933,419 research outputs found

    Information flow between composite stock index and individual stocks

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    We investigate the strength and the direction of information transfer in the U.S. stock market between the composite stock price index of stock market and prices of individual stocks using the transfer entropy. Through the directionality of the information transfer, we find that individual stocks are influenced by the index of the market.Comment: 8 pages, 4 figure

    How “Point Blindness” Dilutes the Value of Stock Market Reports

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    The stock index “point” is a focal component of financial news reports. While much attention is paid to changes in stock index point totals, few people realize that the value of a stock index “point” varies (and has recently declined). We call this perceptual phenomenon “point blindness” and explain its threat to investors. Simple changes in media presentations of stock index information can counter point blindness. These changes are easy to implement and can help audiences make better financial decisions. An experiment on over 2000 participants shows such changes significantly altering their perceptions of the stock market.behavioral economics: personal finance; communication

    How “Point Blindness” Dilutes the Value of Stock Market Reports

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    The stock index “point” is a focal component of financial news reports. Though many reports draw attention to point changes in major indices, few people realize that the value of a stock index “point” changes frequently. We call this perceptual phenomenon “point blindness.” We examine causes of point blindness and then propose alternate ways of reporting stock market information to counter it. The alternatives are easy to implement and can help citizens draw important inferences about stock values. An experiment shows that alternate modes of presentation have significant effects on public perceptions of the stock market.stock market; stock index; financial reporting; news; real nominal relations

    The market efficiency in the stock markets

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    We study the temporal evolution of the market efficiency in the stock markets using the complexity, entropy density, standard deviation, autocorrelation function, and probability distribution of the log return for Standard and Poor's 500 (S&P 500), Nikkei stock average index, and Korean composition stock price index (KOSPI). Based on the microscopic spin model, we also find that these statistical quantities in stock markets depend on the market efficiency.Comment: 8 pages, 5 figure

    An Empirical Analysis of the Taiwan Institutional Trading Volume Volatility Spillover on Stock Market Index Return

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    This paper provides interesting empirical evidence on the relation between the volatility impact effect of the Taiwan institutional trading volume and the stock market index by using the MEGARCH model. We found a significant autoregressive coefficient of institutional trading volume and stock market index. The cross-volatility spillover effect, asymmetric leverage effect, and persistence of volatility effect are statistically significant. The feedback and lead-lag relationship between trading volume and stock index return are also statistically significant. Therefore, Taiwan¡¦s institutional trading volume can affect the stock market index through volatility effect and causality.

    Indonesian Stock Market Crisis Observation with Spectral and Composite Index

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    The paper discusses the employment of the index composed from the dynamical tree of correlations among stock prices both with the popularly used standard (conventional) composite one. The spectral index focus on the dynamics of the correlation coefficients among stock prices while composite index is the dynamical aggregate of the whole stocks traded in the market. Some advantages is conjectured by incorporating both indexes to the historical data of Indonesian Stock Market data. Both are shown potentially useful for detecting the crisis as well as the general stock-prices relations on fundamental issues, generally social, economic, and political situations on which the Indonesian stock market is influenced.composite index, spectral data, crisis, social economic and political issues

    Relationship between Crude Oil Prices and Stock Prices of Alternative Energy Companies with Recent Evidence

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    This paper examines the recent interactive relationships between crude oil prices and stock performances of alternative energy companies. Oil prices and stock index of alternative energy sector are found independent from each other before late 2006. Contrary to existing studies, however, we find significant interdependence between oil prices and stock index of alternative energy industry in the recent years. Since late 2006, oil prices become significantly responsible for the stock performances of alternative energy companies. This finding suggests that the stock market investors of alternative energy sector incorporate oil price shocks into their trading decisions only recently.Crude oil price; Alternative energy; Oil stock index

    Pembentukan Portofolio Saham Dengan Model Indeks Tunggal (Suatu Studi Pada Perusahaan Perkebunan Yang Listed Di PT Bursa Efek Indonesia)

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    Capital market in Indonesia has grown rapidly since 1989, after the government issuedvarious deregulation to spur the growth of the capital market. Individual investors in theequity investment must try to obtain optimal return and reduce risk. Regarding on thepurpose, this research used a single index models found by Sharpeto form a stock portfolio.The problem in this research is how to do stock selection in the plantation sector in order toestablish optimal stock portfolio with single index model and how much the proportion offunds to be allocated to the portfolio? The research objective is to determine whichplantation stocks will form a stock portfolio and how many percentage the allocation offunds to each stock. The research was descriptive form, using secondary data. The data used in this study is quantitative data that individual stock price index, the stock price index and the rate of Bank Indonesia (BI Rate). From the calculation, there are six stocks will establish the optimal stock portfolio. They are PT Smart, Tbk., PTPP London Sumatra Indonesia, Tbk., PT Tunas Baru Lampung, Tbk., PT Sampoerna Agro, Tbk., PT Gozco Plantations, Tbk. and PT Astra Agro Lestari, Tbk. The allocation of funds will be invested by the investor, it is obtained the biggest investment will be invested in stock of PTPP London Sumatra Indonesia, Tbk. amounted to 31.32%, PT Tunas Baru Lampung, Tbk. amounted to 20.20%, PT Sampoerna Agro, Tbk. amounted to 16.59%, PT Smart, Tbk. amounted to 12.09%, PT Gozco Plantations, Tbk. 10.71% and the smallest investment amounted to 9.08%. in stock of PT Astra Agro Lestari, Tbk

    The Warsaw Stock Exchange Index WIG: Modelling and Forecasting

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    In this paper we have assessed an influence of the NYSE Stock Exchange indexes (DJIA and NASDAQ) and European Stock indexes (DAX and FTSE) on the Warsaw Stock Exchange index WIG within a framework of a GARCH model. By applying a procedure of checking predictive quality of econometric models as proposed by Fair and Shiller (1990), we have found that the NYSE market has relatively more power than European markets in explaining the WSE index WIG.Warsaw Stock Exchange, stock index, GARCH model, forecasting

    Coupling Index and Stocks

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    In this paper, we are interested in continuous time models in which the index level induces some feedback on the dynamics of its composing stocks. More precisely, we propose a model in which the log-returns of each stock may be decomposed into a systemic part proportional to the log-returns of the index plus an idiosyncratic part. We show that, when the number of stocks in the index is large, this model may be approximated by a local volatility model for the index and a stochastic volatility model for each stock with volatility driven by the index. This result is useful in a calibration perspective : it suggests that one should first calibrate the local volatility of the index and then calibrate the dynamics of each stock. We explain how to do so in the limiting simplified model and in the original model
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