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Journal articles on the topic 'Limited stock'

Author: Grafiati
Published: 29 June 2021
Last updated: 4 February 2022

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1

Kokkalis, Alexandros, Anne Maria Eikeset, Uffe H. Thygesen, Petur Steingrund, and Ken H. Andersen. "Estimating uncertainty of data limited stock assessments." ICES Journal of Marine Science 74, no. 1 (August 22, 2016): 69–77. http://dx.doi.org/10.1093/icesjms/fsw145.

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Many methods exist to assess the fishing status of data-limited stocks; however, little is known about the accuracy or the uncertainty of such assessments. Here we evaluate a new size-based data-limited stock assessment method by applying it to well-assessed, data-rich fish stocks treated as data-limited. Particular emphasis is put on providing uncertainty estimates of the data-limited assessment. We assess four cod stocks in the North-East Atlantic and compare our estimates of stock status (F/Fmsy) with the official assessments. The estimated stock status of all four cod stocks followed the established stock assessments remarkably well and the official assessments fell well within the uncertainty bounds. The estimation of spawning stock biomass followed the same trends as the official assessment, but not the same levels. We conclude that the data-limited assessment method can be used for stock assessment and that the uncertainty estimates are reliable. Further work is needed to quantify the spawning biomass of the stock.
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Guan, Lisha, Yong Chen, Robert Boenish, Xianshi Jin, and Xiujuan Shan. "Improving data-limited stock assessment with sporadic stock index information in stock reduction analysis." Canadian Journal of Fisheries and Aquatic Sciences 77, no. 5 (May 2020): 857–68. http://dx.doi.org/10.1139/cjfas-2018-0500.

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As most exploited fisheries lack a coherent time series of biomass index, development of data-limited stock assessment methods such as stock reduction analysis (SRA), is critical for fishery stock assessment due to their modest data requirements for estimating stock status and overfishing catch limits. In this study, we propose that sporadic time series of biomass indices, if available, may be fully utilized to inform priors of recent relative biomass (BT/B1) for data-limited stocks. We evaluated the performance of SRA incorporating this index-based prior by comparing two other common SRA priors (a deterministic prior set at 40% of the unfished biomass and a catch-based prior) with estimates from the likelihood-based assessments of 91 fish stocks from the RAM Legacy database. We extended our analysis by evaluating performance based on life history attributes and two depletion levels with BT/BMSY equaling 1 as the breakpoint. Results suggest index-based priors enhance accuracy for fish stocks at both depletion levels. We demonstrate that performance of SRA can be affected by three factors: the reliability of priors for BT/B1, recent depletion level, and life history.
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Guo, Hui. "Limited Stock Market Participation and Asset Prices in a Dynamic Economy." Journal of Financial and Quantitative Analysis 39, no. 3 (September 2004): 495–516. http://dx.doi.org/10.1017/s0022109000004002.

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AbstractThis paper presents a consumption-based model that explains the equity premium puzzle through two channels. First, because of borrowing constraints, the shareholder cannot completely diversify his income risk and requires a sizable risk premium on stocks. Second, because of limited stock market participation, the precautionary saving demand lowers the risk-free rate but not stock return and generates a substantial liquidity premium. This model also replicates many other salient features of the data, including the first two moments of the risk-free rate, excess stock volatility, stock return predictability, and the unstable relation between stock volatility and the dividend yield.
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Rothenstein, Roland, and Klaus Pawelzik. "Limited profit in predictable stock markets." Physica A: Statistical Mechanics and its Applications 348 (March 2005): 419–27. http://dx.doi.org/10.1016/j.physa.2004.09.010.

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5

Fischer, Simon H., José A. A. De Oliveira, and Laurence T. Kell. "Linking the performance of a data-limited empirical catch rule to life-history traits." ICES Journal of Marine Science 77, no. 5 (June 12, 2020): 1914–26. http://dx.doi.org/10.1093/icesjms/fsaa054.

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Abstract Worldwide, the majorities of fish stocks are data-limited and lack fully quantitative stock assessments. Within ICES, such data-limited stocks are currently managed by setting total allowable catch without the use of target reference points. To ensure that such advice is precautionary, we used management strategy evaluation to evaluate an empirical rule that bases catch advice on recent catches, information from a biomass survey index, catch length frequencies, and MSY reference point proxies. Twenty-nine fish stocks were simulated covering a wide range of life histories. The performance of the rule varied substantially between stocks, and the risk of breaching limit reference points was inversely correlated to the von Bertalanffy growth parameter k. Stocks with k>0.32 year−1 had a high probability of stock collapse. A time series cluster analysis revealed four types of dynamics, i.e. groups with similar terminal spawning stock biomass (collapsed, BMSY, 2BMSY, 3BMSY). It was shown that a single generic catch rule cannot be applied across all life histories, and management should instead be linked to life-history traits, and in particular, the nature of the time series of stock metrics. The lessons learnt can help future work to shape scientific research into data-limited fisheries management and to ensure that fisheries are MSY compliant and precautionary.
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Chong, Lisa, Tobias K. Mildenberger, Merrill B. Rudd, Marc H. Taylor, Jason M. Cope, Trevor A. Branch, Matthias Wolff, and Moritz Stäbler. "Performance evaluation of data-limited, length-based stock assessment methods." ICES Journal of Marine Science 77, no. 1 (November 11, 2019): 97–108. http://dx.doi.org/10.1093/icesjms/fsz212.

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Abstract Performance evaluation of data-limited, length-based methods is instrumental in determining and quantifying their accuracy under various scenarios and in providing guidance about model applicability and limitations. We conducted a simulation–estimation analysis to compare the performance of four length-based stock assessment methods: length-based Thompson and Bell (TB), length-based spawning potential ratio (LBSPR), length-based integrated mixed effects (LIME), and length-based risk analysis (LBRA), under varying life history, exploitation status, and recruitment error scenarios. Across all scenarios, TB and LBSPR were the most consistent and accurate assessment methods. LBRA is highly biased, but precautionary, and LIME is more suitable for assessments with time-series longer than a year. All methods have difficulties when assessing short-lived species. The methods are less accurate in estimating the degree of recruitment overfishing when the stocks are severely overexploited, and inconsistent in determining growth overfishing when the stocks are underexploited. Increased recruitment error reduces precision but can decrease bias in estimations. This study highlights the importance of quantifying the accuracy of stock assessment methods and testing methods under different scenarios to determine their strengths and weaknesses and provides guidance on which methods to employ in various situations.
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7

Chrysafi, Anna, Jason M. Cope, and Anna Kuparinen. "Eliciting expert knowledge to inform stock status for data-limited stock assessments." Marine Policy 101 (March 2019): 167–76. http://dx.doi.org/10.1016/j.marpol.2017.11.012.

