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Bid, Ask and Transaction Prices in a Specialist Market With Heterogeneously Informed Traders
Abstract
The presence of traders with superior information leads to a positive bid-ask spread even when the specialist is risk-neutral and makes zero expected profits. The resulting transaction prices convey information, and the expectation of the average spread squared times volume is bounded by a number that is independent of insider activity. The serial correlation of transaction price differences is a function of the proportion of the spread due to adverse selection. A bid-ask spread implies a divergence between observed returns and realizable returns. Observed returns are approximately realizable returns plus what the uninformed anticipate losing to the insiders.
... Finally, our analysis shows a nonlinear relationship between FCRE and stock liquidity, moderated by the information environment and investor sentiment. Therefore, this research contributes to the literature on information asymmetry and the behavioral dimensions of stock liquidity (Dang et al., 2022;Debata, Dash, & Mahakud, 2018;Glosten & Milgrom, 1985;Wang, Mbanyele, & Muchenje, 2022). Overall, our study sheds light on the impact of managers' perception of environmental risk on financial market trading dynamics, specifically in relation to stock liquidity outcomes. ...
... This suggests that firms providing clearer and less complex MD&A disclosures and demonstrating enhanced information transparency have bolstered investor confidence, mitigated the costs linked to climate risks and helped companies maintain liquidity despite unpredictable environmental challenges. This outcome aligns with the empirical evidence (Boubaker et al., 2019;Luo et al., 2018) and supports the information asymmetry theories associated with stock liquidity, including those proposed by Diamond and Verrecchia (1991) and Glosten and Milgrom (1985). Aboody et al. (2018) measure) and IO (institutional ownership) on the nexus between FCRE (firm-level climate risk exposure based on textual analysis) and two stock liquidity proxies such as Amihud (opposite of Amihud's (2002) illiquidity measure) and HLS (opposite of high low spread). ...
... The probable reason could be that firms with greater information transparency have enhanced investor confidence, reduced the costs linked to climate risks and assisted companies in preserving liquidity amidst unpredictable environmental challenges. These findings are consistent with the empirical evidence (Boubaker et al., 2019;Luo et al., 2018) and the information asymmetry theories of stock liquidity, such as those of Diamond and Verrecchia (1991) and Glosten and Milgrom (1985). ...
Purpose
This study examines the impact of firm-level climate risk exposure (FCRE) on firm stock liquidity by using a sample of Indian-listed firms from the financial years 2003–2004 to 2022–2023. Further, it endeavors to investigate the moderating role of environmental, social and governance (ESG) disclosure in this relationship.
Design/methodology/approach
A novel text-based FCRE metric is introduced using a sophisticated Word2Vec model through a Python-generated algorithm for each firm and year based on the management discussions and analysis (MD&A) reports. The panel fixed effect model is used to study how FCRE affects stock liquidity.
Findings
The result shows that FCRE negatively affects firms’ stock liquidity, and the effect remains robust after addressing endogeneity concerns. In addition, we find that a high ESG disclosure rating significantly moderated the adverse effect of FCRE. Furthermore, our analysis reveals that investor sentiment, information quality, corporate life cycle and institutional holdings moderate the impact of FCRE on liquidity.
Practical implications
The study offers valuable insights for investors, managers and policymakers on integrating climate risk into investment strategies, improving corporate climate governance and shaping policies that incentivize sustainable corporate behavior.
Originality/value
To the best of our knowledge, this study is an early study to explore the relationship between firm-specific climate risk exposure and stock liquidity using advanced machine learning techniques. It contributes to the existing literature by illustrating how climate risk can lead to adverse market reactions while highlighting the critical roles of corporate ESG practices, investor sentiment and disclosure quality in influencing this relationship.
... Noise traders, who misinterpret signals or act on rumors (Hellwig, 1980), further amplify market inefficiencies. Kyle (1985) and Glosten and Milgrom (1985) highlight the role of trade timing and asymmetric information in reflecting informed trading, while Barclay and Warner (1993) provide evidence that longer trade durations signal deliberate, information-driven transactions. 1 Building on these foundations, Jegadeesh and Titman (1993) demonstrate that momentum arises from the delayed reaction of market participants to information, further linking trade durations to momentum and reversals. ...
... At the same time, longer trade durations are positively associated with momentum over short-and medium-term horizons, indicating a systematic process driven by greater information efficiency and investor sentiment. 1 The idea that information takes time to diffuse into prices and that longer trade durations indicate a more deliberate process of price discovery is grounded in economic intuition and supported by microstructure theory (e.g., Kyle (1985), Glosten-Milgrom (1985)). In Kyle's model (Kyle, 1985), informed traders trade on private information, while liquidity providers adjust their prices accordingly. ...
... In Kyle's model (Kyle, 1985), informed traders trade on private information, while liquidity providers adjust their prices accordingly. Similarly, in the Glosten-Milgrom model (Glosten and Milgrom, 1985), market makers adjust their quotes to account for the asymmetry between informed and uninformed traders. Shorter trade durations reflect a quicker reaction to new information, consistent with this study's models' predictions about how information asymmetry drives rapid price adjustments. ...
This study investigates the role of inter-trade duration in predicting short-term price dynamics, specifically momentum and return reversals, using intraday trading data from 2019 to 2022 across different time horizons. Longer trade durations are linked to a lower probability of short-term reversals and a higher probability of momentum over various timeframes, reducing noise trading and improving price discovery. These results are consistent across firms of all sizes. The study highlights how the interaction between trade durations and institutional ownership, bullish market sentiment, and market volatility (VIX) impact price dynamics, revealing that institutional investors, lower market volatility and favorable sentiment strengthen momentum predictability and reduce the likelihood of reversals. Granger causality tests further prove the predictive power of trade durations, without evidence of reverse causality.
... Noise traders, who misinterpret signals or act on rumors (Hellwig, 1980), further amplify market inefficiencies. Kyle (1985) and Glosten and Milgrom (1985) highlight the role of trade timing and asymmetric information in reflecting informed trading, while Barclay and Warner (1993) provide evidence that longer trade durations signal deliberate, information-driven transactions. 1 Building on these foundations, Jegadeesh and Titman (1993) demonstrate that momentum arises from the delayed reaction of market participants to information, further linking trade durations to momentum and reversals. ...
