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1
Brownlees, C. T., F. Cipollini, and G. M. Gallo. "Intra-daily Volume Modeling and Prediction for Algorithmic Trading." Journal of Financial Econometrics 9, no. 3 (July 5, 2010): 489–518. http://dx.doi.org/10.1093/jjfinec/nbq024.
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Li, Edward Xuejun, K. Ramesh, and Min Shen. "The Role of Newswires in Screening and Disseminating Value-Relevant Information in Periodic SEC Reports." Accounting Review 86, no. 2 (March 1, 2011): 669–701. http://dx.doi.org/10.2308/accr.00000023.
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ABSTRACT: We examine the role of newswires in identifying and conveying market-moving information in periodic SEC reports to capital market participants. Using data on Dow Jones Newswires, we find that newswires are more likely to send alerts on firms that do not release preliminary earnings, have credit ratings, are included in major market indices, have litigation exposure, or report losses. Reflective of the market’s focus on certain key events, firms with a nonstandard audit opinion, in the process of delisting, reporting unusual accounting items, or raising equity capital also receive alerts. Moreover, not only do we find significant price and volume reactions to the alerts at the daily level, but also we document immediate intra-day market activity triggered by the alerts, whereas we detect no similar reaction for SEC filings that trigger the alerts. Additional analysis suggests that the intra-day reaction is not driven by noise trading.
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Hahn, Sang Buhm, and Seung Hyun Oh. "The Impact of Program Trading on the Short-run and Long-run Volatility of Korean Stock Market." Journal of Derivatives and Quantitative Studies 15, no. 1 (May 31, 2007): 101–33. http://dx.doi.org/10.1108/jdqs-01-2007-b0004.
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This study investigates the impact of program trading on the market volatility by separating the volatility into long-run and short-run components using VA-CEGARCH model. This approach allows us to observe the two channels through which the program trading affects the market volatility. We have following results. Program trading and non-program trading both have no impact on the long-run component but do increase short-run component. In case of short-run component‘ program trading has a larger impact compared to non-program trading. Secondly, in both daily and intra-day analysis, arbitrage program trading is found to have a larger impact on short-run components than non-arbitrage program trading. Thirdly, ARCH effects are found in short-run components of daily analysis and long-run components of intra-day analysis. And the volatility’s asymmetric responses to good or bad news are introduced through long-run components. What is noteworthy is the fact that non-arbitrage program trading is actually found to reduce short-run volatility in the intra-day analysis. Which means that non-arbitrage program trading, such as hedging transactions, helps promote intra-day market stability. Our findings mean that the short-run component is the main channel by which program trading produce unnecessary market volatility.
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Kambeu, Edson. "Trading Volume as a Predictor of Market Movement." International Journal of Finance & Banking Studies (2147-4486) 8, no. 2 (July 20, 2019): 57–69. http://dx.doi.org/10.20525/ijfbs.v8i2.177.
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A logistic regression model is has also become a popular model because of its ability to predict, classify and draw relationships between a dichotomous dependent variable and dependent variables. On the other hand, the R programming language has become a popular language for building and implementing predictive analytics models. In this paper, we apply a logistic regression model in the R environment in order to examine whether daily trading volume at the Botswana Stock Exchange influence daily stock market movement. Specifically, we use a logistic regression model to find the relationship between daily stock movement and the trading volumes experienced in the recent five previous trading days. Our results show that only the trading volume for the third previous day influence current stock market index movement. Overall, trading volumes of the past five days were found not have an impact on today’s stock market movement. The results can be used as a basis for building a predictive model that utilizes trading as a predictor of stock market movement.
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Acker, Daniella, Mathew Stalker, and Ian Tonks. "Daily Closing Inside Spreads and Trading Volumes Around Earnings Announcements." Journal of Business Finance Accounting 29, no. 9&10 (November 2002): 1149–79. http://dx.doi.org/10.1111/1468-5957.00465.
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Muryani, Muryani, and Anisa Dyan Pratiwi. "Intra-Industry Trading Factors and Patterns in ASEAN-5 Region." Jurnal Global Strategis 12, no. 2 (November 30, 2018): 41. http://dx.doi.org/10.20473/jgs.12.2.2018.41-52.
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The large expansion of trade in the form of Intra-Industry Trade (IIT) in ASEAN is driving large volumes and variety of traded goods and is changing patterns of trade across members. This paper examines the factors affecting the level of IIT for ASEAN-5 countries (Indonesia, Malaysia, Philippines, Singapore, and Thailand) in the period of 2004-2014. IIT is measured with Grubel-Lloyd index covering ten different one-digit SITC categories. The result indicates a large Intra-Industry Trade among ASEAN countries and across most manufacturing sectors. IIT Index is employed as a dependent variable, and four variables are used as independent variables: 1) different GDP per capita, 2) foreign direct investment (FDI), 3) trade openness, and 4) distance. Different GDP per capita and trade openness have a positive effect on IIT. FDI does not affect IIT, and distance has a negative effect on IIT across intra-ASEAN trade. Keywords: International Trade, Intra-Industry Trade, Grubel-Lloyd, Panel Data Analysis
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Leung, Charles Ka Yui, Patrick Wai Yin Cheung, and Erica Jiajia Ding. "International Real Estate Review." International Real Estate Review 11, no. 2 (December 31, 2008): 47–74. http://dx.doi.org/10.53383/100097.
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Previous studies of the office market have tended to focus on either the rental market or the aggregate sales market. This paper focuses on the intra-metropolitan sales market and on office price and trading volume dynamics in Hong Kong. According to our findings, buildings trading at higher prices are not necessarily traded more often than those trading at lower prices. In addition, the price of offices in different categories does not necessarily move in tandem. The trading volumes of higher priced buildings tend to Granger cause the lower priced buildings, and this conclusion is robust to alternative classifications. The paper contrasts several existing theories. Suggestions for future research are also discussed.
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Lv, Qiuna, Liyan Han, Yipeng Wan, and Libo Yin. "Stock Net Entropy: Evidence from the Chinese Growth Enterprise Market." Entropy 20, no. 10 (October 19, 2018): 805. http://dx.doi.org/10.3390/e20100805.
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By introducing net entropy into a stock network, this paper focuses on investigating the impact of network entropy on market returns and trading in the Chinese Growth Enterprise Market (GEM). In this paper, indices of Wu structure entropy (WSE) and SD structure entropy (SDSE) are considered as indicators of network heterogeneity to present market diversification. A series of dynamic financial networks consisting of 1066 daily nets is constructed by applying the dynamic conditional correlation multivariate GARCH (DCC-MV-GARCH) model with a threshold adjustment. Then, we evaluate the quantitative relationships between network entropy indices and market trading-variables and their bilateral information spillover effects by applying the bivariate EGARCH model. There are two main findings in the paper. Firstly, the evidence significantly ensures that both market returns and trading volumes associate negatively with the network entropy indices, which indicates that stock heterogeneity, which is negative with the value of network entropy indices by definition, can help to improve market returns and increase market trading volumes. Secondly, results show significant information transmission between the indicators of network entropy and stock market trading variables.
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HE, LING-YUN, and XING-CHUN WEN. "PREDICTABILITY AND MARKET EFFICIENCY IN AGRICULTURAL FUTURES MARKETS: A PERSPECTIVE FROM PRICE–VOLUME CORRELATION BASED ON WAVELET COHERENCY ANALYSIS." Fractals 23, no. 02 (May 28, 2015): 1550003. http://dx.doi.org/10.1142/s0218348x15500036.
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In this paper, we use a time-frequency domain technique, namely, wavelet squared coherency, to examine the associations between the trading volumes of three agricultural futures and three different forms of these futures' daily closing prices, i.e. prices, returns and volatilities, over the past several years. These agricultural futures markets are selected from China as a typical case of the emerging countries, and from the US as a representative of the developed economies. We investigate correlations and lead–lag relationships between the trading volumes and the prices to detect the predictability and efficiency of these futures markets. The results suggest that the information contained in the trading volumes of the three agricultural futures markets in China can be applied to predict the prices or returns, while that in US has extremely weak predictive power for prices or returns. We also conduct the wavelet analysis on the relationships between the volumes and returns or volatilities to examine the existence of the two "stylized facts" proposed by Karpoff [J. M. Karpoff, The relation between price changes and trading volume: A survey, J. Financ. Quant. Anal.22(1) (1987) 109–126]. Different markets in the two countries perform differently in reproducing the two stylized facts. As the wavelet tools can decode nonlinear regularities and hidden patterns behind price–volume relationship in time-frequency space, different from the conventional econometric framework, this paper offers a new perspective into the market predictability and efficiency.
