Liquidity Provision Research Articles

Research on Well Selection Method for Intermittent Pumping in Oil Wells Based on the Analytic Network Process and Fuzzy Logic

In the later stages of oilfield development, the decline in oil well production and the increase in development costs, attributed to issues such as insufficient liquid supply, necessitate the implementation of intermittent pumping measures. However, current methods for selecting these wells lack comprehensiveness in the decision-making process. This article proposes a novel method for selecting intermittent pumping wells utilizing the analytic network process (ANP) and fuzzy logic. Initial surveys identified the main factors influencing intermittent pumping effectiveness. The ANP was employed to screen and integrate six core factors, including submergence depth and water cut. Subsequently, a fuzzy-logic-based model was developed, incorporating trapezoidal and rectangular membership functions to establish detailed correlations among the factors. The model’s efficacy was validated and tested using real-world data from the oilfield. Results indicate that the model’s assessments of intermittent pumping wells align closely with professional engineering judgments. This approach not only provides clear guidance for well selection but also demonstrates high scalability and adaptability across different oilfields by adjusting membership functions, thereby showcasing significant practical value.

Reinforcement learning and rational expectations equilibrium in limit order markets

This paper shows that simple payoff-based reinforcement learning can help to achieve rational expectations equilibrium in limit order markets. In equilibrium, speculators mainly supply liquidity, while liquidity consumption increases in the private values of no-speculators with intrinsic motives for trade. Driven by information acquisition of the non-speculators, liquidity consumption is hump-shaped in fundamental volatility for the speculators but U-shaped for the non-speculators. In contrast, liquidity supply decreases in fundamental volatility for the speculators but is hump-shaped for the non-speculators. Unlike the informed traders who trade on asset fundamentals, the uninformed traders trade more on order book and trading information.

ROLE OF FINANCIAL INSTRUMENTS IN ENSURING LIQUIDITY AND STABILITY OF THE CURRENCY MARKET OF UKRAINE IN THE CONDITIONS OF MILITARY CONFLICT

In the conditions of military actions, liquidity of the currency market is of critical importance for the financial stability and security of the state, which stipulates significant relevance of the issue of instruments of liquidity provision. The research aims to identify the influence of the instruments of the National Bank of Ukraine (NBU) on the liquidity of the currency market of Ukraine within the context of long-term military conflict.The methods of regression analysis, correlation analysis, and analysis of variance were used in the study to determine the leading factors that influence the liquidity of the currency market in Ukraine in the conditions of military conflict.The study of the liquidity of the currency market through the prism of linear regression reveals the relation between the core economic indicators and the level of liquidity of the currency market during the military conflict. The model with a coefficient of determination 0,774 was found to effectively describe 77,4% of liquidity variability, underlining the significant influence of such factors as central bank policies and macroeconomic conditions. Significant coefficients for central bank interventions (1,7867), regulatory measures (59,8199), volume of international aid (-1,5684) and inflation (-99,9780) indicate their influence on the liquidity of the currency market in the conditions of military conflict. The influence of regulatory measures with a correlation of 0,59 is especially important.The article emphasises the necessity for minimising dependence on external financing and inflation control through monetary measures to ensure price stability. Further study perspectives involve consideration of the influence of digital currency of central banks on the liquidity of the currency market.

Quantum Chemical Analysis of the Molecular and Fragment Ion Formation of Butyrophenone by High-Electric Field Tunnel Ionization at Atmospheric Pressure.

The molecular ion M+· was observed when the liquid sample of butyrophenone was supplied using atmospheric pressure corona discharge (APCD). In contrast, the vapor supply resulted in the formation of the protonated molecule [M+H]+. The mass spectrum obtained with the liquid supply showed two distinctive fragment ions at m/z 105 and 120, resulting from α-cleavage and McLafferty rearrangement (McLR), respectively. The APCD spectrum showed peaks of M+· and the characteristic two fragment ions that were the same as the field ionization mass spectra of butyrophenone as reported by Chait et al. and Beckey et al. The formation of the molecular and fragment ions strongly indicated that high-electric field tunnel ionization (HEFTI) occurs by the HEF strength exceeding 108 V/m at the tip of the corona needle in APCD. The charge and spin density distributions of the molecular and fragment ions were analyzed by quantum chemical calculations using time-dependent density functional theory (TDDFT) and natural bond orbital (NBO) analysis.

