Pricing Grid Research Articles

Tick Size, Competition for Liquidity Provision, and Price Discovery: Evidence from the U.S. Treasury Market

This paper studies how a tick size change affects market quality, price discovery, and the competition for liquidity provision by dealers and high-frequency trading firms (HFTs) in the U.S. Treasury market. Using difference-in-differences regressions around the November 19, 2018, tick size reduction in the 2-year Treasury note and a similar change in the 2-year futures eight weeks later, we find significantly improved market quality. Moreover, dealers become more competitive in liquidity provision and price improvement, consistent with the hypothesis that HFTs find liquidity provision less profitable in the smaller tick size environment. Last, we find a significant shift in short-run price discovery toward the cash market, which then reverses when the futures market tick size is reduced, suggesting that the finer pricing grid in the cash market allows traders to act on small information signals that are not profitable to exploit in the larger-tick futures market. Our findings suggest that reducing the tick size in tick-constrained and highly liquid markets like the Treasury market is on balance beneficial. This paper was accepted by Bruno Biais, finance. Funding: F. Ruela acknowledges support from the National Science Foundation Graduate Research Fellowship Program [Grant DGE-1746045]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.4663 .

A Price-Based Grid Resources Pricing Approach for NonStorable Real Assets

A grid-computing paradigm delivers the processing power of massively parallel computation to all subscribed users. Current trends, research, and developments in grid computing show that the available grid resources exist as non-storable compute commodities and are distributed geographically – the grid problem. To solve the grid problem, several initiatives have developed frameworks for grid economy and have proposed several algorithms towards an optimized resources scheduling in a grid environment. However, since the grid resources availability depends on the time of usage and are transient, such generic approaches lack the ability to capture the realistic valuation of the resources and fail to guarantee the certainty in their availability measured as Quality of Service (QoS). Uncertainties in grid resource availability do not guarantee a user expected QoS without over committing (e.g., storing the non-storable resources) resources to the users. To guarantee QoS (satisfy a users’ computing needs), we propose a price-based and quality-aware model that captures the realistic value of the grid compute commodities. We use the financial option theory from a real option perspective to value grid resources by treating them as real assets. We discuss a set of results on pricing grid compute cycles. Our results are based on the compute cycle usage obtained from the WestGrid node at the University of Manitoba. We extend and generalize our study to any grid in general but with specific reference to the WestGrid. Keywords: Financial Options, Price Stochasticity, Compute Cycles, Real Options, Quality of Service. Allenotor, D. & Oyemade, D. A. (2022): A Price-Based Grid Resources Pricing Approach for Non-Storable Real AssetsJournal of Advances in Mathematical & Computational Science. Vol. 10, No. 2. Pp 1-18 DOI: dx.doi.org/10.22624/AIMS/MATHS/V10N2P1. Available online at www.isteams.net/mathematics-computationaljournal.

Tick Size Wars: The Market Quality Effects of Pricing Grid Competition

AbstractWe explore the effects of a “tick size war” in which European trading venues directly competed on the minimum pricing increment in the limit order book, the tick size. We find that venues that reduced their tick size immediately captured market shares of both quoted and executed volume from the exchanges that kept their ticks large. We find that tick size competition improves market quality, reducing trading costs, and increasing market-wide depth and volume. These market quality improvements are strongest in stocks where the bid–ask spread was constrained to one tick, where liquidity providers use the finer pricing grid to engage in price competition.

A Responsive Pricing Grid Operator Sourcing from Competing Generators under Uncertain Supply and Demand

Electricity supply chains involve more sources of uncertainty than typical production and manufacturing supply chains, owing to the intermittent nature of renewable energy generation. Therefore, it is critical but challenging to mitigate supply disruption risks by improving management methods. The extant literature has mainly investigated the sourcing strategies of manufacturers with price-taking suppliers. Where there is an option to source from multiple generators, including regular but unreliable generators and reliable backup generators, a flexible sourcing strategy is usually regarded as the best tactic for the grid operator. Our objective is to evaluate the costs and benefits of flexible sourcing and sole sourcing when generators are strategic price-setters. In this paper, we develop a Stackelberg game with wholesale prices contingent on the dominant grid operator’s sourcing strategy. We describe and analyze the resulting equilibriums under different scenarios. The results show that the grid operator does not necessarily benefit from a backup generator and that the flexible sourcing mode is not in fact optimal, except when the disruption ratio of the unreliable generator is medium and the penalty-sharing ratio of the unreliable generator is low. The model is applied to a numerical case study of a real-word electricity supply chain to illustrate the validity and effectiveness of the proposed conclusions.

