Journal articles: 'Bull market'

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Brown, Jeff L. "Bull Market." Civil Engineering Magazine Archive 82, no. 1 (January 2012): 62–69. http://dx.doi.org/10.1061/ciegag.0000383.

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Arnott, Robert D., and Peter L. Bernstein. "Bull Market? Bear Market?" Journal of Portfolio Management 24, no. 1 (October 31, 1997): 26–29. http://dx.doi.org/10.3905/jpm.1997.26.

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Montgomery, H. "A bull market (GPS)." IEEE Aerospace and Electronic Systems Magazine 7, no. 8 (August 1992): 26–28. http://dx.doi.org/10.1109/62.151143.

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Caporali, Roberto P. L. "A Statistic Method for the Prediction of the Succession of Bear and Bull Stock Market." International Journal of Basic Sciences and Applied Computing 9, no. 6 (February 28, 2023): 1–7. http://dx.doi.org/10.35940/ijbsac.f0482.029623.

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In this paper, we define an innovative method for predicting the stochastic behavior of the Bull and Bear periods of the stock market. The direct study of the prediction of possible Bull and Bear markets is a different and new approach about the analysis of stock markets. Our work is based on the collection of 40 years of data from the Italian stock market. The proposed solution is defined using the statistical analysis of the Bear and Bull Stock markets and it includes a criterion for statistically generating the most probable values of the next Bear and Bull markets, as well as especially the lengths of the time intervals corresponding to these market situations. We defined a new system for a stock market price trend prediction, where the trend of the succession of Bull and Bear markets can be described by a probability density function given by a Gaussian distribution. Furthermore, we considered the inverses of the relative time intervals as a measure of the speed with which the phenomenon of the Bear market (or, equivalently, the Bull market) develops in that interval of time and therefore, ultimately, it can represent a first statistical weight of the single percentage variation. Again, the time intervals of the individual Bear and Bull market periods are considered, calculated from 01/01/1973. This is based on the hypothesis that a secondary factor of probability is the temporal distance of the event that has already occurred. In this paper, we conduct a comprehensive evaluation of more frequently used statistical methods for evaluating Stock markets, highlighting the novelty of the described method. Simulation results show the ability of the method to define a statistical prediction of the next Bull and Bear markets.

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Kim, Kwansoo, Sang-Yong Tom Lee, and Saïd Assar. "The dynamics of cryptocurrency market behavior: sentiment analysis using Markov chains." Industrial Management & Data Systems 122, no. 2 (November 23, 2021): 365–95. http://dx.doi.org/10.1108/imds-04-2021-0232.

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PurposeThe authors examine cryptocurrency market behavior using a hidden Markov model (HMM). Under the assumption that the cryptocurrency market has unobserved heterogeneity, an HMM allows us to study (1) the extent to which cryptocurrency markets shift due to interactions with social sentiment during a bull or bear market and (2) the heterogeneous pattern of cryptocurrency market behavior under these two market conditions.Design/methodology/approachThe authors advance the HMM model based on two six-month datasets (from November 2017 to April 2018 for a bull market and from December 2018 to May 2019 for a bear market) collected from Google, Twitter, the stock market and cryptocurrency trading platforms in South Korea. Social sentiment data were collected by crawling Bitcoin-related posts on Twitter.FindingsThe authors highlight the reaction of the cryptocurrency market to social sentiment under a bull and a bear market and in two hidden states (an upward and a downward trend). They find: (1) social sentiment is relatively relevant during a bull compared to a bear market. (2) The cryptocurrency market in a downward state, that is, with a local decreasing trend, tends to be more responsive to positive social sentiment. (3) The market in an upward state, that is, with a local increasing trend, tends to better interact with negative social sentiment.Originality/valueThe proposed HMM model contributes to a theoretically grounded understanding of how cryptocurrency markets respond to social sentiment in bull and bear markets through varied sequences adjusted for cryptocurrency market heterogeneity.

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Kanojia, Sunaina, and Neha Arora. "Bull and Bear Phases: An Empirical Perusal of Indian Stock Market NSE and BSE Stock Markets?" GIS Business 11, no. 5 (September 22, 2016): 11–24. http://dx.doi.org/10.26643/gis.v11i5.3410.

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In general, any one known to stock market is acquainted with the phenomenon of bull and bear phases, but whether the traders or investors put air to these phases while making a decision to buy, sell, or stay invested. The present paper attempts to identify and analyze the two most popular market phases, i.e. bull and bear, for better investment decisions with the use of Bry and Boschan Algorithm and time series data. Further, it seeks to analyze the distributional characteristics of the variances in stock returns and search evidence of asymmetries, if any, in volatility under different market conditions which may help to shed light on the bull and bear phases of Indian equity market. The study arrange for evidence that in bull markets, stock prices run far ahead of earnings and for fairly long periods of time. The paper indicates 12 bull and bear phases in the Sensex and Nifty during the sample period of 19 years with the associated factors responsible for the shift of bull and bear market phases. The results provide considerable support for the view that markets choose to ignore adverse possibilities and react with zest to favorable possibilities and market declines can partly be explained by increases in risk.

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Kanojia, Sunaina, and Neha Arora. "Investments, Market Timing and Portfolio Performance across Indian Bull and Bear Markets." Asia-Pacific Journal of Management Research and Innovation 13, no. 3-4 (September 2017): 98–109. http://dx.doi.org/10.1177/2319510x18776403.

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The returns generated from an investment alternative are exponentially higher when espoused with appropriate timings. This article expound on the market timing used by investors to formulate profitable investment strategies in the stock market, which requires gathering of information at both micro- and macro-levels along with market trends to make timely decisions and evaluating the universe of stocks available. The market trends are been broadly classified into bull and bear phases, which have dynamic influence on buying and selling in the stock market. Further, the study supports the retail investors’ participation in the market for long-term to generate higher returns as compared to other conventional alternatives. The study attempts to identify bull and bear market turning points using a formal turning point identification procedure and formulate a profitable investment strategy in bull or bear market phases to maximise the returns. Hence, the present study provides to understand how the two phases influence investment decisions and determine the implications of bull and bear market phases on investors’ investment strategy.

