Order Imbalance Research Articles

The Cross-Section of Non-Professional Analyst Skill

We examine the cross-section of skill among non-professional analysts (NPAs) on Seeking Alpha, a prominent crowd-sourced investment research platform. We estimate that 60% of NPAs are skilled, and we document substantial dispersion in skill. Even after accounting for bid-ask spreads and allowing for a three-day investment delay, following NPAs in the top quintile of past skill earns annualized abnormal returns of 10%. In contrast, an unconditional strategy that follows all NPAs earns insignificant returns. An examination of retail and institutional order imbalances following NPA recommendations suggests that neither group recognizes the size-able differences in ability across NPAs.

Investor participation and the volatility-volume relation: Evidence from an emerging market

Using a unique dataset from the Chinese stock market that keeps track of the daily number of shareholders, we find that the ownership breadth (proxied by the number of shareholders) is negatively related to stock price volatility. However, consistent with the previous literature on volatility-volume relation, we find that the stock price volatility remains positively related to number of traders participating in the market. We also find that the relations of both the daily order imbalance and the daily depth imbalance with the number of shareholders (traders) are negative (positive). Our results suggest that a higher number of shareholders tend to supply liquidity and reduce volatility, while a higher number of traders tend to compete for liquidity and increase volatility.

A systematic analysis of vascular paroxysm pathophysiology in perimenopause: methods for nutritional correction

Materials and Methods. A systematic analysis of publications retrieved from PubMed/MEDLINE database as well as in the list of primary sources of the identified scientific papers was carried out by using current methods for large data analysis within the framework of topological and metric approaches applied for data recognition/classification. A map of molecular-pathophysiological processes was compiled followed by performing analysis of metric condensations.Results. Three clusters of terms describing an impact of various biological processes into the pathophysiology of hot flushes were identified: inflammation combined with insulin resistance (cluster 1), the presence of chronic comorbid pathologies in patients (cluster 2), and disorders of serotonin metabolism (cluster 3). The use of menopausal hormone therapy (MHT) is not accepted for all patients. A promising direction in treatment of mild and moderate hot flushes is based on using nutraceuticals: vitamins, trace elements and substances obtained from plant extracts (isoflavones, phytoestrogens, etc.). Here, this set of interactions between pathophysiology of hot flushes and deficiency of certain micronutrients, inflammation, insulin resistance, chronic comorbid pathologies and disorders of serotonin metabolism is described. Replenished deficiency of vitamins C, E, A, B2, PP, B6, B12, and folates aids to reduce chronic inflammation, insulin resistance and normalize functioning of the autonomic nervous system. Natural and synthetic agonists of GABA receptors and tryptophan derivatives are necessary for serotonin biosynthesis and elimination of other neurotransmitter imbalances in order to normalize activity of the hypothalamic thermoregulatory region.Conclusion. Plant isoflavones (including phytoestrogens) together with vitamins and other micronutrients help to overcome estrogen-dependent withdrawal symptoms and eliminate dysfunction of autonomic nervous system

How Smart is Instiutional Trading?

We estimate daily aggregate order flow of individual stocks from institutional investors as well as for hedge funds and other institutions separately. We find that the estimated institutional order imbalance positively predicts stock return on the next day and outperforms other institutional order flow estimates. The institutional order flow from hedge funds generates greater and more persistent price impact than the order flow from other institutions. We also find that hedge funds trade on well-known anomalies while the other institutions do not. Our findings suggest that the superior trading skills of institutional investors can be largely attributed to hedge funds.

Forecasting stock returns using first half an hour order imbalance

AbstractWe explore the predictive power of the first half‐hour order imbalance (FOIB) to stock returns in Chinese stock market. Our results show that FOIB predicts returns better than daily order imbalance both in‐sample and out‐of‐sample. The predictive power of FOIB is both statistically and economically significant. Moreover, we provide evidence that the predictive power of FOIB appears stemming from large trade size.