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8

Pepin, Pierre. "Reconsidering the impossible — linking environmental drivers to growth, mortality, and recruitment of fish." Canadian Journal of Fisheries and Aquatic Sciences 73, no. 2 (February 2016): 205–15. http://dx.doi.org/10.1139/cjfas-2015-0091.

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After a century of research into the drivers of early life (EL) growth and mortality, fisheries science has acquired limited capacity to predict future recruitment. A meta-analysis of stock assessment time series revealed that it may be difficult to identify stock– or environmental–recruitment drivers given limited variability in spawner biomass, recruitment, and survivorship in most populations. In nearly 50% of the stocks, there was limited information at low spawner biomass, limiting the reliability of fits to stock–recruitment models. Furthermore, variations in survivorship in 50% of year-classes resulted in less than a 2.5-fold change in recruitment. Simulations of three scenarios of change in EL growth and mortality rates demonstrated that they must covary positively to reproduce variations in survivorship consistent with observations. The potentially limited reliability of stock–recruitment relationships to predict year-class strength in many stocks and the low variability in survivorship in a large proportion of year-classes has important implications for the development of projections of stock productivity used in scientific advice. Furthermore, if a positive growth–mortality relationship underlies variations in survivorship, new research approaches are required to understand the trophic relationships that govern the dynamics of early life stages of fish and patterns of recruitment variability.
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9

Pulkkinen, Henni, and Samu Mäntyniemi. "Maximum survival of eggs as the key parameter of stock–recruit meta-analysis: accounting for parameter and structural uncertainty." Canadian Journal of Fisheries and Aquatic Sciences 70, no. 4 (April 2013): 527–33. http://dx.doi.org/10.1139/cjfas-2012-0268.

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Despite their name, hierarchical stock–recruit meta-analyses are often parameterized in terms of steepness, which depends not only on the assumed stock–recruitment relationship but also on the recruit–spawner relationship. This parameterization requires assumptions about the reproductive potential of the recruit that are not desirable if the focus of the study is limited to the spawning–recruitment phase instead of the full life cycle. Thus, usage of steepness should be avoided in studies that aim to produce informative priors for the stock–recruit relationship for use in studies of other salmon stocks. An alternative key parameter for stock–recruit models is the maximum survival of eggs, which is the slope at the origin of the stock–recruitment curve when spawning stock size is defined in terms of the number of eggs. Furthermore, the current widely used practices in stock–recruit modeling could be improved by taking into account the stock-specific model uncertainty. We use the method of Bayesian model averaging to build a hierarchical stock–recruit model that allows stock-specific model structures with Beverton–Holt, Ricker, and hockey stick models as alternatives, all of which can be parameterized with the maximum survival of eggs. We illustrate our approach by analyzing nine previously published datasets for Atlantic salmon (Salmo salar).
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10

Gomathi, M., and Dr S. Nirmala. "Analysis of Nifty Movement on Share Prices of Selected Construction Companies." INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 1, no. 3 (September 27, 2012): 59–65. http://dx.doi.org/10.24297/ijmit.v1i3.1421.

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This study aims at analyzing and predicting the price movements of construction companies stocks contributing to the NIFTY50 Index. To analyze the volatility of telecom stock and understand the behavior of stock prices in construction sector stocks i.e. (JP ASSOCIATES LIMITED, DLF LIMITED, GAMMON INDIA LIMITED, PUNJ LLOYD LIMITED, HCC LIMITED). The data for these stocks are collected from magazines, newspaper and websites. The stocks are analyzed by monitoring their respective price movements using technical tools. The technical tools used in this study are Exponential moving average, Relative strength index, Rate of change, MACD. Using these tools the trend over the recent past was deciphered. The expected trend in the immediate future was also predicted. Technical Analysis studies the price and volume movement in the market and predicts the future. It helps in identifying that the best time to buy and sell equity. Technical Analysis is a method of evaluating equities by analyzing the statistics generated by market activity, such as past prices and volume.
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11

Fischer, Simon H., José A. A. De Oliveira, John D. Mumford, and Laurence T. Kell. "Using a genetic algorithm to optimize a data-limited catch rule." ICES Journal of Marine Science 78, no. 4 (March 6, 2021): 1311–23. http://dx.doi.org/10.1093/icesjms/fsab018.

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Abstract Many data-limited fish stocks worldwide require management advice. Simple empirical management procedures have been used to manage data-limited fisheries but do not necessarily ensure compliance with maximum sustainable yield objectives and precautionary principles. Genetic algorithms are efficient optimization procedures for which the objectives are formalized as a fitness function. This optimization can be included when testing management procedures in a management strategy evaluation. This study explored the application of a genetic algorithm to an empirical catch rule and found that this approach could substantially improve the performance of the catch rule. The optimized parameterization and the magnitude of the improvement were dependent on the specific stock, stock status, and definition of the fitness function. The genetic algorithm proved to be an efficient and automated method for tuning the catch rule and removed the need for manual intervention during the optimization process. Therefore, we conclude that the approach could also be applied to other management procedures, case-specific tuning, and even data-rich stocks. Finally, we recommend the phasing out of the current generic ICES “2 over 3” advice rule in favour of case-specific catch rules of the form tested here, although we caution that neither works well for fast-growing stocks.
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12

Wetzel, Chantell R., and André E. Punt. "Performance of a fisheries catch-at-age model (Stock Synthesis) in data-limited situations." Marine and Freshwater Research 62, no. 8 (2011): 927. http://dx.doi.org/10.1071/mf11006.