... At the same time, longer trade durations are positively associated with momentum over short-and medium-term horizons, indicating a systematic process driven by greater information efficiency and investor sentiment. 1 The idea that information takes time to diffuse into prices and that longer trade durations indicate a more deliberate process of price discovery is grounded in economic intuition and supported by microstructure theory (e.g., Kyle (1985), Glosten-Milgrom (1985)). In Kyle's model (Kyle, 1985), informed traders trade on private information, while liquidity providers adjust their prices accordingly. ...
... In Kyle's model (Kyle, 1985), informed traders trade on private information, while liquidity providers adjust their prices accordingly. Similarly, in the Glosten-Milgrom model (Glosten and Milgrom, 1985), market makers adjust their quotes to account for the asymmetry between informed and uninformed traders. Shorter trade durations reflect a quicker reaction to new information, consistent with this study's models' predictions about how information asymmetry drives rapid price adjustments. ...
... 6 Analytical models show that information asymmetry among investors can increase adverse selection risk for liquidity providers. To compensate for the increased risk, liquidity providers demand a larger risk premium and set a wider bid-ask spread, thereby reducing liquidity and raising the cost of capital (e.g., Copeland & Galai, 1983;Glosten & Milgrom, 1985;Kyle, 1985;Amihud & Mendelson, 1986;Easley & O'Hara, 2004;Hughes et al., 2007;Lambert et al., 2012). Empirical research reports similar findings (e.g., Brennan & Subrahmanyam, 1996;Easley et al., 2002;Bhattacharya et al., 2012;Armstrong et al., 2011;Akins et al., 2012). ...
... Analytical studies show that information asymmetry among shareholders increases the adverse selection risk for liquidity providers. To compensate for the increase in risk, liquidity providers demand a larger risk premium and set a wider bid-ask spread, thereby lowering liquidity and raising the cost of capital (e.g., Glosten & Milgrom, 1985;Kyle, 1985;Easley & O'Hara, 2004;Lambert et al., 2012). Numerous empirical studies document that an increased level of information asymmetry negatively affects the cost of capital (e.g., Brennan & Subrahmanyam, 1996;Easley et al., 2002;Bhattacharya et al., 2012;Armstrong et al., 2011;Akins et al., 2012). ...
... 9 We acknowledge it is possible that mergers between a shareholder and a lender of the same firm affect disclosure in an indirect way. These mergers could increase the information asymmetry perceived by other shareholders observing the merger transactions, and prompt them to demand a larger risk premium as compensation for the perceived increase in risk associated with the perceived increase in information asymmetry (e.g., Copeland & Galai, 1983;Glosten & Milgrom, 1985;Kyle, 1985). Firms might then respond by increasing disclosure and improving disclosure quality to mitigate these negative effects. 10 Kelly and Ljungqvist (2012) find evidence that the closures and mergers of brokerage houses' research operations represent a plausibly exogenous shock to information asymmetry and use this setting to show that information asymmetry is priced. ...
We use a quasi-exogenous shock to information asymmetry among shareholders to evaluate the effect of information asymmetry on corporate disclosure. In the post-Regulation Fair Disclosure (FD) period, the merger between a shareholder and a lender of the same firm provides a shock to the information asymmetry among equity investors, because Regulation FD applies to shareholders but not lenders. After the merger, the shareholder gains access to the firm-specific private information held by the lender, which produces an asymmetry in the information held by shareholders. We first provide evidence that information asymmetry among shareholders indeed increases after the shareholder–lender mergers. We then use a difference-in-differences research design to show that after shareholder–lender merger transactions, firms issue more quarterly forecasts (including earnings, sales, capital expenditure, earnings before interest, taxes, amortization (EBITDA), and gross margin), and the quarterly earnings forecasts are more precise. This study provides direct empirical evidence that information asymmetry among shareholders affects corporate disclosure. Firms can address increased information asymmetry by providing more disclosures, fostering a more equitable information environment. Additionally, policymakers might consider these results when evaluating the implications of Regulation FD, particularly in the context of mergers and acquisitions (M&A) of financial institutions where a shareholder gains access to private information held by a debt holder.
... A central endeavour in market microstructure is to reconcile the predictability of trade signs with price efficiency, i.e. to uncover the adequate price formation process. Following Glosten and Milgrom [1985], Madhavan et al. [1997] (henceforth MRR) developed a simple theory of price formation: Prices are impacted proportionally to the innovation in the transaction history (order flow). This alone removes all price predictibility when transaction signs are correlated. ...
... This alone removes all price predictibility when transaction signs are correlated. Included in their theory is Glosten and Milgrom [1985]'s assumption that market makers avoid ex-post regrets by setting a finite spread. Accordingly, the theory yields relationships between price impact, trade sign correlations, and the bid-ask spread. ...
... The MRR model proposed a price formation process which accomodates the strong serial correlations of the trade signs [Hasbrouck and Ho, 1987, Biais et al., 1995, Bouchaud et al., 2004, Farmer and Lillo, 2004, Toth et al., 2015 with the very weak auto-correlation of price returns. The MRR price formation model heavily relies on the theory of market making developed in Glosten and Milgrom [1985]. In recent years, Glosten and Milgrom [1985]'s work was significantly refined, for example in Wyart et al. [2008], Bouchaud et al. [2009]. ...
This paper develops a model of liquidity provision in financial markets by adapting the Madhavan, Richardson, and Roomans (1997) price formation model to realistic order books with quote discretization and liquidity rebates. We postulate that liquidity providers observe a fundamental price which is continuous, efficient, and can assume values outside the interval spanned by the best quotes. We confirm the predictions of our price formation model with extensive empirical tests on large high-frequency datasets of 100 liquid Nasdaq stocks. Finally we use the model to propose an estimator of the fundamental price based on the rebate adjusted volume imbalance at the best quotes and we empirically show that it outperforms other simpler estimators.
... Traditional market makers are losing their importance as automated systems have largely assumed the role of liquidity provision in markets. We update the model of Glosten and Milgrom (1985) to analyze this new world: we add multiple securities and introduce an automated market maker who uses the relationships between securities to price order flow. ...
... The model we detail below is an extension of Glosten and Milgrom (1985). Instead of using a single security, we include multiple securities, and we introduce a new type of liquidity provider called an automated market maker. ...
