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Academic literature on the topic 'NIFTY'

Author: Grafiati

Published: 11 September 2023

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Journal articles on the topic "NIFTY"

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Vijay, Dr S., and Dr V. Prabakaran. "A study on Bank and IT nifty influence on Nifty 50." Journal of University of Shanghai for Science and Technology 23, no. 12 (December 18, 2021): 316–22. http://dx.doi.org/10.51201/jusst/21/121030.

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NIFTY 50 is one of the benchmark indices which is been used in India. The index is built upon by the companies which are represented from various sectors. Each sector is given separate weightage depending upon the representations from each sector. This paper focused on to identify Pairwise Granger Causality between NIFTY 50 Index, NIFTY Bank Index and NIFTY IT Index. The researcher also focused on to identify the influence of Bank NIFTY and IT NIFTY and NIFTY 50 Index. The research was carried out with a total of 532 observations (closing value of each index) of spanned across January 2018 – February 2020. The study revealed that Bank NIFTY Granger Cause IT NIFTY and not vice-versa. NIFTY 50 Index is highly influenced by Bank NIFTY IT NIFTY.

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Amuthan, R. "Co relating NIFTY 50 Index Trend’s impact on NSE’s Sector based Indices Growth Momentum in Post COVID-19 led Indian Economy with Special reference to NIFTY Bank, NIFTY Consumer Durables, NIFTY IT and NIFTY Pharma Indices using Arithmetic Modelling." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 5, 2021): 2184–89. http://dx.doi.org/10.17762/turcomat.v12i6.4824.

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The NIFTY 50 is the flagship index on the National Stock Exchange of India Ltd. (NSE). The Index tracks the behavior of a portfolio of blue chip companies, the largest and most liquid Indian securities. It includes 50 of the approximately 1600 companies traded (listed & traded and not listed but permitted to trade) on NSE, captures approximately 65% of its float-adjusted market capitalization and is a true reflection of the Indian stock market. This study probed in to the correlation between NIFTY 50 and NIFTY Bank, NIFTY 50 and NIFTY Consumer Durables, NIFTY 50 and NIFTY IT and NIFTY 50 and NIFTY Pharma Indice.

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Narayan, Parab, and Y. V. Reddy. "Exploring the Causal Relationship Between Stock Returns, Volume, and Turnover across Sectoral Indices in Indian Stock Market." Metamorphosis: A Journal of Management Research 16, no. 2 (November 12, 2017): 122–40. http://dx.doi.org/10.1177/0972622517730140.

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The traditional saying “Market Discounts Everything” is applicable to stock returns, trading volume, and turnover as well. The present study is an analytical attempt to examine the causal relationship between stock returns, trading volume, and turnover across 10 sectoral indices of National Stock Exchange (NSE) for the period 2006–2016. To critically examine this relation, the study uses various statistical techniques such as descriptive statistics, correlation analysis, regression analysis, and econometric tests such as Granger causality test and augmented Dickey–Fuller test. The required analyses have been performed using statistical software E-views, SPSS, and Microsoft Excel. The study noticed a weak positive relationship between stock returns and turnover for Nifty Auto Index, Nifty Bank Index, Nifty Financial Services Index, Nifty Media Index, Nifty Metal Index, and Nifty Private Bank Index. The study also found a significant impact of turnover on stock returns in the case of Nifty Auto Index, Nifty Bank Index, Nifty FMCG Index, Nifty Metal Index, and Nifty Pharma Index and a significant impact of volume on stock returns in the case of Nifty Bank Index, Nifty FMCG Index, and Nifty Pharma Index. Augmented Dickey–Fuller test suggests that there exists no unit root in the data ( p < 1) and the data are stationary. It is evident from the study that the causal relationship between stock returns, turnover, and volume varies across the sectoral indices.

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Dharani, M. "Seasonal Anomalies between S&P CNX Nifty Shariah Index and S&P CNX Nifty Index in India." Journal of Social and Development Sciences 1, no. 3 (April 15, 2011): 101–8. http://dx.doi.org/10.22610/jsds.v1i3.633.