A New Metric of Market Underreaction to Earnings Announcements: An Empirical Test*

AbstractThis paper provides empirical evidence that the squared correlation coefficient between order imbalance and earnings surprise (COE) measures market underreaction and predicts the post‐earnings announcement drift. We find strong evidence that COE during the announcement period predicts price movements (returns) during the post‐announcement period in the expected direction. We find qualitatively similar results using risk‐adjusted returns (i.e., Fama‐French, Carhart, and Pastor‐Stambaugh factor alphas), suggesting that well‐known risk factors do not explain the profitability of trading strategy based on COE.

Order imbalance and stock returns: New evidence from the Chinese stock market

AbstractWe examine the relation between daily order imbalance and stock returns in the Chinese stock market. We show that lagged order imbalance significantly and negatively predicts future stock returns. In addition, the predictive relation is robust for size and turnover subsamples, but stronger for small stocks and stocks with high turnover. Finally, we show that a dynamic trading strategy based on lagged order imbalance generates positive returns with a Sharpe ratio much higher than those of passive strategies. Our results shed new light on the role of inventory effects in stock price movements in an order‐driven market.

Market sentiment, marketable transactions, and returns

Using unique data from the Taiwanese stock market, I explore the transaction aggressiveness of mutual funds, foreign institutions, dealers and retail investors during periods of different market sentiment. Retail investors’ marketable transaction ratios are positively related to stocks’ systematic risk. In contrast, mutual funds and foreign institutions’ marketable transaction ratios are negatively related. Although the marketable transaction ratios of all the four types of investors are higher when market sentiment is more fearful, mutual funds’ trades on the sell side can mitigate the marketable transaction ratios during market panics. Marketable transaction ratios of the four types of investors have significant impacts on stock prices, both directly and indirectly through the influence on order imbalances.

Order imbalance beta and stock returns

ABSTRACT This paper studies the impact of order imbalance beta on cross-sectional stock returns in the Chinese stock market. We measure the daily order imbalance beta, which is defined as the sensitivity of stock returns to changes in stock order imbalance, and show at the individual stock level that stocks with higher order imbalance betas contemporaneously have higher average returns. Furthermore, we find that higher order imbalance beta stocks tend to be smaller, and have lower trading volumes, lower prices and lower turnover rates. Moreover, we find that the long-horizon (1-, 3-, 6- and 12-month) effect of order imbalance beta on stock returns is consistent with the previous daily effect. Finally, we prove that the positive relationship between order imbalance beta and stock returns is robust in different stock markets in China and when using different minimum day limits (30, 45 and 60 days) to estimate order imbalance beta.

Time-varying demand for lottery: Speculation ahead of earnings announcements

Investor preferences for holding speculative assets are likely to be more pronounced ahead of firms’ earnings announcements, probably because of lower inventory costs and immediate payoffs or because of enhanced investor attention. We show that the demand for lottery-like stocks is stronger ahead of earnings announcements, leading to a price run-up for these stocks. In sharp contrast to the standard underperformance of lottery-like stocks, lottery-like stocks outperform non-lottery stocks by about 52 basis points in the 5-day window ahead of earnings announcements. However, this return spread is reversed by 80 basis points in the 5-day window after the announcements. Moreover, this inverted-V-shaped pattern on cumulative return spreads is more pronounced among firms with a greater retail order imbalance, among firms with low institutional ownership, and in regions with a stronger gambling propensity, and it is also robust after controlling for past 12-month returns and various proxies for investor attention.

Trading performance and market efficiency: Evidence from algorithmic trading

In India, National Stock Exchange directly identifies algorithmic trading participation. Algorithmic traders possess intraday market timing skills. Results are not motivated by extreme short-term signals or transitory price trading. Magnitude of market timing performance in cross-sectional group of traders shows that they earn profit across all the cases, and maximize while providing liquidity. Volume-weighted-average-price decomposition analysis reports algorithmic traders earn profits through intraday market timing performance for five-minute and one-minute intervals, and it is higher compared to short-term market timing performance across all trader groups. Order imbalance and price delay regressions show that algorithmic trading significantly improves price efficiency.

