226 research outputs found
Data for: Influence of strain and substitution on magnetocrystalline anisotropy of R2Fe14B (R=Pr, Dy and Y)
No full textCalculation files from WIEN2k are labeled LAPW, the ones from VASP are labeled PAW. 1. LAPW - Y2Fe14B (5 files for c/a changes from -2% to +2%)2. LAPW - Pr2Fe14B (5 files for c/a changes from -4% to 0%)3. LAPW - Dy2Fe14B (5 files for c/a changes from 0% to +4%)4. PAW - Y2Fe14B5. PAW - YPrFe14B6. PAW - YDyFe14B7. PAW - Pr2Fe14B8. PAW - PrYFe14B9. PAW - PrDyFe14B10. PAW - Dy2Fe14B11. PAW - DyYFe14B12. PAW - DyPrFe14
HUMAN CAPITAL IN THE CONTEXT OF SOCIAL-ECONOMIC DEVELOPMENT STRATEGY
No full textThe article deals with the role and importance of human capital of society in the processes of shaping and development of national economy at the expense of creating its own competitive product with high added value. From theoretical and methodological point of view the component analysis of human capital structure is shown. Methods of its assessment at different levels of business activity are described and key problems of effective use of human capital and building economic processes on this basis are identified. From the practical point of view the author discusses possibilities and the necessity to show processes of using human capital while developing and realizing strategy of long-term social and economic development both at the level of the country and at the level of regions. The author substantiates mechanisms of developing human capital within the frames of the adopted long-term strategy of social and economic development of the Russian Federation
Urban youth unemployment, marginalization and politics in MENA
No full textThis book focuses on Arab youth marginalization along intersectional lines of gender, ethnicity and social class in four cities: Jerusalem, Amman, Cairo, and Tunis. The author explores how the political and economic climates in each city influence the life prospects of youth and uncovers their narratives around their aspirations, disappointments and life choices. Providing an interdisciplinary approach, the project will interest a wide range of audiences including graduate students, scholars, and policy makers in the fields of the Middle Eastern studies, political science, urban studies, and education
Verba beri dalam bahasa Melayu Deli Serdang : Kajian Metabahasa Alami
No full textSyarah, 160702026, Verba beri dalam bahasa Melayu Deli Serdang : Kajian Metabahasa Alami. Skripsi, Program Studi Bahasa dan Sastra Melayu, Fakultas Ilmu Budaya, Universitas Sumatera Utara. Pembimbing : Drs. Baharuddin, M. Hum.
Penelitian ini ditulis untuk mengetahui struktur semantis dan makna verba beri dalam bahasa Melayu Deli Serdang dengan menerapkan pendekatan metabahasa semantik alami (MSA) yang dikemukakan oleh Wierzbicka. Data yang digunakan adalah data lisan, data tulis, dan data intuitif. Data dikumpulkan dengan metode cakap dan metode simak dengan teknik sadap, teknik Simak Libat Cakap, dan metode cakap dengan teknik catat dan teknik rekam. Analisis data yang digunakan metode padan kemudian menggunakan teknik hubung. Verba beri dalam bahasa Melayu Deli Serdang dibentuk oleh dua makna asali yaitu MELAKUKAN dan BERPINDAH yang membentuk sintaksis makna universal “Sesuatu (X) melakukan sesuatu pada sesuatu (Y), karena itu sesuatu berpindah pada seseorang/sesuatu yang lain (Z)‟. Struktur semantis verba beri dikaji dengan menggunakan makna asali untuk membatasi makna kata dengan menggunakan sistem parafrasa73 HalamanSkripsi Sarjan
Cálculo de rutas en Sistemas de E-Learning utilizando un algoritmo de optimización por colonias de hormigas
