1,720,960 research outputs found
Share price dynamics of listed companies on the Dhaka stock exchange using geometric Brownian motion
Full text linkThe stock prices of publicly traded companies exhibit continuous and random fluctuations over time, necessitating the inclusion of a stochastic term in dynamic models to accurately capture this behavior. This study applies the geometric Brownian motion (GBM) model to analyse the stock prices of 20 randomly selected companies listed on the Dhaka Stock Exchange (DSE). The GBM model was resolved through Monte Carlo simulation to forecast stock prices over a trading horizon of approximately 30 to 35 days. Using historical data from the first four months of 2024, we predicted the share prices for the subsequent one-and-a-half months. The comparison between forecast and actual prices demonstrated a high level of concordance, with a mean absolute percentage error (MAPE) of less than 8%. These findings underscore the efficacy of the model in providing robust predictions of share prices for selected companies
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
A comparative analysis of stochastic models for stock price forecasting: the influence of historical data duration and volatility regimes
Full text linkAccurate stock price forecasting is essential for informed financial decision-making. This study presents a comparative analysis of four foundational stochastic models—Geometric Brownian Motion (GBM), the Heston Stochastic Volatility model, the Merton Jump-Diffusion (MJD) model, and the Stochastic Volatility with Jumps (SVJ) model—each formulated to capture distinct features of financial market dynamics. Utilizing maximum likelihood estimation (MLE) for parameter calibration and Monte Carlo simulation for forecasting, we assessed model performance over varying historical calibration windows (3-month, 6-month, and 1-year) and a 3-months prediction horizon. Empirical findings demonstrate that the SVJ model consistently achieves superior predictive performance, as quantified by root mean square error (RMSE) and mean absolute percentage error (MAPE), across assets with both low and high volatility profiles. Moreover, the analysis reveals that for low-volatility stocks, such as AAPL and MSFT, a 1-year calibration window yields lower forecast errors, whereas for high-volatility stocks, such as TSLA and MRNA, a 6-month calibration window provides improved forecasting accuracy. These results highlight the importance of selecting model structures and estimation periods that align with the underlying volatility characteristics of the asset
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Statistics of Lagrangian quantum turbulence
No full textWe consider the dynamics of small tracer particles in turbulent quantum fluids. The complicated interaction processes of vortex filaments, the quantum constraints on vorticity, and the varying influence of both the superfluid and the normal fluid on the tracer particle effectively lead to a superstatistical Langevin-like model that in a certain approximation can be solved analytically. An analytic expression for the probability density function of velocity
v of the tracer particle is derived that exhibits not only the experimentally observed v⁻³ tails but also the correct behavior near the center of the distribution, in excellent agreement with experimental measurements and numerical simulations. Our results are universal and do not depend on details of the quantum fluid
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