Periodic Auctions Research Articles

A framework for seasonal groundwater banking in agricultural regions: A case study

Groundwater banking has been used for demand-oriented management of groundwater resources in semi-arid and arid regions. This paper aims to propose a new framework for seasonal groundwater banking. In this framework, crop production functions are used to estimate users' bid packages representing the price of each unit volume of water in each auction period. The bid packages, along with users' water rights, are considered inputs of an optimization model, which maximizes the profit of users participating in the groundwater bank. The main outputs of the optimization model are the volumes of exchange and storage of water, as well as the water price in the auction periods. The efficiency of the proposed framework has been evaluated by applying it to the Nough region in the Rafsanjan Plain, central Iran. An existing plan for inter-basin water transfer to this region is also considered in the water banking framework. The results illustrate that the total annual profit of all users after the establishment of the bank compared to the status quo has increased up to 43.8 %. The profit of the water-recipient basin has also increased more than 4 times compared to the existing condition. In addition, water banking with a water transfer system increases the economic productivity of water and crop production by 37.32 % and 22.41 %, respectively.

Quality Uncertainty and Repeat Purchases in Fish Auctions: Are Price Affected?

Abstract Auctions are widely used for agricultural and seafood products worldwide. However, buyer uncertainty regarding product quality may affect auction participation and efficiency negatively. This study examines repeat purchases (RPs) as a strategy to reduce buyer uncertainty regarding product quality and whether prices are affected. We also examine whether prices are affected by buyers’ option to prioritise among bids for several lots in the same auction period. Using hedonic price functions on data from the Norwegian pelagic auction, we find that RPs are associated with lower prices and that lots with first priority obtain higher prices than comparable random transactions.

Banning dark pools: Venue selection and investor trading costs

We analyze the relation between transaction costs and venue choice using proprietary transaction-level data from institutional trade executions in the U.K. equity market. We show that, for a given investor, a higher share of dark trading (midpoint dark pools) is associated with lower execution costs. In the context of a recent ban on dark trading, we provide evidence consistent with migration towards substitute trading venues such as periodic auctions, which has mitigated adverse effects on trading costs for large investors. We also provide micro-evidence on Menkveld et al.’s (2017) pecking order theory of venue choice over the life-cycle of large parent orders.

Research on the impact of certification emission reduction price on energy price based on big data

Global warming has seriously affected human production and life. At present, countries around the world are committed to finding ways to save energy and reduce emissions. The Kyoto Protocol introduced a market mechanism to trade the power of carbon dioxide and other greenhouse gas emissions as a commodity. In the process of actual economic operation, due to advanced emission reduction technology, extensive use of new energy, implementation of environmental protection policies and other factors, certification emission reduction (CER) in some countries are less than the emission limit. At present, the scarcity of CER is mainly determined by the government, and the government can intervene in the dynamics of the carbon emission trading market through various means, such as formulating different carbon quota allocation methods, or holding periodic auction of emission rights, etc. This paper studies the phenomenon that CER is a commodity traded in the market, and the tight relationship between supply and demand of CER determines the carbon price. This paper analyzes the application of big data in the price control of CER, and the influence mechanism of CER on energy prices. Finally, the development plan and prospect of the exploration market are put forward.

Using Statistical Model to Study the Daily Closing Price Index in the Kingdom of Saudi Arabia (KSA)

Classification in statistics is usually used to solve the problems of identifying to which set of categories, such as subpopulations, new observation belongs, based on a training set of data containing information (or instances) whose category membership is known. The article aims to use the Gaussian Mixture Model to model the daily closing price index over the period of 1/1/2013 to 16/8/2020 in the Kingdom of Saudi Arabia. The daily closing price index over the period declined, which might be the effect of corona virus, and the mean of the study period is about 7866.965. The closing price is the last regular deal that took place during the continuous trading period. If there are no transactions on the stock during the day, the closing price is the previous day’s closing price. The closing auction period comes after the continuous trading period (from 3 : 00 PM to 3 : 10 PM), during which investors can enter by buying and selling the stocks at this period. The experimental results show that the best mixture model is E (equal variance) with three components according to the BIC criterion. The expectation-maximization (EM) algorithm converged in 2 repetitions. The data source is from Tadawul KSA.

Price discovery, order submission, and tick size during preopen period

Using limit order book data, this study investigates the effects of minimum tick size reduction on price discovery and order submission strategies during the preopen call auction period in the Tokyo Stock Exchange. Studying the largest stocks' changes before and after the tick size reduction, our findings suggest that price discovery becomes more efficient when a smaller tick size is employed. A reduction in tick size induces a decrease in market depth and spread and enhances the speed of price discovery by encouraging more aggressive order to be placed and providing investors a better learning and communicating environment to incorporate information into order decisions. Our results demonstrate that, although orders are not matched and no transaction occurs during the preopen period, the order placement at these moments is neither necessarily noisy nor completely manipulative; factors that impact the investor's order choice during the normal trading period also work in this period.