No full textEsta tesis plantea un escenario en el que existen itinerarios de aprendizaje alternativos para adquirir las mismas competencias y habilidades, cuyo nivel de asimilación se evalúa al finalizar el programa completo, compuesto por una secuencia de cursos concreta. El objetivo de este trabajo es estudiar la aplicación de la metaheurística de optimización mediante colonias de hormigas al problema de adaptar el itinerario a seguir por un alumno, en función de las calificaciones obtenidas en cada curso. Para llevar a cabo este estudio se modifica el algoritmo Ant System con el fin de adaptarlo al escenario propuesto (algoritmo ASALI) y se estudian, mediante simulación por ordenador, los resultados obtenidos y la velocidad de adaptación a los cambios, verificando su utilidad en el problema propuesto. Como estudio previo se ofrece el estado del arte actual en algoritmos de optimización por colonias de hormigas, con una breve descripción de los algoritmos más relevantes tanto para un único objetivo como para múltiples objetivos
Elektronenstruktur Berechnungen der Magnetisierung und magnetokristallinen Anisotropieenergie von neuen hartmagnetischen Materialien
No full textIn den 1960en Jahren wurden neue binäre und ternäre Übergangsmetall-Seltene Erde Phasen (T-R) mit großen Magnetisierungen (M_S) und magnetokristallinen Anisotropieenergien (MAE) entdeckt. Seitdem haben die darauf basierenden Materialien weitreichende Anwendungen in vielen Technologien wie Autoindustrie, Datenund Energiespeicherung gefunden. Diese Phasen sind auch vom Interesse wegen ihrer komplexen atomaren Physik, von der ihre hervorragenden makroskopischen Eigenschaften stammen. Die Zusammenwirkung von Spin-Bahn-Kopplung und Kristallfeldeffekt beeinflusst die Fermifläche in so einer Weise, dass große magnetokristalline Anisotropien erzielt werden. Um eine große J_s zu erhalten, ist eine ferromagnetische Kopplung der Magnetisierungen der T und der R-Atome maßgeblich. So eine vorteilhafte Kopplung wird in den zwei Phasen RT_5 and R_2 T_14 B beobachtet, mit R=Y, Pr, Sm, Nd, Dy and T=Co, Fe and Cu. Die Kristallstruktur der RCo_5 Phase und ihre Symmetrien sind eine Quelle der ungewöhnlich großen Orbitalmomente der Co-Atome in diesen Systemen. Die technisch relevanten makroskopischen Eigenschaften Koerzivität und Remanenz werden durch mikroskopische Eigenschaften, besonderes MAE und M_s bestimmt. Das Ziel dieses Werks ist es, diese zwei Größen für ideale Kristalle zu rechnen. Weiteres sind die Substitution von einem Co-atom durch Fe und Cu in RCo_5 und die Einflusse dieser Substitution in Betracht genommen. So eine Veränderung beeinflusst nicht nur die Kristallstruktur, sondern auch die magnetische Eigenschaften. In den 2-14-1 Phasen wird ein R-Atom durch ein anderes R- Atom, wie z.B. Pr durch Dy ersetzt. Fremde Atome, die die Bestandteile der Phasen ersetzen oder sich in den Zwischenräumen lagern, verändern die Fermifläche und dadurch auch MAE und M_s, die auf kleinsten Änderungen in der Fermienergie reagieren. Ein weiterer Aspekt dieser Arbeit ist die Betrachtung des Einflusses der Gitterparameterund Volumenänderungen auf der MAE und M_s. Solch eine strukturelle Änderung ist eine Simulation einer Substitution. Numerische Rechnungen basierend auf Dichtefunktionaltheorie (DFT) ermöglichen eine genaue Beschreibung der elektronischen Struktur der Festkörper sowie eine Feststellung des Einflusses einer Substitution oder struktureller Änderung ohne zeitund kostenintensive Experimentalmessungen. Diese DFT Rechnungen erlauben auch die Optimierung und die Relaxation der Kristallsysteme durch Minimierung der Grundzustandsenergie. In diesem Werk wurden zwei DFT-Codes, WIEN2k und VASP, verwendet, um MAE und M_s zu rechnen. WIEN2k ist basiert auf die Methode der „linearisierten, augmentierten Ebenenwellen“ (LAPW), und VASP ist basiert auf „projizierten, augmentieren Wellen“ (PAW).In the 1960s new transition metalrare earth (T-R) binary and ternary phases with large magnetization (M_s) and magnetic anisotropy energies (MAE) were discovered. These permanent magnetic phases have since found wide spread application in many