Retail Trading Around Earnings Announcements: Evidence from Robinhood Traders

Retail investors from the discount broker Robinhood swarm into stocks with pending earnings announcements and stay away from them immediately after the announcements. We study four competing explanations for this phenomenon: liquidity provision, informed trading, lottery preference, and attention-induced herding by noise traders. We find strong evidence that, immediately around earnings announcements, Robinhood investors’ behavior is primarily driven by attention-induced noise trading. Our results offer new insights into retail traders’ motivation for trading when they face heightened uncertainty from earnings announcements. We also find corroborative evidence from a proprietary data that tracks retail trading activities from NASDAQ.

Enhanced Phase Change Heat Transfer with Fused Deposition Modeling (FDM) Printed Pit and Pillar (Pi2) Arrays

Phase change heat transfer, crucial in thermal management systems, can be significantly enhanced through optimized surface structures. This study investigates pool boiling heat transfer enhancement using 3D printed structures with carefully designed pillar and pit geometries. We present a novel approach combining the Dual Rise model with separate liquid–vapor pathways to improve Critical Heat Flux (CHF) and Heat Transfer Coefficients (HTC). Using copper-infused Polylactic Acid (PLA) filaments, we created and sintered structured surfaces featuring pit-assisted nucleation sites, interpillar spacing for vapor escape, and pillar roughness for enhanced liquid supply. Experiments with deionized water and ethanol under atmospheric pressure demonstrated substantial improvements over plain surfaces: water showed an 87% increase in CHF and 39% in maximum HTC, while ethanol exhibited even greater enhancements of 122% in CHF and 61% in HTC. These improvements are attributed to the synergistic effects of optimized surface geometry and separated liquid–vapor pathways, reducing counterflow resistance and improving hydrodynamic stability. A theoretical framework based on the Dual Rise model explains these enhancements, providing insights into coupled capillary action and hemiwicking effects in boiling heat transfer. The study introduces predictive models for CHF and HTC enhancement, offering valuable tools for future design optimization in applications ranging from electronics cooling to power plant thermal management and advanced heat exchangers.

A comparative performance study of terminal control strategy for the multi-split backplane cooling system in data centers

Multi-split backplane cooling, a typical rack-level cooling technology, has the advantage of solving local hot-spot problems with huge energy-saving potential. These systems adopt the multi-split mode, and the operation effect is affected by terminal control performance. However, there are factors in the operation process, such as superheat degree (SH), rack airflow, evaporating/condensing pressures, etc., which improve the control complication, particularly under large head load differences among different terminals. Therefore, appreciative control strategies for outlet air temperatures of terminal evaporators, including single-loop control limited by minimum stable superheat degree (SLC) and fan/electronic expansion valve (EEV) double-loop control (DLC), are proposed considering that cooling performance can be affected by both refrigerant flow and airflow. Then, comparative simulation studies are carried out to evaluate energy efficiency, control effect, and feasibility under the condition of different server heat distribution characteristics. Results indicate that the DLC strategy achieves 23% higher energy efficiency than the SLC strategy with a better temperature control effect when the inlet air temperature (IAT) difference between terminal evaporators is within ±5K. The SLC strategy has better reliability by more stable control of SH at IATs below 42°C, but it may lead to cooling failure when IATs exceed 42°C. An insufficient liquid supply problem may happen to the evaporator adopting the DLC strategy when the IAT is too high, which can be solved by adjusting the pressure differential between the evaporator and condenser. Moreover, the DLC system exhibits intense coupling effects, and how to decouple it is worthy of further study.

Decentralized Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision

Decentralized Finance and Automated Market Making: Predictable Loss and Optimal Liquidity Provision

Large Orders in Small Markets: Execution with Endogenous Liquidity Supply

Abstract We model the execution of a large uninformed sell order in the presence of strategic competitive market makers. We solve for the unique symmetric equilibrium of the model in closed form. Analysis of this equilibrium reveals that large orders unequivocally benefit market makers, while smaller investors stand to benefit only if the order trades with a sufficiently high intensity. The equilibrium results further provide a rationale for the empirically observed patterns of (i) shorter orders trading at higher intensities, and (ii) price pressures potentially subsiding before large orders stop executing.