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Jain, Pawan, Spenser J. Robinson, Arjun J. Singh, and Mark Sunderman. "Hospitality REITs and financial crisis: a comprehensive assessment of market quality." Journal of Property Investment & Finance 35, no. 3 (April 3, 2017): 277–89. http://dx.doi.org/10.1108/jpif-08-2016-0068.
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Purpose The purpose of this paper is to examine market microstructure differences in stock market quality for hospitality real estate investment trusts (REITs) during the pre- and post-financial crisis eras. It provides insight on different trading strategies based on the underlying liquidity and volatility of hospitality REITs as compared traditional REITs and the broader market. Design/methodology/approach The paper uses established microstructure measures for liquidity, trading volumes and risk assessment and compares daily and intraday trading patterns of REITs, hospitality REITs and the broad market. Findings The results suggest a quicker recovery of performance for hospitality REITs and some fundamental increases in liquidity measures post-crisis. The results of the study highlight the differences in trading volumes, liquidity and risk profile of hospitality REITs compared to traditional REITs both in the pre- and post-financial crisis periods. Practical implications The quicker recovery of hospitality REITs in key trading measures may suggest flight to quality during periods of high volatility. Originality/value This study fills the gap in the literature relative to microstructure studies and provides information to help hotel firms and portfolio managers choose an appropriate organizational structure and investment vehicle, respectively.
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Hadady, Hartaty, and Rachman Dano Mustafa. "Investor Herding Behavior in Infrastructure Companies on the IDX: Data Panel Approach." Society 10, no. 2 (December 30, 2022): 375–89. http://dx.doi.org/10.33019/society.v10i2.483.
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This research aims to examine the behavior of herding investors due to the information on interest rates and trading volume. By using daily infrastructure company data on the IDX, it is found that interest rates have a negative effect, while volume has a positive effect on herding behavior. The results show that herding behavior decreases when information on interest rates is entered, while herding behavior increases when there is a trend in trading volume. These results indicate that information announced and scheduled will reduce the behavior of herding investors, such as information about interest rates. On the other hand, investor herding behavior tends to increase when information is random, such as trends in stock trading volumes.
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FAJARIYAH, Saadila, and Mohamad DJASULI. "Stock Price Reaction Analysis Before And After The Announcement Of The First Covid-19 PSBB Implementation On The Lq-45 Index Listed On The Indonesia Stock Exchange." Journal of Governance, Taxation and Auditing 1, no. 2 (November 30, 2022): 75–80. http://dx.doi.org/10.38142/jogta.v1i2.401.
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This study was conducted to determine the reaction of stock prices before and after implementing the PSBB for the first time. Stock price reactions were measured by abnormal returns and trading volume activity using the event study method with an adjusted market model approach. The population used in this arrangement is the number of companies listed on the LQ-45 index for the February-July 2020 period, as many as 45 companies. The sample used a saturated sampling technique for as many as 45 companies. This research data uses secondary data consisting of daily stock closing prices and daily stock trading volumes with an observation period of seven days before the event, one day when the PSBB was implemented, and seven days after the PSBB was implemented. The statistical tools used were the normality test and the one-sample t-test. The results of this study indicate that there is a significant average abnormal return. However, there is no difference in abnormal returns before and after implementing the first PSBB. Besides that, the results show a significant average trading volume activity. However, trading volume activity is the same before and after the first PSBB implementation.
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Kravchenko, Yu. "Functioning of foreign exchange markets in modern conditions." Mezhdunarodnaja jekonomika (The World Economics), no. 1 (January 1, 2020): 55–70. http://dx.doi.org/10.33920/vne-04-2001-05.
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In the article the author considers the dynamics of average daily foreign exchange market turnover. It is revealed that the evolution of foreign exchange trading volumes continues to be dominated mostly by fi nancial institutions’ motives as opposed to needs arising directly from real economic activity. Geographical distribution and structure of average daily foreign exchange market turnover by foreign exchange instrument, counterparty, currency, currency pairs, location of transactions are analyzed. At end of the article, the author concludes that the process of internationalization of world economic relations is slowing down.
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Fousekis, Panos, and Dimitra Tzaferi. "Monotonicity, linearity and symmetry in the price volatility–volume relationship." Studies in Economics and Finance 37, no. 1 (February 10, 2020): 110–33. http://dx.doi.org/10.1108/sef-09-2019-0344.
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Purpose This paper aims to investigate the contemporaneous link between price volatility and trading volume in the futures markets of energy. Design/methodology/approach Non-parametric (local linear) regression models and formal statistical tests are used to assess monotonicity, linearity and symmetry. The data are daily price and volumes from five futures markets (West Texas Intermediate, Brent, gasoline, heating oil and natural gas) in the USA. Findings Trading volume and price volatility have, in all markets, a strong nonlinear relation to each other. There are violations of monotonicity locally but not globally. The qualitative nature of the price shocks may have implications for the trading activity locally. Originality/value To the authors’ best knowledge, this is the first manuscript that investigates simultaneously and formally all the three important issues (i.e. monotonicity, linearity and asymmetry) for the price volatility–volume relationship using a highly flexible nonparametric approach.
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Karmakar, Madhusudan, and Madhumita Chakraborty. "A Trading Strategy for the Indian Stock Market: Analysis and Implications." Vikalpa: The Journal for Decision Makers 25, no. 4 (October 2000): 27–38. http://dx.doi.org/10.1177/0256090920000404.
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A curious seasonality reported in finance is the monthly effect which implies that the mean daily return for stock is positive and higher during the first half of the month than the second half. Another related anomaly is the turn-of-the-month effect which is said to exist when the average daily return at the turn of the month is significantly higher than the daily return on the remain ing days of the month. This paper examines both the monthly effect and the turn-of-themonth effect in the Indian stock market by applying two different approaches: calendar day approach and trading day approach. The results of both the approaches reveal significantly higher return at the first half of the month than that of the second half and abnormally high returns at the turn of the month. Various explanations for the ob served anomalies have been considered including the problem of ‘data mining,’ proxy of other anomalies, etc., but none could provide adequate explanations for the observed intra-month return regularities. However, based on the findings, the study tries to evolve certain trading strategies which would benefit in the decision making of the investors concerned with timing of stock purchases and sales.
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Sugimura, Nobuhiro, Nguyen Quang Thinh, Shohei Kohama, Yutaka Fukui, and Koji Iwamura. "A Study on Demand Forecasting of Wholesale Markets of Lettuces for Production Planning in Plant Factories." International Journal of Automation Technology 16, no. 2 (March 5, 2022): 218–29. http://dx.doi.org/10.20965/ijat.2022.p0218.
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Much emphasis is now being placed on the research and development of fully closed and controlled plant factories aimed at supplying fresh vegetables safely and constantly. Plant factories produce large volumes of clean and safe vegetables in an artificially controlled environment. One of the important issues in the management and control of plant factories is establishing systematic methods for planning the production and shipping of daily produced vegetables to various customers, such as supermarkets, vegetable shops, and restaurants. Customer demand is influenced by the sales in the individual shops and trade volumes, and prices in the wholesale markets of the vegetables, since the share of the plant factory-made vegetables is very small. Systematic methods are required for the management and control of plant factories to forecast both orders from individual customers and wholesale market conditions. In the previous study, the market situations and the trading processes of the factory-made lettuces were investigated, and a market model was proposed to simulate the trading processes between the customers and the plant factories. This study deals with demand forecasting of wholesale markets for vegetables, aimed at taking into consideration the wholesale market conditions for production planning in plant factories.
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KAIZOJI, TAISEI, and MASAHIDE NUKI. "SCALING LAW FOR THE DISTRIBUTION OF FLUCTUATIONS IN SHARE VOLUME." Fractals 12, no. 01 (March 2004): 49–53. http://dx.doi.org/10.1142/s0218348x04002318.
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We show power-scaling behaviors for fluctuations in share volume, which no other studies have done so far. After analyzing a database of the daily transactions for all securities listed on the Tokyo Stock Exchange, we selected 1050 large companies that each had an unbroken series of daily trading activity from January 1975 to January 2002. We found that the cumulative distributions of daily fluctuations in share volumes can be well described by a power-law decay, and that the cumulative distributions for almost all of the companies can be characterized by an exponent within the stable Lévy domain 0 < α < 2. Furthermore, more than 35% of the cumulative distributions can be well approximated by Zipf's law, i.e. the cumulative distributions have an exponent close to unity.
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Abba Abdullahi, Saada, Reza Kouhy, and Zahid Muhammad. "Trading volume and return relationship in the crude oil futures markets." Studies in Economics and Finance 31, no. 4 (September 30, 2014): 426–38. http://dx.doi.org/10.1108/sef-08-2012-0092.