technologies, especially in automotive, data storage and energy production branches and are produced on an industrial scale. They are also the subject of interest because of the complex physics on the atomic scale, from which their outstanding macroscopic properties stem. The interplay of spin-orbit coupling and crystal electric field influences the Fermi Surface so that large magnetic anisotropies are produced. To achieve a large magnetization, a ferromagnetic coupling between the total magnetization of the R and the T-atoms is advantageous, which is observed in the two phases RT_5 and R_2 T_14 B, with R=Y, Pr, Sm, Nd, Dy and T=Co, Fe and Cu. On the other hand the crystal structure of RCo_5 phases and its symmetries are the source of the unusually large orbital magnetic moments of the T-atoms in these phases. The decisive macroscopic properties coercivity and remanence are determined by microscopic and atomistic properties, most importantly MAE and M_s. Studying these two microscopic properties are the focus of this work. Aside from calculating the magnetization and magnetocrystalline anisotropy energies in ideal single crystals, we also consider the case of replacing a Co atom in 1-5 compounds with an Fe or Cu-atom. Such a substitution not only changes the crystal structure, it also influences the magnetic properties. In the 2-14-1 systems, one R-atom is replaced by another R-atom. Substitution or interstitial atoms influence both MAE and M_s, which are sensitive to small changes in the Fermi Surface. Another important aspect of this work is to study the change in MAE based on the variation of lattice parameters and volume changes. Such changes simulate the strain effects caused by substitution atoms. Numerical calculations based on the density functional theory (DFT) allow an accurate description of the electronic structure as well as the influence of changing different physical parameters without the need for complicated and expensive experimental measurements. Such DFT calculations also allow the optimization of the crystal lattice parameters and atomic positions based on the minimization of ground state energy. Using DFT-based methods of “linearized augmented planewaves” and “projector augmented waves” implemented in the codes WIEN2k and VASP respectively, the two quantities M_s and MAE are calculated
On the effects of foreign direct investment on local human capital formation
No full textEl presente paper presta tanto argumentos teóricos como soporte econométrico a la
idea de un nivel óptimo de inversión extranjera directa (FDI). Lo hace descubriendo una relación
con forma de U invertida entre dicha inversión y el esfuerzo educativo local. La optimalidad de
un flujo limitado de FDI depende de la formación de incentivos para educarse entre la población
local, que es heterogénea en términos de destreza o habilidad. Estos incentivos se forman en
presencia de incertidumbre e información asimétrica entre la multinacional y sus potenciales
empleados. Nuestras estimaciones revelan la existencia (y significatividad) de un impacto
positivo (lineal) y otro negativo (no lineal) de la inversión extranjera directa sobre la
escolarización terciaria, tanto en países desarrollados como en vías de desarrolloThis paper looks at both the theoretical and econometric support to the notion of
optimal FDI levels. It does so by uncovering an inverted-U-shaped relationship between FDI and
educational effort. The optimality of a particular FDI inflow depends on the educational
incentives induced by FDI on the local, heterogeneous population. Those incentives are formed
in the face of uncertainty and asymmetric information between the multinationals and their
potential workers. Our estimates confi rm the signifi cance of a positive (linear) and a negative (non-linear) impact of FDI per capita on tertiary schooling, both in developed and
developing countrie
