Higher Price Impact Research Articles

Balancing innovation and affordability in anti-obesity medications: the role of an alternative weight-maintenance program.

Despite remarkable clinical advances in highly effective anti-obesity medications, their high price and potential budget impact pose a major challenge in balancing equitable access and affordability. While most attention has been focused on the amount of weight loss achieved, less consideration has been paid to interventions to sustain weight loss after an individual stops losing weight. Using a policy simulation model, we quantified the impact of a weight-maintenance program following the weight-loss plateau from the initial full-dose glucagon-like peptide 1 (GLP-1) receptor agonists or incretin mimetic use. We measured long-term health care savings and the loss of some health benefits (eg, maintenance of weight loss, improvements in cardiometabolic risk factors, and reductions in diabetes and cardiovascular events). Our model suggested that, compared with continuous long-term full-dose GLP-1 receptor agonists or incretin mimetic drugs, the alternative weight-maintenance program would generate slightly fewer clinical benefits while generating substantial savings in lifetime health care spending. Using less expensive and potentially less effective alternative weight-maintenance programs may provide additional headroom to expand access to anti-obesity medications during the active weight-loss phase without increasing total health care spending.

Publication bias in simulation model studies: The case of ethanol literature.

In this study, we explore the potential for publication bias using market simulation results that estimate the effect of US ethanol expansion on corn prices. We provide a new test of whether the publication process routes market simulation results into one of the following two narratives: food-versus-fuel or greenhouse gas (GHG) emissions. Our research question is whether model results with either high price or large land impact are favored for publication in one body of literature or the other. In other words, a model that generates larger price effects might be more readily published in the food-versus-fuel literature while a model that generates larger land use change and GHG emissions might find a home in the GHG emission literature. We develop a test for publication bias based on matching narrative and normalized price effects from simulated market models. As such, our approach differs from past studies of publication bias that typically focus on statistically estimated parameters. This focus could have broad implications: if in the future more studies assess publication bias of quantitative results that are not statistically estimated parameters, then important inferences about publication bias could be drawn. More specifically, such a body of literature could explore the potential that practices common in either statistical methods or other methods tend to encourage or deter publication bias. Turning back to the present case, our findings in this study do not detect a relationship between food-versus-fuel or GHG narrative orientation and corn price effects. The results are relevant to debates about biofuel impacts and our approach can inform the publication bias literature more generally.

The Effects of Volatility on Liquidity in the Treasury Market

We study the relationship between volatility and liquidity in the market for on-the-run Treasury securities using a novel framework for quantifying price impact. We show that at times of relatively low volatility, marginal trades that go with the flow of existing trades tend to have a smaller price impact than trades that go against the flow. However, this difference tends to diminish at times of high volatility, indicating that the perceived information content of going against the flow is less when volatility is high. We also show that market participants executing trades aggressively using market orders will experience larger increases in price impact than those executing trades passively using limit orders as volatility increases. And times of low market depth are associated with increased risk of high price impact and high sensitivity to volatility in future, perhaps because liquidity is more reliant on high-speed quote replenishment and is therefore more fragile.

High Frequency Quote Proportion, Price Impact and Predictability of Factors

High Frequency Quote Proportion, Price Impact and Predictability of Factors

High Frequency Quote Proportion, Price Impact and Predictability of Factors

High Frequency Quote Proportion, Price Impact and Predictability of Factors

Measurement of the sound absorption coefficient of palm frond fiber composites with synthetic adhesives

Natural fiber composite materials have been widely applied for various purposes, one of which is reducing noise. Many efforts have been tried to reduce noise by using sound absorbing materials such as glasswool, rockwool, and gypsum as sound absorbers, but because of the high price and bad impact on health, many studies have been conducted to find materials that are practical, cheap, and abundant availability in nature, one of which is natural fiber as an alternative to commercial sound absorbing materials. In this study, we want to know the effect of the composition of palm fronds with polyester resin can affect the sound absorption of a material and the effect of composition on sound absorption. The composition of palm frond fiber and polyester resin was varied 60%:40%, 65%:35%, 70%:30%, 75%:25%, 80%:20%, 85%:15%, 90%:10%, arranged randomly with a length of 5 mm. The specimen synthesis process starts with cutting the palm fronds, decomposing the palm frond fibers so that the fibers are separated from the flesh. Acoustic testing was conducted using a single microphone impedance tube. The test results showed that the largest absorption coefficient value is 0.984 at a frequency of 1500 Hz and is obtained in materials with a composition of 70%: 30%, and for the largest acoustic impendance value is 1.714 which is found at a frequency of 500 Hz and is obtained in the composition of 85%: 15%.