... As in Glosten and Milgrom (1985), we assume a pure dealership market where informed investors and liquidity traders submit unit-sized buy and sell orders for a security with a random end-of-period value. These orders are priced and cleared by a competitive, risk neutral market maker. ...
Traditional market makers are losing their importance as automated systems have largely assumed the role of liquidity provision in markets. We update the model of Glosten and Milgrom (1985) to analyze this new world: we add multiple securities and introduce an automated market maker who uses the relationships between securities to price order flow. This new automated participant transacts the majority of orders, sets prices that are more efficient, and increases informed and decreases uninformed traders' transaction costs. These results can explain the recent dominance of high frequency trading in US markets and the corresponding increase in trading volume and decrease in transaction costs for US stocks.
... Quote adjustments typically occur in response to inventory build-ups by market makers (Stoll 1978;Amihud and Mendelson 1980;Ho and Stoll 1983) or reflect information gleaned from trading activities (Glosten and Milgrom 1985;Kyle 1985;Easley and O'Hara 1987). Quote cancellations and revisions tend to result in asset price changes more frequently than actual trades (Easley et al. 2012). ...
... The assumption of rational investor behavior in EMH has faced heavy criticism (Grossman and Stiglitz 1980;Milgrom and Stokey 1982;Black 1986), and spurred the development of BFT price models that incorporate irrational or "noise" traders (see Gupta et al. 2023 for a review). Noise trading models (e.g., Kyle 1985;Glosten and Milgrom 1985;Admati and Pfleiderer 1988;De Long et al. 1990) can effectively explain excess market volatility, a phenomenon that challenges EMH. However, these models have limitations when it comes to real-time market monitoring and predicting future directions. ...
Although momentum strategies result in abnormal profitability, thereby challenging the efficient market hypothesis (EMH), concerns persist regarding their reliability due to their significant volatility and susceptibility to substantial losses. In this study, we investigate the limitations of these strategies and propose a solution. Our literature review reveals that the volatile profits are due to statistical analyses that assume the persistence of past patterns, leading to unreliable results in out-of-sample scenarios when underlying mechanisms evolve. Statistical analysis, the predominant method in financial economics, often proves inadequate in explaining market fluctuations and predicting crashes. To overcome these limitations, a paradigm shift towards dynamic approaches is essential. Drawing inspiration from three groundbreaking economists, we introduce the extended Samuelson model (ESM), a dynamic model that connects price changes to market participant actions. This paradigm transition uncovers several significant findings. First, timely signals indicate momentum initiations, cessations, and reversals, validated using S&P 500 data from 1999 to 2023. Second, ESM predicts the 1987 Black Monday crash weeks in advance, offering a new perspective on its underlying cause. Third, we classify sequential stock price data into eight distinct market states, including their thresholds for transitions, laying the groundwork for market trend predictions and risk assessments. Fourth, the ESM is shown to be a compelling alternative to EMH, offering potent explanatory and predictive power based on a single, realistic assumption. Our findings suggest that ESM has the potential to provide policymakers with proactive tools, enabling financial institutions to enhance their risk assessment and management strategies.
... The bid-ask spread increases in the fraction of informed traders. This effect is due to classical adverse selection effect going back to [28]: the market maker reacts to the presence of more informed traders by widening the spread. 16 We also observe that the bid-ask spread increases when the running penalty on inventory increases. ...
... Quoting[28]: "Generally, ask prices increase and bid prices decrease if the insiders' information becomes better, or the insiders become more numerous relative to liquidity traders". ...
We characterise the solutions to a continuous-time optimal liquidity provision problem in a market populated by informed and uninformed traders. In our model, the asset price exhibits fads -- these are short-term deviations from the fundamental value of the asset. Conditional on the value of the fad, we model how informed traders and uninformed traders arrive in the market. The market maker knows of the two groups of traders but only observes the anonymous order arrivals. We study both, the complete information and the partial information versions of the control problem faced by the market maker. In such frameworks, we characterise the value of information, and we find the price of liquidity as a function of the proportion of informed traders in the market. Lastly, for the partial information setup, we explore how to go beyond the Kalman-Bucy filter to extract information about the fad from the market arrivals.
... 3 In general, the difference between the bid and ask is explained by the various risks that the market maker or broker faces when intermediating trades, e.g. adverse selection and inventory risk, see for instance Glosten and Milgrom (1985), Grossman andMiller (1988), de Jong andRindi (2009). Here, we focus on the effect that LAs have on spreads, and one could include these other effects, which would widen the spreads. ...
... The dashed line in Figure 2 shows the asymptotic solution. This asymptotic form has a connection to the Glosten and Milgrom (1985) (GM) model. To see this, note that ...
We examine the Foreign Exchange (FX) spot price spreads with and without Last Look on the transaction. We assume that brokers are risk-neutral and they quote spreads so that losses to latency arbitrageurs (LAs) are recovered from other traders in the FX market. These losses are reduced if the broker can reject, ex-post, loss-making trades by enforcing the Last Look option which is a feature of some trading venues in FX markets. For a given rejection threshold the risk-neutral broker quotes a spread to the market so that her expected profits are zero. When there is only one venue, we find that the Last Look option reduces quoted spreads. If there are two venues we show that the market reaches an equilibrium where traders have no incentive to migrate. The equilibrium can be reached with both venues coexisting, or with only one venue surviving. Moreover, when one venue enforces Last Look and the other one does not, counterintuitively, it may be the case that the Last Look venue quotes larger spreads.
... Related Work: There is a large collection of studies that examines information asymmetry and price discovery in financial markets, in both the theoretical and empirical fields. In theoretical studies, a large set of papers analyze non-fragmented markets, including the two pioneering works in price discovery, Glosten and Milgrom (1985), and Kyle (1985). Other studies examine fragmented lit markets, for example Viswanathan and Wang (2002), Chowdhry and Nanda (1991), and Hasbrouck (1995). ...
... A lit market is an exchange for the asset. The exchange is modeled in the spirit of Glosten and Milgrom (1985). Precisely, in the lit market, there is a risk neutral market maker who facilitate transactions. ...