Recommended from our members
Learning through building: Approaches to craft training in thin-tile vaulting
No full textShort-term training is becoming the dominant model of knowledge transfer in construction crafts. In the case of thin-tile vaulting, the historical master-apprentice training model is being partly replaced with experimental and project-specific training programs, some of which introduce the techniques to new regions and cultures. Challenges of time, site conditions, and the adaptation of the technique to local construction become intrinsic to the learning process. To address these challenges, this article will examine two thin-tile vault training programs in Rwanda and Spain. An ethnographic study will draw on social learning theories to explore how training is connected to the social and economic context of each project. Lessons from these workshops will form a training strategy model for traditional construction crafts. Finally, the study will project these lessons onto the pedagogy of architecture and design.La formación a corto plazo se está convirtiendo en el modelo predominante para la transferencia de conocimientos en los oficios de la construcción. En el caso de la bóveda tabicada, el modelo histórico de formación de maestro-aprendiz está siendo sustituido, en parte, por programas de formación experimentales centrados en proyectos específicos, algunos de los cuales introducen estas técnicas en nuevas regiones y culturas. Los retos impuestos por el tiempo, las condiciones del lugar y la adaptación de la técnica a la construcción local son consustanciales al proceso de aprendizaje. Para abordar estos problemas, en el artículo se examinan dos programas para enseñar a construir bóvedas tabicadas en Ruanda y España. Un estudio etnográfico se basará en las teorías sobre el aprendizaje social para explorar cómo se integra la enseñanza en el contexto socioeconómico de cada proyecto. Las lecciones aprendidas en estos talleres formarán un modelo de estrategia para la enseñanza de los oficios de la construcción tradicional. Por último, el estudio proyectará estas lecciones sobre la pedagogía de la arquitectura y el diseño
ANALYSIS OF INTEREST RATE. INFLATION RATE, AND EXCHANGE RATE ON STOCK PRICE VOLATILITY AND TRADING VOLUME: EVIDENCE FROM INDONESIA STOCK EXCHANGE
No full textABSTRACTThe capital market plays an important role in the economic development of a country. One of the main factors that motivate investors to invest their fund in the capital market is because of the expectation of a return. Besides expecting returns, investors should bear the risk of investment. Volatility can represent the risk that may be faced by the investor when conduct stock trading activity. Investors will look to the stock price volatility in determining the risk and opportunity of stock trading. Besides the volatility of stocks, trading volume is one indicator that can be used by the investors in analyzing the overall performance of the stocks. Fluctuation in the stock price is mostly related to the change in macroeconomic factors in a country. It is important for the investor to figure out how the macroeconomic variables affect the stock market to pick out the best-fit investment. Hence, this study is aimed to analyze the impact of macroeconomic variables on stock price volatility and trading volume.The sample in this study is monthly data listed in Indonesia Stock Exchange in the period of 2008 to 2018. The number of observation in this study is 132. The macroeconomic variables are measured by interest rate, inflation, and exchange rate. The data are analyzed using GARCH Model. The model selection is based on the value of R2, AIC and SC.The results show that only inflation has a significant influence on stock price volatility in Indonesia Stock Exchange. Inflation has a negative and significant relationship with stock price