The Value of Coordination in Multimarket Bidding of Grid Energy Storage

Grid energy storage plays a key role in making carbon-free, renewable energy production a reality. Yet, when it comes to maximizing profit, owners of storage assets still struggle with coordinating their trading activities across time because of the complex nature of multisettlement electricity markets. In “Coordination of Multimarket Bidding of Grid-Energy Storage,” Nils Löhndorf and David Wozabal propose a multistage stochastic programming model for market-oriented optimization of energy storage. To calculate lower and upper bounds on optimal values, they develop novel methods for scenario-tree generation and information relaxation. They show that a coordinated policy that reserves capacity for the short-term markets is optimal and that the gap to a sequential policy increases with short-term price volatility and market liquidity. The authors find that coordination is beneficial for all considered asset types and that flexible storages with high price impact benefit most. Their findings inform storage owners which markets contribute most value, how to organize trading across time, and how to calculate optimal bidding strategies.

Who is buying and (not) lending when shorts are selling?

Stock lending markets are unique because stock buyers become potential stock lenders. During periods of high short demand, loan supply should expand as some new buyers of loaned shares lend them. Using instrumental variables, we find instead that loan supply contracts: during times of high short demand, the marginal buyer lends stock at a lower rate than the average seller. We find that this puzzling result is concentrated among closely held stocks with high disagreement among investors, high price impact measures, and lottery-like returns. Thus, non-lending buyers may believe that withholding shares from short sellers could enhance their expected returns.

Price Discovery in the U.S. Treasury Cash Market: On Principal Trading Firms and Dealers

<ns3:p>We explore the following question: does the trading activity of registered dealers on Treasury interdealer broker (IDB) platforms differ from that of principal trading firms (PTF), and if so, how and to what effect on market liquidity? To do so, we use a novel dataset that combines Treasury cash transaction reports from FINRA’s Trade Reporting and Compliance Engine (TRACE) and publicly available limit order book data from BrokerTec. We find that trades conducted in a limit order book setting have high permanent price impact when a PTF is the passive party, playing the role of liquidity provider. Conversely, we find that dealer trades have higher price impact when the dealer is the aggressive party, playing the role of liquidity taker. Trades in which multiple firms (whether dealers or PTFs) participate on one or both sides, however, have relatively low price impact. We interpret these results in light of theoretical models suggesting that traders with only a “small” informational advantage prefer to use (passive) limit orders, while traders with a comparatively large informational advantage prefer to use (aggressive) market orders. We also analyze the events that occurred in Treasury markets in March 2020, during the onset of the COVID-19 pandemic.</ns3:p>

The dynamics of the aggressive order during a crisis.

We investigate the dynamics of aggressive order in the financial market to further understand volatility. To analyze aggressive order, market orders in the order book are scrutinized. The market orders have different degrees of aggressiveness; therefore, we categorize market orders into four types: types Zero, One, A, and B, of which type B is the most aggressive. To examine the dynamics and impacts of each type of order, we use both macro- and micro-level approaches. From the macroscopic perspective, the burstiness and memory of type B is highly correlated with volatility. When traders face a financial crisis, they place bursty aggressive orders, and the orders are more predictable than usual. From the microscopic perspective, we additionally focus on the influence of the orders, particularly the price impact and resilience. The aggressive order has a greater impact than others, even when the price change of the aggressive order is smaller. Moreover, the aggressive order delivers more information on price because the aggressive order has a higher price impact than the execution cost.

