistent with Hayek's notion of price discovery (Hayek 1948).

scholarly journals Neoclassical Supply and Demand, Experiments, and the Classical Theory of Price Formation

2021 ◽  
pp. 37-73
Author(s):  
Sabiou M. Inoua ◽  
Vernon L. Smith
Keyword(s):  
Price Discovery ◽  
Adam Smith ◽  
Supply And Demand ◽  
Market Price ◽  
Price Formation ◽  
Modern Theory ◽  
Collective Interaction ◽  
Large Numbers ◽  
Open Outcry ◽  
Market Experiments

Neoclassical price theory was founded on axioms of price-taking behavior and the law of one price in a market, axioms inconsistent with a theory of endogenous price discovery in markets. Classical economists including Adam Smith narrated a price discovery process based on buyer and seller reservation values and their motivation to buy low and sell high; the classical sketch of price formation offers a quite fruitful foundation for a modern theory of price discovery, supplied below. Market experiments, based on private distributed reservation values and using rules governing open-outcry double auctions, converged endogenously, in three to four periods of repeat interaction, to an efficient outcome. These observations contradicted the widely believed, thought, and taught necessity for perfect information, large numbers, and price-taking behavior. However, these results were consistent with the old, classical, conception of price formation emerging from the collective interaction of the traders. Aggregation and price discovery constitute essential functions of classical markets. We explore the divergence of neoclassical scholars from this classical tradition. Revealingly, in describing the microdynamics of market price formation, prominent neoclassical utilitarians such as Marshall, with his description of a “corn-market in a county town,” and Böhm-Bawerk with his farmers’ horse market, reverted to this classical reservation-value framework.

Factors of Price Formation for Art Objects With the Application of Text Analysis of Twitter News

2020 ◽  
pp. 114-131
Author(s):  
Elena A. Fedorova ◽  
Diana V. Zaripova ◽  
Igor S. Demin
Keyword(s):  
Text Analysis ◽  
Price Formation ◽  
Works Of Art ◽  
Art Objects ◽  
Online Resource ◽  
The Difference

This work confirmed the hypotheses about the influence of the mood index on Twitter on the pricing of art objects and the difference between the experts' estimations and the final price of the auction. The hypotheses were tested with the use of a sample of 83 paintings selected on the basis of ratings of ARTNET's online resource about the most expensive works of art ever sold in the last 10–15 years. The sample consisted of 25 artists, for each of them was made an index of moods on Twitter. This index was created by a sentimental analysis of each tweet about the artist on the hashtag for a period of 2 to 4 months between the announcements of sales in the open sources and the direct sale of the work with the use of the two dictionaries AFINN and NRC.

Intraday Price Formation in U.S. Equity Index Markets

CFA Digest ◽  
2004 ◽  
Vol 34 (3) ◽  
pp. 56-57
Author(s):  
Robert A. McLean
Keyword(s):  
Price Formation ◽  
Equity Index
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