Speed and learning in high-frequency auctions

Faster trading improves liquidity in periodic call auction markets, in contrast to continuous-time markets. We build a model where high-frequency traders (HFTs) engage in duels to trade on stale quotes. More frequent periodic auctions increase the likelihood that a single HFT arrives in any given auction and subsequently acts as a monopolist on information. Higher trading speed increases the expected number of arbitrageurs participating in auctions, promoting competition between snipers and improving liquidity. We find that faster trading and longer auction intervals are substitute instruments to reduce bid-ask spreads. Relative to continuous-time trading, periodic batch auctions reduce HFT informational rents.

Institutional investment in online business lending markets

We provide new insights into the business lending decisions of institutional investors in online credit markets by benchmarking their lending performance against that of retail investors.We find superior performance for loans financed by institutional investors, although large sized retail investor groups achieve equivalent performance. Lending decisions of institutional investors are not default risk minimising, and we quantify lending inefficiencies. From a platform perspective, we show that (i) the platform-administered loan allocation process is not biased in favour of institutional investors, (ii) institutional participation in the retail marketplace is not a distorting factor in loan performance, and (iii) the platform’s move to a fixed rate system had detrimental effects on loan outcomes for institutional investors. The superior loan performance achieved by institutional investors is confined to the auction period, when institutional investors had autonomy over setting interest rates.

AuditChain: A Trading Audit Platform Over Blockchain

A blockchain architecture and solution is proposed to audit processing under exchange regulation for trading activity of exchanges. A particular focus is made on dark pools and periodic auctions. An architecture of the solution is described conceptually and an implementation of the proposed solution is made in .NET framework in C# via a RESTful API for chain interaction with the periodic auction venue. The framework proof of concept is tested for different efficiency and latency considerations. This opens the concept to significantly more detailed and extensive developments.

Frequent Batch Auctions Under Liquidity Constraints

We exploit European regulatory interventions to investigate the effects of sub-second periodic auctions on market quality under dark trading restrictions. The restrictions are linked to an observable increase in periodic auctions and an economically meaningful loss of liquidity. While periodic auctions ameliorate illiquidity, their effects are significantly less than those of the restrictions; therefore, the combined effects of periodic auctions’ increases and the restrictions are general declines in liquidity and informational efficiency. However, consistent with theory, periodic auctions are linked to reductions in adverse selection costs, thereby underscoring their potential to address latency arbitrage and the technological arms race.

AHEAD: Ad Hoc Electronic Auction Design

We introduce a new matching design for financial transactions in an electronic market. In this mechanism, called ad hoc electronic auction design (AHEAD), market participants can trade between themselves at a fixed price and trigger an auction when they are no longer satisfied with this fixed price. In this context, we prove that a Nash equilibrium is obtained between market participants. Furthermore, we are able to assess quantitatively the relevance of ad hoc auctions and to compare them with periodic auctions and continuous limit order books. We show that from the investors’ viewpoint, the microstructure of the asset is usually significantly improved when using AHEAD.

Non‐Clairvoyant Dynamic Mechanism Design

We introduce a new family of dynamic mechanisms that restricts sellers from using future distributional knowledge. Since the allocation and pricing of each auction period do not depend on the type distributions of future periods, we call this family of dynamic mechanisms non‐clairvoyant.We develop a framework (bank account mechanisms) for characterizing, designing, and proving lower bounds for dynamic mechanisms (clairvoyant or non‐clairvoyant). We use the same methods to compare the revenue extraction power of clairvoyant and non‐clairvoyant dynamic mechanisms.

Blockchain based uniform price double auctions for energy markets

The energy sector is undergoing a massive transformation that greatly affects and is being affected by its market mechanisms. This paper presents the design, the prototype implementation and the analysis of a decentralized, real-time, uniform-price double auction energy market. The proposed market is a distributed and decentralized application and its rules may be specified through a smart contract. Market participants interact with the smart contract sending their asks and offers and the distributed application clears the market based on a uniform-price economic dispatch model. We propose and analyze three different implementation approaches on an Ethereum blockchain network. A model representing a physical demonstration project conducted in Seattle, USA, is utilized to simulate the power grid and to provide real-life scenarios for our analysis. We systematically evaluate our three implementation approaches and elucidate several blockchain issues regarding the decentralization of next-generation energy markets. In particular, we identify that certain computation modules may be installed on smart consuming devices in order to increase efficiency, security and decentralization and reduce the overall blockchain overhead cost. Furthermore, we show that in order to fulfill the market’s high demand for step timing, we ought to have the block generation time several magnitudes smaller compared to the auction period.