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The present study compares the risk and return of the Nifty Shariah index and Nifty index at days, months and quarters wise during the period 2nd January 2007 to 31st December 2010. The raw returns of the both indices are calculated as today price minus yesterday price divided by yesterday price. The t- test has been used to test the mean returns difference between both indices. The average Monday return of the Nifty Shariah index is compared with average return of the Nifty index by using two sample t-test. Like that, the average returns of the remaining of the days of Nifty Shariah index are compared with average returns of remaining days of the Nifty Index. The study finds that there is no difference between average day -wise returns of the Nifty Shariah index and average day return of the Nifty Index during the study period. The study also compares the average January return of the Nifty Shariah index with average January return of the Nifty index, average February return of the Nifty Shariah index with average return of the Nifty index and so on. Finally, the average return of the first, second, third and fourth quarter of Nifty Shariah with average return of the respective first, second, third and fourth quarter of Nifty index are compared. The study finds that there is a significant difference between average return of the Nifty Shariah and Nifty indices in the month of July and September. It is derived from the study that the Muslim Investors are evincing more interest to sell the shares in the market from July to September. The reason being, expenses inconnection with Ramalan Festival during that period. Therefore, the study confirms that Ramalan effect have been prevailing in the Indian Stock Market. Thus, this study reveals that the seasonal variation exits very much in Shariah Index

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Stevens, Kerrie. "Nifty Newsletters." ANZTLA EJournal, no. 15 (September 15, 2017): 94–101. http://dx.doi.org/10.31046/anztla.vi15.460.

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Parlante, Nick, David Matuszek, Jeff Lehman, David Reed, John K. Estell, and Donald Chinn. "Nifty assignments." ACM SIGCSE Bulletin 36, no. 1 (March 2004): 46–47. http://dx.doi.org/10.1145/1028174.971318.

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Parlante, Nick. "Nifty reflections." ACM SIGCSE Bulletin 39, no. 2 (June 2007): 25–26. http://dx.doi.org/10.1145/1272848.1272876.

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Kim, Tae-Il. "Nifty fifty." Journal of Periodontal & Implant Science 40, no. 3 (2010): 103. http://dx.doi.org/10.5051/jpis.2010.40.3.103.

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Parlante, Nick. "Nifty assignments." ACM SIGCSE Bulletin 40, no. 1 (February 29, 2008): 112–13. http://dx.doi.org/10.1145/1352322.1352173.

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Parlante, Nick, Thomas P. Murtagh, Mehran Sahami, Owen Astrachan, David Reed, Christopher A. Stone, Brent Heeringa, and Karen Reid. "Nifty assignments." ACM SIGCSE Bulletin 41, no. 1 (March 4, 2009): 483–84. http://dx.doi.org/10.1145/1539024.1509031.

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Dissertations / Theses on the topic "NIFTY"

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Yutzy, Evan. "Nifty Shades of Beige: The Exploration of Color Lexicology Related to Sexual Identity." Kent State University Honors College / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ksuhonors1430744655.

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Pack, Kendall G. ""We want to get down to the nitty-gritty": The Modern Hardboiled Detective in the Novella Form." DigitalCommons@USU, 2015. https://digitalcommons.usu.edu/etd/4247.

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This thesis approaches the issue of the detective in the 21st century through the parodic novella form. The main body of the work is a piece of fiction about an amateur detective trying to find a solution to an imagined crime. This comes from my study of detective fiction, starting with Oedipus and ending with twentieth and twenty-first century examples, especially in the works of Thomas Pynchon and Chester Himes, where the detective loses power. The novella follows Whitney Sloat as he acts as detective in a world that can’t let go of the hardboiled traditions. He and the people around him struggle to connect with reality, pursuing a way of life that cannot exist outside of their world.