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Limited data are a common challenge posed to fisheries stock assessment. A simulation framework was applied to examine the impact of limited data and data type on the performance of a widely used catch-at-age stock-assessment method (Stock Synthesis). The estimation method provided negatively biased estimates of current spawning-stock biomass (SSB) relative to the unfished level (final depletion) when only recent survey indices were available. Estimation of quantities of management interest (unfished SSB, virgin recruitment, target fishing mortality and final depletion) improved substantially even when only minimal-length-composition data from the survey were available. However, the estimates of some quantities (final depletion and unfished SSB) remained biased (either positively or negatively) even in the scenarios with the most data (length compositions, age compositions and survey indices). The probability of overestimating yield at the target SSB relative to the true such yield was ~50%, a risk-neutral result, for all the scenarios that included length-composition data. Our results highlight the importance of length-composition data for the performance of an age-structured assessment model, and are encouraging for the assessment of data-limited stocks.
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13

Poldi, Kelly Cristina, and Marcos Nereu Arenales. "Heuristics for the one-dimensional cutting stock problem with limited multiple stock lengths." Computers & Operations Research 36, no. 6 (June 2009): 2074–81. http://dx.doi.org/10.1016/j.cor.2008.07.001.

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14

Johnson, Samuel D. N., and Sean P. Cox. "Evaluating the role of data quality when sharing information in hierarchical multistock assessment models, with an application to Dover sole." Canadian Journal of Fisheries and Aquatic Sciences 76, no. 10 (October 2019): 1819–35. http://dx.doi.org/10.1139/cjfas-2018-0048.

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An emerging approach to data-limited fisheries stock assessment uses hierarchical multistock assessment models to group stocks together, sharing information from data-rich to data-poor stocks. In this paper, we simulate data-rich and data-poor fishery and survey data scenarios for a complex of Dover sole (Microstomus pacificus) stocks. Simulated data for individual stocks were used to compare estimation performance for single-stock and hierarchical multistock versions of a Schaefer production model. The single-stock and best-performing multistock models were then used in stock assessments for the real Dover sole data. Multistock models often had lower estimation errors than single-stock models when assessment data had low statistical power. Relative errors for productivity and relative biomass parameters were lower for multistock assessment model configurations. In addition, multistock models that estimated hierarchical priors for survey catchability performed the best under data-poor scenarios. We conclude that hierarchical multistock assessment models are useful for data-limited stocks and could provide a more flexible alternative to data pooling and catch-only methods; however, these models are subject to nonlinear side effects of parameter shrinkage. Therefore, we recommend testing hierarchical multistock models in closed-loop simulations before application to real fishery management systems.
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15

Teng, Xiao, Tuo Wang, Xiang Zhang, Long Lan, and Zhigang Luo. "Enhancing Stock Price Trend Prediction via a Time-Sensitive Data Augmentation Method." Complexity 2020 (February 17, 2020): 1–8. http://dx.doi.org/10.1155/2020/6737951.

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Stock trend prediction refers to predicting future price trend of stocks for seeking profit maximum of stock investment. Although it has aroused broad attention in stock markets, it is still a tough task not only because the stock markets are complex and easily volatile but also because real short-term stock data is so limited that existing stock prediction models could be far from perfect, especially for deep neural networks. As a kind of time-series data, the underlying patterns of stock data are easily influenced by any tiny noises. Thus, how to augment limited stock price data is an open problem in stock trend prediction, since most data augmentation schemes adopted in image processing cannot be brutally used here. To this end, we devise a simple yet effective time-sensitive data augmentation method for stock trend prediction. To be specific, we augment data by corrupting high-frequency patterns of original stock price data as well as preserving low-frequency ones in the frame of wavelet transformation. The proposed method is motivated by the fact that low-frequency patterns without noisy corruptions do not hurt the true patterns of stock price data. Besides, a transformation technique is proposed to recognize the importance of the patterns at varied time points, that is, the information is time-sensitive. A series of experiments carried out on a real stock price dataset including 50 corporation stocks verify the efficacy of our data augmentation method.
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Pathania, Arti, and Ravikant Swami. "Stock Price Analysis for Reliance Industry Limited (RIL)." Asian Journal of Management 9, no. 1 (2018): 313. http://dx.doi.org/10.5958/2321-5763.2018.00047.1.

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17

Hasan, Rajib, and Abdullah Shahid. "How Does Experts’ Limited Attention Affect Stock Prices?" Academy of Management Proceedings 2016, no. 1 (January 2016): 16826. http://dx.doi.org/10.5465/ambpp.2016.16826abstract.

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18

Polkovnichenko, Valery. "Limited stock market participation and the equity premium." Finance Research Letters 1, no. 1 (March 2004): 24–34. http://dx.doi.org/10.1016/j.frl.2003.11.001.

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19

Ceylan, Ozcan. "Limited information-processing capacity and asymmetric stock correlations." Quantitative Finance 15, no. 6 (November 21, 2013): 1031–39. http://dx.doi.org/10.1080/14697688.2013.808374.

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20

Vestman, Roine. "Limited Stock Market Participation Among Renters and Homeowners." Review of Financial Studies 32, no. 4 (August 10, 2018): 1494–535. http://dx.doi.org/10.1093/rfs/hhy089.

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Abstract The stock market participation rate among homeowners is twice as high as among renters. This paper builds a life-cycle portfolio choice model with endogenous housing tenure choice. A stylized form of preference heterogeneity generates a substantial difference in participation rates. A majority of households have a large savings motive and choose to be homeowners and participate. A minority of households have a small savings motive and find it less worthwhile to participate. Fewer of these households become homeowners. Difference-in-difference regressions on panel data do not find evidence of a crowding-out effect of homeownership on participation, supporting the message that preference heterogeneity matters. Received January 25, 2017; editorial decision March 21, 2018 by Editor Wei Jiang. Authors have furnished an Online Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
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21

Meeson, Richard. "Making internal fixation work with limited bone stock." In Practice 39, no. 3 (February 20, 2017): 98–106. http://dx.doi.org/10.1136/inp.j595.

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22

Bentley, Nokome. "Data and time poverty in fisheries estimation: potential approaches and solutions." ICES Journal of Marine Science 72, no. 1 (March 5, 2014): 186–93. http://dx.doi.org/10.1093/icesjms/fsu023.