This paper investigates the impact of dark pools on price discovery (the efficiency of prices on stock exchanges to aggregate information). Assets are traded in either an exchange or a dark pool, with the dark pool offering better prices but lower execution rates. Informed traders receive noisy and heterogeneous signals about an asset's fundamental. We find that informed traders use dark pools to mitigate their information risk and there is a sorting effect: in equilibrium, traders with strong signals trade in exchanges, traders with moderate signals trade in dark pools, and traders with weak signals do not trade. As a result, dark pools have an amplification effect on price discovery. That is, when information precision is high (information risk is low), the majority of informed traders trade in the exchange hence adding a dark pool enhances price discovery, whereas when information precision is low (information risk is high), the majority of the informed traders trade in the dark pool hence adding a dark pool impairs price discovery. The paper reconciles the conflicting empirical evidence and produces novel empirical predictions. The paper also provides regulatory suggestions with dark pools on current equity markets and in emerging markets.
... This in turn makes cryptocurrency markets topical to reconsider a specific class of models, identifying informed trading. A popular approach is PIN measure, proposed by Easley, Kiefer, O'Hara, and Paperman (1996), which uses Glosten and Milgrom (1985) setting to estimate the probability of informed trading. There was a debate whether PIN is a measure of liquidity rather than of informed trading activity as well as its critics that it mathematically fails to explain empirical positive correlation between buy and sell trades. ...
... Easley et al. (1996) proposed one of the most popular metrics -Probability of Informed Trading (PIN) which captures the posterior probability of informed trading. PIN model is based on the Glosten and Milgrom (1985) framework and uses the observed order imbalance to identify information asymmetry. By order imbalance in this case we understand the difference between buyer and seller initiated trades. ...
... Managers may manipulate earnings to send personal information and, as a result, improve the earnings' informational value, which would be helpful to different market participants (Jiraporn et al., 2008). Moreover, information mechanisms decrease the spread of bid-ask and enhance SL (Glosten & Milgrom, 1985). Finally, management aims to provide suitable information to shareholders about performance and projected earnings, which improves the informativeness of SL (Lev, 1988). ...
... Variations influence the return volatility of commodity futures in supply and demand, which can be affected by factors such as order imbalances, liquidity transactions, international trade policies, the dissemination of various types of information, and weather conditions. Existing literature on the relationships between return volatility and information primarily focus on the stock market, suggesting that factors like the rate of information flow, private information, investor sentiment, and the irrationality of noise traders are related to return volatility (Glosten and Milgrom 1985;Grossman and Stiglitz 1980;Kyle 1985;McGroarty et al. 2009;Ross 1989;Wang et al. 2006;Zhang et al. 2016). In particular, information flow displays in a clustered fashion as return volatility (Berger et al. 2009); therefore, the impact of the rate of information flow is widely accepted as an underlying mechanism for the formation of asset prices and trading volumes (Bergemann et al. 2015;Shen et al. 2018). ...
This study uses Baidu News data and introduces a novel proxy for the rate of information flow to examine its relationship with return volatility in Chinese commodity futures and to test two competing hypotheses. We examine the contemporaneous relationships using correlation coefficient analysis, and find apparent differences between the information flow-return volatility relationship and the information flow-trading volume relationship. The empirical evidence contradicts the mixture of distribution hypothesis (MDH) and suggests that the rate of information flow distinctly affects trading volume and volatility. We conducted linear and nonlinear Granger causality tests to explore the sequential information arrival hypothesis (SIAH). The empirical results prove that a lead-lag linear and nonlinear causality exists between the information flow and return volatility of commodity futures, which is consistent with SIAH. In other words, a partial equilibrium exists before reaching the ultimate equilibrium when the new information arrives in the market. Finally, these findings are robust to alternative measurement of return volatility and subperiod analysis. Our findings reject the MDH and support the SIAH in the context of Chinese commodity futures.
... These metrics (Equation (2)) can be aligned with theories of price formation. Traditional price theories view the price as the balance of an asset's supply and demand [25,26]. Naturally, transaction volume is influenced by the price [27]. ...
This study examines a cross-correlation analysis of companies included in the S&P 500 Index at three different intervals: before, during, and after the pandemic’s onset. The aim is to evaluate how the pandemic and related governmental actions have affected market structures and economic conditions. This paper introduces the notion of momentum time series, integrating return and volume data. We show that these momentum time series provide unique insights that differ from return time series, suggesting their potential utility in economic analysis. Our analysis employs the Manhattan and Mantegna distances to construct a threshold-based network, which we subsequently scrutinize. Lastly, we evaluate how the pandemic has influenced these outcomes.
... There is correlation between many of the above features; for example, it is well-known that there is positive correlation between the bid-ask spread and any of the measures of volatility we consider; see for example, Grossman and Miller (1988), Glosten and Milgrom (1985), O'Hara (1998). For each share in our study, we use the first 4 weeks of data to fit a principal component analysis (PCA) transformation and project the fifty-three features down to thirty features, see Figure 2. ...
We build statistical models to describe how market participants choose the direction, price, and volume of orders. Our dataset, which spans 16 weeks for four shares traded in Euronext Amsterdam, contains all messages sent to the exchange and includes algorithm identification and member identification. We obtain reliable out-of-sample predictions and report the top features that predict direction, price, and volume of orders sent to the exchange. The coefficients from the fitted models are used to cluster trading behavior and we find that algorithms registered as Liquidity Providers exhibit the widest range of trading behavior among dealing capacities. In particular, for the most liquid share in our study, we identify three types of behavior that we call (i) directional trading, (ii) opportunistic trading, and (iii) market making, and we find that around one-third of Liquidity Providers behave as market markers.
... Traditional finance has long stressed that market makers vary their bid-ask spreads to compensate for adverse selection and inventory risk. Early works by Kyle (1985) and Glosten and Milgrom (1985) formalize how spreads react to the presence of informed traders, while Easley and O'Hara (1987) shows that rising volatility tends to widen bid-ask spreads. These insights shape modern finance's view that market-making fees should be sensitive to both information asymmetry and price risk. ...
Automated market makers (AMMs) facilitate ∼$1 trillion of transactions yearly, yet their reliance on static fees contrasts with classical microstructure theory, which emphasizes volatility-sensitive spreads in mitigating adverse selection. To assess whether this theory extends to AMMs, we develop a structural model capturing the interconnected decisions of noise traders, arbitrageurs, and liquidity providers. We empirically test this model using transaction-level data from Uniswap, leveraging a two-stage GMM approach to overcome endogeneity between trading and liquidity volumes. We find the optimal AMM fee structure dynamically adjusts to volatility, leading to improved trade. Our results suggest that, despite their microstructure differences, both traditional and decentralized markets can share fundamental design principles.