Experimental Characterization of Process Pressure Variations on The Accuracy and Performance of Liquid Ultrasonic Flow Meters

This paper investigated the influence of process pressure variations on the accuracy and performance of ultrasonic flow meters. Process measurement technology provides a tool for optimizing production processes and dosing operations. Accurate measurement is key and primary to profitability in the business of supply and purchase of liquids like petroleum, gas and chemical products. Three 6” size ultrasonic flow meters were mounted on a skid and used to carry out the experiment parallel in connections each other to take flows from a common header, measure and discharge their individual flows into a common discharge header. The three meters were designate 1, 2 and 3 respectively. Meters 1 and 2 being service meters while Meter 3 is the calibrated master meter. The experiment was carried ten times to increase reliability of results. Experimental data were collected and analyzed using computational formulae technique. Results showed that; Meter 1 had an optimum process pressure of 12.38 and 9.43 bar with respect to flow rate and meter factor respectively as performance indicator. While Meter 2 had an optimum process pressure of 12.4 and 12.41 bar with respect to flow rate and meter factor respectively as performance indicator. Findings indicated significant relationship between process pressure, flow rate and meter factor using ultrasonic flow meter. The outcome of this study will be a useful guide to users of ultrasonic flow meters to maintain optimum process pressures of each meter during fluid supply.

Predictive crypto-asset automated market maker architecture for decentralized finance using deep reinforcement learning

This study proposes a quote-driven predictive automated market maker (AMM) platform with on-chain custody and settlement functions, alongside off-chain predictive reinforcement learning capabilities, to improve the liquidity provision of real-world AMMs. The proposed architecture augments Uniswap V3, a cryptocurrency AMM protocol, by using a novel market equilibrium pricing to reduce divergence and slippage losses. Furthermore, the proposed architecture involves a predictive AMM capability, for which a deep hybrid long short-term memory (LSTM) and Q-learning reinforcement learning framework is used. It seeks to improve market efficiency through obtaining more accurate forecasts of liquidity concentration ranges, where liquidity starts moving to expected concentration ranges prior to asset price movement; thus, liquidity utilization is improved. The augmented protocol framework is expected to have practical real-world implications through (1) reducing divergence loss for liquidity providers; (2) reducing slippage for crypto-asset traders; and (3) improving capital efficiency for liquidity provision for the AMM protocol. The proposed architecture is empirically benchmarked against the well-established Uniswap V3 AMM architecture. The preliminary findings indicate that the novel AMM framework offers enhanced capital efficiency, reduced divergence loss, and diminished slippage, which could potentially address several of the challenges inherent to AMMs.

Optimization of process parameters for Trifolium pratense L. seed granulation coating using GA-BP neural network

Regarding the issue of low granulation qualification rates during the granulation coating of red clover seeds, this study theoretically analyzed the force conditions of seeds and powder particles under the action of liquid to obtain the main factors affecting seed coating quality. During the seed granulation coating process, an intermittent powder supply method combined with continuous liquid supply was utilized to control the ratio of powder to liquid. Using the granulation qualification rate as the evaluation index, single-factor experiments were conducted to investigate the effects of coating pan fill ratio, single powder supply amount, powder supply interval, and liquid supply amount on the quality of red clover seed granulation coating. Based on the results of the single-factor experiments, orthogonal experiments were conducted, revealing that the interaction of factors would influence the experimental results. To further optimize the quality of seed granulation coating, the mechanisms of powder and liquid in the adhesion process on granulation coating were explored. Orthogonal experiments were conducted on the process parameters of the granulation coating machine, and the GA-BP model was employed for optimization and solution. The optimal process parameter combination obtained was a coating pan fill ratio of 33.78 %, a single powder supply amount of 5.17 g, a powder supply interval of 7.7 s, and a liquid supply amount of 0.42 mL/s. Under this optimal parameter combination, granulation coating experiments with red clover seeds were performed, and the seed granulation coating quality was relatively high, with a granulation qualification rate of 97.7 %. The research results can provide a reference for optimization experiments on coating irregular seeds.