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Purpose – The purpose of this paper is to examine the relationship between trading volume and returns in the West Texas Intermediate (WTI) and Brent crude oil futures markets. In so doing, the paper addresses two important issues. First, whether there is a positive relationship between returns and trading volume in the crude oil futures markets. Second, whether information regarding trading volume contributes to forecasting the magnitude of return in the markets, an important issue because the ability of trading volume to predict returns imply market inefficiency. Design/methodology/approach – The paper used daily closing futures price and their corresponding trading volumes for WTI and Brent crude oil markets during the sample period January 2008 to May 2011. Both the log volume and the unexpected component of the detrended volume are used in the analysis in other to have robust alternative conclusion. The generalized method of moments (GMM) approach is used to examine the contemporaneous relationship between returns and trading volume while the Granger causality approach, impulse response and variance decomposition analysis are used to investigate the ability of trading volume to predict returns in the oil futures markets. Findings – The results reject the postulation of a positive relationship between trading volume and returns, suggesting that trading volume and returns are not driven by the same information flow which contradicts the mixture of distribution hypothesis in all markets. The results also show that neither trading volume nor returns have the power to predict the other and therefore contradicting the sequential arrival hypothesis and noise trader model in all markets. Finally, the findings support the weak form efficient market hypothesis in the crude oil futures markets. Originality/value – The findings has important implications to market regulators because daily price movement and trading volume do not respond to the same information flow and therefore the measures that control price volatility should not focused more on volume; otherwise they may not provide fruitful outcomes. Additionally, traders and investors who participate in oil futures should not base their decisions on past trading volume because it will lead to profit loss. The results also have implications for market efficiency as past information cannot assist speculators to forecast returns in all the oil markets. Finally, investors can benefit from portfolio diversification across the two markets.
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Reintam Blaser, Annika, Pille Parm, Reet Kitus, and Joel Starkopf. "Intra-Abdominal Hypertension and Gastrointestinal Symptoms in Mechanically Ventilated Patients." Critical Care Research and Practice 2011 (2011): 1–5. http://dx.doi.org/10.1155/2011/982507.
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Background. We aimed to describe the incidence of intra-abdominal hypertension (IAH) and gastrointestinal (GI) symptoms and related outcome in mechanically ventilated (MV) patients.Methods. Intra-abdominal pressure (IAP) and gastric residual volumes were measured at least twice daily. IAH was defined as a mean daily value ofIAP≥12 mmHg.Results. 398 patients were monitored for all together 2987 days. GI symptom(s) occurred in80.2%patients. 152 (38.2%) patients developed IAH. Majority (93.4%) of patients with IAH had GI symptoms. The more severe IAH was associated with the higher number of concomitant GI symptoms (P<.001). 142 (35.7%) patients developed both IAH and at least one GI symptom at any time in ICU, and in 77 patients they occurred simultaneously on the same day. This subgroup had the highest ICU mortality (21.8%). In contrast, the small group of patients presenting only IAH, but not GI symptoms (10 patients), had no lethal outcome. Three patients (4.4%) died without showing either IAH or GI symptoms.Conclusions. GI symptoms and IAH often, but not always, occur together. The patients having IAH solely without developing GI symptoms have rather good outcome.
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Hahn, Sang Buhm. "Short-Selling and Behavioral Bias in Korean Stock Market." Journal of Derivatives and Quantitative Studies 25, no. 2 (May 31, 2017): 255–78. http://dx.doi.org/10.1108/jdqs-02-2017-b0004.
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This study investigates whether or not the short-selling behavioral bias of investors exists in the Korean stock market. We analyze how the weather bias related to climate factors affects short-selling traders, commonly known as informed traders. To do this we estimated the dynamic panel model using daily data and examined the relationship between market variables such as stock returns, short sale volume, non-short sale volume, total trading volume, and weather variables consisting of cloud cover and sunshine hours. This study shows that not only returns but also short selling volumes are all affected by weather factors. In the case of stock returns, both cloud cover and sunshine hours have a statistically significant impact on returns, and its sign is estimated to be inversely proportional to both factors. That is, we find that returns decrease on cloud days, but increase on sunny days. In terms of the trading behavior of the market participants, it is interesting to note that the trading volume decreases when the weather is blunted, But did not show any statistical significances. On the other hand, both the original and the seasonally adjusted weather factors of cloud cover have a statistically significant positive effect on the short-sale volume. This means that as the weather worsens, short-selling traders submit more orders, indicating the presence of behavioral bias.
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Sancovschi, Moacir, Adolfo Henrique Coutinho e. Silva, and José Paulo Cosenza. "The Market and Investors Reactions to Mariana’s and Brumadinho’s Environmental Disasters: Sentimental or Rational Decisions?" Journal of Management and Sustainability 12, no. 1 (January 8, 2022): 37. http://dx.doi.org/10.5539/jms.v12n1p37.
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This research carried out event studies to analyze the reactions of the market and investors in Vale S.A. to the collapses of the Mariana and Brumadinho dams. It also assessed the extent to which the causes attributed to the market reactions to major disasters in previous research has helped to explain the reactions of the market and investors to the collapses of these dams. The analyses have shown that, in the case of the Fundão dam, there was a relevant reduction in the abnormal cumulative returns of common stocks and ADRs at the end of the eleven days of the collapse, despite the fact that the daily abnormal returns were not statistically significant. However, the abnormal trading volumes of these securities in the eleven days after the dam failure were generally negative and all statistically significant. In contrast, concerning the collapse of the Brumadinho dam, the abnormal returns on common stocks and ADRs were negative, relevant, and statistically significant, and, after the eleven days, the losses were considerable. The abnormal trading volumes of the securities were all positive and statistically significant, but the reactions of ADR investors were more intense than those of investors in common stocks. Examining the causal attributions made previously, there are indications that the market and investor reactions to the failures of the two dams were probably derived from the expectation that Vale and the other companies involved would incur severe losses and high contracting costs in political processes that would follow to the disasters, and from the difficulty the investors have had to assess the magnitude of these losses and costs.
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Smit, E. V. D. M., and M. W. Louw. "The relationship between volatility, volume and open interest: Some evidence from the South African futures market." South African Journal of Business Management 27, no. 4 (December 31, 1996): 113–21. http://dx.doi.org/10.4102/sajbm.v28i4.816.
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Using the methodology devised by Bessembinder Seguin, the relationships between volatility on the one hand and volume and market depth in the South African futures market are examined. Daily mark-to-market prices, trading volumes and open interest on six futures contracts traded on SAFEX over the period 1990 to 1994 are utilized. The evidence suggests that linking price volatility to total volume does not capture all information. When total volume is divided into expected and unexpected components, the latter is shown to have a more substantial effect on volatility. Furthermore, coefficients pertaining to open as well as unexpected open interest tend to be negative, implying that lower volatility shocks are associated with a given volume in deeper markets. It is further shown that positive unexpected volume shocks are associated with higher levels of volatility and that asymmetry exists, insofar as positive shocks have larger effects on volatility than negative shocks.
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Smit, E. V. D. M., and M. W. Louw. "The relationship between volatility, volume and open interest: Some evidence from the South African futures market." South African Journal of Business Management 27, no. 4 (December 31, 1996): 113–21. http://dx.doi.org/10.4102/sajbm.v27i4.816.
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Using the methodology devised by Bessembinder Seguin, the relationships between volatility on the one hand and volume and market depth in the South African futures market are examined. Daily mark-to-market prices, trading volumes and open interest on six futures contracts traded on SAFEX over the period 1990 to 1994 are utilized. The evidence suggests that linking price volatility to total volume does not capture all information. When total volume is divided into expected and unexpected components, the latter is shown to have a more substantial effect on volatility. Furthermore, coefficients pertaining to open as well as unexpected open interest tend to be negative, implying that lower volatility shocks are associated with a given volume in deeper markets. It is further shown that positive unexpected volume shocks are associated with higher levels of volatility and that asymmetry exists, insofar as positive shocks have larger effects on volatility than negative shocks.
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Tashpulatov, Sherzod N. "The Impact of Regulatory Reforms on Demand Weighted Average Prices." Mathematics 9, no. 10 (May 14, 2021): 1112. http://dx.doi.org/10.3390/math9101112.
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Average prices are popularly used in the literature on price modeling. Calculating daily or weekly prices as an average over hourly or half-hourly trading periods assumes the same weight ignoring demand or traded volumes during those periods. Analyzing demand weighted average prices is important if producers may affect prices by decreasing them during low-demand periods and increasing them during high-demand periods within a day. The prediction of this price manipulation might have motivated the regulatory authority to introduce price caps not only on annual average prices but also on annual demand weighted average prices in the England and Wales wholesale electricity market. The dynamics of demand weighted average prices of electricity has been analyzed little in the literature. We show that skew generalized error distribution (SGED) is the appropriate assumption for model residuals. The estimated volatility model is used for evaluating the impact of regulatory reforms on demand weighted average prices during the complete history of the England and Wales wholesale electricity market.