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Abstract The increasingly sophisticated methods developed for stock assessment are not always suited to data-poor fisheries. Data-poor fisheries are often low in value, so the researcher time available for their assessment is also small. The dual constraints of reduced data and reduced time make stock assessments for low-value stocks particularly challenging. Prior probability distributions are useful for transferring knowledge from data-rich to data-poor fisheries. When data are limited, it is important to make the most of what few data is available. However, fully understanding potential biases in data are just as important in the data-poor context as it is in data-rich fisheries. A key aspect of stock assessment is peer review. Providing a comprehensive, yet concise, set of diagnostics is crucial to a stock assessment where time is limited. Against the standards by which data-rich stock assessments are judged, stock assessments for data-poor stocks are likely to be found deficient. A key challenge is to maintain a balance between the opposing risks of inappropriate management “action” due to assessment inaccuracy, and inappropriate management “inaction” due to assessment uncertainty.
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23

Aalto, Emilius A., Francesco Ferretti, Matthew V. Lauretta, John F. Walter, Michael J. W. Stokesbury, Robert J. Schallert, and Barbara A. Block. "Stock-of-origin catch estimation of Atlantic bluefin tuna (Thunnus thynnus) based on observed spatial distributions." Canadian Journal of Fisheries and Aquatic Sciences 78, no. 8 (August 2021): 1193–204. http://dx.doi.org/10.1139/cjfas-2019-0445.

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Atlantic bluefin tuna (Thunnus thynnus) are a large, highly migratory fish distributed throughout the North Atlantic Ocean and adjacent seas currently managed as two discrete stocks: western and eastern. Both stocks forage in the North Atlantic, and a high degree of intermixing occurs, which combined with limited single-stock survey data makes it difficult to assess the abundance and status of individual populations. In this study, we used movement patterns from a multidecadal tagging dataset to create monthly distribution maps for these two major stocks. We then used these maps to separate the overall catch records into stock-specific catch (catch per unit effort, CPUE) time series. We identified an increase in the past two decades in the proportion of catch estimated to come from the eastern stock, attributable to a decrease in CPUE in regions dominated by the western stock, relative to other regions. The stock-specific catch series can be used to improve the accuracy of stock assessments and inform spatial management.
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Chen, Yan, Changyu Hu, Wenjie Zhang, and Qing Li. "CEO Exposure, Media Influence, and Stock Returns." Journal of Global Information Management 29, no. 6 (November 2021): 1–19. http://dx.doi.org/10.4018/jgim.20211101.oa43.

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Media-aware stock movements are well acknowledged by the behavioral finance. As the soul of a firm, CEO’s media behavior is critical to the operation of a firm. CEO’s exposure could have captured the investors’ attention and enhanced the media effect in the stock market in terms of the “eyeball economics”, or CEO’s overexposure could have attracted more attention than firm-specific news, which attenuate the media effect in the stock market due to the investors’ limited attention. This study systematically explores the role and the moderating effect of CEO’s media behavior on the relationship between media content and stock markets. Using daily frequency data for a sample of Chinese stocks, this study shows that higher CEO media exposure attenuates the media effect on stock markets, especially consumer-related stocks.
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Pons, Maite, Jason M. Cope, and Laurence T. Kell. "Comparing performance of catch-based and length-based stock assessment methods in data-limited fisheries." Canadian Journal of Fisheries and Aquatic Sciences 77, no. 6 (June 2020): 1026–37. http://dx.doi.org/10.1139/cjfas-2019-0276.

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The quantity of data from many small-scale fisheries is insufficient to allow for the application of conventional assessment methods. Even though in many countries they are moving to closed-loop simulations to assess the performance of different management procedures in data-limited situations, managers in most developing countries are still demanding information on stock status. In this study we use the common metric of harvest rate to evaluate and compare the performance of the following catch-only and length-only assessment models: catch – maximum sustainable yield (Catch-MSY), depletion-based stock reduction analysis (DBSRA), simple Stock Synthesis (SSS), an extension of Catch-MSY (CMSY), length-based spawning potential ratio (LBSPR), length-based integrated mixed effects (LIME), and length-based Bayesian (LBB). In general, results were more biased for slightly depleted than for highly depleted stocks and for long-lived than for short-lived species. Length-based models, such as LIME, performed as well as catch-based methods in many scenarios, and among the catch-based models, the one with the best performance was SSS followed by CMSY.
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Friedmann, Ralph, and Walter G. Sanddorf-Köhle. "A conditional distribution model for limited stock index returns." Journal of Economic Dynamics and Control 31, no. 3 (March 2007): 721–41. http://dx.doi.org/10.1016/j.jedc.2006.01.003.

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27

Li, Yun-Xian, Jiang-Cheng Li, Ai-Jun Yang, and Nian-Sheng Tang. "The mean time-limited crash rate of stock price." Physics Letters A 381, no. 17 (May 2017): 1477–83. http://dx.doi.org/10.1016/j.physleta.2017.02.038.

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28

Ramos, Sofia B., Pedro Latoeiro, and Helena Veiga. "Limited attention, salience of information and stock market activity." Economic Modelling 87 (May 2020): 92–108. http://dx.doi.org/10.1016/j.econmod.2019.07.010.

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Kirkulak Uludag, Berna, and Muzammil Khurshid. "Volatility spillover from the Chinese stock market to E7 and G7 stock markets." Journal of Economic Studies 46, no. 1 (January 7, 2019): 90–105. http://dx.doi.org/10.1108/jes-01-2017-0014.

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PurposeThe purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.Design/methodology/approachThe authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.FindingsThe findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.Originality/valueTo the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.
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Hong, Harrison, and Jeremy C. Stein. "Disagreement and the Stock Market." Journal of Economic Perspectives 21, no. 2 (April 1, 2007): 109–28. http://dx.doi.org/10.1257/jep.21.2.109.