The Benefits of European Periodic Auctions beyond MiFID Dark Trading Caps

Initially designed as a better alternative than dark trading, the success of periodic auctions has spread across all European stocks. On capped stocks, the market share of periodic auctions rose from 1 to 4.5 percent between early March and September 2018. Nevertheless, on uncapped stocks, periodic auctions doubled in popularity from 0.75 to 1.5 percent over the same period. The random auction end time prevents adverse selection, as shown by the price reversion. In lit and dark trading, passive buy trades are followed by a strong drop in midpoint due to the aggressive sellers. In contrast, periodic auction trades show almost no sign of adverse selection. This feature derives from the random end time of the auction, which creates a level playing field for all market participants. Based on Kepler Cheuvreux trades, this study shows that periodic auction participation mitigates the market impact. In addition, using public market data, this study shows that, on average, trading intensity diminishes after a periodic auction trade while it increases after a dark trade. TOPICS:Exchanges/markets/clearinghouses, security analysis and valuation, developed markets, performance measurement

Quasi-Dark Trading: The Effects of Banning Dark Pools in a World of Many Alternatives

We show that “quasi-dark” trading venues, i.e., markets with somewhat non-transparent trading mechanisms, are important parts of modern equity market structure alongside lit markets and dark pools. Using the European MiFID II regulation as a quasi-natural experiment, we find that dark pool bans lead to (i) volume spill-overs into quasi-dark trading mechanisms including periodic auctions and order internalization systems; (ii) little volume returning to transparent public markets; and consequently, (iii) a negligible impact on market liquidity and short-term price efficiency. These results show that quasi-dark markets serve as close substitutes for dark pools and consequently mitigate the effectiveness of dark pool regulation. Our findings highlight the need for a broader approach to transparency regulation in modern markets that takes into consideration the many alternative forms of quasi-dark trading.

AuditChain: A Trading Audit Platform Over Blockchain

A blockchain architecture and solution is proposed to audit processing under exchange regulation for trading activity of exchanges. A particular focus is made on dark pools and periodic auctions. An architecture of the solution is described conceptually and an implementation of the proposed solution is made in .NET framework in C# via a RESTful API for chain interaction with the periodic auction venue. The framework proof of concept is tested for different efficiency and latency considerations. This opens the concept to significantly more detailed and extensive developments.

Research Resource Scheduling Scheme Based on Joint Bidding

A resource scheduling scheme based on combined bidirectional auction is proposed for resource scheduling across data centers. Based on the definition of user priority and task urgency, the scheme estimates the SLA(service level agreement) violation occurred in each work during the auction process and calculates the income of the cloud provider. Simulation results show that this algorithm ensures the success rate of auction, and compared with the traditional combined bidirectional auction scheme in which a single auction is completed, the energy consumption reduction of this scheme in the auction period and the profit of the auction cloud provider are greatly optimized.

MiFID II and Equity Market Liquidity, or There and Back Again

This article examines the impact of MiFID II on European equity market liquidity. MiFID II eliminated broker crossing networks, introduced caps on dark trading, and brought about new types of venues. The authors investigate the changes in the market in the lead-up to the January 3, 2018, implementation date and the early evidence supporting the expected liquidity shift toward block networks, periodic auctions, and systematic internalizers. Although all signs indicate limited change for end-investors, the delay in implementation of the double-volume caps means it is too early to fully assess the impact on trading costs. <b>TOPICS:</b>Exchanges/markets/clearinghouses, developed

The use of auctions for allocating airport access rights

This paper considers the challenge of managing congestion at an airport by restricting the total number of flight operations at that airport. It reviews historical evidence, economic theory and data analysis related to the challenge of airport congestion management. It argues that this evidence presents a strong case for the use of a market mechanism to control access and more specifically for the use of periodic auctions to allocate limited term slot leases. It then shows that the existing body of knowledge and practical experience with the use of combinatorial auctions lead naturally to highly viable auction designs for the airport slot context. It further provides analysis of a variety of specific issues related to the use of auctions in the context of airport slots.

The Illiquidity of Water Markets: Efficient Institutions for Water Allocation in Southeastern Spain

Water is an essential good for human life but there is controversy over whether it should be allocated using markets. In 1966, the irrigation community in Mula (Murcia, Spain) switched from a market institution, a 700 year old auction, to a system of fixed quotas with a ban on trading to allocate water from the town’s river. We present a dynamic demand model in which farmers face liquidity constraints (LC) to explain why the new, non-market institution is more efficient. We show that ignoring the presence of LC biases the estimated (inverse) demand and demand elasticity downwards. We use the dynamic demand model and data from the auction period to estimate both farmers’ demand for water and their financial constraints, thus obtaining unbiased estimates. In our model, markets achieve the first-best allocation only in the absence of LC. By contrast, quotas achieve the first-best allocation only if farmers are homogeneous in productivity. We compute welfare under both types of institutions using the estimated parameters. We find that the quota is more efficient than the market.