Optimal portfolio execution problem with stochastic price impact

In this paper, we provide a closed-form solution to an optimal portfolio execution problem with stochastic price impact and stochastic net demand pressure. Specifically, each trade of an investor has temporary and permanent price impacts, both of which are driven by a continuous-time Markov chain; whereas the net demand pressure from other inventors is modelled by an Ornstein—Uhlenbeck process. The investor optimally liquidates his portfolio to maximize his expected revenue netting his cumulative inventory cost over a finite time. Such a problem is first reformulated as an optimal stochastic control problem for a Markov jump linear system. Then, we derive the value function and the optimal feedback execution strategy in terms of the solutions to coupled differential Riccati equations. Under some mild conditions, we prove that the coupled system is well-posed, and establish a verification theorem. Financially, our closed-form solution shows that the investor optimally liquidates his portfolio towards a dynamic benchmark. Moreover, the investor trades aggressively (conservatively) in the state of low (high) price impact.

Information Environments and High Price Impact Trades: Implication for Volatility and Price Efficiency

We include trade matchedness to Limit Order Book (LOB) as an extended identification dimension of High Price Impact Trades (HPITs). HPITs are trades associated with disproportionately large price changes in comparison with their volume proportion and are related to informed trades. We show that the introduction of matchedness provides finer informed trading identification, and we find that a stronger presence of HPITs leads to a decline in volatility due to more contrarian informed trades, but this decline varies with information environments. Finally, we conclude that HPITs mainly reflect belief-based (fundamental-based) information in a high (low) public disclosure environment.

How Pervasive and Investable is the Asset Growth Anomaly?

Based on U.S. stock returns from 1973 to 2015, this study found that the asset growth anomaly does not seem to be pervasive and investable. The trading strategy is robust only among a tiny portion of the equity market in terms of both number of stocks and capitalization. In addition to underdiversifcation and capacity constraint, the implementation also involves high arbitrage risk, illiquidity and price impact, low stock loan supply, and potentially non-negligible brokerage fee.

Quantifying immediate price impact of trades based on the k-shell decomposition of stock trading networks

Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into k classes using the k-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.

Order Anticipation in Large Order Executions

This paper studies the presence of order anticipation strategies by examining predictable patterns in large order executions. I construct four simple signals based on child-order execution patterns that may potentially leak order flow information to algorithmic traders and find empirical evidence that stronger signals are correlated with higher execution costs. This effect is more pronounced for stocks with higher algorithmic trading activity consistent with the order anticipation hypothesis. Higher price impact due to predictable signals can be transitory and permanent suggesting that algorithmic traders may exploit both the liquidity needs and private information of the investors.

Development of Large Format NMC-Graphite Lithium Ion Pouch Cell with Aqueous Processed Electrodes

The current lithium ion battery (LIB) technology has reached a very high degree of development and market share [1, 2]. However, several important bottlenecks still impede further spreading of lithium ion batteries into the EV market [2, 3]. Among them, their relatively high price and negative environmental impact have been addressed in this work. In particular, at the electrode manufacturing stage, the replacement of toxic and expensive N-Methyl-2-pyrrolidone (NMP) solvent by water is considered an innovative and promising approach to reduce both the environmental impact and the final price of the batteries [4] without sacrificing electrochemical performance [5]. Here, we report the development of a large format LiNixMnyCozO2 (NMC) - Graphite (C) pouch cell, with both electrodes prepared via aqueous processes using waterborne binders. The NMC-Graphite electrochemical system was chosen because it is considered as one of the most promising combinations for large format batteries for EV applications, in which both active materials are compatible with aqueous binders [6]. The positive electrode was composed of a commercial NMC (111) material. The negative electrode was prepared on the basis of C-NERGY™ ACTILION_1 graphite (IMERYS Graphite & Carbon) specially developed for better processability in aqueous slurries. Waterborne PVdF latexes (SOLVAY SPECIALTY POLYMERS ITALY) have been used as binders for both electrodes. Commercially available sodium carboxymethyl cellulose has been used as a dispersant for negative and positive electrode slurries. The formulation and design of the positive and negative electrodes was tailored to meet the MAT4BAT European project tasks and cell specifications. The negative and positive electrode slurries with elaborated formulations have been successfully scaled up to 3 and 6 kg, respectively. Then, more than 100 metres length double-side coated electrode rolls have been manufactured on a coating pilot line. Finally, several NMC/Graphite pouch cells with a stack design were assembled on automated pilot equipment. As shown in Figure 1, the manufactured NMC/C pouch cell with nominal capacity 17 Ah has demonstrated promising C-rate capability and stable long term cyclability with no negative influence of the aqueous processing. It should be noted that obtained specific energy density of 143 Wh/kg (@ 0.2C discharge) is very close to the commercial benchmark as defined within the MAT4BAT EU project. Thus, presented results allow for the conclusion that aqueous processing is a successful approach for manufacturing large format NMC-Graphite lithium ion cells for EV applications. The study has been performed within the MAT4BAT project funded by the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement #608931. We would like to acknowledge Celaya, Emparanza y Galdós Internacional S.A. for the manufacturing of the NMC/C pouch cells.