volatility. Other variables such as interest rate and exchange rate have an insignificant influence on stock price volatility. On the other hand, interest rate, inflation, and exchange rate have no significant influence on trading volume. Keywords: Stock Price Volatility, Trading Volume, Interest Rate, Inflation, Exchange RateREFERENCESAdjasi, C. K. (2009). Maccroeconomic Uncertainty and Conditional Stock-price Volatility in Frontier African Markets Evidence from Ghana. The Journal of Risk Finance, 10(4).Agung, I. G. (2009). Time Series Data Analysis Using Eviews. Singapore: John Wiley & Sons (Asia) Pte Ltd.Amata, E. O. (2017). Effect of Macroeconomic Variables on Stock Market Volatility in kenya (Unpublished Doctoral Thesis), Jomo Kenyatta University of Agriculture and Technology, Kenya.Andiani, N. W., & Gayatri. (2018). Pengaruh Volume Perdagangan Saham, Volatilitas Laba, Dividend Yield, dan Ukuran Perusahaan Pada Volatilitas Harga Saham. E-Jurnal Akuntansi Universitas Udayana, 24(3).Asteriou, D., & Hall, S. G. (2007). Applied Econometrics A Modern Approach . New York: PALGRAVE MACMILLAN.Azis, M., Mintarti, S., & Nadir, M. (2015). Manjemen Investasi Fundamental, Teknikal, Perilaku Investor dan Return. Yogyakarta: Deepublish.Chan, K., & Fong, W.-M. (2000). Trade size, order imbalance, and the volatility-volume relation. Journal of Financial Economics 57, 247-273.Chinzara, Z. (2010). Macroeconomic uncertainty and emerging market stock market volatility: The case for South Africa. Rhodes University, Working Paper 187.Creswell, J. W. (2003). Research Design Qualitative, Quantitative, and Mixed Methods Approach. United States: Sage Publications.Dewi, N. M., & Suaryana, I. G. (2016). Pengaruh Volume Perdagangan Saham, Leverage, dan Tingkat Suku Bunga Terhadap Volatilitas Harga Saham. E-Jurnal Akuntansi Universitas Udayana, 17(2).Enders, W. (2004). Applied Econometric Time Series. John Wiley & Sons.Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.Fontanills, G. A., & Gentile, T. (2003). The Volatility Course. Hoboken: John Wiley & sons, Inc.Gallant, R. A., Rossi, P. E., & Tauchen, G. (1992). Stock Prices and Volume. The Review of financial Studies, 5(2).Ginting, M. R., Topowijono, & Sulasmiyati, S. (2016). Pengaruh Tingkat Suku Bunga, Nilai Tukar dan Inflasi terhadap Harga Saham (Studi Pada Sub-Sektor Perbankan di Bursa Efek Indonesia Periode 2011-2015). Jurnal Administrasi Bisnis (JAB), 35(2).Girard, E., & Omran, M. (2009). On the Relationship between Trading Volume and Stock Price Volatility in CASE. Intenational Journal of Managerial Finance, 5(1), 110-134.Griffiths, W. E., Hill, R. C., & Lim, G. C. (2008). Using Eviews for Principles of Econometrics Third Edition. New Jersey: John Wiley & Sons.Heryanto. (2010). Analisis Inflasi. BI Rate, Infalsi, Kurs Rupiah dan Jumalh Uang Beredar, Terhadap Volume Perdagangan Saham di Bursa Efek Indonesia (Unpublised Thesis), Universitas Islam Negeri Syarif Hidayatullah, Indonesia.Huang, R. D., & Masulis, R. W. (2002). Trading Activity and Stock Price Volatility: Evidence from the London Stock Exchange. Journal of Emprical Finance.Hugida, L. (2011). Analisis Faktor-faktor yang Mempengaruhi Volatilitas Harga Saham (Studi Pada Perusahaan yang Terdaftar dalam Indeks LQ45 periode 2006-2009) (Unpublised Thesis), Universitas Diponegoro, Indonesia.Hussainey, K., Mgbame, C. O., & Chijoke-Mgbame, A. M. (2011). Dividend Policy and Share Price Volatility: UK Evidence. Journal of Risk Finance, 12(1).Hyde, K. (2000). Recognising Deductive Processes in Qualitative Research. Qualitative Market Research: An International Journal, 3, 82-89.Jawaid, S. T., & Ul Haq, A. (2012). Effects of Interest Rate, Exchange Rate, and Their Volatilities on Stock Prices: Evidence from Banking Industry of Pakistan. Theoritical and Applied Economics, 155-166.Jonathan, T. I. (2013). Analisa Pengaruh Inflasi, Suku Bunga dan