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Bairstow, Rhianna, Michelle Cain, Phil Reynolds, and Pete Bridge. "Evaluation of seminal vesicle volume variability in patients receiving radiotherapy to the prostate." Journal of Radiotherapy in Practice 19, no. 1 (June 21, 2019): 20–24. http://dx.doi.org/10.1017/s1460396919000384.
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AbstractIntroduction:Prostate positional variability has been widely explored with seminal vesicle (SV) variability, coming into the forefront only in recent years. While planning target volume (PTV) margins and preparation protocols ameliorate the effects of bladder and rectum volume changes on prostate, studies on SV variation have looked at only position, not volume variability.Aim:The aim of this study was to investigate whether the inter-fraction volume variability of the VSs can exist in patients receiving radiotherapy to the prostate.Method:SV variability was investigated by comparing four on-treatment cone beam computer tomography scans to a planning computer tomography (CT) image for two patients receiving prostate radiotherapy. For each case, variation in volumes (cm3) was compared with intra-observer variation.Results:SV volume variability was seen in both patients, with the largest change in volume being 78·38%. This variance was considerably (between 2 and 10 times) larger than the measured intra-observer variance.Conclusion:This study identified the potential for daily SV volume variability in patients receiving prostate radiotherapy. Future large-scale studies are warranted to identify the extent of this motion and potential clinical impact. Evidence-informed PTV margins and possible SV volume control protocols may need to be adopted.
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Perry, Donna. "Rural weekly markets and the dynamics of time, space and community in Senegal." Journal of Modern African Studies 38, no. 3 (September 2000): 461–85. http://dx.doi.org/10.1017/s0022278x00003426.
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This article examines reciprocal relations among Wolof small farmers in Senegal after the emergence of rural weekly markets (loumas) and the implementation of neoliberal policies in the 1980s. Contrary to the notion that markets are a force of social dissolution, new trading practices and free market policies have not weakened community relations among small farmer neighbours and kin. Rather, the spatial and temporal patterning of loumas has served to strengthen intra-community bonds. Farmers have, since the formation of loumas, limited their travel beyond their home zones. While at loumas they interact avidly with extralocal merchants, they have not allowed outsiders to settle permanently in local villages. Furthermore, because loumas occur only once a week, farmers continue to benefit from daily, multiplex interactions with one another. After analysing the spatial and temporal organisation of loumas, this article looks at specific examples of small farmers augmenting their economic security during a period of economic restructuration by innovating new modes of reciprocal exchange with one another.
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Alam, Md Saniul, Lucy Corcoran, Eoin A. King, Aonghus McNabola, and Francesco Pilla. "Modelling of intra-urban variability of prevailing ambient noise at different temporal resolution." Noise Mapping 4, no. 1 (March 28, 2017): 20–44. http://dx.doi.org/10.1515/noise-2017-0002.
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AbstractThe impact of temporal aspects of noise data on model development and intra-urban variability on environmental noise levels are often ignored in the development of models used to predict its spatiotemporal variation within a city. Using a Land Use Regression approach, this study develops a framework which uses routine noise monitors to model the prevailing ambient noise, and to develop a noise variability map showing the variation within a city caused by land-use setting. The impact of data resolution on model development and the impact of meteorological variables on the noise level which are often ignored were also assessed. Six models were developed based on monthly, daily and hourly resolutions of both the noise and predictor data. Cross validation highlighted that only the hourly resolution model having 59%explanatory power of the observed data (adjusted R2) and a potential of explaining at least 0.47% variation of any independent dataset (cross validation R2), was a suitable candidate among all the developed models for explaining intraurban variability of noise.In the hourly model, regions with roads of high traffic volumes, with higher concentrations of heavy goods vehicles, and being close to activity centreswere found to have more impact on the prevailing ambient noise. Road lengthswere found to be the most influential predictors and identified as having an impact on the ambient noise monitors.
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IRFAN ULLAH, DR. MUHAMMAD ZAHID, and ZAIN ULLAH. "The Impact of Behavioural Biases on Stock Volatility: Evidence From Pakistan Stock Exchange." Journal of Business & Tourism 5, no. 1 (November 6, 2021): 215–25. http://dx.doi.org/10.34260/jbt.v5i1.128.
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The main purpose of the current study is to investigate the impact of behavioural biases such as confidence, optimism, and pessimism on stock volatility evidence from Pakistan Stock Exchange (PSX). Prospect theory and overconfidence theory formed the foundation of this study. The methodology composed of positivist philosophical stance, deductive approach and quantitative methods with secondary data. Data analysis involved the use of descriptive statistics, correlation and regression. The study consists ofa 10-years analysis from June 2008 to June 2018 and includes daily trading volumes KSE-100 index in PSX. Results reveal that behavioral biases such as confidence have a positive impact on stock volatility. Similarly, optimism bias has also a positive impact on stock volatility. While pessimism bias has recorded a negative impact on stock volatility. Therefore, it is concluded that behavioural biases have an impact on stock volatility. The current study has a contribution to the body of knowledge on the ground that it attempts to change the traditional notion of society who believes in the efficient market hypothesis. The study has implications for different stakeholders of stock markets.
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Narang, Sunita, and Madhu Vij. "Long-Term Effects of Expiration of Derivatives on Indian Spot Volatility." ISRN Economics 2013 (August 6, 2013): 1–6. http://dx.doi.org/10.1155/2013/718538.
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This paper examines the impact of expiration of derivatives on spot volatility of Indian capital market. The review of the literature shows that the previous Indian studies have covered a period of only 4–6 years after the introduction of derivative trading in India in 2000. They are unanimous about volume effect but not about return and volatility effect. This paper uses regression techniques and one symmetric and three asymmetric GARCH models, namely, TGARCH, EGARCH, and PGARCH, to evaluate the impact. It uses daily data on popular index S&P CNX Nifty of National Stock Exchange of India, during a period of more than a decade from June 12, 2000 to January 10, 2012. Findings of the study show that spot returns, volume, and volatility are high on expiration day and they build up further on the day after expiry which shows that the Indian market is weakly efficient. The expiration effect is mainly due to concentration of volumes in near-month contracts and absence of physical settlement.
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Jo, Yoon Young, Ji Woon Yea, Jaehyeon Park, Se An Oh, and Jae Won Park. "Optimized Adaptive Radiotherapy with Individualized Plan Library for Muscle-Invasive Bladder Cancer Using Internal Target Volume Generation." Cancers 14, no. 19 (September 26, 2022): 4674. http://dx.doi.org/10.3390/cancers14194674.
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The bladder is subject to filling variation, which poses a challenge to radiotherapy (RT) delivery. We aimed to assess feasibility and clinical outcomes in patients with bladder cancer treated with adaptive RT (ART) using individualized plan libraries. We retrospectively analyzed 19 patients who underwent RT for muscle-invasive bladder cancer (MIBC) in 2015–2021. Four planning computed tomography (CT) scans were acquired at 15-min intervals, and a library of three intensity-modulated RT plans were generated using internal target volumes (ITVs). A post-treatment cone-beam CT (CBCT) scan was acquired daily to assess intra-fraction filling and coverage. All patients completed the treatment, with 408 post-treatment CBCT scans. The bladder was out of the planning target volume (PTV) range in 12 scans. The volumes of the evaluated PTV plans were significantly smaller than those of conventional PTV. The 1-year and 2-year overall survival rates were 88.2% and 63.7%, respectively. Of eight cases that experienced recurrence, only two developed MIBC. There were no grade 3 or higher RT-related adverse events. ART using plan libraries and ITVs demonstrated good survival outcomes with a high local control rate. Irradiated normal tissue volume and treatment margins may be reduced through this approach, potentially resulting in lower toxicity rates.
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Sehgal, Sanjay, and Tarunika Jain Agrawal. "Impact of Commodity Transaction Tax on Market Liquidity, Volatility, and Government Revenues: An Empirical Study for India." Vikalpa: The Journal for Decision Makers 44, no. 1 (March 2019): 12–29. http://dx.doi.org/10.1177/0256090919826316.
