High Volume Days Research Articles

Artificial intelligence and big data tokens: Where cognition unites, herding patterns take flight

Artificial intelligence (AI) and big data tokens have emerged as unique investment options, garnering interest due to their connectedness with other assets and financial markets. Utilizing Chang et al. (2000)'s cross-sectional absolute deviation (CSAD) model, we investigate static and time-varying herding in the AI and big data token markets. This research contributes to the growing discourse on AI and big data token investment through the lens of behavioral finance, with a particular focus on examining investor herding. The study's findings confirm market-wide herding of AI and big data tokens. The results suggest that investors exhibit herding in up markets, low volatility, and low volume days. Conversely, anti-herding is more prevalent in down markets, high volatility, and high volume days. Our analysis shows that herding is time-varying and emerges during a crisis period. The finding carries robust regulatory and policy implications to mitigate systemic risk and safeguard investor interests, ensuring market stability and resilience. The provided insights offer a valuable understanding of investors’ behavior across various market scenarios.

Corporate bond price reversals

I demonstrate empirically that corporate bond dealers mitigate adverse selection risk by passing potentially informed transactions to institutional investors. I contrast price reversals following days with abnormal trading volume across bonds with different information asymmetry. In informed trading, the part of reversal specific to high-volume days should increase with information asymmetry. In uninformed trading, there is no such effect. Following high-volume days when investors provide liquidity, the reversals are consistent with the former case. When dealers provide liquidity, I observe the latter. The results suggest that the informational content of bond prices is higher when dealers do not take inventory.

The Influence of Full-Time Holistic Support Delivered by a Sports Nutritionist on Within-Day Macronutrient Distribution in New Zealand Provincial Academy Rugby Union Players

Dietary intake is an important consideration for rugby union ('rugby') players to ensure substrate provision for optimal performance and facilitate recovery. Within-day meal distribution is especially important for athletes, particularly those with congested schedules and multiple daily training sessions. In the present study, 10 provincial academy rugby players engaged in a holistic support protocol informed by behaviour-change techniques led by a full-time sports nutritionist. Dietary intake was estimated during a 4-week monitoring and 4-week intervention period using the remote food photography method on one high-volume training day (two training sessions) and two low-volume training days (≤1 training session) per week. Lean body mass did not change significantly in response to the intervention. Significant increases were observed for protein on both low-volume (breakfast, AM snack, evening snack) and high-volume (post-gym, AM snack, evening snack) training days. Carbohydrate intake post-intervention was significantly greater at the pre-gym eating occasion but lower at PM snack and dinner eating occasions on high-volume days. These data suggest that incorporating a holistic support protocol led by a sports nutritionist can influence within-day nutrient intake in rugby players; however, no change to lean body mass was observed, and the influence of these changes in nutrient intake on performance and recovery warrants further investigation.

Last hour momentum in the Chinese stock market

PurposeTo capture the last hour momentum over the intraday session, the authors develop a trading strategy for the exchange-traded fund (ETF) that is effective because of the T+0 trading rule. This strategy generates annualized excess return of 9.673%.Design/methodology/approachIn this study, the authors identify a last hour momentum pattern in which the sixth (seventh) half-hour return predicts the next half-hour return by employing high frequency 2012–2017 data from the China Securities Index (CSI) 300 and its ETF.FindingsOverall, both the predictability and the trading strategy are statistically and economically significant. In addition, the strategy performs more strongly on high volatility days, high trading volume days, high order-imbalance days and days without economic news releases than on other days.Originality/valueNoise trading, late-information trading, infrequent rebalancing and disposition effects from retail investors may account for this phenomenon.

Are Smaller Emergency Departments More Prone to Volume Variability?