... Market liquidity is an essential indicator of asset value in the financial market (Amihud, 2002;Easley and O'Hara, 2004;Corwin and Schultz, 2012). Specialists secure trading against the risk of an informed counterparty (Glosten and Milgrom, 1985;Saleemi, 2020), which is often considered a priced factor (Amihud et al., 2015;Saleemi, 2022). Information transparency about the fundamental value of an asset is critical in determining market liquidity (Gorton and Metrick, 2010). ...
Investors are keenly interested in the risk of informed trading, as it can have an immediate impact on transaction costs imposed by liquidity providers. This paper examines microblogging-based informed trading as a systematic risk for liquidity at both market and firm levels. Assets at firm level were categorized into financial and non-financial perspective. In this context, the study constructed a bank index and non-financial firms (NFF) index within the broader market. In a relative market, the liquidity was priced pessimistically and a higher probability for appearance of spread was noted during pessimism environments. The bank index liquidity was significantly responsive towards systematic bearish and bullish sentiments. In addition, the posterior probability of systematic sentiment risk was considerably higher for bank assets’ liquidity. The NFF index liquidity was not exposed to the systematic bearish and bullish sentiments. Meantime, the posterior probability of systematic sentiment risk was considerably lower for non-financial assets’ liquidity. The relative market’s liquidity was not influenced by changes in past series of bearish and bullish sentiments. Similarly, the sentiments’ lags were not strong enough to impact the firm index liquidity in the short or long run.
... This problem arises from information asymmetries between market participants and AMMs: market participants, who are better informed about external token prices, exploit stale AMM prices and thus buy underpriced (or sell overpriced) tokens from (or to) an AMM. Although this updates AMM prices, it also incurs financial losses for AMMs and their LPs [17,26,29]. ...
To trade tokens in cryptoeconomic systems, automated market makers (AMMs) typically rely on liquidity providers (LPs) that deposit tokens in exchange for rewards. To profit from such rewards, LPs must use effective liquidity provisioning strategies. However, LPs lack guidance for developing such strategies, which often leads them to financial losses. We developed a measurement model based on impermanent loss to analyze the influences of key parameters (i.e., liquidity pool type, position duration, position range size, and position size) of liquidity provisioning strategies on LPs' returns. To reveal the influences of those key parameters on LPs' profits, we used the measurement model to analyze 700 days of historical liquidity provision data of Uniswap v3. By uncovering the influences of key parameters of liquidity provisioning strategies on profitability, this work supports LPs in developing more profitable strategies.
... Secondly, it offers companies the chance to obtain the equity capital they need from different areas [1]. It has also been found that the bid-ask spread is lower for dual-listed stocks, given that dual-listed stocks have more trading demand and are part of the portfolios of a larger portfolio manager base compared to local stocks [10,[16][17][18][19]. Due to such positive values, in recent years, developed and emerging financial markets have witnessed an increasing trend towards dual-listed and traded stocks [20]. ...
Companies are looking for ways to access capital from developed markets instead of local markets to find financing. While some companies use debt instruments for this purpose, others use equity financing methods. One of the techniques used in equity financing is the simultaneous registration of shares on national and foreign stock exchanges, also known as the dual-registration method. Investors entering international markets by investing in dual-registered shares is important for companies to gain capital. However, another important issue for those investing in stocks is the ability to gain capital through accurate prediction of price movements. The aim of this study is to predict the prices of Turkcell stocks traded on Borsa Istanbul and the New York Stock Exchange (NYSE) using machine learning and deep learning methodologies. The results of the analyses conducted with the Random Forest Regressor and Long Short-Term Memory algorithms, which are machine learning and deep learning algorithms, respectively, showed that both algorithms exhibited a lower error rate in predicting the closing prices of Turkcell stocks on the NYSE.
... According to the studies of Pourhosseini, Sharifi Renani, and Karimzadeh (2022), one of the risk factors of financial assets is the liquidity of these assets, and the investigation of factors affecting the liquidity of these assets can help people predict the risk of financial assets.\ According to Easley and O'Hara (1992) and the studies of Glosten and Milgrom (1985), a market with high liquidity has little or zero transaction costs, and transactions are executed with great ease. ...
... (Saleem and Usman, 2021) كما، . (Bertrand and Schoar, 2003;Hackbarth, 2008;Ferris et al., 2017 (Bonsall et al., 2017;Cornaggia et al., 2017 (Lambert et al., 2007;Richardson et al., 2021;Rjiba et Hermalin and Weisbach, 1998;Bebchuk et al., 2002;Bebchuk and Fried, 2004;Kalyta and Magnan, 2008;Francis et al., 2008 Baik et al., 2018;Petkevich and Prevost, 2018;García-Meca and García-Sánchez, 2018;Huang and Sun, 2017;Choi et al., 2015;Demerjian et al., 2013 Glosten and Milgrom, 1985;Callahan et al., 1997;Habib, 2005 ...
... Information asymmetry referred a situation where one party has more information than the other. Lack of information asymmetry among capital market traders is considered a key mechanism for decreased cost of capital and increased market efficiency (Milgrom and Glosten, 1985;Lang and Lundholm, 1996;Welker, 1995). According to theoretic analyses and empirical evidences, increased information asymmetry or imbalance is related to the decreased number of traders, high costs of transactions, low liquidity of securities, and low trading turnover. ...
This research investigated the effect of capital gains and stock liquidity on stock expected return. The stock expected return is measured based on capital assets pricing model. Stock liquidity is measured by stock trading turn over and capital gain is measured by the return made through the changes in stock prices. In order to control other factors that may have an effect on stock expected return, some variables like market to book ratio, size, dividend payout ratio, leverage and profitability have been studied. Research hypotheses tested using regression model based on pooled data. Research sample includes 172 companies listed in Tehran Stock Exchange over the period 2010-2014. Results showed that there is not any significant relationship between capital gains and stock expected return. But the results found that stock liquidity has a significant and positive effect on stock expected return. In fact, stock expected return is a direct function of changes in stock liquidity.
... Theory suggests that, prior to a scheduled disclosure (e.g., an earnings announcement or an annual report release), investors have incentives to gather private information and profit from trading on that information. Traditional asymmetric information models (e.g., Glosten and Milgrom 1985) consider two classes of traders: informed traders and uninformed liquidity traders. Informed traders either are endowed with private information or have incentives to acquire private information about an anticipated disclosure event, making uninformed investors reluctant to trade. ...