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A large catalog of variables with no apparent connection to risk has been shown to forecast stock returns, both in the time series and the cross-section. For instance, we see medium-term momentum and post-earnings drift in returns—the tendency for stocks that have had unusually high past returns or good earnings news to continue to deliver relatively strong returns over the subsequent six to twelve months (and vice-versa for stocks with low past returns or bad earnings news); we also see longer-run fundamental reversion—the tendency for “glamour” stocks with high ratios of market value to earnings, cashflows, or book value to deliver weak returns over the subsequent several years (and vice-versa for “value” stocks with low ratios of market value to fundamentals). To explain these patterns of predictability in stock returns, we advocate a particular class of heterogeneous-agent models that we call “disagreement models.” Disagreement models may incorporate work on gradual information flow, limited attention, and heterogeneous priors, but all highlight the importance of differences in the beliefs of investors. Disagreement models hold the promise of delivering a comprehensive joint account of stock prices and trading volume—and some of the most interesting empirical patterns in the stock market are linked to volume.
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31

Hameed, Allaudeen, and G. Mujtaba Mian. "Industries and Stock Return Reversals." Journal of Financial and Quantitative Analysis 50, no. 1-2 (July 14, 2014): 89–117. http://dx.doi.org/10.1017/s0022109014000404.

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AbstractThis paper documents pervasive evidence of intra-industry reversals in monthly returns. Unlike the conventional reversal strategy based on stock returns relative to the market portfolio, we document intra-industry return reversals that are larger in magnitude, consistently present over time, and prevalent across subgroups of stocks, including large and liquid stocks. These return reversals are driven by order imbalances and noninformational shocks. Consistent with reversals representing compensation for supplying liquidity, intra-industry reversals are stronger following aggregate market declines and volatile times, reflecting binding capital constraints and limited risk-bearing capacity of liquidity providers.
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Karadas, Serkan, William McAndrew, and Minh Tam Tammy Schlosky. "Local corruption and local stock returns." Journal of Financial Crime 26, no. 4 (October 7, 2019): 1065–77. http://dx.doi.org/10.1108/jfc-01-2018-0011.

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Purpose The purpose of this study is to investigate the effect of corruption on stock returns in the USA. In particular, this study examines the relationship between corruption in a state (i.e. local corruption) and stock returns of firms headquartered in that state (i.e. local returns). Design/methodology/approach This paper uses the Fama–MacBeth two-step regressions. In the first step, the authors estimate the coefficients on the market, size, value and momentum factors for individual stocks. In the second step, they use those coefficients along with the corruption score of the state where stocks are headquartered to explain stock returns. Findings This paper finds that corruption in a state adversely affects stock returns of firms headquartered in that state. It further documents that the effect of corruption on stock returns is limited to geographically concentrated firms. Originality/value To the best of the authors’ knowledge, this paper is the first to document the effect of state-level corruption on individual stock returns in the USA using the Fama–MacBeth regressions. This study contributes to the literature by documenting the effect of local corruption on local stock returns in a low corruption country.
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崔祯植 Jeong‐sig Choi. "Some Opinions on Foreign-invested Limited Liability Company and Foreign-invested Joint-stock Limited Company." Chinese Law Review 10, no. ll (December 2008): 49–62. http://dx.doi.org/10.22415/clr.2008.10..003.

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Le Pape, Olivier, Youen Vermard, Jérome Guitton, Elliot J. Brown, Karen E. van de Wolfshaar, Romuald N. Lipcius, Josianne G. Støttrup, and Kenneth A. Rose. "The use and performance of survey-based pre-recruit abundance indices for possible inclusion in stock assessments of coastal-dependent species." ICES Journal of Marine Science 77, no. 5 (June 24, 2020): 1953–65. http://dx.doi.org/10.1093/icesjms/fsaa051.

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Abstract We reviewed the use of survey-based pre-recruit abundance indices in short-term recruitment forecasts for fish species relying on coastal habitats at the juvenile stage and that are assessed by ICES. We collated information from stock assessment reports and from a questionnaire filled out by the stock assessors. Among the 78 stocks with juvenile coastal dependence, 49 use short-term forecasts in stock assessment. Survey-based pre-recruit abundance indices were available for 35 of these stocks, but only 14 were used to forecast recruitment. The questionnaire indicated that the limited use of survey-based pre-recruit abundance indices was primarily due to sampling inefficiency, which may preclude reliable recruitment estimates. The sampling is inefficient because the juvenile coastal distribution is outside the geographical area covered by large-scale surveys or targeted coastal surveys are conducted on limited spatial and temporal scales. However, our analysis of the relationship between survey-based pre-recruit indices and assessment-generated recruitment indices revealed that survey-based pre-recruit abundance indices were sufficiently accurate to provide useful information for predicting future recruitment. We recommend expansion of the use of survey-based indices of pre-recruit abundance in stock assessment and recruitment forecasting, and consideration of how to include juveniles in ongoing and future surveys.
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Priyanto, Panji. "The Value of GARP Investing: Evidence from the Indonesian Stock Exchange." JABE (JOURNAL OF ACCOUNTING AND BUSINESS EDUCATION) 5, no. 2 (March 30, 2021): 9. http://dx.doi.org/10.26675/jabe.v5i2.15743.

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The purpose of this study was to examine whether or not the GARP in selecting the stock portfolios can provide a more stable growth rate of return when compared to the value stock and growth stock as well as to examine the stock return on value stock and growth stock based on the changes in its fundamentals. The population in this study was all companies listed on the Indonesia Stock Exchange (known as IDX) in the period of 2015-2019. The samples were selected using a comparative-quantitative approach and consisted of 20 companies: seven companies included in the value stock portfolio category and ten companies included in the portfolio category. Growth stock and three companies were included in the GARP's stock portfolio category. The formation of stock portfolios in the company's fundamentals was based on price to book value ratio, price-earnings ratio, and price-earnings growth ratio. This study used the ANOVA method equipped with SPSS by performing four tests: Homogeneity of Variance, Between-Subject, Post Hoc, and Homogenous Subset test. The results of this study show that there were differences in the portfolio return of value stocks, growth stocks, and GARP stocks on the Indonesia Stock Exchange in the period of 2015-2019. Meanwhile, the GARP investment strategy was stable for the growth when compared to the value investment and growth investment in the Indonesia Stock Exchange in the period of 2015-2019. The implementation of GARP concept in managing the investment portfolios and criteria for choosing the stocks have the profitable growth, first in forming the GARP because investors in the stock market tend to expect obtaining high investment returns with a limited time horizon. The implementation of GARP concept has prevented the investors from the value trap because the GARP strategy is a hybrid solution for the growth stock and value stock, thus. The GARP investors will experience a combination of returns
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Sidorenko, V. G., Chzho Min Aung, V. M. Alekseev, E. N. Rozenberg, and V. I. Umanskii. "Planning Electric-Rolling-Stock Maintenance in Conditions of Limited Resources." Russian Electrical Engineering 88, no. 12 (December 2017): 839–41. http://dx.doi.org/10.3103/s106837121712015x.