IntroductionDaily patient volume in emergency departments (ED) varies considerably between days and sites. Although studies have attempted to define “high-volume” days, no standard definition exists. Furthermore, it is not clear whether the frequency of high-volume days, by any definition, is related to the size of an ED. We aimed to determine the correlation between ED size and the frequency of high-volume days for various volume thresholds, and to develop a measure to identify high-volume days.MethodsWe queried retrospective patient arrival data including 1,682,374 patient visits from 32 EDs in 12 states between July 1, 2018–June 30, 2019 and developed linear regression models to determine the correlation between ED size and volume variability. In addition, we performed a regression analysis and applied the Pearson correlation test to investigate the significance of median daily volumes with respect to the percent of days that crossed four volume thresholds ranging from 5–20% (in 5% increments) greater than each site’s median daily volume.ResultsWe found a strong negative correlation between ED median daily volume and volume variability (R2 = 81.0%; P < 0.0001). In addition, the four regression models for the percent of days exceeding specified thresholds greater than their daily median volumes had R2 values of 49.4%, 61.2%, 70.0%, and 71.8%, respectively, all with P < 0.0001.ConclusionWe sought to determine whether smaller EDs experience high-volume days more frequently than larger EDs. We found that high-volume days, when defined as days with a count of arrivals at or above certain median-based thresholds, are significantly more likely to occur in lower-volume EDs than in higher-volume EDs. To the extent that EDs allocate resources and plan to staff based on median volumes, these results suggest that smaller EDs are more likely to experience unpredictable, volume-based staffing challenges and operational costs. Given the lack of a standard measure to define a high-volume day in an ED, we recommend 10% above the median daily volume as a metric, for its relevance, generalizability across a broad range of EDs, and computational simplicity.

Visual outcomes of high-volume compared with low-volume manual small-incision cataract surgery in Nepal.

To study whether manual small-incision cataract surgery (MSICS) in a high-volume setting gives acceptable postoperative visual outcomes. Geta Eye Hospital, Kailali, Nepal. Single-center retrospective study. One-year records of all MSICS in adult patients without any other ocular comorbidity were analyzed retrospectively. Surgical outcomes of cataract cases when surgeons performed more than 72 surgeries (high volume) in a single operating session (1 day) were compared with when fewer than 30 surgeries (low volume) were performed in a single operating session (1 day). Of 23 717 cases in the study, 20 574 patients (87%) had preoperative visual acuity of less than 3/60; 15 632 patients (66%) achieved good visual outcome (uncorrected distance visual acuity of 6/18 or better) postoperatively. Patients operated during high-volume months achieved good visual outcomes in 9930 cases (66.9%) as compared with 5702 (64.3%) in low-volume months. However, 6235 patients (61.7%) operated on during high-volume days had good visual outcomes as compared with 3053 (71.4%) during low-volume days; 175 patients in the high-volume group and 73 patients in the low-volume group (1.7% each) achieved visual acuity worse than 3/60. There were comparable posterior capsular rupture rates (423 [1.78%]) during high- and low-volume months, and 21 cases (0.09%) of postoperative endophthalmitis were noted. MSICS can be used to reduce large cataract backlogs in developing countries as good visual outcomes could be achieved in high-volume settings if standard protocols for quality control are followed.

Influence of emergency department patient volumes on CT utilization rate of the physician in triage.

Physician in triage (PIT) has been used as a potential solution to emergency department (ED) overcrowding and to decrease ED length of stay (LOS). This study examined the relationship between computerized tomography (CT) utilization of PIT and ED patient volumes. We hypothesized that despite the pressure on PIT to improve throughput on the busiest days, they will continue to utilize CT at the same rate. This retrospective chart review evaluated CT ordering patterns of PIT on patients with abdominal pain who presented to the ED over a 6-year period. CT utilization rate was calculated on days with the lowest 5% (LD5) and highest 5% (HD5) volumes based on average yearly volume. CT positive and negative rates were correlated with volume using Chi square analysis. Odds ratio and confidence intervals were calculated for the magnitude of effect difference. We found no statistically significant difference in CT utilization rate on HD5 vs LD5 (p=0.833). There was a statistically significant increase in the rate of negative CT scans on HD5 (p=0.046) which represented a 17% relative difference. LOS was longer on HD5 (p=0.013) and when a CT scan was ordered (p<0.001). No difference was found in the rate at which the PIT ordered CT scans on high volume vs low volume days. The rate of CT scans without clinically relevant findings did increase slightly on high volume days. LOS was longer on high volume days and when a CT was ordered.