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Zhang, Yuanyuan, Stephen Chan, Jeffrey Chu, and Hana Sulieman. "On the Market Efficiency and Liquidity of High-Frequency Cryptocurrencies in a Bull and Bear Market." Journal of Risk and Financial Management 13, no. 1 (January 3, 2020): 8. http://dx.doi.org/10.3390/jrfm13010008.

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The market for cryptocurrencies has experienced extremely turbulent conditions in recent times, and we can clearly identify strong bull and bear market phenomena over the past year. In this paper, we utilise algorithms for detecting turnings points to identify both bull and bear phases in high-frequency markets for the three largest cryptocurrencies of Bitcoin, Ethereum, and Litecoin. We also examine the market efficiency and liquidity of the selected cryptocurrencies during these periods using high-frequency data. Our findings show that the hourly returns of the three cryptocurrencies during a bull market indicate market efficiency when using the detrended-fluctuation-analysis (DFA) method to analyse the Hurst exponent with a rolling window. However, when conditions turn and there is a bear-market period, we see signs of a more inefficient market. Furthermore, our results indicated differences between the cryptocurrencies in terms of their liquidity during the two market states. Moving from a bull to a bear market, Ethereum and Litecoin appear to become more illiquid, as opposed to Bitcoin, which appears to become more liquid. The motivation to study the high-frequency cryptocurrency market came from the increasing availability of higher-frequency cryptocurrency-pricing data. However, it also comes from a movement towards higher-frequency trading of cryptocurrency. In addition, the efficiency of cryptocurrency markets relates not only to whether prices are predictable and arbitrage opportunities exist, but, more widely, to topics such as testing the profitability of trading strategies and determining the maturity of cryptocurrency markets.

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McChesney, Robert W., and John Nichols. "The Bull Market: Political Advertising." Monthly Review 63, no. 11 (April 1, 2012): 1. http://dx.doi.org/10.14452/mr-063-11-2012-04_1.

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ADAMS, KENNETH. "The Bull Market in Corrections." Prison Journal 76, no. 4 (December 1996): 461–67. http://dx.doi.org/10.1177/0032855596076004006.

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America has experienced a tremendous bull market in corrections, as evidenced by tremendous growth in offender populations. Demand remains at an all-time high, and consumers stand ready to buy any and all prison construction schemes without concern for quality or value. Professional traders in the form of lobbyists and executives of prison-related industries have made a killing, although returns for the average citizen have been decidedly mixed. Emotion will have a way of driving prison populations still higher, because fear is rarely in short supply when it comes to dealing with crime.

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Fang, Fang, Weijia Dong, and Xin Lv. "Asymmetric Reactions of China’s Stock Market to Short-Term Interest Rates." International Journal of Economics and Finance 8, no. 5 (April 25, 2016): 260. http://dx.doi.org/10.5539/ijef.v8n5p260.

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This paper investigates how China’s stock market reacts to short-term interest rates, as represented by the Shanghai Interbank Offered Rate (Shibor). We adopt the Markov Regime Switching model to divide China’s stock market into Medium, Bull and Bear market; and then examine how Shibor influences market returns and risk in different market regimes. We find that short-term interest rates have a significant negative effect on stock returns in Medium and Bull market, but could not affect stock returns in Bear market. In addition, different maturities of Shibor have different effects on stock returns. Furthermore, we find that the short-term interest rates have a negative effect on market risk in Bull market, but a positive effect in Bear market. Our findings show that China’s market is quite peculiar and distinctive from the U.S. market or other developed countries’ markets in many ways.

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Chi, Wei, Robert Brooks, Emawtee Bissoondoyal-Bheenick, and Xueli Tang. "Classifying Chinese bull and bear markets: indices and individual stocks." Studies in Economics and Finance 33, no. 4 (October 3, 2016): 509–31. http://dx.doi.org/10.1108/sef-01-2015-0036.

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Purpose This paper aims to investigate Chinese bull and bear markets. The Chinese stock market has experienced a long period of bear cycle from early 2000 until 2006, and then it fluctuated greatly until 2010. However, the cyclical behaviour of stock markets during this period is less well established. This paper aims to answer the question why the Chinese stock market experienced a long duration of bear market and what factors would have impacted this cyclical behaviour. Design/methodology/approach By comparing the intervals of bull and bear markets between stocks and indices based on a Markov switching model, this paper examines whether different industries or A- and B-share markets could lead to different stock market cyclical behaviour and whether firm size can determine the relationship between the firm stock cycles on the market cycles. Findings This paper finds a high degree of overlapping of bear cycles between stocks and indices and a high level of overlapping between the bear market and a fraction of stock with increasing stock prices. This leads to the conclusion that the stock performance and trading behaviour are widely diversified. Furthermore, the paper finds that the same industry may have different overlapping intervals of bull or bear cycles in the Shanghai and Shenzhen stock markets. Firms with different sizes could have different overlapping intervals with bull or bear cycles. Originality/value This paper fills the literature gap by establishing the cyclical behaviour of stock markets.

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Chen, Muzi, Yuhang Wang, Boyao Wu, and Difang Huang. "Dynamic Analyses of Contagion Risk and Module Evolution on the SSE A-Shares Market Based on Minimum Information Entropy." Entropy 23, no. 4 (April 7, 2021): 434. http://dx.doi.org/10.3390/e23040434.

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The interactive effect is significant in the Chinese stock market, exacerbating the abnormal market volatilities and risk contagion. Based on daily stock returns in the Shanghai Stock Exchange (SSE) A-shares, this paper divides the period between 2005 and 2018 into eight bull and bear market stages to investigate interactive patterns in the Chinese financial market. We employ the Least Absolute Shrinkage and Selection Operator (LASSO) method to construct the stock network, compare the heterogeneity of bull and bear markets, and further use the Map Equation method to analyse the evolution of modules in the SSE A-shares market. Empirical results show that (1) the connected effect is more significant in bear markets than bull markets and gives rise to abnormal volatilities in the stock market; (2) a system module can be found in the network during the first four stages, and the industry aggregation effect leads to module differentiation in the last four stages; (3) some stocks have leading effects on others throughout eight periods, and medium- and small-cap stocks with poor financial conditions are more likely to become risk sources, especially in bear markets. Our conclusions are beneficial to improving investment strategies and making regulatory policies.