Algorithmic trading in turbulent markets

Does Algorithmic Trading (AT) exacerbate price swings in turbulent markets? We find that stocks with high AT experience less price drops (surges) on days when the market declines (increases) for more than 2%. This result is consistent with the view that AT minimizes price pressures and mitigates transitory pricing errors. Further analyses show that the net imbalances of AT liquidity demand and supply orders have smaller price impacts compared to non-AT net order imbalances and algorithmic traders reduce their price pressure by executing their trades based on the prevailing volume-weighted average prices.

Germany After the Social Democratic Century: The Political Economy of Imbalance

The end of the social democratic century has marked the beginning of a new era of political and economic imbalance in Europe. These dynamics are visible even in Germany, despite its reputation for stability. This article proposes reorienting the paradigm for research on Germany’s political economy from stability to imbalance in order to help illuminate central causal processes within the country and across the rich democracies. As our review of prominent approaches to the German Model reveals, recent developments have unseated the mechanisms that once balanced competing social forces. Putting contemporary tensions centre stage, we outline three vantage points from which to study political and economic imbalance: the systemic properties of capitalism, multivalent policy feedback, and the organisational foundations of creative adjustment. This conceptual reorientation should equip scholars to use Germany not merely for theorising the roots of stability in the past, but also to employ it as a powerful prism to explain the dynamics of imbalance in the current era.

ETFs’ high overnight returns: The early liquidity provider gets the worm

I examine the extent to which exchange-traded funds’ (ETFs) unusually high overnight returns are distorted by market microstructure effects; specifically, positive order imbalances and overnight increases in bid-ask spreads. Introducing a model that isolates these effects, I show that they artificially increase ETFs’ overnight returns by an average of over 6% annually. I find that the ETF market is prone to these distortions because its rapid growth is accompanied by order imbalances exceeding 10%. I provide detailed intraday statistics on order imbalances and spreads, and an example of an overnight investment strategy selecting ETFs susceptible to overnight biases.

Do Proxies for Informed Trading Measure Informed Trading? Evidence from Illegal Insider Trades

AbstractThis paper exploits hand-collected data on illegal insider trades to provide new evidence on the ability of a host of standard measures of illiquidity to detect informed trading. Controlling for unobserved cross-sectional and time-series variation, sampling bias, and strategic timing of insider trades, I find that when information is short-lived, only absolute order imbalance and effective spread are statistically and economically robust predictors of illegal insider trading. However, when information is long-lasting, insiders strategically time their trades to avoid illiquidity, and none of the standard measures considered are reliable predictors, including bid-ask spreads, order imbalance, Kyle’s λ, and Amihud illiquidity. (JEL D53D82G12G14K42)Received: March 14, 2019; Editorial decision: February 18, 2020 by Editor Thierry Foucault. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Breaking of Josephson junction oscillations and onset of quantum turbulence in Bose–Einstein condensates

We analyse the formation and the dynamics of quantum turbulence in a two-dimensional Bose–Einstein condensate with a Josephson junction barrier modeled using the Gross–Pitaevskii equation. We show that a sufficiently high initial superfluid density imbalance leads to randomisation of the dynamics and generation of turbulence, namely, the formation of a quasi-1D dispersive shock consisting of a train of grey solitons that eventually breakup into chains of distinct quantised vortices of alternating vorticity followed by random turbulent flow. The Josephson junction barrier allows us to create two turbulent regimes: acoustic turbulence on one side and vortex turbulence on the other. Throughout the dynamics, a key mechanism for mixing these two regimes is the transmission of vortex dipoles through the barrier: we analyse this scattering process in terms of the barrier parameters, sound emission and vortex annihilation. Finally, we discuss how the vortex turbulence evolves for long times, presenting the optimal configurations for the density imbalance and barrier height in order to create the desired turbulent regimes which last as long as possible.