Predicting daily surgical volume for an academic medical center

BackgroundSurgical volume is highly variable and perioperative managers expend substantial time and energy adjusting resources in the days before surgery to accommodate unexpected low or high volume days. Last-minute changes lead to increased workload, adjustment of human and material resources, and potential for errors and delays which can impact employee morale and retention. Our objective was to improve forecasting of daily surgical volume weeks in advance of the day of surgery to allow perioperative managers adequate time to adjust staffing levels and material resources. MethodsAccumulating surgery schedule and block release data were collected from July 2017 to October 2018 from two hospital-based operating room campuses at an academic medical center. Regression analyses were performed on accumulating schedule data 7, 14, and 21 business days before the day of surgery to create predictive analytic models. ResultsAssuming average daily volume of 32 cases for Campus 1 and 43 cases for Campus 2, the 7-day-out-model had an average error of 11.0% (standard deviation (SD) 8.6%) and 9.9% (SD 6.6%), respectively. Although the 21-day-out model had an average error of 14.5% (SD 10.9%) for Campus 1 and 12.2% (SD 9.1%) for Campus 2, cross-validation results indicated predicted volumes were within 7 cases 81.4% of days and 68.6% of days. ConclusionBuilding on previously published research, a predictive analytic model was created that improved estimated daily surgical volume up to 4 weeks before day of surgery. Achieving face validity with perioperative management is paramount in order to make use of predicted volume estimates.

Corporate Bond Price Reversals

I demonstrate that investors trade U.S. corporate bonds not only for liquidity reasons but also on private information. Bond dealers let less-informed investors provide liquidity to informed traders and are not adversely selected. I obtain these results by contrasting corporate bond price reversals in bonds with different information asymmetry, trading volume, and dealers' capital commitment. I find strong price reversals that become less pronounced following high-trading-volume days. The effect is the strongest for bonds with high information asymmetry, and when dealers' end-of-day inventory does not change. The results suggest that information reveals itself in prices on high-volume days when dealers do not accept overnight inventory risk. The findings are in line with the predictions of a theoretical model in which investors trade both for liquidity reasons and on private news that arrive independently of changes in inventory. I further show that realized bid-ask spreads are not wide enough to negate reversal profits of high-asymmetry bonds. Such reversal portfolios earn 3% per year after trading cost adjustment. By connecting low market transparency with high non-fundamental price volatility, the paper also contributes to the ongoing policy debate.

Do investors herd in cryptocurrencies – and why?

We investigate herding and its possible determinants in the cryptocurrency market for the December 2013 – July 2018 period. Herding is significant (irrespective of Bitcoin’s presence and trends over time) and strongly asymmetric (appearing stronger during up-markets, low volatility and high volume days), with smaller cryptocurrencies enhancing its magnitude. Our findings suggest that the cryptocurrency market entails strong destabilizing potential, the latter being of particular relevance to the authorities entrusted with its regulatory treatment.

Predicting influenza-like illness-related emergency department visits by modelling spatio-temporal syndromic surveillance data.

Predicting the magnitude of the annual seasonal peak in influenza-like illness (ILI)-related emergency department (ED) visit volumes can inform the decision to open influenza care clinics (ICCs), which can mitigate pressure at the ED. Using ILI-related ED visit data from the Alberta Real Time Syndromic Surveillance Net for Edmonton, Alberta, Canada, we developed (training data, 1 August 2004-31 July 2008) and tested (testing data, 1 August 2008-19 February 2014) spatio-temporal statistical prediction models of daily ILI-related ED visits to estimate high visit volumes 3 days in advance. Our Main Model, based on a generalised linear mixed model with random intercept, incorporated prediction residuals over 14 days and captured increases in observed volume ahead of peaks. During seasonal influenza periods, our Main Model predicted volumes within ±30% of observed volumes for 67%-82% of high-volume days and within 0.3%-21% of observed seasonal peak volumes. Model predictions were not as successful during the 2009 H1N1 pandemic. Our model can provide early warning of increases in ILI-related ED visit volumes during seasonal influenza periods of differing intensities. These predictions may be used to support public health decisions, such as if and when to open ICCs, during seasonal influenza epidemics.