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Wainewright, S. A., A. J. Parker, W. E. Holmes, H. Zerby, and L. A. Fitzpatrick. "An economic case study of entire male grain-fed beef from a north-western Queensland production system." Animal Production Science 51, no. 6 (2011): 570. http://dx.doi.org/10.1071/an10266.

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Assessing the differences in gross margins for a north-western Queensland beef-production system was undertaken using herd-budgeting software. The analysis reviewed the viability of producing beef for the domestic market from either a steer or bull production system. A hypothetical herd of 1200 breeders was created for the case study evaluation. An integrated beef production system from breeding to feedlot finishing was found to be less profitable for bull beef production than for steers at the current market prices. Although bull production was more profitable than steer production during the feedlot phase, the production of bulls in this phase failed to compensate for the earlier economic losses in the weaning phase of –AU$24.04 per adult equivalent for bulls. During the feedlot phase, bull production systems had lower break-even sale prices than did steer production systems. In reviewing two pricing scenarios for bulls, it was found that marketing bulls at the same price as steers was the most profitable production system. We conclude that the production of bull beef from a north-western Queensland production system can be profitable only if bulls can be sold without discount relative to steers.

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Valls Pereira, Pedro L., and André Barbosa Oliveira. "Strategies of portfolio investment with estimates of bull and bear markets." Brazilian Review of Finance 19, no. 4 (December 24, 2021): 160–85. http://dx.doi.org/10.12660/rbfin.v19n4.2021.80765.

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The financial market has non-linear patterns, with different return behavior in bull versus bear markets. This article uses multivariate model estimates to study portfolios in changing conditions, and develops investment strategies for portfolios in light of uncertainty about the bear or bull status of the stock market. Portfolios were optimized for the main stocks listed on the Brazilian market index Ibovespa. The portfolios proposed with estimates of changing market status outperformed others over the analyzed period, with rebalancing adjustments made either weekly or monthly.

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ЧИНАРОВ, В. И. "FORMATION OF DOMESTIC BULL SEMEN MARKET." Molochnoe i miasnoe skotovodstvo, no. 8 (February 2, 2022): 7–10. http://dx.doi.org/10.33943/mms.2021.78.19.002.

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Государственные вложения, направленные на развитие отечественного племенного скотоводства, позволили сформировать на всей территории страны широкую сеть племенных заводов, репродукторов и генофондных хозяйств для обеспечения отрасли племенной продукцией. С 2016 года в племенном скотоводстве наблюдается расширенное воспроизводство, и отрасль полностью обеспечена нетелями отечественной селекции для ремонта стада. Почти по всем породам крупного рогатого скота, разводимым в племенных хозяйствах, обеспечивается простое воспроизводство, и уже имеется достаточное поголовье молодняка для реализации внутри страны и поставок на экспорт. В области развития внутреннего рынка племенного молодняка наблюдается положительная тенденция по увеличению доли и наращиванию объемов реализации скота отечественной селекции. На рынке спермы быков-производителей искусственным осеменением охвачено 60% потенциально возможного поголовья, а импортопотребление в 2020 году достигло 62%. В АО «Головной центр по воспроизводству сельскохозяйственных животных» в настоящее время содержится треть потенциально, необходимого для нашей страны поголовья быков производителей всех пород и доля холдинга на внутреннем рынке спермы быков составила 35,1%. При этом накопленные запасы уже приготовленных доз спермы превышают объемы импорта за последние 5 лет. State investments aimed at development of domestic cattle breeding made it possible to form a wide network of breeding plants, breeding reproducers and gene pool farms throughout the country to provide the industry with breeding resources. Since 2016, there has been an expanded reproduction at cattle breeding and the industry is fully provided with domestic breeding heifers for herd repair. Almost all breeds of cattle are provided with simple reproduction at breeding farms and there is a sufficient number of young animals for sale inside the country and for export. At domestic market of young breeding animals, there is a positive trend for increasing the share and sales volumes of domestic breeds. The situation is more complicated at bull semen market: artificial insemination covers only 60% of the potentially possible cattle population, and import consumption reached 62% in 2020. Head Center for Reproduction currently has one third of bulls – producers of all breeds which are potentially necessary for our country. The holding's share at domestic bull sperm market s 35.1%. At the same time, the accumulated stocks of already prepared doses of sperm exceed the volume of imports over the past 5 years.

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Gurin, Joanne B. "A Bull Market for Biomedical Ethics." American Journal of Bioethics 2, no. 4 (September 2002): 35–36. http://dx.doi.org/10.1162/152651602320957394.

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Mason, Josh. "Three Scenes From a Bull Market." Baffler 9 (March 1997): 87–95. http://dx.doi.org/10.1162/bflr.1997.9.87.

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Dębski, Wiesław, and Ewa Feder-Sempach. "Beta Coefficients of Polish Blue Chip Companies in the Period Of 2005–2011." Folia Oeconomica Stetinensia 12, no. 2 (December 1, 2012): 90–102. http://dx.doi.org/10.2478/v10031-012-0025-6.

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Abstract Risk plays a significant role in various aspects of financial decision throughout the world financial markets. Beta parameter is one of the commonly used coefficient to estimate the systematic risk associated with stocks. Beta is mostly calculated using single index market model by W. Sharpe. This study examined the beta parameter under bull and bear market conditions on the Warsaw Stock Exchange (WSE). This paper analyses the beta responses for bad and good news for 44 stocks (14 stocks from the WIG20 index and 30 stocks from the mWIG40 index) over the last six years of trading at the WSE. Beta was calculated using monthly returns over the period 2005-2011, separately for the bull and the bear market. Our analysis finds strong evidence that beta is different in bull and bear market phase.