The liquidity premium in CDS transaction prices: Do frictions matter?

Based on individual CDS transactions cleared by the Depository Trust & Clearing Corporation, we show that illiquidity strongly affects credit default swap premiums. We identify the following effects: first, transaction direction affects prices, as buy (sell) orders lead to premium increases (decreases). Second, larger transactions have a higher price impact. This finding stands in stark contrast to corporate bond markets. Third, traders charge higher premiums as a price for liquidity provision, not as compensation for asymmetric information. Fourth, buy-side investors pay significantly higher prices than dealers for demanding liquidity. Finally, inventory risk seems to matter little in explaining liquidity premiums.

Information Efficiency and Firm-Specific Return Variation

Reasoning that private firm-specific information causes firm-specific return variation that drives down market-model R2s, [Morck et al., 2000, The Information Content of Stock Markets: Why do Emerging Markets have Synchronous Stock Price Movements? Journal of Financial Economics, 58, 215–260] begin a large body of research which interprets R2 as an inverse measure of price informativeness. Low-R2s or "synchronicity," as it is called in this literature, signal that prices more efficiently incorporate private firm-specific information, and high R2s indicate less. For this to be true, we would expect that low-R2 stocks have characteristics that facilitate private informed trade, i.e., lower information costs and fewer impediments to arbitrage. However, in this paper we document the opposite: Low-R2 stocks are small, young, and followed by few analysts, and have high bid-ask spreads, high price impact, greater short-sale constraints and are infrequently traded. In fact, microstructure measures suggest that private-information events are less likely for low-R2 stocks than high, and that differences in R2 are driven as much by firm-specific volatility on days without private news as by firm-specific volatility on days with private news. These results call into question prior research using R2 to measure the information content of stock prices.

The Impact of Political Uncertainty and Abnormal Market Conditions on Institutional Trading Behavior

This article investigates the impact of political uncertainty and abnormal market conditions on institutional trading behavior. The study finds that institutional investors are net buyers during abnormal market decreases and net sellers during abnormal market increases. Institutional investors’ net buying activity declines because of aversion to political uncertainty. Institutional investors face high price impact during times of high political uncertainty and abnormal market conditions. In abnormal market declines, institutional sells face a 2.98% price impact. In abnormal market increases, institutional buys generate a price impact of 3.24%. This study also finds that high political uncertainty increases price impact during abnormal market declines by up to 0.10%. <b>TOPICS:</b>Tail risks, analysis of individual factors/risk premia, financial crises and financial market history

Comparing Time-Varying Price Impact and Information Impounding Time Across Asian Stock Exchanges: An Adaptive Lasso Approach

In this paper we construct a parsimonious vector autoregression model with durations, trades and quote revisions to compare price impact and information impounding time in four Asian stock exchanges. We conduct simultaneous model selection and estimation using the adaptive lasso approach. We measure the price impact and the information impounding time via examining the impulse response of a new trade. Weekly estimation from January 2007 to August 2012 allows us to compare the time-varying price impacts. We find that the price impact and the information impounding time vary considerably across time. Traders in Korean and Japanese markets pay more attention to high price impact trades while traders in Hong Kong and Chinese markets pay less attention. Larger mean price impact has larger impact uncertainty measured by the price impact’s standard deviation. Longer mean information impounding time has higher convergence uncertainty measured by the information impounding time’s standard deviation. For many stocks, price impacts have spikes during the 2008 financial crisis. The price impact is negatively related to liquidity and positively related to systematic risk. The average correlation among price impacts of different stocks also varies across time. In Korean and Chinese markets, when systematic risk is high, the average correlation among price impacts is also high.