A ‘busy day’ effect on perinatal complications of delivery on weekends: a retrospective cohort study

ObjectiveTo evaluate whether busy days on a labour and delivery unit are associated with maternal and neonatal complications of childbirth in California hospitals, accounting for weekday/weekend births.DesignThis is a population-based retrospective cohort study.SettingLinked vital statistics/patient discharge data for California births between 2009 and 2010 from the Office of Statewide Health Planning and Development.ParticipantsAll singleton, cephalic, non-anomalous California births between 2009 and 2010 (N=724 967).Main outcomesThe key exposure was high daily obstetric volume, defined as giving birth on a day when the number of births exceeded the hospital-specific 75th percentile of daily delivery volume. Outcomes were a range of maternal and neonatal complications.ResultsSeveral maternal and neonatal complications were increased on high-volume days and weekends following adjustment for maternal demographics, annual hospital birth volume and teaching hospital status. For example, compared with low-volume weekdays, the odds of Apgar <7 on low-volume weekend days and high-volume weekend days were 11% (adjusted OR (aOR) 1.11, CI 1.03 to 1.21) and 29% higher (aOR 1.29, CI 1.10 to 1.52), respectively. High volume was associated with increased odds of neonatal seizures on weekdays (aOR 1.33, CI 1.01 to 1.71) and haemorrhage on weekends (aOR 1.11, CI 1.01 to 1.22). After accounting for between-hospital variation, weekend delivery remained significantly associated with increased odds of Apgar score <7, neonatal intensive care unit admission, prolonged maternal length of stay and the odds of neonatal seizures remained increased on high-volume weekdays.ConclusionsOur findings suggest that weekend delivery is a consistent risk factor for a range of perinatal complications and there may be variability in how well hospitals handle surges in volume.

The Law and Economics of Insider Trading

Several recent high-profile insider trading losses have not stopped the federal government from aggressively prosecuting insider trading cases. The first of its kind, this law review article offers both a legal analysis and an empirical analysis that would aid the government in detecting and prosecuting insider trading. Specifically, this article finds that insider traders move prices more than non-insider trades of similar characteristics and insiders trade on high-volume days based on a dataset generated from SEC litigation releases.

Systems Factors in Obstetric Care

To evaluate whether relatively high-volume days are associated with measures of obstetric care in California hospitals. This is a population-based retrospective cohort study of linked data from birth certificates and antepartum and postpartum hospital discharge records for California births in 2006. Birth asphyxia and nulliparous, term, singleton, vertex cesarean delivery rates were analyzed as markers of quality of obstetric care. Rates were compared between hospital-specific relatively high-volume days (days when the number of births exceeded the 75th percentile of daily volume for that hospital) and low-volume or average-volume days. Analyses were stratified by weekend and weekday and overall hospital obstetric volume. Multivariable logistic regression was used to control for confounders. On weekends, relatively high-volume days were significantly associated with an elevated risk of asphyxia (27 out of 10,000 compared with 17 out of 10,000; P=.013), whereas no association was present on weekdays (13 out of 10,000 on high-volume days and 15 out of 10,000 on low-volume or average-volume days; P=.182). The cesarean delivery rate among the nulliparous, term, singleton, vertex population was significantly lower on high-volume weekend days (22.0% compared with 23.6% on low-volume or average-volume weekend days; P=.009), whereas no association was present on weekdays (27.1% on high-volume days and 27.6% on low-volume or average-volume days; P=.092). Delivery on relatively high-volume weekend days is a risk factor for birth asphyxia in California. High-volume weekend days also are associated with a lower rate of cesarean delivery in nulliparous women with singleton, vertex presentation pregnancies at term. : II.