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Hartung, Anett. "An essential role of IRF4 in translating TCR a nity-mediated activation and CD8+ e ector T cell fate decisions." Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17555.

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CD8+ T Zellen unterstützen die Beseitigung von Pathogenen und sind somit entscheidend bei der Bekämpfung von Infektionen. Neben der Antigendosis und dem inflammatorischen Zytokinemilieu hat auch die Stimulation durch den TZR einen entscheidenden Einfluss auf die CD8+ T Zellantwort. Das transkriptionelle Programm, die finale Größe und Dauer der klonalen Expansion und der Start der Kontraktionsphase werden durch die TZR-Signalstärke bestimmt. Schwache TZR-Stimulation führt zu einer verminderten Expansion und vermittelt eine frühzeitige Kontraktionsphase, die eine Entwicklung von Gedächtniszellen auf den Kosten der Effektorzellen favorisiert. IRF4 wird nach TZR-Ligand-Interaktion in CD8+ T-Zellen hoch reguliert. Seine Expressionskinetik ist stark von der TZR-Signalstärke der Aktivierung abhängig, übersetzt diese und sorgt für die Umsetzung in ein entsprechendes transkriptionelles und differentielles Programm. In dieser Arbeit konnte erstmals gezeigt werden, dass die IRF4-Defizienz in CD8+ T-Zellen zu einem verfrühten Abbruch der Expansion und zu einem vorzeitigen Beginn der Kontraktion führt, die durch den FAS-vermittelten Tod-induzierenden Signalweg initiiert wird. Außerdem präsentieren IRF4-defiziente CD8+ T-Zellen vermehrt Phosphatidylserine an ihrer Oberfläche und Komplementdeposition, beides begünstigt die Erkennung und Aufnahme durch Phagozyten. Diese Ergebnisse weisen zudem stark darauf hin, dass durch die fehlende Expression von IRF4 in CD8+ T Zellen, ein schwaches TZR-Signal übermittelt wird, unabhängig von der tatsächlichen Stärke und Dauer des aktivierenden Signals, dass zu einer Verkürzung der Expansionsphase führt und eine verfrühte Kontraktionsphase der Effektorzellen auslöst. Diese Arbeit erweitert schon bekanntes Wissen um IRF4 als Schlüsselregulator für die Differenzierung und Funktionalität der ag-spezifischen CD8+ T-Zellen, da es den Beginn der Kontraktionsphase diktiert mittels Aktivierung von verschiedenen Apoptose- und Phagocytose Signalwegen.
CD8+ T cells promote pathogen clearance and play a crucial role in controlling infections. Besides antigen dose and inflammatory cytokine milieu, the TCR stimulation contributes to the programming of the CD8+ T cell response. A distinct developmental program, the final magnitude and duration of clonal expansion, as well as the timing of the onset of T cell contraction, are determined by the TCR signaling strength. Weak TCR stimulation results in a diminished magnitude of expansion and accelerates the onset of contraction, as it favors the development of memory cells at the expense of effector cells. IRF4 is a transcription factor, that is upregulated in CD8+ T cells following TCR stimulation. Furthermore, its expression kinetic is highly dependent on the TCR signaling strength, which initiated activation. Therefore, it translates the strength of the activating signal and transmits it into a proper transcriptional and developmental program. This study provides unique evidence that the absence of IRF4 expression in CD8+ T cells leads to a hasted termination of clonal expansion and a premature contraction, initiated by the FAS-mediated cell death pathway. Moreover, IRF4-deficient CD8+ T cells exposed phosphatidylserine on their cell surface and showed complement deposition, both facilitating their recognition and uptake by phagocytes. The findings of this study additionally strongly indicate that IRF4 deficiency mimics weak TCR engagement and in turn transmits every TCR signal, independent of its actually affinity and duration, into a developmental program, that give rise to an early memory formation and results in a premature onset of effector CD8+ T cell contraction. This data extend previous knowledge of IRF4 being essential for the differentiation and functionality of ag-specific effector CD8+ T cells, as it furthermore dictates the onset of CD8+ T cell contraction via the activation of several death and phagocytosis inducing pathways.