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Executive Summary A commodity transaction tax (CTT) of 0.01 per cent is levied on non-agricultural commodity futures trading since 1 July 2013 by the Government of India. This article examines the impact of CTT on market liquidity, volatility and government tax revenues for the Indian commodities market. We use daily data of five sample commodities, namely gold, aluminium, copper, zinc and crude oil available from 1 May 2010 to 31 August 2016. It is found that CTT imposition has destroyed the parity of the Indian commodity futures market with the international markets as CTT is absent on COMEX, LME, NYMEX, and so on. Moreover, evidence of trade migration can be found by drawing a comparison across MCX and international exchanges. This argument is further substantiated by observing the decline in liquidity after the imposition of CTT. It should be further noted that parity with the equity market is also lost as the transaction taxes imposed in equity and commodity markets are not in line with the level of volatilities of the two markets. CTT has also failed to curb speculative pressure as average volatility on major commodities has risen significantly by about 33 per cent post its imposition. Considering the transaction tax, income tax and service tax aspects and decline in the trading volume attributed solely to the CTT imposition, it is found that CTT results in huge revenue loss to the exchequer. It is estimated that at the current CTT rate, government is losing an annual net tax revenue worth ₹30 billion. Even at a lower rate of 0.001 per cent (which is one-tenth of the current rate of 0.01%), the government’s fiscal loss is expected to be about ₹2.50 billion. Even if we make a conservative assumption that CTT accounts for only 25 per cent decline in the trading volumes, the optimal CTT rate, in terms of tax revenue collections, is found at 0.003 per cent, well below the current rate. There is, therefore, no justification for retaining CTT on the commodity futures trading in India as it leads to a huge revenue loss to the government, owing to reduced trading activity and trade migration. Withdrawal of CTT would be ideal for Indian commodities market development, improving its liquidity and making it more internationally competitive.
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Vințe, Claudiu, Marcel Ausloos, and Titus Felix Furtună. "A Volatility Estimator of Stock Market Indices Based on the Intrinsic Entropy Model." Entropy 23, no. 4 (April 19, 2021): 484. http://dx.doi.org/10.3390/e23040484.
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Grasping the historical volatility of stock market indices and accurately estimating are two of the major focuses of those involved in the financial securities industry and derivative instruments pricing. This paper presents the results of employing the intrinsic entropy model as a substitute for estimating the volatility of stock market indices. Diverging from the widely used volatility models that take into account only the elements related to the traded prices, namely the open, high, low, and close prices of a trading day (OHLC), the intrinsic entropy model takes into account the traded volumes during the considered time frame as well. We adjust the intraday intrinsic entropy model that we introduced earlier for exchange-traded securities in order to connect daily OHLC prices with the ratio of the corresponding daily volume to the overall volume traded in the considered period. The intrinsic entropy model conceptualizes this ratio as entropic probability or market credence assigned to the corresponding price level. The intrinsic entropy is computed using historical daily data for traded market indices (S&P 500, Dow 30, NYSE Composite, NASDAQ Composite, Nikkei 225, and Hang Seng Index). We compare the results produced by the intrinsic entropy model with the volatility estimates obtained for the same data sets using widely employed industry volatility estimators. The intrinsic entropy model proves to consistently deliver reliable estimates for various time frames while showing peculiarly high values for the coefficient of variation, with the estimates falling in a significantly lower interval range compared with those provided by the other advanced volatility estimators.
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Ahmed, Walid M. A. "The asymmetric price-volume relation revisited: evidence from Qatar." Journal of Asia Business Studies 12, no. 2 (May 8, 2018): 193–219. http://dx.doi.org/10.1108/jabs-11-2015-0194.
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Purpose This study aims to revisit the stock price–volume relations, providing new evidence from the emerging market of Qatar. In particular, three main issues are examined using both aggregate market- and sector-level data. First, the return–volume relation and whether or not this relation is asymmetric. Second, the common characteristics of return volatility; and third, the nature of the relation between trading volume and return volatility. Design/methodology/approach The study uses the OLS and VAR modeling approaches to examine the contemporaneous and dynamic (causal) relations between index returns and trading volume, respectively, while an EGARCH-X(1,1) model is used to analyze the volatility–volume relation. The data set comprises daily index observations and the corresponding trading volumes for the entire market and the individual seven sectors of the Qatar Exchange (i.e. banks and financial services, consumer goods and services, industrials, insurance, real estate, telecommunications and transportation). Findings The empirical analysis reports evidence of a positive contemporaneous return–volume relation in all sectors barring transportation and insurance. This relation appears to be asymmetric for all sectors. For the market and almost all sectors, there is no significant causality between returns and volume. By and large, these findings lend support for the implications of the mixture of distributions hypothesis (MDH). Lastly, the information content of lagged volume seems to have an important role in predicting the future dynamics of return volatility in all sectors, with the industrials being the exception. Practical implications The findings provide important implications for portfolio managers and investors, given that the volume of transactions is generally found to be informative about the price movement of sector indices. Specifically, tracking the behavior of trading volume over time can give a broad portrayal of the future direction of market prices and volatility of equity, thereby enriching the information set available to investors for decision-making. Originality/value Based on both market- and sector-level data from the emerging stock market of Qatar, this study attempts to fill an important void in the literature by examining the return–volume and volatility–volume linkages.
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Radikoko, Ishmael, and Emmanuel Ndjadingwe. "Investigating the Effects of Dividends Pay-out on Stock Prices and Traded Equity Volumes of BSE Listed Firms." International Journal Of Innovation And Economic Development 1, no. 4 (2015): 24–37. http://dx.doi.org/10.18775/ijied.1849-7551-7020.2015.14.2002.
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The main objective of this study is to examine the effect of dividend pay-out on the prices of stock in Botswana’s equity market as well as the effect of traded volumes of such stocks. Other objectives of the research are to determine the optimal pay-out ratio based on the profits of the firm and to determine the optimal time to declare and pay dividends. We use quota-sampling technique and selected 5 companies from the 22 domestic listed companies in the Botswana Stock Exchange. The companies under consideration are Barclay Bank, RDCP, Chobe, Engen and Sefalana Plcs. These companies are chosen based on the availability of daily closing trading information for the past five years and easiness to get information to use for our study that includes dividends pay-outs, profits made, volumes traded, etc. The result of this study reveals that there is a direct relationship between dividend announcement, ex-dividends, dividend pay-out ratio and volume of stock traded and the stock price in Botswana. Furthermore, the study concludes that there is a direct relationship between change in dividends and change in dividend per share. Lastly, the finding reveals that most of the companies sampled pay dividends between December and March. We recommend that companies should have an optimal dividend policy as this have been proven to increase firm value. We also recommend that firms should announce dividends around December to March to counter the end of year effect that usually suppresses stock prices.
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Rizal Yulianto, Mochamad, Zulfani Anggraini, and Nurasik. "Perbedaan Harga Saham Dan Volume Transaksi Sebelum Dan Sesudah Pengumuman Kasus Covid-19 (Studi Pada Indeks Saham LQ-45)." AKUA: Jurnal Akuntansi dan Keuangan 1, no. 1 (January 10, 2022): 01–08. http://dx.doi.org/10.54259/akua.v1i1.133.
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The purpose of this research is to find out whether there are differences in stock prices and transaction volumes due to the announcement of the Covid-19 case. This research includes quantitative research. The population of companies in this study are companies listed on the LQ-45 stock index. Data in the form of daily closing stock prices and trading volume activity data, namely 5 days before and after the first case of Covid-19 was announced. For the data analysis method, this study applies a nonparametric difference test, namely the Wilcoxon Signed Ranks Test with the SPSS 25 program. Based on the results of this study, it shows that the significance value is 0.000 < 0.05, so there is a difference between stock prices before and after the Covid-19 case was announced. Stock prices tend to decline. Meanwhile, the results of the transaction volume research show that if the significance value is 0.488 > 0.05, it means that there is an insignificant difference between before and after the Covid-19 case was announced. The volume of stock transactions has increased more than decreased.
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DOUADY, RAPHAEL, and ANTOINE KORNPROBST. "AN EMPIRICAL APPROACH TO FINANCIAL CRISIS INDICATORS BASED ON RANDOM MATRICES." International Journal of Theoretical and Applied Finance 21, no. 03 (May 2018): 1850022. http://dx.doi.org/10.1142/s021902491850022x.
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The aim of this work is to build a class of financial crisis indicators based on the spectral properties of the dynamics of market data. After choosing an appropriate size for a rolling window, the historical market data inside this rolling window are seen every trading day as a random matrix from which a correlation matrix is obtained. Our goal is to study the correlations between the assets that constitute this market and look for reproducible patterns that are indicative of an impending financial crisis. A weighting of the assets in the market is then introduced and is proportional to the daily traded volumes. This manipulation is realized in order to give more importance to the most liquid assets. Our financial crisis indicators are based on the spectral radius of this weighted correlation matrix. The idea behind this type of financial crisis indicators is that large eigenvalues are a sign of dynamic instability. The out-of-sample predictive power of the financial crisis indicators in this framework is then demonstrated, in particular by using them as decision-making tools in a protective put strategy.