Minitab 20 and Python based-the forecasting of demand and optimal inventory of liquid aluminum sulfate supplies

In a company, inventory management is crucial due to the significant impact on various aspects of the business. Similarly, the Indonesian water supply company (PDAM) requires effective inventory management to ensure the supply of liquid aluminum sulfate chemicals. The probabilistic statistical inventory control (SIC) model is commonly used for inventory management. However, previous research on chemical inventory models in PDAMs often relied on simple linear regression to forecast demand data, which fails to capture the inherent volatility in demand. Therefore, this research aimed to predict demand data using the seasonal autoregressive integrated moving average (SARIMA) method and determine the optimal policy for supplying liquid aluminum sulfate chemicals. The results showed that the best demand forecasting model was SARIMA (2,1,2) (1,1,0)12 with a mean absolute percentage error (MAPE) value of 8.19%. The finding of the optimal inventory policy showed a safety stock value of 11,922.35 kg, a reorder point value of 49,511.20 kg, and an order quantity of 21,526.59 kg, leading to a total cost of IDR 11,132,034,145.45. The sensitivity test also showed that variations in lead time, price, μ, and σ parameters directly influence changes in total cost, reorder point, and safety stock. These calculations were conducted using Minitab and Python software.

Automated market makers and their implications for liquidity providers

Automated market making for crypto tokens is an extremely attractive and efficient way to establish decentralized exchanges. An inevitable prerequisite for this type of market is the willingness of participants to provide liquidity. Except in the case of two correlated pairs, providing liquidity is often sub-optimal. In fact, one often faces significant opportunity cost commonly referred to as impermanent loss. Prevailing transaction fee levels, even with levered positions, are often insufficient to compensate for the opportunity costs incurred. Marketability and exchangeability are essential prerequisites for attributing value to many crypto tokens. Therefore, when issuing fiat tokens for the viability of intriguing business models, one ends up with the chicken-or-the-egg causality dilemma; how to achieve sustainable incentives to the liquidity provision for an abstract good whose intrinsic value is defined solely by that liquidity system? This article derives and discusses useful formulas for the quantitative risk management in the context of automated market makers. In addition, order size and pool size-dependent transaction costs are proposed that may incentivize the desired level of liquidity.

Systemic bank runs without aggregate risk: How a misallocation of liquidity may trigger a solvency crisis

We develop a general equilibrium model of self-fulfilling bank runs. The key novelty is the way in which the banking system’s assets and liabilities are connected. Banks issue loans to entrepreneurs who sell goods to households, which in turn pay for the goods by redeeming bank deposits. The return on bank assets is thus contingent on households being able to withdraw their deposits. In a run, not all households that wish to consume manage to withdraw, since part of banks’ cash reserves end up in the hands of households without consumption needs. This misallocation of liquidity lowers revenues of entrepreneurs and bank asset returns, thereby rationalising the run. Interventions that restrict redemptions in a run can be self-defeating due to their negative effect on demand in goods markets. We show how runs can sometimes be prevented with combinations of deposit freezes and redemption penalties as well as with the provision of emergency liquidity.

Development of Highly Efficient Lamb Wave Transducers toward Dual-Surface Simultaneous Atomization.

Highly efficient surface acoustic wave (SAW) transducers offer significant advantages for microfluidic atomization. Aiming at highly efficient atomization, we innovatively accomplish dual-surface simultaneous atomization by strategically positioning the liquid supply outside the IDT aperture edge. Initially, we optimize Lamb wave transducers and specifically investigate their performance based on the ratio of substrate thickness to acoustic wavelength. When this ratio h/λ is approximately 1.25, the electromechanical coupling coefficient of A0-mode Lamb waves can reach around 5.5% for 128° Y-X LiNbO3. We then study the mechanism of droplet atomization with the liquid supply positioned outside the IDT aperture edge. Experimental results demonstrate that optimized Lamb wave transducers exhibit clear dual-surface simultaneous atomization. These transducers provide equivalent amplitude acoustic wave vibrations on both surfaces, causing the liquid thin film to accumulate at the edges of the dual-surface and form a continuous mist.