Kurs Terhadap Volume Transaksi Pada Indeks LQ45. FINESTA, Vol.1, No.2.Kamuti, H. M. (2013). The Dynamic Relationship Between Stock Price Volatility and Trading Volume at the Nairobi Securities Exchange, Research Project, University of Nairobi.Karpoff, J. M. (1986). A Theory of Trading Volume. The Journal of Finance, 41(5).Khurniaji, A. W., & Raharja, S. (2013). Hubungan Kebijakan Dividen (Deividen Payout Ratio dan Dividend Yield) terhadap Volatilitas Harga Saham Perusahaan-perusahaan yang Terdaftar di Bursa Efek Indonesia. Diponegoro Journal of Accounting, 2(3).Kirui, E., Wawire, N. H., & Onono, P. O. (2014). Macroeconomic Variables, Volatility and Stock Market Returns: A Case of Nairobi Securities Exchange, Kenya. International Journal of Economics and Finance, 6(8).Kothari, C. R. (2004). Research Methodology Methods and Techniques. New Delhi: New Age International (P) Ltd.Lucey, B. M. (2005). Does Volume Provide Infromation? Evidence from the Irish Stock Market. Applied Financial Economic Letters, 1(2).Malkiel, B. G. (2003). The Efficient Market Hypothesis and Its Critics. Journal of Economic Perspectives, 17(1), 59-82.Malliaris, A. G., & Urrutia, J. L. (1998). Volume and Price Relationships: Hypothesis and Testing for Africultural Futures. The Journal of Futures markets, 18(1), 53-72.Mankiw, N. G. (2004). Priciples of Macroeconomics (Vol. Third Edition). Thomson South Western.Marczyk, G., DeMatteo, D., & Festinger, D. (2005). Essential of Research Design and Methodology. Hoboken: John Wiley &Sons, Inc.Muibi, S. O., Osi, A. R., Evans, O., & Seun, T. (2016). Determinants of Stock Trading volume in Nigeria: Money Demand Approach. Journal of Empirical Economics, 5(2), 74-89.Muktadir-al-Mukit, D. (2012). Effects of Interest Rate and Exchange Rate on Volatility of Market Index at Dhaka Stock Exchange. VII(2).Mumo, M. P. (2017). Effects of Macroeconomic Volatility on Stock Prices in Kenya: A Cointegration Evidence from the Nairobi Securities Exchange (NSE). International Journal of Economics and Finance, 9(2).Nasir, J. L., Diana, N., & Mawardi, M. C. (2018). Analisis Faktor-Faktor yang Mempengaruhi Volatilitas Harga Saham. E-JRA, 7(9).Newbold, P., Carlson, W. L., & Throne, B. M. (2003). Statistics for Business and Economics. Pearson Education, 5.Nugroho, H. (2008). Analisis Pengaruh Inflasi, Suku Bunga, Kurs dan Jumlah Uang Beredar Terhadap Indeks LQ45 (Studi Kasus Pada BEI Periode 2002-2007) (Unpublished Thesis), Universitas Diponegoro, Indonesia.Omorokunwa, O. G., & Ikponmwosa, N. (2014). Macroeconomics Variables and Stock Price Volatility in Nigeria. Annals of the University of Petrosani, Economics, 14(1), 259-268.Omotunde, R. A., Nwaogwugwu, I., & Nwokoma, N. I. (2016). Interest Rate Shocks and Stock Market Volatility in Nigeria. West African Journal of Monetary and Economic Integration, 16(2).Oseni, I. O., & Nwosa, P. I. (2011). Stock Market Volatility and Macroeconomic Variables Volatility in Nigeria: An Exponential GARCH Approach. Journal of Economics ad Sustainable Development, 2(10).Osisanwo, B. G., & Atanda, A. A. (2012). Determinant of stock market returns in Nigeria: A Time Series Analysis. African Journal of Scientific Research, 9(1).Pramaditya , R. (2008). Pengaruh SBI, Nilai Kurs AS (USD) dan Inflasi Terhadap Volume Perdagangan Saham Perbankan yang Terdaftar di Bursa Efek Indonesia Periode Tahun 2004-2006 (Unpublished Thesis), Universitas Mercu Buana, Indonesia.Pratama, M. A. (2011). Analisis Pengaruh Suku Bunga dan Nilai Tukar Terhadap Volatilitas dan Return Pada Indeks Saham Sektoral di Bursa Efek Indonesia, Institut Pertanian Bogor, Indonesia.Prempeh, K. B. (2016). Macroeconomic Variables and Stock Price Volatility in Ghana. MPRA Paper No. 70545.Rahardjo, S. (2006). Kiat Membangun Aset Kekayaan. Jakarta: Elex Media Komputindo.Reilly, F. K., & Brown, K. C. (2003). Investment Analysis & Portfolio Management (Vol. Seventh