How important is equal access to mandatory disclosures? We exploit the postal strike of 1970 that caused a delay in the delivery of annual reports via mail. This strike created unequal access because certain investors (e.g., institutions) had both the incentives and ability to obtain the annual reports by other means. Theory predicts that, when differential access exists, adverse selection problems intensify, causing a decline in stock trading. Our findings support this prediction: stock trading volume decreased by approximately 28% for firms unable to deliver the annual reports to shareholders during the strike, and this trading decline gradually dissipated afterward. Further tests confirm adverse selection as the primary mechanism. Overall, our paper underscores the importance of equal access to annual reports—a key mandated disclosure—and demonstrates the value of these reports to shareholders, as evidenced by their reluctance to trade absent this information.
... In tandem, the development of econometric tools to study the dynamic properties of high-frequency data has become an important subject area in economics and statistics. A major challenge is provided by the accumulation of market microstructure noise at higher frequencies, which can be attributed to various market microstructure effects including, for example, information asymmetries (see Glosten and Milgrom (1985)), inventory controls (see Ho and Stoll (1981)), discreteness of the data (see Harris (1990)), and transaction costs (see Garman (1976)). ...
In this paper, we develop econometric tools to analyze the integrated volatility of the efficient price and the dynamic properties of microstructure noise in high-frequency data under general dependent noise. We first develop consistent estimators of the variance and autocovariances of noise using a variant of realized volatility. Next, we employ these estimators to adapt the pre-averaging method and derive a consistent estimator of the integrated volatility, which converges stably to a mixed Gaussian distribution at the optimal rate . To refine the finite sample performance, we propose a two-step approach that corrects the finite sample bias, which turns out to be crucial in applications. Our extensive simulation studies demonstrate the excellent performance of our two-step estimators. In an empirical study, we characterize the dependence structures of microstructure noise in several popular sampling schemes and provide intuitive economic interpretations; we also illustrate the importance of accounting for both the serial dependence in noise and the finite sample bias when estimating integrated volatility.
... A common assumption in the literature is that Ψ is linear in Σ 0 , Σ 1 (see [2,26,37], as well as the more recent [38,49]). In other words, agents securitize their risky positions, and through trading achieve a mutually beneficial risk reduction. ...
This paper studies the optimal investment problem with random endowment in an inventory-based price impact model with competitive market makers. Our goal is to analyze how price impact affects optimal policies, as well as both pricing rules and demand schedules for contingent claims. For exponential market makers preferences, we establish two effects due to price impact: constrained trading, and non-linear hedging costs. To the former, wealth processes in the impact model are identified with those in a model without impact, but with constrained trading, where the (random) constraint set is generically neither closed nor convex. Regarding hedging, non-linear hedging costs motivate the study of arbitrage free prices for the claim. We provide three such notions, which coincide in the frictionless case, but which dramatically differ in the presence of price impact. Additionally, we show arbitrage opportunities, should they arise from claim prices, can be exploited only for limited position sizes, and may be ignored if outweighed by hedging considerations. We also show that arbitrage inducing prices may arise endogenously in equilibrium, and that equilibrium positions are inversely proportional to the market makers' representative risk aversion. Therefore, large positions endogenously arise in the limit of either market maker risk neutrality, or a large number of market makers.
... The followings are proposed as the cause of market microstructure: bid-ask spread (Roll [44]), discretization error (Gottlieb and Kalay [18]), and asymmetric information (Glosten and Milgrom [17]). On the other hand, the relationship between the additive noise modeling and the market microstructure is not so clearly explained. ...
Kimura and Yoshida treated a model in which the finite variation part of a two-dimensional semimartingale is expressed by time-integration of latent processes. They proposed a correlation estimator between the latent processes and proved its consistency and asymptotic mixed normality. In this paper, we discuss the confidence interval of the correlation estimator to detect the correlation. %between latent processes. We propose two types of estimators for asymptotic variance of the correlation estimator and prove their consistency in a high frequency setting. Our model includes doubly stochastic Poisson processes whose intensity processes are correlated It\^o processes. We compare our estimators based on the simulation of the doubly stochastic Poisson processes.
... The market microstructure theory studies how the latent demand and latent supply of market participants are ultimately translated into prices by studying the specific market structure in detail. The cornerstone papers include Glosten and Milgrom [1985], Kyle [1985], both of them are using (pesudo) 1 game-theoretical argument in information economics. More comprehensive books include O'Hara [1995], Hasbrouck [2007]. ...
In this paper, we provide non-parametric statistical tools to test stationarity of microstructure noise in general hidden Ito semimartingales, and discuss how to measure liquidity risk using high frequency financial data. In particular, we investigate the impact of non-stationary microstructure noise on some volatility estimators, and design three complementary tests by exploiting edge effects, information aggregation of local estimates and high-frequency asymptotic approximation. The asymptotic distributions of these tests are available under both stationary and non-stationary assumptions, thereby enable us to conservatively control type-I errors and meanwhile ensure the proposed tests enjoy the asymptotically optimal statistical power. Besides it also enables us to empirically measure aggregate liquidity risks by these test statistics. As byproducts, functional dependence and endogenous microstructure noise are briefly discussed. Simulation with a realistic configuration corroborates our theoretical results, and our empirical study indicates the prevalence of non-stationary microstructure noise in New York Stock Exchange.
... There have been many attempts to model the continuous double auction using equilibrium theory. One famous example is the Glosten model [78], which predicts the expected equilibrium distribution of orders under a single period model. Tests of this model show that it does not match reality very well [141]. ...
The use of equilibrium models in economics springs from the desire for parsimonious models of economic phenomena that take human reasoning into account. This approach has been the cornerstone of modern economic theory. We explain why this is so, extolling the virtues of equilibrium theory; then we present a critique and describe why this approach is inherently limited, and why economics needs to move in new directions if it is to continue to make progress. We stress that this shouldn't be a question of dogma, but should be resolved empirically. There are situations where equilibrium models provide useful predictions and there are situations where they can never provide useful predictions. There are also many situations where the jury is still out, i.e., where so far they fail to provide a good description of the world, but where proper extensions might change this. Our goal is to convince the skeptics that equilibrium models can be useful, but also to make traditional economists more aware of the limitations of equilibrium models. We sketch some alternative approaches and discuss why they should play an important role in future research in economics.