Tick Size Change and Market Quality in the U.S. Treasury Market

This paper studies the effects of a recent tick size reduction in the U.S. Treasury securities market. We find significantly narrower bid-ask spreads, increased trading activity, improveddepth within one old tick despite lower overall market depth, and improved price efficiency.Moreover, slow traders become more competitive in liquidity provision and price improvement.Finally, high-frequency price discovery shifts to the smaller-tick cash market from the associatedfutures market, supporting the idea that a finer pricing grid allows traders to act promptly on even small information signals otherwise not profitable. Overall, we conclude that the tick sizereduction improves market quality.

Third decimal place odd prices trigger competition: evidence from the Italian retail gasoline market

ABSTRACTRecent literature shows that in the US gasoline prices are higher in locations using more odd prices (particularly those ending in five and nine digits), since they coarse the pricing grid and act as a focal collusive point. We replicate this analysis for the Italian market, obtaining the opposite result. Since the rightmost digit of the retail gasoline prices in Italy is the third and not the second decimal place, coarsening the pricing grid is not sufficient to support a collusive behaviour.

Animal Carcass Pricing Grid. Evidences from the Romanian Pigmeat Market

Abstract Until the introduction of SEUROP system, price negotiation between pig producers and slaughterhouses was based on two subjective criteria: animal weight and visual inspection of the quality of pigs. To ensure producers a fair payment, European Union created the possibility of binding the price on two objective factors: carcass weight and carcass composition. This paper describes the pricing mechanism developed by Romania in order to respond to European Union requirements for ensuring a fair payment to pig producers. It raises the attention on the difficulties encountered by the producers in understanding the way the commercial value of a pig carcass is calculated in case the selling price is negotiated on a flat rate basis or on a lean content basis (per kg of carcass weight or per kg of live weight).

APPLICATION OF THEORY OF CONSTRAINTS AND CRITICAL CHAIN METHOD FOR PROJECT MANAGEMENT IN ULTRA MEGA POWER PROJECTS (UMPP)

In Developing countries like India, there is a huge demand for Power and the country itself faces challenges in meeting the demand in an effective manner. In India, Planning commission has come up with a solution by bringing in Ultra Mega Power projects (UMPP) in recent years. Large number of power projects (XI and XII five year plans) is under construction to overcome the power shortages and meet the growing energy requirements in the country. So Government of India has planned for Mega / Ultra Mega Power Generation projects with revised tariff regulations for existing central government projects, competitive bidding for all future power generation projects, tariff norms for renewable energy / introduction of Renewable Energy Certificates, new transmission pricing grid code, power market regulations, Re – structured Accelerated Power Development Reform Programme (APDRP2), National Electricity Fund, etc. Ministry of Power and Central Electricity Authority (CEA) have projected a total investment requirement of Rs. 11,35,142 Crore for the power sector during the 12th Plan period, which also includes investment for generation of additional capacity of about 1,00,000 MW to the existing capacity of about 1,64,508 MW for the country. The above stated reforms are good sign of development but India’s performance in power sector (Planning to Operation) is not remarkable. Always delays are encountered in all phases. The Second main constraint in UMPP is managing the criticality of material and inventory for the project. But, this criticality has been overcome effectively in Mundra project which is an UMPP. The Phase- 1,2,3 of Mundra Power plant has been successfully completed and will start its effective operation soon (Capacity of 800 MW each).The success includes timely completion with available resource in a significant manner. The success delivery is by application of Theory of Constraints and Critical chain management in critical phases. So, the effectiveness of the above said concepts has to be realised and adopted in other ongoing and proposed UMPP for better service to the country on time.