Thermofluidic behavior of a 2-m nitrogen-charged cryogenic capillary pumped loop during its supercritical startup

A cryogenic capillary pumped loop (CCPL) is a highly efficient two-phase capillary-force-driven heat transport device that operates at cryogenic temperatures. CCPL satisfies the demands for space applications in cryogenic regions as it can transport heat over long distances without mechanical moving parts. In this study, the transient internal flow during the supercritical startup of CCPL was predicted, and various temperature relationships were used to determine whether CCPL starts up or not. The utilized CCPL comprised a wick (pore radius = 1.0 μm), exhibited a heat transport distance of 2 m, and was filled with nitrogen as the working fluid. The supercritical startup experiments were performed at a temperature range of 77–300 K; the startup procedure was initiated when the maximum temperature of CCPL decreased to ∼150 K. Three different liquid supply cycles were tested during the supercritical startup, and the startup time was reduced (a maximum and minimum of 4.1 and 1.9 h, respectively). CCPL started when the evaporator temperature was below the cold reservoir temperature. Thus, the temperature relationship between the cold reservoir and evaporator at the time of applying the heat load to the evaporator could be used to determine the possibility of starting CCPL. The startup was considered successful when the cold reservoir temperature was higher than the evaporator temperature, as the cold reservoir, which exhibited a two-phase state, supplied sufficient liquid to the evaporator, filling the inside of the evaporator with liquid.

Treasury Bill Shortages and the Pricing of Short‐Term Assets

ABSTRACTWe propose a model of post‐Great Financial Crisis (GFC) money markets and monetary policy implementation. In our framework, capital regulation may deter banks from intermediating liquidity derived from holding reserves to shadow banks. Consequently, money markets can be segmented, and the scarcity of Treasury bills available to shadow banks is the main driver of short‐term spreads. In this regime, open market operations have an inverse effect on net liquidity provision when swapping ample reserves for scarce T‐bills or repos. Our model quantitatively accounts for post‐2010 time series for repo rates, T‐bill yields, and the Fed's reverse repo facility usage.

玉米植保无人机离心喷施系统设计与雾滴分布特性试验

Aiming at the problems of spraying pole-type plant protection machines difficult to get down to the field after row closure of maize in the middle and late stages, uneven droplet distribution of pressure nozzle-type plant protection drone, and difficult to change the droplet particle size, this paper designed a UAV centrifugal spraying system for maize planting protection through the designed centrifugal nozzle combined with a plant protection drone. A single nozzle parameter test was carried out to study the relationship between nozzle speed, flow rate and droplet size. The variable parameter flow rate is set in the range of 300 ml ~ 1000 mL / min, and the nozzle rotation speed is set in the range of 8000 ~ 18000 r / min gradient change. The test results show that the droplet size is related to the liquid supply flow rate and the nozzle rotation speed. According to the theory of optimal biological particle size, the centrifugal nozzle parameter is determined to select the liquid supply flow rate of 1000 mL / min and the nozzle rotation speed of 14000 r / min. The droplet distribution characteristics test under the actual operating conditions was carried out with this parameter, and the important index parameters such as droplet size, droplet density and coverage rate were analyzed to characterize the UAV aerial spraying operation. The experimental results show that the flight speed of the UAV has an important effect on the droplet deposition parameters, which significantly affects the droplet coverage, droplet density and deposition amount of the bottom layer of maize, and the droplet coverage and the droplet deposition amount of each sampling layer tends to decrease with the increase of flight speed, and the coefficient of variation (CV) value of the centrifugal spraying system was the smallest at the flight speed of 1.5m/s, and the effect of droplet deposition was the most uniform. at a flight speed of 1.5m/s. The effect of droplet deposition is the most uniform. This study can provide a reference basis for the optimization of parameters and the correct use of centrifugal plant protection UAV in the middle and late stage plant protection operations of tall crops such as maize.

Asset prices when large investors interact strategically

This paper examines equilibrium asset prices and leverage in an exchange economy populated with both retail and institutional investors. Institutional investors influence the price of the stocks they trade and are aware of the price impact of the opponent and, thus, interact strategically. Because of the price impact, institutional investors decrease their demand for stocks and lend money to the retail sector, thereby increasing leverage in the economy. The risk-free rate (equity premium) tends to be lower (higher) as compared to an economy populated by retail investors only. Retail investors' compensation for liquidity provision depends on the behavior of institutional investors and the state of the economy.