Prior literature documents a temporary spike in information asymmetry between sophisticated and unsophisticated traders around corporate disclosures because the former process new information faster. Using advances in textual analysis, we show that when management issues more uncertain financial statements, the resulting spike in information asymmetry is significantly lower than for firms that use less uncertain text. Furthermore, textual uncertainty measures of the disclosures are negatively associated with Intermarket Sweep Order (ISO) volume, an order type commonly used by sophisticated traders. This suggests sophisticated traders and algorithms are less able to extract value‐relevant information from financial disclosures when they are uncertain.
This study investigates the effects of institutional investor cliques on stock price efficiency. Using a community network algorithm, it identifies cliques of institutional investors and finds that they significantly undermined stock price efficiency in China. The robustness of this finding is demonstrated through a range of methodologies, including the substitution of dependent variables, the alteration of estimation methods, the exclusion of data from extreme market periods, and the application of instrumental variables. The role of institutional investor cliques in diminishing market efficiency is attributed to market speculation. The detrimental effect of cliques on efficiency is exacerbated in environments characterized by low stock liquidity, poor information disclosure, and heightened panic among retail investors. However, regulatory interventions, such as inquiry letters, are shown to mitigate these effects and enhance market efficiency. These findings highlight the unexpected ways institutional investor cliques can influence emerging market economies and underscore the critical importance of effective regulation to safeguard market efficiency.
The aggregate leverage of broker‐dealers responds to demand and supply disturbances that have opposite effects on financial markets. Specifically, leverage supply shocks that relax broker‐dealers' funding constraints increase leverage, liquidity, and returns and carry a positive price of risk, while leverage demand shocks also increase leverage but reduce liquidity and returns and carry a negative price of risk. Disentangling demand‐ and supply‐like shocks resolves existing puzzles around the price of leverage risk and yields consistent evidence across many markets of a central role for intermediation frictions and dealers' aggregate leverage in asset pricing.
This study investigates the impact of common institutional ownership on commonality in liquidity. We find that common institutional ownership reduces commonality in liquidity through synergistic governance, which is driven by the economy of scale and externality of common ownership. However, the negative relationship is weakened by exit threats of common ownership, emphasising the important role of active investor monitoring. We show that information transparency is the primary channel through which common institutional ownership reduces liquidity commonality. Moreover, the impacts are more pronounced for large‐cap stocks, and firms with high institutional ownership stability and high stock pricing efficiency.
This study uses a difference-in-differences approach to examine the influence of market-maker agreements on liquidity alterations in Boursa Kuwait. Our research indicates that signing a market-maker agreement augments the number of executed trades, turnover, and trading volume while decreasing instances of zero trades, bid–ask spread, and Amihud Illiquidity within the first week. Interestingly, these agreements do not affect stock return volatility.
Our study extends the knowledge about the role of market makers in emerging markets.
JEL Codes: G10, G18, O53
We propose a series of simple models for the microstructure of a double auction market without intermediaries. We specialize to those markets, such interdealer broker markets, which are dominated by professional traders, who trade mainly through limit orders, watch markets closely, and move their limit order prices frequently. We model these markets as a set of buyers and a set of sellers diffusing in price space and interacting through an annihilation interaction. We seek to compute the purely statistical effects of the presence of large numbers of traders, as scaling laws on various measures of liquidity, and to this end we allow our model very few parameters. We find that the bid-offer spread scales as .In addition we investigate the scaling of other intuitive relationships, such as the relation between fluctuations of the best bid/offer and the density of buyers/sellers. We then study this model and its scaling laws under the influence of random disturbances to trader drift, trader volatility, and entrance rate. We also study possible extensions to the model, such as the addition of market order traders, and an interaction that models momentum-type trading. Finally, we discuss how detailed simulations may be carried out to study scaling in all of these settings, and how the models may be tested inactual markets.
This study examines, month-by-month, the empirical relation between abnormal returns and market value of NYSE and AMEX common stocks. Evidence is provided that daily abnormal return distributions in January have large means relative to the remaining eleven months, and that the relation between abnormal returns and size is always negative and more pronounced in January than in any other month — even in years when, on average, large firms earn larger risk-adjusted returns than small firms. In particular, nearly fifty percent of the average magnitude of the ‘size effect’ over the period 1963–1979 is due to January abnormal returns. Further, more than fifty percent of the January premium is attributable to large abnormal returns during the first week of trading in the year, particularly on the first trading day.
This study considers the problem of a price-setting monopolistic market-maker in a dealership market where the stochastic demand and supply are depicted by price-dependent Poisson processes [following Garman (1976)]. The crux of the analysis is the dependence of the bid-ask prices on the market-maker's stock inventory position. We derive the optimal policy and its characteristics and compare it to Garman's. The results are shown to be consistent with some conjectures and observed phenomena, like the existence of a ‘preferred’ inventory position and the downward monotonicity of the bid-ask prices. For linear demand and supply functions we derive the behavior of the bid-ask spread and show that the transaction-to-transaction price behavior is intertemporally dependent. However, we prove that it is impossible to make a profit on this price dependence by trading against the market-maker. Thus, in this situation, serially dependent price-changes are consistent with the market efficiency hypothesis.
This paper relates quality and uncertainty. The existence of goods of many grades poses interesting and important problems for the theory of markets. On the one hand, the interaction of quality differences and uncertainty may explain important institutions of the labor market. On the other hand, this paper presents a struggling attempt to give structure to the statement: “Business in under-developed countries is difficult”; in particular, a structure is given for determining the economic costs of dishonesty. Additional applications of the theory include comments on the structure of money markets, on the notion of “insurability,” on the liquidity of durables, and on brand-name goods.
This paper reexamines the anomalous evidence concerning the efficiency of the listed options exchanges. We focus on the structure of trading costs in that market, and note several costs which generally have been ignored, the largest of which is the bid-ask spread. When we adjust the published trading rules for our estimates of these trading costs, the reported abnormal returns are eliminated.