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37

Hirshleifer, David, Sonya S. Lim, and Siew Hong Teoh. "Limited Investor Attention and Stock Market Misreactions to Accounting Information." Review of Asset Pricing Studies 1, no. 1 (July 27, 2011): 35–73. http://dx.doi.org/10.1093/rapstu/rar002.

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38

Vronskaya, Mariya, and Ekaterina Vasilenko. "Abuse of law in limited liability and joint stock companies." Территория новых возможностей. Вестник Владивостокского государственного университета экономики и сервиса, no. 4 (2020): 137–45. http://dx.doi.org/10.24866/vvsu/2073-3984/2020-4/137-145.

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В настоящей статье рассмотрена дефиниция «злоупотребление правом», сделаны выводы о том, какие действия физического лица в рамках корпоративных отношений являются правомерным поведением, а какие – злоупотреблением. Определено, чем отличаются формы злоупотребления правом в хозяйственных обществах друг от друга и как в связи с этим разрешается судебная практика. Сформированы рекомендации для субъектов, действующих правомерно, с целью защиты от правовых и материальных последствий, возникающих в связи с недобросовестным поведением других участников, а также предложены средства, с помощью которых уда- стся минимизировать количество злоупотреблений в обществах с ограниченной ответственностью и акционерных обществах. Ключевые слова и словосочетания: злоупотребление правом, добросовестность, хозяйственные общества, общество с ограниченной ответственностью, акционерное общество, корпоративные отношения.
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39

Pons, Maite, Laurence Kell, Merrill B. Rudd, Jason M. Cope, and Flávia Lucena Frédou. "Performance of length-based data-limited methods in a multifleet context: application to small tunas, mackerels, and bonitos in the Atlantic Ocean." ICES Journal of Marine Science 76, no. 4 (February 6, 2019): 960–73. http://dx.doi.org/10.1093/icesjms/fsz004.

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Abstract Large scombrids, commercial tuna species, are regularly assessed and managed. However, most of the small scombrids, many mackerels and bonitos, lack accurate catch data to implement traditional stock assessments despite their economic importance in many small-scale fisheries. In this study, we analysed different approaches using length composition data from multiple fleets with different gear selectivity to assess small scombrids in the Atlantic Ocean. Using simulated populations, we compared two length-based methods (length-based spawning potential ratio and length-based integrated mixed effects ), under different length data grouping scenarios. We found that using length data from the fleet targeting the broadest range of sizes resulted in the lowest bias in spawning potential ratio of all options tested. Based on these results, we used biological and length data to estimate a quantitative proxy of current stock status for ten small scombrid stocks in the Atlantic Ocean. We found that some stocks are likely to be overfished, such as little tunny (Euthynnus alletteratus) in the Southeast Atlantic and wahoo (Acanthocybium solandri) in the Northwest Atlantic. This is a starting point in the estimation of stock status for these species, but should not be thought of as a replacement for other more data-intensive assessments.
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Berry, Thomas, and Keith Jacks Gamble. "The Information Content of Investors' Expectations for Risk and Return." Quarterly Journal of Finance 03, no. 03n04 (September 2013): 1350017. http://dx.doi.org/10.1142/s2010139213500171.

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This study reveals the information content of individual investors' risk-adjusted return expectations. Although individual investors overestimate the performance of their stock purchases on an average, the cross-sectional variation in their risk-adjusted return expectations is predictive of future risk-adjusted stock performance. Stock purchases that investors expect to outperform the most do outperform the stock purchases that investors expect to outperform the least by an annualized alpha of 16%. The best performing stocks are those that investors with excellent experience expect to outperform the most while the worst performing stocks are those that investors with limited experience expect to outperform the least. The most experienced investors appear to be successfully using information gathered from personal experience with the company's products or services, contact with someone who works for or with the company on a regular basis, and proximity to the company's operations.
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41

Armitage, A. R., and J. W. Fourqurean. "Carbon storage in seagrass soils: long-term nutrient history exceeds the effects of near-term nutrient enrichment." Biogeosciences 13, no. 1 (January 15, 2016): 313–21. http://dx.doi.org/10.5194/bg-13-313-2016.

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Abstract. The carbon sequestration potential in coastal soils is linked to aboveground and belowground plant productivity and biomass, which in turn, is directly and indirectly influenced by nutrient input. We evaluated the influence of long-term and near-term nutrient input on aboveground and belowground carbon accumulation in seagrass beds, using a nutrient enrichment (nitrogen and phosphorus) experiment embedded within a naturally occurring, long-term gradient of phosphorus availability within Florida Bay (USA). We measured organic carbon stocks in soils and above- and belowground seagrass biomass after 17 months of experimental nutrient addition. At the nutrient-limited sites, phosphorus addition increased the carbon stock in aboveground seagrass biomass by more than 300 %; belowground seagrass carbon stock increased by 50–100 %. Soil carbon content slightly decreased ( ∼ 10 %) in response to phosphorus addition. There was a strong but non-linear relationship between soil carbon and Thalassia testudinum leaf nitrogen : phosphorus (N : P) or belowground seagrass carbon stock. When seagrass leaf N : P exceeded an approximate threshold of 75 : 1, or when belowground seagrass carbon stock was less than 100 g m−2, there was less than 3 % organic carbon in the sediment. Despite the marked difference in soil carbon between phosphorus-limited and phosphorus-replete areas of Florida Bay, all areas of the bay had relatively high soil carbon stocks near or above the global median of 1.8 % organic carbon. The relatively high carbon content in the soils indicates that seagrass beds have extremely high carbon storage potential, even in nutrient-limited areas with low biomass or productivity.
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42

Armitage, A. R., and J. W. Fourqurean. "Carbon storage in seagrass soils: long-term nutrient history exceeds the effects of near-term nutrient enrichment." Biogeosciences Discussions 12, no. 19 (October 2, 2015): 16285–312. http://dx.doi.org/10.5194/bgd-12-16285-2015.