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Chawla, Deepak. "Stability of Alphas and Betas over Bull and Bear Markets: An Empirical Examination." Vision: The Journal of Business Perspective 7, no. 2 (July 2003): 57–77. http://dx.doi.org/10.1177/097226290300700205.

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This paper examines the influence of bull and bear markets on the stability of alpha and beta for the single index market model. The data for the study is collected for the period March 01, 1996 to March 31, 2001. The data pertains to the adjusted daily closing prices of 74 scrips that form a part of BSE-100 index. Two definitions of bull and bear markets are used. The analysis is carried out by estimating dummy variable regression, conducting a joint test (F-test) on alphas and betas, test for correlation coefficient and the paired t-test. The results indicate that alpha varies over both definitions of bull and bear market conditions whereas beta varies for one definition and is stable for the other. The variability of beta also dependents upon specific industry groups. However, one should take large samples from each industry group to draw any generalizations. The implications of the results for a portfolio manager are explained. It is also observed that the stability of alpha and beta depends upon the choice of bull and bear market conditions.

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Sun, Yunpeng, and Xueying Wang. "Asymmetric Effects of Chinas Monetary Policy on the Stock Market: Evidence from a Nonlinear VAR Mode." Asian Economic and Financial Review 8, no. 6 (May 23, 2018): 745–61. http://dx.doi.org/10.18488/journal.aefr.2018.86.745.761.

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This study uses Markov switching vector autoregression (MS-VAR) model to explore the asymmetric effects of China’s monetary policy on the stock market in the bull market and the bear market. With China’s economy in a rapid development, China’s stock market as the main representative of the virtual economy has attracted large assets. Since 1990 to the present, China’s stock market has experienced several times states’ change between the bull market and bear market. The results indicate that China’s quantity-based direct instrument and price-based indirect instrument have asymmetric effects on the stock market in the bull market and the bear market. Moreover, the relationship between China’s economy and stock market exist a degree of dichotomy. Furthermore, China’s monetary policy has stronger effects on the bull market than the bear market.

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Charteris, Ailie. "Another look at the CAPM in South Africa: The influence of bull and bear markets." Journal of Economic and Financial Sciences 7, no. 2 (July 31, 2014): 341–60. http://dx.doi.org/10.4102/jef.v7i2.144.

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Several studies of the Capital Asset Pricing Model (CAPM) in South Africa find that beta cannot explain returns. However, these studies do not consider the effect of bull and bear markets, yet over the period 1995-2009, excess market returns were positive in only 98 of 180 months. The influence of market conditions on the risk-return relationship is examined internationally by evaluating the conditional risk-return relationship where risk premiums are allowed to vary in bull and bear markets, and the dual-beta CAPM, which allows for the sensitivity of an asset to the market to vary under the two economic states. In this study, the ability of these two models to explain returns on South African shares is compared to the CAPM using the Fama and MacBeth (1973) and panel data approaches. The dual-beta model is found to be more successful than either the conditional relation or CAPM, as bull- and bear-market betas differ; but the estimates of the risk premiums in this model are significant only after adjusting for market segmentation. The findings thus indicate that asset-pricing models with time-varying risk should be the focus of future asset-pricing tests.

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刘, 昱. "The Research and Examination of Bull Market and Bear Market." Statistics and Application 08, no. 04 (2019): 631–45. http://dx.doi.org/10.12677/sa.2019.84072.

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Obalade, Adefemi A., and Paul Francois Muzindutsi. "The Adaptive Market Hypothesis and the Day‑of‑the‑Week Effect in African Stock Markets: the Markov Switching Model." Comparative Economic Research. Central and Eastern Europe 22, no. 3 (August 19, 2019): 145–62. http://dx.doi.org/10.2478/cer-2019-0028.

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In line with the Adaptive Market Hypothesis (AMH), the objective of this study is to investigate how the day‑of‑the‑week (DOW) effect behaves under different bull and bear market conditions in African stock markets, and to examine the likelihood of being in a bull or bear regime for each market. A Markov Switching Model (MSM) was employed as the analytical technique. The results show that the DOW effect appears in one regime and disappears in another, in all markets, as rooted in the AMH. Lastly, all markets, except the Johannesburg Stock Exchange have a higher tendency to be in a bearish state than a bullish one. Our findings show that active investment management may yield profits for investors investing in most African markets during bearish conditions.

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Kan, Yoke Yue. "Macroeconomic environment of bull markets in Malaysia." Qualitative Research in Financial Markets 9, no. 1 (February 6, 2017): 72–96. http://dx.doi.org/10.1108/qrfm-05-2016-0015.

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Purpose The aim of this paper is to investigate the circumstances and events surrounding bull runs in Malaysia from 1990 to 2015. The research question posed here is: What were the historical circumstances and events surrounding bull runs in Malaysia? Design/methodology/approach Case study approach is used. This research resorts to multiple resources such as academic journals, macroeconomic statistics, official publications, stock broker reports, annual reports of listed companies as well as articles from regional newspaper and magazines. Findings The results show that the bull runs in recent years happened with lower volatility after the Asian Financial Crisis. It can be conjectured that the specific environment in which the bull runs occurred can be somewhat different from period to period. Based on stylised facts and historical evidence, this study identified five major themes that were behind the bull markets in Malaysia, which include capital flow, spill-over effect from global development, change in ratings, speculative activities and investors’ sentiment, as well as government policies announcement. The findings have practical implications for investors who seek to understand and predict stock market boom through lessons learned from historical perspective. Research limitations/implications The analysis in this paper may have limitation, as the facts gathered are from secondary sources, which sources are derived from the observations of others. Therefore, secondary sources inevitably reflect the assumptions and biases of the people who wrote them. As the availability of data is limited by factors that are not under the control of the researcher, results may likely be limited in their generalizability. This case study does not attempt to establish causality or relationship between macroeconomic variables and stock prices. Further studies would therefore be necessary to examine the evolving nature of the relationship that may exist. Practical implications The findings of this study have significant policy implications for Malaysia, and also for other emerging markets. First, a prudent macroeconomic measures and concerted stance on fiscal, monetary and exchange rate policy to improve fundamentals and smooth volatility in the business cycle is vital for a bullish stock market. Second, the stock market derived significant benefits from openness to foreign capital and its resilience can be enhanced by fostering deeper and more liquid capital markets with diverse institutional investors, including domestic and foreign participants. Third, the environment that affects a stock market could be related to the political, regulatory and global environments. Malaysia stock market is susceptible to extreme events, capital flow, speculative activities and government interventions. Having a good grasp of which themes are operative at any point in time is central to investment decision making. Continuous rebalancing of portfolios based on information arriving in the market is also vital. Originality/value Previous studies on Malaysian stock market movement focus on quantitative analysis based on macroeconomic variable. This research is original in terms of giving background information and additional context to explain phenomena missed by quantitative research methods. The construction of quantitative model is also constraint by the measurability of non-quantitative data and data with different frequencies (such as annual, quarterly and monthly data). Therefore, it is important to contemplate the importance of non-quantitative factors, such as political, legal, regulatory and governance considerations. This study seeks to fill in this void.