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Ahmed, Walid M. A. "Cross-border equity flows and market volatility: the case of Qatar Exchange." International Journal of Emerging Markets 11, no. 3 (July 18, 2016): 395–418. http://dx.doi.org/10.1108/ijoem-11-2013-0177.
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Purpose – Extending the extant literature and using Qatar’s equity market as a case study, this paper aims to look into the potential impacts of foreign investor groups’ trading activities on market volatility in comparison with those of Qatar’s domestic investor counterparts. Design/methodology/approach – The dataset is comprised of daily aggregated values of stock purchases and sales made separately by four investor groups, namely, foreign individual investors, foreign institutional investors, domestic individual investors, and domestic institutional investors. An ex post measure of volatility introduced by Rogers and Satchell (1991) is employed. Four proxies for investor trading are considered separately in the analysis. The objective of the study is empirically addressed in the context of the Generalized Method of Moments estimation technique. Findings – In general, there exists substantial contemporaneous price impact associated with foreign equity investment in the Qatari capital market, despite the fact that foreigners’ buy and sell trades are not as large as those of their domestic counterparts. More specifically, foreign institutional sales (purchases) tend to increase (reduce) market volatility. Like those of foreign institutions, the sell trades by foreign individuals have a positive impact on volatility. On the other hand, domestic institutional purchases are significantly negatively related with market volatility, whereas the sell trades by the same category have no impact on volatility. Finally, surprises in foreigners’ trading volumes turn out to be responsible for adding to volatility. Practical implications – Although a sudden reversal of foreign capital flows can pose a real threat to the stability of the Qatari capital market, such capital flows are deemed to be an indispensable vehicle for enhancing the liquidity and efficiency of the market. Accordingly, policy makers in Qatar should overhaul the current foreign investment legislation to make it even more streamlined and better suited to achieving the country’s strategic vision for the market. Foremost in these reforms is relaxing the stringent 25 percent foreign ownership restriction. Such a relaxation process is highly recommended to be phased in only gradually, in order to weigh its pros and cons. In this regard, the authorities concerned should consider embarking on a range of procedures intended to ward off the adverse ramifications of foreign capital outflows. Originality/value – To the author’s best knowledge, no study about the impact of foreign equity flows on domestic markets has been so far conducted using trading data from the Qatari market. This work presents one such attempt.
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Anđelković, Branislav. "Hegemony for Beginners: Egyptian Activity in the Southern Levant during the Second Half of the Fourth Millennium B.C." Issues in Ethnology and Anthropology 7, no. 3 (March 1, 2016): 793–807. http://dx.doi.org/10.21301/eap.v7i3.9.
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After a modest start in the mid-20th century, thousands of Protodynastic Egyptian objects have been unearthed and identified as such in the Southern Levant, including serekh-signs of several Dynasty 0 (Narmer, "Double Falcon", Ny-Hor, IryHor, Ka), and 1st Dynasty (Hor Aha) pharaohs. The explanatory models presented so far fail to integrate the totality of the archaeologically manifested parameters, especially considering the impact of the last fifteen years of finds and their contextual and other analysis, into the proper semiotic matrix. The conundrum of Egyptian activity in the Southern Levant displays, at the same time, features of a small-scale trading partner, a colonizer, and a suzerain. Egyptian pottery of local origin provides an indication of a south-north flow of the Egyptian daily-life repertoire of pottery types, or rather their contents, between the Egyptian-related sites, that clearly demonstrates an Egyptian distribution system operating on an intra-regional level in the Early Bronze IB Southern Levant. The ‘Egyptian phenomenon’ is far from being unique since reestablishment of a similar geopolitical pattern, only on a considerably greater scale, can be recognized during the New Kingdom – the Egyptian province in Asia.
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MATHIVANAN, Sandeepkumar, and Prabhu JAYAGOPAL. "A Big Data Virtualization Role in Agriculture: A Comprehensive Review." Walailak Journal of Science and Technology (WJST) 16, no. 2 (September 3, 2018): 55–70. http://dx.doi.org/10.48048/wjst.2019.3620.
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Big data is a collection of large volumes of data sets which are more complicated to analyze using standard data processing methods. It also emphasizes parameters like data variety and velocity data. Big data will play a most significant role in our daily life regarding applications like healthcare electronic commerce, agriculture, telecommunication, government, and financial trading. In the agriculture domain, big data is an optimal method to increase the productivity of farming by gathering and processing information like plant growth, farmland monitoring, greenhouse gases monitoring, climate change, soil monitoring and so forth. Virtualization is an emerging technique that can be combined with big data in agriculture. Virtualization has been used extensively in research for a long time, the term “virtual” entities affecting a real-life form. In agriculture, it has many more physical objects, sensors, and devices. This physical object is virtualized and has digital representation to store, communicate and process via the internet. The information from the virtual object has a large volume of data which helps meaningful data analysis or aspects to make application services like decision making, problem notification, and information handling. This paper provides a comprehensive review of big data virtualization in the agriculture domain. The virtualization methodology, and tools used by many researchers is surveyed.
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Park, Yongmi, Ho-Seon Park, Subin Han, Kyucheol Hwang, Seunghyun Lee, Jin-Young Choi, Jae-Bum Lee, et al. "Intra–Community Scale Variability of Air Quality in the Center of a Megacity in South Korea: A High-Density Cost-Effective Sensor Network." Applied Sciences 11, no. 19 (September 30, 2021): 9105. http://dx.doi.org/10.3390/app11199105.
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To investigate the spatial and temporal variability of air quality (CO, NO2, O3, and PM2.5) with a high spatial resolution in various adjacent micro-environments, 30 sets of sensor-nodes were deployed within an 800 × 800 m monitoring domain in the center of the largest megacity (Seoul) in South Korea. The sensor network was operated in summer and winter. The daily variation in air pollutant concentrations revealed a similar trend, with discernible concentration differences among monitoring sub-sites and a government-operated air quality monitoring station. These differences in pollutant levels (except PM2.5) among the sub-sites were pronounced in the daytime with high volumes of traffic. The coefficient of divergence and Pearson correlation coefficient showed that spatial and temporal variability was more significant in summer than winter. Ozone displayed the greatest spatial variability, with little temporal variability among the sub-sites and a negative correlation with NO2, implying that ozone concentrations were primarily determined by vehicular NOX emissions due to NO titration effects under the urban canopy. The PM2.5 concentration displayed homogeneous spatial and temporal distributions over the entire monitoring period, implying that PM2.5 monitoring with at least a 1 × 1 km resolution is sufficient to examine the spatial and temporal heterogeneity in urban areas.
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Yeung, Kay K., Maarten J. van der Laan, Jan J. Wever, Paul F. G. M. van Waes, and Jan D. Blankensteijn. "New Post-Imaging Software Provides Fast and Accurate Volume Data from CTA Surveillance after Endovascular Aneurysm Repair." Journal of Endovascular Therapy 10, no. 5 (October 2003): 887–93. http://dx.doi.org/10.1177/152660280301000507.
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Purpose: To quantify intra- and interobserver variabilities when measuring total aneurysm volume after endovascular aneurysm repair using the Vitrea 2 System and to compare it in terms of accuracy and processing time with the gold standard methods using the Easy Vision workstation. Methods: Total aneurysm volumes from 30 postendograft CTA datasets were randomly selected from a database consisting of ∼400 CTA datasets recorded in 89 patients. The intra- and interobserver variabilities were measured on the Vitrea workstation by 2 investigators. The intermodality variability was calculated for the same measurements using the Easy Vision workstation. The differences of each pair of measurements were plotted against their mean, and the repeatability coefficient (RC) was calculated. The mean differences were also expressed as a percentage of the first measurements. Results: The intraobserver mean difference was 1.6 mL (1.4%) with an RC of 10.8 mL (10.1%) and the interobserver mean difference was −1.4 mL (–1.4%) with an RC of 11.7 mL (10.2%). The intermodality mean difference was 1.8 mL (2.0%) with an RC of 15.8 mL (11.1%). The Vitrea workstation required a median of 8 minutes (interquartile range 7–10) for 1 observer and 6 minutes (interquartile range 5–8) for the other to perform a complete volume segmentation of each patient dataset compared to an estimated average of 30 minutes using the Easy Vision workstation. Conclusions: The Vitrea workstation provides fast and accurate volume data from spiral CTA follow-up of endovascular aneurysm repair. This software may enhance the acceptability of volume surveillance in daily practice.
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Bruce, Sadia, and Spain. "A Comparative Study of Bitcoin’s Price Fluctuations and Twitter Sentiments." International Journal of Economics, Business and Management Research 07, no. 01 (2023): 10–16. http://dx.doi.org/10.51505/ijebmr.2023.7102.