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Abstract. The carbon sequestration potential in coastal soils is linked to aboveground and belowground plant productivity and biomass, which in turn, is directly and indirectly influenced by nutrient input. We evaluated the influence of long-term and near-term nutrient input on aboveground and belowground carbon accumulation in seagrass beds, using a nutrient enrichment (nitrogen and phosphorus) experiment embedded within a naturally occurring, long-term gradient of phosphorus availability within Florida Bay (USA). We measured organic carbon stocks in soils and above- and belowground seagrass biomass after 17 months of experimental nutrient addition. At the nutrient-limited sites, phosphorus addition increased the carbon stock in aboveground seagrass biomass by more than 300 %; belowground seagrass carbon stock increased by 50–100 %. Soil carbon content slightly decreased (~ 10 %) in response to phosphorus addition. There was a strong but non-linear relationship between soil carbon and Thalassia testudinum leaf nitrogen: phosphorus (N : P) or belowground seagrass carbon stock. When seagrass leaf N : P exceeded a threshold of 75 : 1, or when belowground seagrass carbon stock was less than 100 g m−2, there was less than 3 % organic carbon in the sediment. Despite the marked difference in soil carbon between phosphorus-limited and phosphorus-replete areas of Florida Bay, all areas of the bay had relatively high soil carbon stocks near or above the global median of 1.8 % organic carbon. The relatively high carbon content in the soils indicates that seagrass beds have extremely high carbon storage potential, even in nutrient-limited areas with low biomass or productivity.
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43

Sayyadi Tooranloo, Hossein, Pedram Azizi, and Ali Sayyahpoor. "Analyzing causal relationships of effective factors on the decision making of individual investors to purchase shares." International Journal of Ethics and Systems 36, no. 1 (November 17, 2019): 12–41. http://dx.doi.org/10.1108/ijoes-03-2019-0053.

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Purpose Changes in economic markets have made it necessary to understand the psychology of individual investors. Conducting effective studies on the decision of investors to buy stock in the stock market can be useful. Therefore, it is necessary to identify and prioritize the factors affecting the decision-making of investors to purchase shares of the stock exchange. The purpose of this study was to analyze causal relationships and to weight effective factors on individual investment to purchase shares of Tehran Stock Exchange. Design/methodology/approach The present study is applied research in the term of its purposes and a descriptive-survey one in the term of data gathering methods. The data required in this study was collected through library and field studies. The study population included 35 investment experts. In present study, multi-criteria decision-making techniques in type-2 fuzzy environments have been used to analyze the causal relationships and weighing the factors affecting individual investment in purchasing stock in the stock market. Findings In the study, 4 indicators and 20 sub-indicators influencing individual investors’ decision to purchase shares of Tehran Stock Exchange were selected based on the literature review in the field of investment in the stock exchange, as well as interviews with experts. Analyzing the opinions of experts showed that they have much paid attention to financial index compare to the economic, political and psychological indicators of the market in determining the priority of indicators. In analyzing sub-indicators, it was identified that Iranian investors pay special attention to economic and political developments, political news and international economic developments. Research limitations/implications The present study has been carried out in Iran, and therefore, is geographically limited to Iran. In thematic terms, it is limited to effective factors of individual investments in Tehran Stock Exchange. The statistical population of present study was limited to investing experts in Tehran Stock Exchange. The difference in financial, economic, social and political conditions of individuals was another limitation of present study. The main consequences of research were the explanation of causes of investors’ higher attention to financial factors than economic, political and mental factors of market in buying stocks. Originality/value Given the uncertainty in the market status, using multi-criteria decision-making techniques in financial analysis can help decision-makers to make better decisions. In addition, it would be possible to take into account many variables that do not have a mathematical aspect but are important in decision-making and lead to increased decision-making satisfaction. The research initially analyzed causal relationships of determinants of individual investment on stock exchange for buying stocks through a type-2 fuzzy approach.
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Hélias, Arnaud. "Data for Fish Stock Assessment Obtained from the CMSY Algorithm for all Global FAO Datasets." Data 4, no. 2 (May 24, 2019): 78. http://dx.doi.org/10.3390/data4020078.

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Assessing the state of fish stocks requires the determination of descriptors. They correspond to the absolute and relative (to the carrying capacity of the habitat) fish biomasses in the ecosystem, and the absolute and relative (to the intrinsic growth rate of the population) fishing mortality resulting from catches. This allows, among other things, to compare the catch with the maximum sustainability yield. Some fish stocks are well described and monitored, but for many data-limited stocks, catch time series are remaining the only source of data. Recently, an algorithm (CMSY) has been proposed, allowing an estimation of stock assessment variables from catch and resilience. In this paper, we provide stock reference points for all global fisheries reported by Food and Agriculture Organization (FAO) major fishing area for almost 5000 fish stocks. These data come from the CMSY algorithm for 42% of the stock (75% of the global reported fish catch) and are estimated by aggregated values for the remaining 58%.
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45

Silver, Steven D. "Representing Social Construction in Consumer Activities: Single-Period and Multi-Period Activity Production." Journal of Interdisciplinary Economics 5, no. 3 (July 1994): 139–56. http://dx.doi.org/10.1177/02601079x9400500302.

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Consumers are seen as limited decision makers who set short-term activity levels from their budgets, stocks of experience, and values following a preference-maximizing heuristic. Disturbances to activity levels in their evolution by exogeneties of social and economic environments, and the feedback of activity levels which agents have no systematic ability to anticipate, reset stock and value levels through the interactive relationships among endogenous variables. Agents then solve the maximization problem for a subsequent period using stock and value levels as modified by the evolutionary process. The dependence of a single-period decision on the stock and value constructs is examined and forms for the dynamic evolution of stock and value constructs that represent the feedback of activity levels to stock and value levels are also introduced. Implications of these forms for the social construction of activities are discussed.
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46

M, Rahini, and Vivek Prabu M. "Downtrend of banking sectors using technical analysis." Kongunadu Research Journal 8, no. 1 (March 31, 2021): 36–40. http://dx.doi.org/10.26524/krj.2021.6.