It is assumed that a collection of market agents can be treated as a statistical ensemble. Their market activities are depicted as the stochastic generation of market orders according to a Poisson process. The objective is to effectively describe the ‘temporal microstructure’, or moment-to-moment trading activities in asset markets. Two basic models, ‘dealership’ vs. ‘auction’ markets (and their variants) are put forth. Implications are drawn from each model. The implications include several testable hypotheses regarding the aggregate behavior of markets and market-makers as well as some qualitative insight into the transaction-to-transaction nature of realistic exchange processes.
In any voluntary trading process, if agents have rational expectations, then it is common knowledge among them that the equilibrium trade is feasible and individually rational. This condition is used to show that when risk-averse traders begin at a Pareto optimal allocation (relative to their prior beliefs) and then receive private information (which disturbs the marginal conditions), they can still never agree to any non-null trade. On markets, information is revealed by price changes. An equilibrium with fully revealing price changes always exists, and even at other equilibria the information revealed by price changes “swamps” each trader's private information.
Research on this project was supported by a grant from the National Science Foundation. I am indebted to Arthur Laffer, Robert Aliber, Ray Ball, Michael Jensen, James Lorie, Merton Miller, Charles Nelson, Richard Roll, William Taylor, and Ross Watts for their helpful comments.
I. Introduction, 488. — II. The model with automobiles as an example, 489. — III. Examples and applications, 492. — IV. Counteracting
institutions, 499. — V. Conclusion, 500.
Previous estimates of a 'size effect' based on daily returns data are biased. The use of quoted closing prices in computing returns on individual stocks imparts an upward bias. Returns computed for buy-and-hold portfolios largely avoid the bias induced by closing prices. Based on such buy-and-hold returns, the full-year size effect is half as large as previously reported, and all of the full-year effect is, on average, due to the month of January.
Recent empirical work by Banz (1981) and Reinganum (1981) documents abnormally large risk-adjusted returns for small firms listed on the NYSE and the AMEX. The strength and persistence with which the returns appear lead both authors to conclude the single-period, two-parameter capital asset pricing model is misspecified. This study (1) confirms that total market value of common stock equity varies inversely with risk-adjusted returns, (2) demonstrates that price per share does also, and (3) finds that transaction costs at least partially account for the abnormality.
The paper examines the optimal behavior of a single dealer who is faced with a stochastic demand to trade (modeled by a continuous time Poisson jump process) and facing return risk on his stock and on the rest of his portfolio (modeled by diffusion processes). Using stochastic dynamic programming, we derive the optimal bid and ask prices that maximize the dealer's expected utility of terminal wealth as a function of the state in which he finds himself. The relationship of the bid and ask prices to inventory of the dealer, instantaneous variance of return, stochastic arrival of transactions and other variables is examined.
This study examines the empirical relationship between the return and the total market value of NYSE common stocks. It is found that smaller firms have had higher risk adjusted returns, on average, than larger firms. This ‘size effect’ has been in existence for at least forty years and is evidence that the capital asset pricing model is misspecified. The size effect is not linear in the market value; the main effect occurs for very small firms while there is little difference in return between average sized and large firms. It is not known whether size per se is responsible for the effect or whether size is just a proxy for one or more true unknown factors correlated with size.
In an efficient market, the fundamental value of a security fluctuates randomly. However, trading costs induce negative serial dependence in successive observed market price changes. In fact, given market efficiency, the effective bid-ask spread can be measured by Spread- 2 J where "cov" is the first-order serial covariance of price changes. This implicit measure of the bid-ask spread is derived formally and is shown empirically to be closely related to firm size. FINANCIAL SCHOLARS AND PRACTITIONERS are interested in transaction costs for obvious reasons: the net gains to investments are affected by such costs and market equilibrium returns are likely to be influenced by cross-sectional differ- ences in costs. For the practical investor, the measurement of trading costs is painful but direct. (They appear on his monthly statement of account.) For the empirical researcher, trading cost measurement can itself be costly and subject to consid- erable error. For example, brokerage commissions are negotiated and thus depend on a number of hard-to-quantify factors such as the size of transaction, the amount of business done by that investor, and the time of day or year. The other blade of trading costs, the bid-ask spread, is perhaps even more fraught with measurement problems. The quoted spread is published for a few markets but the actual trading is done mostly within the quotes. This paper presents a method for inferring the effective bid-ask spread directly from a time series of market prices. The method requires no data other than the prices themselves; so it is very cheap. It does, however, require two major assumptions:
An individual who chooses to serve as a market‐maker is assumed to optimize his position by setting a bid‐ask spread which maximizes the difference between expected revenues received from liquidity‐motivated traders and expected losses to information‐motivated traders. By characterizing the cost of supplying quotes, as writing a put and a call option to an information‐motivated trader, it is shown that the bid‐ask spread is a positive function of the price level and return variance, a negative function of measures of market activity, depth, and continuity, and negatively correlated with the degree of competition. Thus, the theory of information effects on the bid‐ask spread proposed in this paper is consistent with the empirical literature.
The market for 'lemons', qualitative uncertainty and the market mechanism Bid-ask spreudF wth heterogeneous expectutions Ho, Thomas and Hans R. Stall, 1981, Optimal dealer pricing under transactions and return uncertainty
- G A L R Akerlof
- P R Glosten
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Akerlof, G.A., 1970, The market for 'lemons', qualitative uncertainty and the market mechanism, L.R. Glosten and P.R. Mdgrom, Bid-ask spreudF wth heterogeneous expectutions Ho, Thomas and Hans R. Stall, 1981, Optimal dealer pricing under transactions and return uncertainty, Journal of Financial Economics 9, 47-73.
Microeconomics of market making, Working paper (Graduate School of Business
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Ohara, Maureen and George Oldfield, 1982, Microeconomics of market making, Working paper (Graduate School of Business, Cornell University, Ithaca, NY).
Neglected firm effect and the inadequacy of the capital asset pricing model
- Avner Arbel
- Paul Strebel
Arbel, Avner and Paul Strebel. 1981, Neglected firm effect and the inadequacy of the capital asset
pricing model, Unpublished
working paper no. 81-08 (State University
of New York at
Binghamton,
Binghamton,
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- Yakov Amihud
- Haim Mendelson
Amihud, Yakov and Haim Mendelson. 1980, Dealership market, JoumaI of Financial Economics
8, 31-53.
Trading costs for listed options: The implications for market efficiency
- Phillips
A simple measure of the effective bid/ask spread in an efficient market
- Roll