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This study is going to determine whether the sentiments in Twitter discourse about Bitcoin have an influence on the overall market and pricing of Bitcoin trades. The study aims to reveal the correlation between the volatility of the price of Bitcoin and how it relates to the sentiments in Twitter discourse. A large dataset of tweets mentioning Bitcoin has been amassed from the Twitter API between the months of February and July 2021, which will then be analysed against the Bitcoin trade performance. For this study, different predictive and descriptive models were applied that are equally important for data analysis. The sentiment for overall daily discourse has been categorised into three polarities, i.e., positive, neutral and negative using the VADER sentiment analysis. The overall polarity is then derived from a compounded and normalised dataset of each of the above-mentioned valencies for any given day. By utilising this study, it is hoped that potential Bitcoin buyers may make better and informed decisions about their purchases and that this study could be generalised to a broader analysis of social media discourse and how such means of communication could be used to drive consumer choice. Our results unequivocally prove that Twitter sentiments have a slight impact on the price and trading volumes of Bitcoin but the cryptocurrency has a unique way of sailing the storm of negative sentiments
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Chang, Chia-Lin, and Michael McAleer. "Modeling Latent Carbon Emission Prices for Japan: Theory and Practice." Energies 12, no. 21 (November 5, 2019): 4222. http://dx.doi.org/10.3390/en12214222.
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Climate change and global warming are significantly affected by carbon emissions that arise from the burning of fossil fuels, specifically coal, oil, and gas. Accurate prices are essential for the purposes of measuring, capturing, storing, and trading in carbon emissions at regional, national, and international levels, especially as carbon emissions can be taxed appropriately when the price is known and widely accepted. This paper uses a novel Capital (K), Labor (L), Energy (E) and Materials (M) (or KLEM) production function approach to calculate the latent carbon emission prices, where carbon emission is the output and capital (K), labor (L), energy (E) (or electricity), and materials (M) are the inputs for the production process. The variables K, L, and M are essentially fixed on a daily or monthly basis, whereas E can be changed more frequently, such as daily or monthly, so that changes in carbon emissions depend on changes in E. If prices are assumed to depend on the average cost pricing, the prices of carbon emissions and energy may be approximated by an energy production model with a constant factor of proportionality, so that carbon emission prices are a function of energy prices. Using this novel modeling approach, this paper estimates the carbon emission prices for Japan using seasonally adjusted and unadjusted monthly data on the volumes of carbon emissions and energy, as well as energy prices, from December 2008 to April 2018. The econometric models show that, as sources of electricity, the logarithms of coal and oil, though not Liquefied Natural Gas (LNG,) are statistically significant in explaining the logarithm of carbon emissions, with oil being more significant than coal. The models generally displayed a high power in predicting the latent prices of carbon emissions. The usefulness of the empirical findings suggest that the methodology can also be applied for other countries where carbon emission prices are latent.
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Hirayama, Kenjiro, and Yoshiro Tsutsui. "International Stock Price Co-movement." Asian Economic Papers 12, no. 3 (October 2013): 157–91. http://dx.doi.org/10.1162/asep_a_00242.
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Two possible causes of international stock price co-movement are examined: the existence of global common shocks and portfolio adjustments by international investors. Empirical analyses indicate that the former explains a significant part of the co-movement and the latter is unlikely to play an important role. We extend the analysis to intra-day high-frequency data. For example, when the Tokyo Stock Exchange begins its daily trading at 9:00 A.M. Japan Standard Time (JST), stock prices in Tokyo exhibit responses to preceding changes in New York. An analysis with minute-byminute data indicates that Tokyo's response to New York dissipates within about six minutes after opening. On the other hand, when the New York Stock Exchange (NYSE) opens at 9:30 A.M. Eastern Standard Time (EST), its response to Tokyo dissipates within 14 minutes. Thus, the movement of stock prices is transmitted rapidly across countries. Finally real-time simultaneous interactions between Shanghai (Shenzhen) and Tokyo are analyzed for a 30-minute period in the morning and a 60-minute period in the afternoon. Investors in Tokyo are watching stock prices in Shanghai, but not vice versa. Tight regulations on Chinese investors to prevent them from holding foreign stocks may be the reason why they do not pay any attention to stock price movements in Tokyo.
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Chen, Xiaoyue, Bin Li, and Andrew C. Worthington. "Higher moments and US industry returns: realized skewness and kurtosis." Review of Accounting and Finance 20, no. 1 (March 29, 2021): 1–22. http://dx.doi.org/10.1108/raf-06-2020-0171.
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Purpose The purpose of this paper is to examine the relationships between the higher moments of returns (realized skewness and kurtosis) and subsequent returns at the industry level, with a focus on both empirical predictability and practical application via trading strategies. Design/methodology/approach Daily returns for 48 US industries over the period 1970–2019 from Kenneth French’s data library are used to calculate the higher moments and to construct short- and medium-term single-sort trading strategies. The analysis adjusts returns for common risk factors (market, size, value, investment, profitability and illiquidity) to confirm whether conventional asset pricing models can capture these relationships. Findings Past skewness positively relates to subsequent industry returns and this relationship is unexplained by common risk factors. There is also a time-varying effect in which the predictive role of skewness is much stronger over business cycle expansions than recessions, a result consistent with varying investor optimism. However, there is no significant relationship between kurtosis and subsequent industry returns. The analysis confirms robustness using both value- and equal-weighted returns. Research limitations/implications The calculation of realized moments conventionally uses high-frequency intra-day data, regrettably unavailable for industries. In addition, the chosen portfolio-sorting method may omit some information, as it compares only average group returns. Nonetheless, the close relationship between skewness and future returns at the industry level suggests variations in returns unexplained by common risk factors. This enriches knowledge of market anomalies and questions yet again weak-form market efficiency and the validity of conventional asset pricing models. One suggestion is that it is possible to significantly improve the existing multi-factor asset pricing models by including industry skewness as a risk factor. Practical implications Given the relationship between skewness and future returns at the industry level, investors may predict subsequent industry returns to select better-performing funds. They may even construct trading strategies based on return distributions that would generate abnormal returns. Further, as the evaluation of individual stocks also contains industry information, and stocks in industries with better performance earn higher returns, risks related to industry return distributions can also shed light on individual stock picking. Originality/value While there is abundant evidence of the relationships between higher moments and future returns at the firm level, there is little at the industry level. Further, by testing whether there is time variation in the relationship between industry higher moments and future returns, the paper yields novel evidence concerning the asymmetric effect of stock return predictability over business cycles. Finally, the analysis supplements firm-level results focusing only on the decomposed components of higher moments.
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Shaikh, Imlak. "The Relation between Implied Volatility Index and Crude Oil Prices." Engineering Economics 30, no. 5 (December 14, 2019): 556–66. http://dx.doi.org/10.5755/j01.ee.30.5.21611.
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Crude oil is a global commodity traded across the world market. The prices of the commodity over an extended period for crude oil have been analyzed using daily prices of crude oil futures and the implied volatility index (OVX). This paper aims to find the predictability of various parameters on the basis of time using neural network and quantile regression methods. Several estimates have been shown based on Barone, Adesi, and Whaley’s (BAW) model of neural network. Estimation parameters include opening, closing, highest and lowest price of the commodity and volumes traded for a given commodity on each trading day. The neural network estimates explain that future prices of the WTI/USO can be predicted with minimal error, and similar can be used to predict future volatility. The quantile regression results suggest that crude oil prices and OVX are strongly associated. The asymmetric association between the WTI/USO and OVX explains that the volatility feedback effect holds good for the OVX market. Bai and Perron least squares estimate evidence of the presence of a break in the time series. The main results uncover several interesting facts that implied volatility tends to remain calm during the global financial crises and higher throughout the post crisis period. The empirical outcome on the OVX market provides some practical implications for the trader and investor, in which oil futures can serve better to hedge the crude price volatility. The crude oil producer can short hedge enough through volatility futures and options to maintain the future quantity of crude to be produced.
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Molot, Lewis A., Peter J. Dillon, and Gillian M. Booth. "Whole-Lake and Nearshore Water Chemistry In Bowland Lake Before and After Treatment with CaCO3." Canadian Journal of Fisheries and Aquatic Sciences 47, no. 2 (February 1, 1990): 412–21. http://dx.doi.org/10.1139/f90-044.