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SPREIJ, M., and M. HOPPER. "Public–private partnerships build SPS capacity and develop market access." Bulletin de l'OIE 2019, no. 3 (January 23, 2020): 1–3. http://dx.doi.org/10.20506/bull.2019.3.3040.

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Khan, Safi Ullah, and Zaheer Abbas. "Does Equity Derivatives Trading Affect the Systematic Risk of the Underlying Stocks in an Emerging Market: Evidence from Pakistan’s Futures Market." LAHORE JOURNAL OF ECONOMICS 18, no. 1 (January 1, 2013): 63–80. http://dx.doi.org/10.35536/lje.2013.v18.i1.a3.

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This paper examines the behavior of beta coefficients (systematic risk) for underlying stocks around the introduction of single-stock futures (SSFs) contracts in the Pakistani market, by employing models that account for nonsynchronous and thin trading and varying market conditions as “bull” and “bear” markets. Unlike the results of earlier studies on US markets, the empirical evidence tends to support a decline in systematic risk for the majority of underlying stocks in the post-futures listings period. Nevertheless, similar to SSFs stocks, we also find empirical evidence of a decrease in systematic risk for many of the control group stocks. This indicates that changes in beta estimates for SSFs-listed stocks might not be induced by the introduction of SSFs contract trading, but could be attributed to other market-wide or industry changes that have affected the overall market. Several plausible reasons, such as lack of program trading activities normally associated with index futures, market microstructure differences between developed markets and a developing market such as Pakistan, and the capturing of the “bear” and “bull” market effects on stock betas in our estimation procedure could explain these different results for Pakistan’s market.

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Wade, C. M., J. W. Wilton, and S. P. Miller. "Determination of breeding strategies for beef cattle bull breeders selling bulls into two competing markets on a non-linear price grid." Canadian Journal of Animal Science 81, no. 2 (June 1, 2001): 169–77. http://dx.doi.org/10.4141/a00-030.

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Computer simulation was used to suggest potential selection strategies for beef cattle breeders with different mixes of clients between two potential markets. The “traditional” market paid on the basis of carcass weight (CWT), while a “new” market considered marbling grade in addition to CWT as a basis for payment. Both markets instituted discounts for CWT in excess of 340 kg and light carcasses below 300 kg. Herds were simulated for each price category on the carcass weight grid for the new market. This enabled the establishment of phenotypic relationships among the traits examined [CWT, percent intramuscular fat (IMF), carcass value in the traditional market, carcass value in the new market, and the expected proportion of progeny in elite price cells in the new market pricing grid]. The appropriateness of breeding goals was assessed on the basis of client satisfaction. Satisfaction was determined by the equitable distribution of available stock between markets combined with the assessment of the utility of the animal within the market to which it was assigned. The best goal for breeders with predominantly traditional clients was a CWT in excess of 330 kg, while that for breeders with predominantly new market clients was a CWT of between 310 and 329 kg and with a marbling grade of AAA in the Ontario carcass pricing system. For breeders who wished to satisfy both new and traditional clients, the optimal CWT was 310–329 kg and the optimal marbling grade was AA–AAA. This combination resulted in satisfaction levels of greater than 75% among clients, regardless of the distribution of the clients between the traditional and new marketplaces. Key words: Beef cattle, carcass, marbling grade, breeding, breeding objectives, breeding goals

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Popescu, Marius, and Zhaojin Xu. "Market states and mutual fund risk shifting." Managerial Finance 43, no. 7 (July 10, 2017): 828–38. http://dx.doi.org/10.1108/mf-09-2016-0278.

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Purpose The purpose of this paper is to explore the motivation behind mutual funds’ risk shifting behavior by examining its impact on fund performance, while jointly considering fund managers’ compensation incentives and career concerns. Design/methodology/approach The study uses a sample of US actively managed equity funds over the period 1980-2010. A fund’s risk shifting is estimated as the difference between the fund’s intended portfolio risk in the second half of the year and the realized portfolio risk in the first half of the year. Using the state of the market to identify the dominating type of incentive that fund managers face, we examine the relationship between performance and risk shifting in a cross-sectional regression setting, using the Fama and MacBeth (1973) methodology. Findings The authors find that poorly performing (well performing) funds are likely to increase (decrease) their risk level in bull markets, while reducing (increasing) it during bear markets. Furthermore, we find that funds that increase risk underperform, while those that decrease their portfolio risk do not. In addition, we find that poorly performing funds that increase (or decrease) their risk underperform across bull and bear markets, while well performing funds that reduce risk during bull markets subsequently outperform. Originality/value The paper contributes to the literature on mutual fund risk shifting by providing evidence that the performance consequence of such behavior is dependent on the state of the market and on the funds’ past performance. The results suggest that loser funds tend to be agency prone or be managed by managers with inferior investment skill, and that winner funds exhibit superior investment ability during bull markets. The authors argue that both the agency and investment ability hypotheses are driving fund managers’ risk shifting behavior.