Edition). USA: South western-Thomson.Retherford, R. D., & Choe, M. K. (1993). Statistical Model for Causal Analysis. New York: John Wiley &Sons, Inc.Romli, H., Wulandari, M. F., & Pratiwi, T. S. (2017). Faktor-faktor yang Mempengaruhi Volatilitas Harga Saham pada PT Waskita Karya Tbk. Jurnal Ilmiah Ekonomi Global Masa Kini, 8(1).Ross, S. A. (1976). The Arbitrage Theory of Capital Asset pricing. Journal of Economic Theory, 13, 341-360.Saatcionglu, K., & Starks, L. (1998). The Stock Price-volume Relationship in Emerging Stock Markets: The Case of Latin America. International Journal of Forecasting 14, 215-225.Sahu, T. N. (2015). Macroeconomic Variables and Security Price in India during the Liberalized Period. New York: Palgrave Macmillan.Samsul, M. (2006). Pasar Modal dan Manajemen Portofolio. Erlangga.Saunders, M., Lewis, P., & Thornhill, A. (2009). Research Methods for Business Students (Vol. 5). England: Pearson Education.Schwert, G. W. (1989). Why Does Stock Market Volatility Changes Over Time? The Journal of Finance, XLIV, No. 5.Sihombing, L. I. (2009). Pengaruh Inflasi, Kurs, Investasi dan Suku Bunga Sertifikat Bank Indonesia (SBI) terhadap Harga Saham dan Volume Perdagangan Saham PT. Bank Rakyat Indonesia (Tbk) di Bursa Efek Indonesia (Unpublished Thesis), Universitas Sumatera Utara, Indonesia.Singh, Y. K. (2006). Fundamental of Research Methodology and Statictics. New Delhi: New Age international (P) Ltd.Spiro, P. S. (1990). The Impact of Interest Rate Chnage on Stock Price Volatility. The Journal of Portfolio Management.Suniarti, L. (2019). Analisis Faktor Fundamental yang Mempengaruhi Volatilitas Harga Saham (Study Pada Perusahaan yang Terdaftar Dalam Inde LQ45 Periode Tahun 2008-2017). 7(1).Sutrisno, B. (2017). Hubungan Volatilitas dan Volume Perdagangan di Bursa Efek Indonesia. Jurnal Bisnis dan Manajemen, 7(1), 15-26.Tandelilin, E. (2010). Portofolio dan Investasi Teori dan Aplikasi. Yogyakarta: Kanisius.Taslim, A., & Wijayanto, A. (2016). Pengaruh Frekuensi Perdagangan Saham, Volume Perdagangan Saham, Kapitalisasi Pasar dan Jumlah Hari Perdagangan Terhadap Return Saham. Management Analysis Journal, 5(1).Tserkezos, E. (2009). Temporal Aggragation and Ramsey's (RESET) Test for Functional Form: results from Monet Carlo Experiment. Conference paper, 1-12.Vogelvang, B. (2005). Econometrics Theory and Applications with Eviews. England: Pearson Education Limited.Walter, E. (1995). Applied Econometric Time Series. Canada: Jhon Wiley & Sons, Inc.Widarjono, A. (2005). Ekonometrika: Teori dan Aplikasi untuk Ekonomi dan Bisnis. Yogyakarta: Ekonisia.Widoatmodjo, S. (2015). Seri Akademis Pengetahuan Pasar Modal untuk Konteks Indonesia. Jakarta: Elex Media Komputindo.Wira, V. (2012). Pengaruh Kinerja Perusahaan Terhadap Likuiditas Saham Menggunakan Trading TurnOver (Studi Kasus Pada Perusahaan yang Terdaftar di Bursa Efek Indonesia). Jurnal Manajemen dan Kewirausahaan, 3, No. 2.Yuliana, F., Wijaya, E. Y., & Haryetti. (2014). Analisa pengaruh Tingkat Suku Bunga, Inflasi, Kurs, dan Jumlah Uang Beredar terhadap Volume Perdagangan Saham. JOM FEKON, 1(2).Zan, S., & Wei, C. (2003). The Macroeconomic Determinants of Stock Price Volatility: Evidence from Taiwan, South Korea, Singapore and Hong Kong. Environmental and Management Research, 8(2).
Data for: Influence of strain and substitution on magnetocrystalline anisotropy of R2Fe14B (R=Pr, Dy and Y)
No full textCalculation files from WIEN2k are labeled LAPW, the ones from VASP are labeled PAW. 1. LAPW - Y2Fe14B (5 files for c/a changes from -2% to +2%)2. LAPW - Pr2Fe14B (5 files for c/a changes from -4% to 0%)3. LAPW - Dy2Fe14B (5 files for c/a changes from 0% to +4%)4. PAW - Y2Fe14B5. PAW - YPrFe14B6. PAW - YDyFe14B7. PAW - Pr2Fe14B8. PAW - PrYFe14B9. PAW - PrDyFe14B10. PAW - Dy2Fe14B11. PAW - DyYFe14B12. PAW - DyPrFe14BTHIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV
- …