Performance-Sensitive Debt The Intertwined Effects of Performance Measurement and Pricing Grid Asymmetry

This paper studies the use of performance pricing (PP) provisions in debt contracts and compares accounting-based with rating-based pricing designs. We find that rating-based provisions are used by volatile-growth borrowers and allow for stronger spread increases over the credit period. Accounting-based provisions are employed by opaque-growth borrowers and stipulate stronger spread reductions. Further, a higher spread-increase potential in rating-based contracts lowers the spread at the loan's inception and improves the borrower's performance later on. In contrast, a higher spread-decrease potential in accounting-based contracts lowers the initial spread and raises the borrower's leverage afterwards. The evidence indicates that rating-based contracts are indeed employed for different reasons than accounting-based contracts: the former to signal a borrower's quality, the latter to mitigate investment inefficiencies.

Integrating stochasticity into the objective function avoids Monte Carlo computation in the optimisation of beef feedlots

The real world contains many sources of natural variation. Useful simulation models of real-world problems, such as the optimal allocation of beef cattle into feedlot pens, need to take this into account. Monte Carlo simulation is the usual method of achieving this, using multiple model runs, each with a different set of randomly generated variables. However, when the goal is system optimisation, this approach can make the computation extremely intensive, and difficult for the optimisation of even moderately-sized models. This problem was addressed in an industry model of feedlot operations, where animals are selected and drafted into separate pens, and grown to the optimal weight and fat ranges in the pricing grid. For each pen, it is planned that the majority of the animals achieve this targeted region of the price grid, so that the number of discounted carcasses will be minimal. The main problem is that animals which appear reasonably similar at intake then display variable growth and fattening rates. Hence deterministic predictions are unrealistic, and stochasticity needs to be factored in. However this interferes with the efficient optimisation of this feedlot operation, which ultimately needs to be done ‘real-time’ (at animal induction), and on-site at the feedlot. Our solution to this dilemma was to transfer all of the modelled stochastic processes onto the evaluation side of this problem, by integrating over Normal distributions applied to the expected prices for each animal. This allows the optimisation runs to directly estimate the expected economic outcome using just one model evaluation for each trial management strategy. This process is illustrated with two case-studies, based on separate past intakes of animals into a commercial feedlot. For both intakes, the simulated results as reflected by the carcass values for the actual times on feed matched well with the observed values. Simulated results indicate that increases in profitability can be obtained both by altering the days on feed, and by better allocation of the animals to the pens. The overall predicted increase in profit per animal was $34 for the first intake, where the actual allocation of animals to the pens was approximately random (the order they were offloaded), and $20 for the second example where the animals had been allocated to pens on a more structured basis (by weights). This optimised allocation scheme appears to offer obvious improvements for feedlot operations, and is currently being trialed by a number of industry collaborators.

Signaling, Financial Constraints, and Performance Sensitive Debt

This paper examines how good borrowers use the design of performance sensitive debt contracts to alleviate financial constraints. I show that borrowers use a convex pricing grid (i.e., a contract where the increase in the loan spread following a decline in performance exceeds the decrease in the spread following a performance improvement) to signal their unobservable creditworthiness and receive better bank loan terms. I find that constrained firms that use convex pricing grids receive loans that are 21-28% larger with a spread that is 31-37 basis points lower than observationally similar borrowers that use fixed spread loans. Consistent with the notion that a costly signal should positively correlate with future financial health, I find that constrained borrowers that use a loan with a convex pricing grid are one third less likely to experience financial distress during the term of their loans.

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Increasing Utilization of US Electric Grids via Smart Technologies: Integration of Load Management, Real Time Pricing, Renewables, EVs and Smart Grid Sensors

Imperfect Competition in Financial Markets: An Empirical Study of Island and Nasdaq

The competition between Island and Nasdaq at the beginning of the century offers a natural laboratory to study competition between and within trading platforms and its consequences for liquidity supply. Our empirical strategy takes advantage of the difference between the pricing grids used on Island and Nasdaq, as well as of the decline in the Nasdaq tick. Using the finer grid prevailing on their market, Island limit order traders undercut Nasdaq quotes, much more than they undercut one another. The drop in the Nasdaq tick size triggered a drop in Island spreads, despite the Island tick already being very thin before Nasdaq decimalization. We also estimate a structural model of liquidity supply and find that Island limit order traders earned rents before Nasdaq decimalization. Our results suggest that perfect competition cannot be taken for granted, even on transparent open limit order books with a very thin pricing grid.