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Zbesko, John. "Determinants of performance in the bull market." Journal of Portfolio Management 15, no. 2 (January 31, 1989): 38–44. http://dx.doi.org/10.3905/jpm.1989.409195.

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Bosselman, Fred. "Planning for a Bull Market for Wetlands." Planning & Environmental Law 61, no. 2 (February 2009): 3–14. http://dx.doi.org/10.1080/15480750902743381.

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Vaughan-Nichols, S. J. "Bull market for IEEE 802.11 WLAM chipsets." Computer 35, no. 11 (November 2002): 17–19. http://dx.doi.org/10.1109/mc.2002.1046966.

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Dumont De Chassart, M., and C. Firer. "The effects of bull and bear periods on market timing strategies." South African Journal of Business Management 32, no. 3 (September 30, 2001): 1–9. http://dx.doi.org/10.4102/sajbm.v32i3.720.

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This study evaluates the performance of traditional timing, bull timing (holding the risk-free asset and buying call options to take advantage of expected market rises) and bear timing (holding the market index and buying put options ahead of expected market falls) strategies on the Johannesburg Stock Exchange during bullish and bearish market phases. Potential returns as well as the forecasting ability required to outperform the ALSI are calculated.When the market is in a bullish phase, bear timing is the better strategy. However, in such a market, very high predictive accuracy (above 85 percent) is required from both bull and bear timers. In a bearish phase, however, bull timers perform better than bear timers. The predictive ability required of bear timers is of the order of 65 percent. For bull timers this required predictive accuracy drops below 50 percent, making it an extremely attractive strategy, provided the bear phases of the market can be predicted.

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Lillywhite, J. M., and J. Simonsen. "Understanding Factors That Influence Breeders to Sell Bulls at Performance Tests." Journal of Agricultural and Applied Economics 40, no. 3 (December 2008): 865–77. http://dx.doi.org/10.1017/s1074070800002388.

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Breeders of purebred bulls have multiple avenues to market their bulls, including consignment at public auctions associated with performance tests. Purebred breeders often have the opportunity to withdraw bulls that are eligible to sell in these auctions. We examine sales data from a public auction held in conjunction with a performance bull test in Tucumcari, NM, to gain insights on breeder decisions to withdraw bulls prior to entering the sales ring. Specifically, we use a binary logit model to identify relevant characteristics that affect a breeder's decision to withdraw a sale eligible bull from the auction.

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Güngöre, Sezen. "Finansal Piyasaların Vahşi Doğasına Analojik Yaklaşım." Journal of Social Research and Behavioral Sciences 8, no. 15 (May 9, 2022): 208–21. http://dx.doi.org/10.52096/jsrbs.8.15.15.

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There are many disciplines, many metaphors, many theories, and many studies that attempt to explain the behavior of financial markets and investors. Psychological, neurological and even genetic sciences are generally used in these studies, whose intensity has increased especially in the process of trying to complete the development of behavioral finance. However, the subject that has been used unchanged over the years and that we think has escaped the attention of researchers is the animal metaphors in the markets. It seems that investor behavior and economic human being the subject of research is new, but our imitation of animals goes back to prehistoric times. This shows us that behavioral patterns borrowed from animals existed long before we knew them. In this study, the names of animals used in financial markets have been examined, and it has been tried to determine how many animal names, especially bear and bull markets, turn financial markets into "jungle" and what behaviors of markets and investors are described by these names. Keywords: Behavioral Finance, Stock Market Jargon, Bear Market, Bull Market, Financial Markets JEL Classification: G40, D47

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Hoque, Mohammad Enamul, and Sourav Batabyal. "Carbon Futures and Clean Energy Stocks: Do They Hedge or Safe Haven against the Climate Policy Uncertainty?" Journal of Risk and Financial Management 15, no. 9 (September 6, 2022): 397. http://dx.doi.org/10.3390/jrfm15090397.

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Using the GARCH model and quantile regression with dummy variables, we investigate the hedging and safe haven properties of carbon futures and clean energy stocks against the U.S. climate policy uncertainty (CPU). We discover that carbon futures and clean energy stocks have a weak hedge and a semi-strong safe haven in different market conditions. Carbon futures exhibit a strong safe haven in both bull and bear markets, depending on the degree of uncertainty. Clean energy stocks, on the other hand, possess a weak hedge across market conditions and a strong safe haven in bull markets. Sub-sample analyses of prior- and post-Paris Agreement of 2016 also exhibit consistent results for safe haven properties of carbon futures and clean energy stocks.

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Moloney, A. P., E. G. O’Riordan, M. McGee, M. G. O’Sullivan, J. P. Kerry, S. S. Wilson, F. J. Monahan, A. K. Kelly, K. McMenamin, and L. Moran. "Carcass characteristics, colour and eating quality of beef from late maturing suckler bulls finished at pasture with or without concentrate supplementation or indoors on a high concentrate ration." Animal Production Science 62, no. 6 (February 17, 2022): 590–600. http://dx.doi.org/10.1071/an21426.