Investigating the Performance of an Order Imbalance based Trading Strategy in a High-Frequency Trading

One of the most interesting and challenging issues in the field of finance at the moment is high-frequency trading (HFT). This is because HFT is a relatively new issue for most of the financial markets and its activity is becoming more common all over the world. So, the study aim is to investigate the performance of an order imbalance based trading strategy in high-frequency trading. Besides, we used Multivariate GARCH models such as BEKK and DCC GARCH to estimate volatility, return and order imbalance relations. Our dataset includes stocks traded on the Tehran Stock Exchange from April 1, 2014, until March 30, 2016 (1095 trading days). Our dataset includes stocks traded on the Tehran Stock Exchange from April 1, 2014, until March 30, 2016 (1095 trading days). Also, the results of lagged return-order imbalance relations show that the percentage of positively significant lagged order imbalances is 1.00% and the percentage of negatively significant coefficients of lagged order imbalance is only 8.21% at confidence level 95% in 2016. Finally, it concluded that order imbalance is a proper measure for predicting future returns. Indeed, order imbalance could be proper measures for predicting returns in HFT.

Option trading and the cross‐listed stock returns: Evidence from Chinese A–H shares

AbstractWe empirically investigate the effects of option trading on the cross‐listed stock returns. Using dual‐listed stocks in mainland China (A) and Hong Kong (H) stock exchanges, we show that option order imbalance (OI) positively and significantly predicts daily stock returns for both markets, controlling for risk factors and firm characteristics. Informed trading rather than price pressure better explain the predictability. High OI stocks have higher trading volume and present lottery‐like properties. Three important events significantly affect the predictive power of OI, consistent with the improved market quality and the episode of speculative trading. Robustness checks support the main findings.

Leveraging Blockchain Technology for Secure Energy Trading and Least-Cost Evaluation of Decentralized Contributions to Electrification in Sub-Saharan Africa.

The International Energy Agency has projected that the total energy demand for electricity in sub-Saharan Africa (SSA) is expected to rise by an average of 4% per year up to 2040. It implies that ~620 million people are living without electricity in SSA. Going with the 2030 vision of the United Nations that electricity should be accessible to all, it is important that new technology and methods are provided. In comparison to other nations worldwide, smart grid (SG) is an emerging technology in SSA. SG is an information technology-enhanced power grid, which provides a two-way communication network between energy producers and customers. Also, it includes renewable energy, smart meters, and smart devices that help to manage energy demands and reduce energy generation costs. However, SG is facing inherent difficulties, such as energy theft, lack of trust, security, and privacy issues. Therefore, this paper proposes a blockchain-based decentralized energy system (BDES) to accelerate rural and urban electrification by improving service delivery while minimizing the cost of generation and addressing historical antipathy and cybersecurity risk within SSA. Additionally, energy insufficiency and fixed pricing schemes may raise concerns in SG, such as the imbalance of order. The paper also introduces a blockchain-based energy trading system, which includes price negotiation and incentive mechanisms to address the imbalance of order. Moreover, existing models for energy planning do not consider the effect of fill rate (FR) and service level (SL). A blockchain levelized cost of energy (BLCOE) is proposed as the least-cost solution that measures the impact of energy reliability on generation cost using FR and SL. Simulation results are presented to show the performance of the proposed model and the least-cost option varies with relative energy generation cost of centralized, decentralized and BDES infrastructure. Case studies of Burkina Faso, Cote d’Ivoire, Gambia, Liberia, Mali, and Senegal illustrate situations that are more suitable for BDES. For other SSA countries, BDES can cost-effectively service a large population and regions. Additionally, BLCOE reduces energy costs by approximately 95% for battery and 75% for the solar modules. The future BLCOE varies across SSA on an average of about 0.049 $/kWh as compared to 0.15 $/kWh of an existing system in the literature.

Volatility of order imbalance of institutional traders and expected asset returns: Evidence from Taiwan

We use the newly-developed “volatility of order imbalance” of Chordia et al. (2019) to examine the relation between information asymmetry costs and expected returns across various types of institutional traders, taking advantage of a unique account-level transaction dataset on the Taiwan Futures Exchange. Our results show that the measure of foreign institutional traders is positively related to future market returns, regardless of whether weekly or monthly frequencies are examined. Turning to stock transaction data on institutional investors, the information risk of foreign institutional investors generates risk-adjusted monthly return differentials in the cross-section. Finally, vector autoregression analyses show that with an increase in the order imbalance volatility of foreign institutional investors in the index futures market, there is a corresponding increase in subsequent order imbalance volatility in the stock market, thereby providing evidence of a monthly lead-lag relation between the futures market and the spot market.