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The Banking industry plays a very significant role in the economy and the development of a country. It is important to our nation’s economy as it caters to the need of credit for all the section of the nation. In this paper, we are focusing on the stocks of Yes Bank Limited, Axis Bank Limited and ICICI Bank Limited and analyze them technically. Using technical analysis, we could predict the future price movements of stocks by examining the present and the past price movements of stocks. It has many tools and indicators like SMA, EMA, RSI, MACD and P&L which are used for forecasting the future stock price and also identify the pattern, trend and it directs when to buy and sell stocks.
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47

Jiang, Jing. "Cross-sectional variation of market efficiency." Review of Accounting and Finance 16, no. 1 (February 13, 2017): 67–85. http://dx.doi.org/10.1108/raf-02-2016-0018.

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Purpose This paper aims to provide evidence that market efficiency varies greatly across individual stock, and across market exchanges. Design/methodology/approach Three approaches, partial adjustment model, Dimson beta model and variance ratio test, are used on a large sample of US stocks. Findings This paper finds prices are closer to random walk benchmarks (i.e. more efficient) for stocks with better liquidity provision, frequent trading, greater return volatility, higher prices, larger market capitalizations and smaller trade sizes. These findings suggest that liquidity stimulates arbitrage activity, which, in turn, enhances market efficiency. Market efficiency also varies with information environment. The results show that stocks with greater information-based trading exhibit higher level of efficiency. Finally, market structure influences market efficiency. New York Stock Exchange stocks achieve higher level of efficiency than NASDAQ stocks do. The empirical results are robust and not driven by differences in stock attributes between the two markets. Research limitations/implications Overall, these results indicate that liquidity provision, stock attributes and market structure exert a significant impact on the realization of market efficiency. Practical implications In addition, this paper is also relevant to both stock exchanges facing increased competition and to market regulators. Originality/value Prior studies offer little evidence on the speed at which new information is impounded into the price. There is also limited evidence regarding how liquidity provision and market structure affect market efficiency. Using a transformation of the speed of price adjustment and other measurements as proxies for individual stock efficiency, this study may shed further lights on our understanding of market efficiency.
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Nadon, Marc O., and Jerald S. Ault. "A stepwise stochastic simulation approach to estimate life history parameters for data-poor fisheries." Canadian Journal of Fisheries and Aquatic Sciences 73, no. 12 (December 2016): 1874–84. http://dx.doi.org/10.1139/cjfas-2015-0303.

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Coastal fisheries are typically characterized by species-rich catch compositions and limited management resources, which typically leads to notably data-poor situations for stock assessment. Some parsimonious stock assessment approaches rely on cost-efficient size composition data, but these also require estimates of life history parameters associated with natural mortality, growth, and maturity. These parameters are unavailable for most exploited stocks. Here, we present a novel approach that uses a local estimate of maximum length and statistical relationships between key life history parameters to build multivariate probability distributions that can be used to parameterize stock assessment models in the absence of species-specific life history data. We tested this approach on three fish species for which empirical length-at-age and maturity data were available (from Hawaii and Guam) and calculated probability distributions of spawning potential ratios (SPR) at different exploitation rates. The life history parameter and SPR probability distributions generated from our data-limited analytical approach compared well with those obtained from bootstrap analyses of the empirical life history data. This work provides a useful new tool that can greatly assist fishery stock assessment scientists and managers in data-poor situations, typical of most of the world’s fisheries.
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Knibb, W. R., J. S. F. Barker, and J. G. Oakeshott. "The genetics of abnormal abdomen, incomplete abdomen, and bobbed in Drosophila buzzatii." Genome 32, no. 5 (October 1, 1989): 754–61. http://dx.doi.org/10.1139/g89-508.

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Five stocks of Drosophila buzzatii with superficially similar abdominal disruptions including partial tergite and sternite loss were isolated by inbreeding. Three of the stocks have indistinguishable phenotypes, the inheritance of which is maternally influenced. This phenotype and its mode of inheritance bear similarities with those of Abnormal abdomen in D. melanogaster. The phenotype in the fourth stock is slightly different and is due to a single autosomal recessive gene, which we denote incomplete abdomen. In the fifth stock the trait is limited to females, and in appearance and mode of inheritance resembles bobbed in D. melanogaster. Furthermore, only in this stock are rDNA deletions evident. The combined frequencies of the three types of abdominal aberration were found to be around 1% in several samples from wild and laboratory populations of D. buzzatii.Key words: Drosophila, abnormal abdomen, ribosomal DNA, selection.
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Eltahir, Yassin Ibrahim, Osama Azmi Sallam, Hussien Omer Osman, and Fethi Klabi. "Does Volatility Generate Major and Minor Stocks in Saudi Stocks Market?" Integrated Journal of Business and Economics 4, no. 1 (January 15, 2020): 14. http://dx.doi.org/10.33019/ijbe.v4i1.239.

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This study attempts to answer the main question: are there reciprocal effects between the variances of the stock returns in the Saudi market, also the answer to a sub-question. What are the leading stocks in the Saudi market?. Study selected a sample of five stocks representing the basic materials, banking, services, food and transport sectors (SABIC, Al Rajhi, Etisalat, Almarai and Al Bahri respectively). The data sample for the period from 2011 to 2016 is taken, which represents the lifespan of the five-year plan. Daily stock returns were calculated during this period. Study applies the M GARCH-VEC methodology to estimate stock return variances and then perform a multiple regression of five equations using the ARCH Heteroscedasticity estimator. Results of the analysis show a positive effect between stock return variances as well as a positive automatic variance of all stocks returns variances. Finally, the results of the regression analysis of the various equations show that the returns variances of SABIC and Al Rajhi stocks have a dominant impact on the rest of the stock's returns. So they are considered as leading stocks in the market. While the variances returns of Etisalat, Almarai and Al Bahri have a limited impact on the rest of the stocks variances returns, so they are considered as minor stocks
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