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Testa, Maurice. "Contribution à la réalisation d'un service de transfert de fichiers et de transfert et de manipulation de travaux sur materiel MITRA suivant le standard NIFTP B (80)." S.l. : Université Grenoble 1, 2008. http://dumas.ccsd.cnrs.fr/dumas-00312748.

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SCHAFFNER, RECKINGER ELISABETH. "Role des motifs cytoplasmiques nply#7#4#7 et nity#7#5#9 de la sous-unite beta(3) dans les fonctions de signalisation de l'integrine alpha(v) beta(3)." Paris 11, 1998. http://www.theses.fr/1998PA112305.

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Les integrines sont des glycoproteines heterodimeriques alpha/beta transmembranaires qui relient la matrice extracellulaire au cytosquelette. Leur double role dans l'adherence cellulaire et la transmission de signaux est regulee surtout par la partie cytoplasmique de la chaine beta. Afin de determiner le role des motifs cytoplasmiques hautement conserves cyto-3 nity#7#5#9 et cyto-2 nply#7#4#7 de la sous-unite beta(3) dans le fonctionnement de l'integrine alpha(v)beta(3), nous avons exprime dans les cellules cho des mutants beta(3), presentant des deletions sequentielles des motifs cyto-3 et cyto-2 ou des substitutions des residus tyrosine en alanine ou phenylalanine. Les etudes fonctionnelles des clones cho transfectes ont montre que le domaine cytoplasmique beta(3) joue un role essentiel dans differentes fonctions de alpha(v)beta(3), telles que la reorganisation du cytosquelette, l'induction de la phosphorylation de la fak et de la paxilline ainsi que la regulation de changements allosteriques extracellulaires a la suite de la fixation d'un ligand. Nos resultats montrent que les substitutions du residu tyr#7#4#7 ont des effets inhibiteurs plus considerables que celles de tyr#7#5#9, soulignant l'importance de la conformation du motif cyto-2 nply#7#4#7. L'etude des mutants y747f et y759f suggere qu'une phosphorylation de tyr#7#5#9 ne joue pas de role dans la transmission de signaux outside-in dependant de alpha(v)beta(3), alors que la presence de tyr#7#4#7 est necessaire pour un fonctionnement optimal du recepteur. Finalement, la deletion du motif nity#7#5#9 entraine la perte totale de toutes les fonctions de alpha(v)beta(3) etudiees, ce qui souligne l'importance de cette region pour les proprietes fonctionnelles de beta(3). L'etude de l'endocytose des recepteurs alpha(v)beta(3)wt et alpha(v)beta(3)y747a permet de suggerer que le motif cyto-2 nply#7#4#7 n'est pas directement implique dans ce mecanisme, puisque les deux recepteurs montrent des taux d'internalisation similaires.

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Hartung, Anett [Verfasser], Kai [Gutachter] Matuschewski, Andreas [Gutachter] Thiel, Hans-Dieter [Gutachter] Volk, and Alf [Gutachter] Hamann. "An essential role of IRF4 in translating TCR a nity-mediated activation and CD8+ e ector T cell fate decisions / Anett Hartung. Gutachter: Kai Matuschewski ; Andreas Thiel ; Hans-Dieter Volk ; Alf Hamann." Berlin : Lebenswissenschaftliche Fakultät, 2016. http://d-nb.info/110984641X/34.

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AKBARITABAR, ALIAKBAR. "QUANTITATIVE SOCIOLOGY OF ACADEMIC WORK IN AN ERA OF HYPERCOMPETITION AND RANKINGS." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/635951.