Full textAbstract:
After neutralization of Bowland Lake, a clear oligotrophic acidified lake, with CaCO3 in August 1983, the whole-lake pH and alkalinity increased from 4.9 and −6 μeq∙L−1 to 6.7 and 89 μeq∙L−1, respectively. Total whole-lake Al decreased gradually from 130 to 30 μg∙L−1, Mn decreased from 80 to 28 μg∙L−1 and the lake became less transparent as dissolved organic carbon (DOC) increased and Secchi depth decreased. Metals other than Al and Mn remained low and did not respond to neutralization. Between August 1983 and March 1986, about 40% of the added alkalinity of Bowland Lake was lost. Decreases of whole-lake pH following snowmelt occurred prior to but not after neutralization. Neutralization of lake water did not prevent acidic melt water from forming a distinctive acidic zone < 1 m thick beneath the ice. The melt layer was more acidic than lake water, it was colder and therefore less dense, it usually contained higher Al, and it was dilute with lower conductivity and Ca. intra-site variation was probably due to variable volumes of melt water received. A snowmelt model based on daily air temperature and precipitation predicted intermittent recharge of groundwater reservoirs during snowmelt. However, runoff was continually observed nearshore under ice suggesting that groundwater reservoirs continued to discharge after recharge ended or that the residence time of melt waters in the littoral zone was relatively long.
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Horbach, T., H. Wolf, H. C. Michaells, W. Wagner, A. Hoffmann, A. Schmidt, and H. Beck. "A Fixed-Dose Combination of Low Molecular Weight Heparin with Dihydroergotamine versus Adjusted-Dose Unfractionated Heparin in the Prevention of Deep-Vein Thrombosis after Total Hip Replacement." Thrombosis and Haemostasis 75, no. 02 (1996): 246–50. http://dx.doi.org/10.1055/s-0038-1650253.
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SummaryThe low dose heparin regimen (LDH) is not appropriate for prevention of intra- and postoperative thromboembolic complications in high risk patients, especially those undergoing elective hip replacement. Despite LDH prophylaxis, the incidence of deep-vein thrombosis (DVT) remains in a range of 20 to 35%. Adjusted-dose unfractionated heparin prophylaxis is thought to be one of the most effective regimens for thrombosis prophylaxis in this indication, but it requires two or three daily injections as well as precise monitoring of the activated partial thromboplastin time (aPTT). As an attractive alternative, we investigated the efficacy and safety of the low molecular weight heparin (LMWH) certoparin combined with dihydroergotamine (DHE) given once daily.In a randomised, open clinical trial, a total number of 305 patients undergoing total elective hip replacement were enrolled and divided into two groups, either receiving a fixed-dose combination of LMWH (3,000 IU) and DHE (0.5 mg) subcutaneously once daily, or adjusted-dose unfractionated heparin (UFH) subcutaneously every 8 h. The UFH dosage was adjusted daily to keep an aPTT of about 50 s. The aPTT was determined 3 h after the morning injection. During the study, the starting dose (15,000 IU/day) was increased to a plateau value of 28,800 ± 7,150 IU/day (mean ± SD) to maintain the aPTT in the prescribed range. The plateau value was achieved after 8 postoperative days. For analysis of efficacy 289 patients were evaluable. The occurrence of deep vein thrombosis was determined by bilateral ascending venography, which was performed on the same day in patients with clinical signs suggesting DVT; and in all remaining patients at the end of the prophylaxis period. Deep vein thrombosis was diagnosed in 17 of 142 patients (12.0%) treated with LMWH/DHE and in 13 of 147 patients (8.8%) treated with adjusted-dose UFH. Combined distal-proximal thrombosis was more frequently in patients receiving UFH (n = 5; 3.4%) compared to the LMWH/DHE group (n = 2; 1.4%). These differences are statistically not significant. In the UFH group one case of non-fatal pulmonary embolism occurred. Both prophylaxis regimens were well tolerated; wound bleeding was observed in 8 (5.3%) patients in the LMWH group and in 6 (4.0%) patients in the UFH group. Intraoperative blood-loss volume (mean±SD) was 751 ± 339 ml (LMWH/DHE) and 736 ± 380 ml (UFH), whereas postoperative drain-loss volume (mean ± SD) was found to be 523 ± 333 ml (LMWH/DHE) and 581 ± 404 ml (UFH). Whole blood transfusion volumes (mean ± SD) were 570 ± 202 ml (LMWH/DHE) and 748 ± 455 ml (UFH). Additionally, red cell replacement volumes (mean ± SD) were 804 ± 435 ml (LMWH/DHE) and 720 ± 328 ml (UHF). Revision of wound or additional drainage were necessary in 3 LMWH/DHE and 7 UFH patients. One patient needed reoperation due to bleeding, 3 (2.0%) had petechia and 1 exhibited an allergic exanthema, all of them in the UFH group. A slight erythema at the injection site was observed in 6 (3.9%) patients receiving LMWH/DHE. During the course of prophylaxis, injection hematomas were documented in 57.9% (LMWH/DHE) and in 61.4% (UFH) of the patients. All differences were statistically not significant.Single daily subcutaneous injections of LMWH/DHE appeared to be safe and efficacious compared to adjusted-dose UFH for prophylaxis of DVT in high-risk patients.
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Tatzber, Franz, Willibald Wonisch, Sonja Lackner, Meinrad Lindschinger, Werner Pursch, Ulrike Resch, Christopher Trummer, et al. "A Micromethod for Polyphenol High-Throughput Screening Saves 90 Percent Reagents and Sample Volume." Antioxidants 9, no. 1 (December 21, 2019): 11. http://dx.doi.org/10.3390/antiox9010011.
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There is ample evidence that polyphenols are important natural substances with pronounced antioxidative properties. This study aimed to develop a fast and reliable method to determine total polyphenol content (TPC) in foodstuffs and human samples. The microtitration format offers the advantage of low sample volumes in the microlitre range, facilitating high-throughput screening with 40 samples simultaneously. We accordingly adjusted the so-called Folin–Ciocalteu method to a microtitre format (polyphenols microtitre—PPm) with 90% reduction of reagents. The assay was standardized with gallic acid in the range between 0.1 and 3 mM, using a 20 µL sample volume. The intra-assay coefficient of variation (CV) was less than 5%, and inter-assay CV was in the range of 10%. Wavelength was measured at 766 nm after two hours of incubation. This micromethod correlates significantly with both the classical Folin–Ciocalteu method and High-Performance Thin-Layer Chromatography (HPTLC) (r2 = 0.9829). We further observed a significant correlation between PPm and total antioxidants (r2 = 0.918). The highest polyphenol concentrations were obtained for red, blue, and black fruits, vegetables, and juices. Extracts of red grapes could be harvested almost sugar free and might serve as a basis for polyphenol supplementation. Beer, flour, and bread contained polyphenol concentrations sufficient to meet the minimal daily requirement. We conclude that PPm is a sensitive and reliable method that detects polyphenols even in samples diluted 10-fold. The literature strongly recommends further investigations on the effects of polyphenol uptake on human and animal health.
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Olsen, Jeffrey R., Parag J. Parikh, Todd A. DeWees, Lindsey Olsen, William G. Hawkins, Steven M. Strasberg, Kian-Huat Lim, et al. "Prospective phase I study of nab-paclitaxel plus gemcitabine with concurrent MR-guided IMRT in patients with locally advanced or borderline resectable pancreatic cancer." Journal of Clinical Oncology 34, no. 4_suppl (February 1, 2016): TPS480. http://dx.doi.org/10.1200/jco.2016.34.4_suppl.tps480.
Full textAbstract:
TPS480 Background: Radiotherapy (RT) for locally advanced and borderline resectable pancreatic cancer (LABPC) is controversial as potential local control benefits are often obscured by high rates of distant progression. However, local failure remains a significant cause of morbidity among patients without distant progression after initial chemotherapy, although toxicity concerns may limit delivery of optimal systemic therapy concurrent with RT. Given known systemic efficacy and radiosensitization effects of nab-paclitaxel (A) with gemcitabine (G), we initiated a phase I study of nab-paclitaxel with gemcitabine (AG) and concurrent intensity modulated radiation therapy with magnetic resonance guidance (MR-IMRT) for LABPC. Methods: A planned 24 patients with LABPC will be enrolled to a phase I dose escalation trial using the Time-to-Event Continual Reassessment Method (TITE-CRM) design. Following one lead-in cycle of GA, MR-IMRT is administered daily with concurrent weekly GA for a total of 25 fractions in 5 weeks. The initial dose levels for RT and AG, respectively, are: 40 Gy MR-IMRT, 75 mg/m2 A and 600mg/m2 G. The maximum possible dose level is 60 Gy MR-IMRT, 100mg/m2 A and 1000mg/m2 G. To reduce toxicity risk, MR-IMRT volumes include the primary tumor only, with cine-MR used for intra-fraction tumor tracking in place of fiducial markers. The primary endpoint is determination of the maximum tolerated dose level, with secondary endpoints including rate of conversion to resectable disease, progression- free survival, overall survival, and patient reported quality of life. Clinical trial information: NCT02283372.