Management Insights

Management Insights

Spread decomposition with common spread components

PurposeThis paper aims to incorporate a market wide buying and selling pressure cost component into a spread decomposition model as spread cost component.Design/methodology/approachThe paper extends a commonly used trade indicator spread decomposition model to include a component common to all stocks of a specialist firm and a market wide component common to all stocks.FindingsStrong evidence is found that specialists consider this common factor cost component when they set bid and ask quotes. Some specialist firms also take the next logical step and specifically manage their firm wide stock inventories. The common factor is in percentage terms largest for securities with the highest trade frequencies.Research limitations/implicationsThe relative importance of the common factor spread component decreases as the pricing grid becomes finer, but remains highly significant under the decimal trading regime.Originality/valueThis is the first study to document not‐security‐specific spread cost components that are common to all stocks for which a specialist firm makes markets and to all stocks in the market. Using the model it is shown that market wide uncertainty translates into spreads of individual securities.

Removing biases in computed returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.

Removing Biases in Computed Returns

This paper presents a straightforward method for asymptotically removing the well-known upward bias in observed returns of equally-weighted portfolios. Our method removes all of the bias due to any random transient errors such as bid-ask bounce and allows for the estimation of short horizon returns. We apply our method to the CRSP equally-weighted monthly return indexes for the NYSE, Amex, and NASDAQ and show that the bias is cumulative. In particular, a NASDAQ index (with a base of 100 in 1973) grows to the level of 17,975 by 2006, but nearly half of the increase is due to cumulative bias. We also conduct a simulation in which we simulate true prices and set spreads according to a discrete pricing grid. True prices are then not necessarily at the midpoint of the spread. In the simulation we compare our method to calculating returns based on observed closing quote midpoints and find that the returns from our method are statistically indistinguishable from the (simulated) true returns. While the mid-quote method results in an improvement over using closing transaction prices, it still results in a statistically significant amount of upward bias. We demonstrate that applying our methodology results in a reversal of the relative performance of NASDAQ stocks versus NYSE stocks over a 25 year window.

Approximating the Embedded M Out of N Day Soft-Call Option of a Convertible Bond: An Auxiliary Reversed Binomial Tree Method

A convertible bond (CB) with a right of m out of n day provisional call or soft-call becomes callable given that the underlying stock closes above a pre-set trigger price for any m or more days over the n consecutive trading days up to the current day. It is computationally challenge to value the contribution of this embedded option to the price of CB. This paper proposes an approximation based on the idea of an auxiliary reversed binomial (ARB) tree, and shows that the approach can be efficiently implemented under the Cox-Ross-Rubinstein parameterization. Two important insights emerge from ARB. First, the convertible bond is unconditionally callable at higher stock prices, but uniformly not callable at lower prices. Second, the effect of the soft-call is rather localized around the trigger price. Surprisingly, the simple One-Touch, or one out of one, approximation is found to yield CB prices that are very close to those from ARB, even though ARB is found to a better approximation in almost every aspect. Further numerical results suggest that in order to generate well-behaved CB prices, cautions need to be taken while designing the terms of soft-call. Being independent of the finite difference pricing grid, the proposed ARB tree can also be used in association with the tree method or Monte Carlo simulation, and could in principle be applicable to exotic derivatives with similar embedded options.

The Impact of Pennies on the Market Quality of the Toronto Stock Exchange

AbstractUsing detailed order flow data from the Toronto Stock Exchange, this paper finds no evidence that a smaller tick size lessens market liquidity for either small or large traders. Rather, there is evidence of lower trading costs, faster time to order execution, and greater price continuity. Consistent with a penny tick allowing a finer pricing grid search, there is an increase in the number of Change Former Orders and cancellations.

Market microstructure: A survey of microfoundations, empirical results, and policy implications

We survey the literature analyzing the price formation and trading process, and the consequences of market organization for price discovery and welfare. We offer a synthesis of the theoretical microfoundations and empirical approaches. Within this framework, we confront adverse selection, inventory costs and market power theories to the evidence on transactions costs and price impact. Building on these results, we proceed to an equilibrium analysis of policy issues. We review the extent to which market frictions can be mitigated by such features of market design as the degree of transparency, the use of call auctions, the pricing grid, and the regulation of competition between liquidity suppliers or exchanges.