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In recent years, higher education institutes have shifted towards managerial organisational models. Some observers see this as a sign of our neoliberal times, with obsession for rankings, performance indicators and resource allocation. The result is that academic work is more competitive nowadays. Rankings and quantitative analysis of research output are more and more crucial for hiring, promotion and funding allocations. Chapter 2 touches upon these themes and suggests the fruitfulness of cross fertilisation between sociology and science studies. To study this hyper-competitive context, we designed a complex research project to answer different questions regarding multi-faceted aspects of the subject. Our main question was to find what factors drive research collaboration and productivity. These factors are helping some researchers be more successful than others in current evaluation based system. We have employed two sets of data to achieve this goal. One national and one international, both considering the case of sociologists. For individual research productivity measurement and to explore correlates of this productivity (Chapter 3) and macro level policy effect analysis (Chapter 4), we reconstructed the full publication list of all currently hired Italian sociologists on available data. We looked into their research productivity and how they have reacted to the ANVUR national policies by taking into account their embeddedness in different academic contexts. Our aim in Chapter 3 was to explain individual research productivity with organisational embeddedness and we found that male scientists, those working more internationally, and those working with a similar group of coauthors were more productive but not necessarily more cited by other members of the community.In Chapter 4, we analysed the effects of the Italian national research assessment exercise (VQR 2004-2010 by ANVUR) on research productivity and publication behavior of sociologists. Results showed that ANVUR had a limited influence on research productivity. Indeed most differences in individual research productivity of Italian sociologists were due to individual characteristics. Academics who experienced a promotion after 2010 were the most prolific authors.To explore the structural and societal effects on research productivity of sociologists in a more competitive arena at the international level, in Chapter 5, we reconstructed gender, background information and coauthorship networks of all published authors in two top sociology journals, i.e., the American Journal of Sociology (AJS) and the American Sociological Review (ASR). We expected that examining the élite of our community could reveal interesting patterns, especially to understand certain implications of the hyper-competitive academic culture. We found that white male authors affiliated to US institutes were over-represented in these journals. We also found that male authors tended to work more in team and found trace of significant gender and ethnicity penalties. In Chapter 6 we looked into research communities formation and evolution through the time among Italian sociologists. We aimed to investigate if being a member of these communities would inspire different patterns of scientific collaboration among Italian sociologists. We used a sophisticated multi-level design by using temporal community detection. We found the two largest and most stable research communities among Italian sociologists who were political and economic sociologists. We further explored the underlying mechanisms and processes of coauthorship tie existence in multi-level exponential random graph models (ERGMs) trying to take individual, community and macro levels into account in one integrated framework. We found that the collaboration ties were mainly driven by research focus while preferential attachment was also at work and highly prolific researchers attracted further coauthorship ties. In Chapter 7, we conclude by emphasising that academic work has changed drastically in 21st century. Scientific collaboration is a multi-faceted phenomenon and any effort at studying it only with one or two approaches or with one observational unit would yield reductionistic results. That was the main reason behind our effort to investigate this phenomenon from different points of views. Finally, in Appendices Chapter, how to access the data and R and Python scripts developed during this research project is described and an Annotated bibliography on different aspects of academic work is provided.

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DEKAA, BARNAA LOHITAA. "STUDY OF IMPACT OF DEMONETIZATION ON INDIAN STOCK MARKET." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16990.

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On 8th November 2016, the then Prime Minister of India, Mr. Narendra Modi announced that the Indian Currency Notes of value 500 and 1000 will no more be a legal tender. This news came as storm for the Indian which was received with mixed feelings. Prior to Demonetization, cash in circulation was nearly 220 Billion dollars of which approximately 87% i.e. nearly 190 Billion Dollar was in INR 500 & INR 1000 currency notes. This meant its impact was bound to be felt by all sections of the society. In this present paper, we wanted to analyse the impact of this event of demonetization particularly on Indian Stock Market. We have gathered stock market data of last one year and have tried to study its behaviour before and after the demonetization in order to understand its impact. Keyword Index: Demonetization, Stock Market, NSE, BSE, SENSEX,NIFTY

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Anderson, BR. "Structure, alteration and mineralisation of the Nifty Copper Deposit, Western Australia: Implications for ore genesis." Thesis, 1999. https://eprints.utas.edu.au/12960/1/Front_Anderson_B_PhD1999.pdf.