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Context Their growth and feed efficiency advantages make bull beef production systems attractive alternatives for producers of beef from steers. Finishing bulls from pasture is less costly and would allow bull beef to be marketed as ‘grass-fed’. However, such carcasses may not meet the minimum fatness classification of 6.0 (on a 15-point scale) required for some beef markets. This is based in part on a perception that meat from bulls with a lower fatness classification per se is inferior in some quality characteristics. Aim To determine the comparative carcass and beef quality characteristics of grass-fed and concentrate-fed bulls. Methods Spring-born, late-maturing breed suckler bull weanlings sourced from commercial beef suckler herds were assigned after their first winter to one of four experimental treatments until they were slaughtered 199 days later at an average age of 19.3 months. Treatments were: (1) grazed grass for 98 days (G), then housed and offered concentrates + grass silage ad libitum indoors for 101 days (G-HC), (2) grazed grass supplemented with concentrates (target 500 g/kg total daily dietary dry matter intake) for 199 days (GC-GC), (3) grazed grass for 98 days, then supplemented with concentrates (target 500 g/kg total daily dietary dry matter intake) at pasture for 101 days (G-GC), or (4) grazed grass only for 199 days (G-G). After slaughter, carcasses were weighed and graded for conformation and fatness. After 72 h, longissimus thoracis (LT) colour was measured. After 14 days ageing, LT was assessed for eating quality characteristics. Results Carcass weight averaged 399, 381, 374 and 361 kg for G-HC, GC-GC, G-GC and G-G bulls, respectively. Corresponding carcass fat scores were 7.5, 5.1, 5.5 and 4.8, only G-HC exceeded the minimum fat score specification. Meat from bulls finished at pasture was less red but the differences were small. After ageing for 14 days at 2°C, there was no difference in tenderness, flavour or acceptability between striploin steaks from any of the treatment groups. Conclusions Although none of the grazing groups achieved the current market specification for carcass fat score, this was not reflected in inferior eating quality. Implications Carcass fat score is a poor indicator of the eating quality of grass-fed bull beef. There is therefore an opportunity for suckler bull producers to access the growing market for ‘grass-fed’ beef.

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Jhamb, H. V., K. L. Dahiya, and Shikha Menani. "THE BULL AND BEAR MARKET BETA – EVIDENCE FROM THE INDIAN STOCK MARKET." Corporate Governance Insight 1, no. 1 (June 1, 2019): 101–14. http://dx.doi.org/10.58426/cgi.v1.i1.2019.101-114.

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Marcus, Jon. "Barefaced Cheating in China's Bull Market for Fraud." International Higher Education, no. 73 (March 17, 2015): 9–11. http://dx.doi.org/10.6017/ihe.2013.73.6119.

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The scope and nature of fraud and other dishonesty in China's higher education admissions system, particularly as it applies to international study, is substantial and growing. Increased competition for places in Western universities has stimulated this phenomenon.

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Gonzalez, Liliana, John G. Powell, Jing Shi, and Antony Wilson. "Two centuries of bull and bear market cycles." International Review of Economics & Finance 14, no. 4 (January 2005): 469–86. http://dx.doi.org/10.1016/j.iref.2004.02.003.

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Dai, Min, Hefei Wang, and Zhou Yang. "Leverage management in a bull–bear switching market." Journal of Economic Dynamics and Control 36, no. 10 (October 2012): 1585–99. http://dx.doi.org/10.1016/j.jedc.2012.04.004.

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Roszkowski, Adam J., and Nivine Richie. "The impact of Mad Money recommendations during bull and bear markets." International Journal of Managerial Finance 12, no. 1 (February 1, 2016): 52–70. http://dx.doi.org/10.1108/ijmf-04-2014-0053.

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Purpose – The purpose of this paper is to examine semi-strong market efficiency by observing the behavioral finance implications of Jim Cramer’s recommendations in bull vs bear markets. The authors extend the literature by analyzing investor reaction through the lenses of prospect theory, overreaction, and herding. Design/methodology/approach – The authors test for abnormal returns in response to Mad Money buy and sell recommendations. The authors use a sample of buy and sell recommendations from MadMoneyRecap.com from July 28, 2005 through February 9, 2009. The 3.5-year time period is the most recent and comprehensive set of Mad Money recommendations that has been tested to date. Findings – The results indicate market inefficiency at the semi-strong level. Furthermore, the findings highlight the loss aversion tendencies of investors in regards to prospect theory of Kahneman and Tversky (1979) as well as the disposition effect of Shefrin and Statman (1985). Evidence also exists consistent with the herding and overreaction hypotheses. Practical implications – The evidence suggests contrarian behavior in which investors respond positively to good news in bad times – perhaps, in effort to stay the course and at least break even. This behavior may suggest that losers tend to hold on to losses in hopes of recouping them. Thus, positive information in bad times could further persuade market participants to hang on to or buy more of losers, while also persuading non-shareholders to buy in as well. Originality/value – Though other studies including Kenny and Johnson (2010) have estimated abnormal returns in response to analyst recommendations, to the knowledge, none has examined behavioral implications of investor reaction to buy and sell recommendations in both bull and bear markets. Furthermore, the study captures a longer bull and bear market and covers two definitions of such markets.

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Yan, Weijian. "Does the Bull Market Have “Buffett”?—An Empirical Study on Chinese Mutual Fund Value Investing in Bull and Bear Markets." Technology and Investment 08, no. 02 (2017): 108–20. http://dx.doi.org/10.4236/ti.2017.82009.

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Barsky, Robert B., and J. Bradford De Long. "Bull and Bear Markets in the Twentieth Century." Journal of Economic History 50, no. 2 (June 1990): 265–81. http://dx.doi.org/10.1017/s0022050700036421.

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The bull and bear markets of this century have suggested that large stock market swings reflect irrational “fads and fashions.” We argue instead that investors perceived shifts in the long-run rate of future growth and that stock prices are sufficiently sensitive to expectations about the future that these perceived shifts plausibly generated the swings of the twentieth century. We document that analysts often viewed as “smart money” assessed fundamentals, based on their perceptions of future economic growth, in a way that tracked decade-to-decade swings closely.

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Kim, Kyungwon, and Minhyuk Lee. "The Impact of the COVID-19 Pandemic on the Unpredictable Dynamics of the Cryptocurrency Market." Entropy 23, no. 9 (September 20, 2021): 1234. http://dx.doi.org/10.3390/e23091234.