Tu1333 High Volume Days Appear to Reduce Adenoma Detection Rate. A Retrospective Study

Tu1333 High Volume Days Appear to Reduce Adenoma Detection Rate. A Retrospective Study

Patterns and factors associated with intensive use of ED services: implications for allocating resources

AimThis study aims to better understand the patterns and factors associated with the use of emergency department (ED) services on high-volume and intensive (defined by high volume and high-patient severity) days to improve resource allocation and reduce ED overcrowding. MethodsThis study created a new index of “intensive use” based on the volume and severity of illness and a 3-part categorization (normal volume, high volume, intensive use) to measure stress in the ED environment. This retrospective, cross-sectional study collected data from hospital clinical and financial records of all patients seen in 2001 at an urban academic hospital ED. ResultsMultiple logistic regression models identified factors associated with high volume and intensive use. Factors associated with intensive days included being in a motor vehicle crash; having a gun or stab wound; arriving during the months of January, April, May, or August; and arriving during the days of Monday, Tuesday, or Wednesday. Factors associated with high-volume days included falling from 0 to 10 ft; being in a motor vehicle crash; arriving during the months of January, April, May, or August; and arriving during the days of Monday, Tuesday, or Wednesday. ConclusionThese findings offer inputs for reallocating resources and altering staffing models to more efficiently provide high-quality ED services and prevent overcrowding.

Strategic illegal insider trading prior to price sensitive announcements

PurposeUsing data for actual insider trading cases prosecuted by the Securities and Exchange Commission, the paper aims to investigate whether insiders trade strategically to avoid detection.Design/methodology/approachThe paper analyzes actual insider trades prior to price sensitive announcements.FindingsIt is found that insiders are more likely to trade on high volume days, which indicates an effort to hide their trades. Further, insider trading raises the number of days with abnormally high trading volume only slightly, again indicating that insiders are avoiding attracting attention. No evidence is found that insider trading intensity increases on the insider trading day closest to the announcement day. The hypothesis that index returns for insider trading days and non‐trading days are the same cannot be rejected, which is consistent with insiders avoiding detection. For stocks sold by insiders, returns are higher for insider trading days than for non‐insider trading days. Hence, insiders are selling on days when the market is up, which tends to hide their trading. But for stocks bought by insiders, returns are significantly higher on insider trading days than on non‐insider‐trading days, indicating that in this case insiders may attract unwanted attention.Originality/valueThe research may be useful to those attempting to detect insider trades.

Individual Investors and Option Trading: Attention Grabbing Versus Long-Term Strategies

This paper analyzes trading records of online retail bank investors to examine whether attention-type events dominate return feedback strategies in explaining individual investors’ stock option trading decisions. We show that although individual investors are net buyers of common stock on abnormally high volume days, they follow contrarian investment strategies after extreme prior day stock price performance. Moreover, we find that individual investors especially exploit stock options to follow contrarian investment strategies in that they initiate over twice as many bullish-type (nearly half as many bearish-type) option contracts after extremely poor (good) prior-day returns. Further, we observe variance in contrarian behavior across investor types: extremely optimistic investors pursue contrarian investment strategies more (less) pronounced around highly negative (positive) prior day returns. Finally, we show that the same extreme optimists especially overweigh short-term compared to long-term return feedback information in making individual stock option trading decisions. Combined, this study provides novel insights in the dynamics of individual investors’ option trading decisions and in the distinctive roles of cognitive biases underlying this process.

262: Quantification of Daily Surge Volume In the Emergency Department

262: Quantification of Daily Surge Volume In the Emergency Department

Information, Trading Volume, and International Stock Return Comovements: Evidence from Cross-Listed Stocks

AbstractWe investigate the joint dynamics of returns and trading volume of 556 foreign stocks cross-listed on U.S. markets. Heterogeneous-agent trading models rationalize how trading volume reflects the quality of traders’ information signals and how it helps to disentangle whether returns are associated with portfolio-rebalancing trades or information-motivated trades. Based on these models, we hypothesize that returns in the home (U.S.) market on high-volume days are more likely to continue to spill over into the U.S. (home) market for those cross-listed stocks subject to the risk of greater informed trading. Our empirical evidence provides support for these predictions, which confirms the link between information, trading volume, and international stock return comovements that has eluded previous empirical investigations.