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The global economy is under great shock again in 2020 due to the COVID-19 pandemic; it has not been long since the global financial crisis in 2008. Therefore, we investigate the evolution of the complexity of the cryptocurrency market and analyze the characteristics from the past bull market in 2017 to the present the COVID-19 pandemic. To confirm the evolutionary complexity of the cryptocurrency market, three general complexity analyses based on nonlinear measures were used: approximate entropy (ApEn), sample entropy (SampEn), and Lempel-Ziv complexity (LZ). We analyzed the market complexity/unpredictability for 43 cryptocurrency prices that have been trading until recently. In addition, three non-parametric tests suitable for non-normal distribution comparison were used to cross-check quantitatively. Finally, using the sliding time window analysis, we observed the change in the complexity of the cryptocurrency market according to events such as the COVID-19 pandemic and vaccination. This study is the first to confirm the complexity/unpredictability of the cryptocurrency market from the bull market to the COVID-19 pandemic outbreak. We find that ApEn, SampEn, and LZ complexity metrics of all markets could not generalize the COVID-19 effect of the complexity due to different patterns. However, market unpredictability is increasing by the ongoing health crisis.

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Hindrayani, Aniek, Fadikia K. Putri, and Inda F. Puspitasari. "Spillover Effect of US Monetary Policy to ASEAN Stock Market." Jurnal Economia 15, no. 2 (October 1, 2019): 232–42. http://dx.doi.org/10.21831/economia.v15i2.26314.

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Abstract: This study analyzes the spillover effects of the US monetary policy on the ASEAN stock market with Markov switching model and investigates differences in empirical results of each country from ASEAN member. The results of this study have important implications for asset price allocation, specifically in the case of a transition between US and other small countries. The results showed that the ASEAN stock market is more affected by the US interest rates during bull-market than bear-markets. This can be seen from the increasing of stock market volatility during expansion comparing with recession period. Therefore, the stock markets of ASEAN countries will not be easily affected by the dollar rate during financial crisis or the recession period. Keywords: stock market, monetary policy, spillover effect, Markov-switching modelEfek Spillover pada Perubahan Kebijakan Moneter Amerika Terhadap Stock Market di ASEANAbstrak: Penelitian ini menganalisis efek spillover akibat adanya perubahan kebijakan moneter Amerika terhadap stock market di ASEAN dengan model Markov switching dan menginvestigasi terkait ada atau tidaknya perbedaan pada hasil empiris di setiap negara anggota ASEAN. Hasil penelitian ini memberikan implikasi penting bagi mekanisme transisi harga aset, khususnya dari Amerika terhadap negara dengan skala perekonomian kecil. Hasil penelitian menunjukkan bahwa stock market ASEAN lebih mudah terpengaruh oleh tingkat suku bunga Amerika pada saat kondisi bull-market dibandingkan saat bear-market. Hal ini dapat dilihat dari tingginya volatilitas stock market pada saat ekspansi dibandingkan saat periode resesi, sehingga stock market negara-negara ASEAN tidak akan mudah terpengaruh oleh dollar pada saat perekonomian mengalami krisis atau saat periode resesi. Kata kunci: stock market, kebijakan moneter, spillover effect, model Markov-switching

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Trivedi, Aaditya, Tajinder Pal Singh, and Kaushal Kishore. "Impact of COVID-19 on Stock Markets: An Investigation and Way Forward." International Review of Business and Economics 5, no. 1 (2021): 1–17. http://dx.doi.org/10.56902/irbe.2021.5.1.8.

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This study analyzes the impact of the COVID-19 pandemic on stock markets in different regions of the world. Impact of COVID-19 on the stock market is like a black swan event. To analyze the impact of COVID-19 on the stock market, study includes different indices, ratios, strategies and past events to compare. Study is focused on the stock market of countries such as the United States and India to see effects on developed and developing countries. The trends were found similar worldwide. The United States, which has been a bull market for a long time, is also experiencing a plummeting stock market. In the Dow Jones Index’s first quarter history, this year’s first quarter has marked the worst performance ever. In the year 2020, Indian stock market from 1st January to 23rd March SENSEX has plunged 37.1% and from 1st January to 18th May SENSEX has plunged 27.2%. The study tries to touch upon the past crises and its impact on various stock markets. Sentiments of an investor play a major role in the stock market. A good strategy if used in this type of stock market can help generate profits and remain stable in the volatile situation as well.

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Drane, Simon. "Portals: Where We Are and the Road Ahead." Legal Information Management 5, no. 4 (December 2005): 219–22. http://dx.doi.org/10.1017/s1472669605000927.

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This article aims to give an overview of the current position of the legal portal market (primarily law firms) and to offer some predictions for the road ahead. The key areas covered will include:[bull ] What are portals? Some basic definitions[bull ] Why might you need a portal?[bull ] What can you do with a portal?[bull ] Where we are at present with portals: technologies and usage[bull ] Key considerations for portal projects[bull ] Future predictions for legal portals

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Liu, Haifei, Tingqiang Chen, and Zuhan Hu. "Dynamic Evolution of Securities Market Network Structure under Acute Fluctuation Circumstances." Complexity 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/4370203.

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This empirical research applies cointegration in the traditional measurement method first to build directed weighted networks in the context of stock market. Then, this method is used to design the indicators and the value simulation for measuring network fluctuation and studying the dynamic evolution mechanism of stock market transaction networks as affected by price fluctuations. Finally, the topological structure and robustness of the network are evaluated. The results show that network structure stability is strong in the bull market stage and weak in the bear market stage. And the convergence rate of the dynamic evolution of network fluctuation is higher in the bull market stage than in the bear market stage.

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Mukhortov, D., and E. Zhovner. "The Bull and Bear Communicative Strategies in the US presidential campaign rhetoric." Rhema, no. 2, 2019 (2019): 48–60. http://dx.doi.org/10.31862/2500-2953-2019-2-48-60.

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This article seeks to introduce bull and bear communicative strategies in the US election discourse. The coinage is derived from the popular images of bull and bear in the economic terms ‘bull market’ and ‘bear market’. The bull strategy focuses on positive self-presentation, while the bear strategy is aimed at negative otherpresentation. Research into US presidential debates shows that most frequent communicative strategies aim either to create and reinforce the politician’s positive image or to discredit his or her opponent and ruin their chances to win. Which of the strategies stands to be more efficient is yet a matter of argument; however it is vividly shown that these strategies provide the perfect breeding ground for discursive confrontation.

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Journal articles on the topic 'Bull market'

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