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The Nifty Cu deposit is located approximately 450km east of Port Hedland, Western Australia in subgreenschist grade rocks of the Proterozoic Paterson Orogen. The deposit consists of a secondary oxide resou~ce of 12.2 Mt@ 2.52% Cu and a primary sulphide ore body of94Mt @1.63% Cu (0.5% cut-off). Mineralisation is hosted in plunging syncline of carbonaceous and dolomitic shales of the upper Broadhurst Formation. The depositional age of the Broadhurst Formation is constrained to between 1132±21 and 816±6Ma. A reinterpretation of the local stratigraphy proposes that the mine sequence consist of the footwall beds, Nifty member, pyrite marker bed, and hanging wall beds. The footwall beds consist of chloritic and pyritic shales. The Nifty member is sub-divided into the lower unit, intermediate shale, upper unit and upper shale. The lower unit contains 40-70m thick package of interbedded finegrained, pale grey, dolomitic mudstone and blue-black, carbonaceous shale. Separating the lower and upper units is a prominent 1-4 metre thick bed of dark-grey to black, very fine-grained, chloritic shale. The upper unit (25-60m) has a similar composition to that of the lower unit and consists of alternating beds of laminated carbonaceous shale and dolomitic mudstone. The upper shale (20-40m) consists of dark-grey to black, laminated, carbonaceous shale with thin to massive framboidal pyrite scams and blebs, disseminated very fine-grained framboidal pyrite and minor dolomitic mudstone. Overlying the Nifty member is the pyrite marker bed, which consists of 1-22m of framboidal pyrite in carbonaceous shale. Above the pyrite marker bed is a 20-60m thick package of carbonaceous and pyritic shales of the hangingwall beds and 5-60m finely laminated dolomitic and calcareous silty shale of the upper carbonate bed. Five deformation events are recognised. 0 1 includes rare variably oriented folds of unknown significance. 0 2 produced regional folding and cleavage during north-east to south-west compression. Folds tend to be doubly plunging with axes trending north-east, south-west. 0 2 deformation has been at dated at Maroochydore as occurring at 717±6Ma (Reed, 1996). 0 3 is an upright folding and faulting event that folds S2. Associated with D3 is a north-north-east striking, slaty cleavage that is less well developed than S2. 0 4 is a complex folding event with sub-horizontal axial planes and fold axis coaxial to 0 2. A brittle deformation event, D5 has also been recognised and this event has resulted in fault offsetting of the ore body. There is significant structural complexity in the Nifty syncline area but most of the complexity is due to small scale, local, fault related events. The Nifty Cu deposit occurs as a structurally controlled, chalcopyrite-quartz-dolomite replacement of carbonaceous and dolomitic shale. The main phase of Cu mineralisation occurred during 0 2 deformation and is associated with a zoned hydrothermal alteration system. Six mineralisation textures were observed; veins, vein networks, breccia matrix, and a progressive sequence of isolated chalcopyrite spots and blebs, to bedding parallel bands, and finally replacement of host rock. Early framboidal pyrite with later chalcopyrite, euhedral pyrite, sphalerite, and galena are the dominant sulphide species. Sphalerite and galena occur in isolated zones in siliceous and pyritic beds of the pyrite marker bed and deposit footwall. Minor diagenetic alteration occurs as £1-Fe-Mg Carbonate in several prominent bands in hangingwall shales 2-5m above the pyrite marker bed. Two main stages of alteration occur at Nifty. A pre-D2• unmineralised, siliceous alteration, £2-Green Quartz, wilh minor chlorite+ pyrite+ hematite+ sericite+ stilpnomelane, replaces interbedded carbonaceous shale and dolomitic mudstone beds of the upper and lowe!' unit of the Nifty member. The second phase (syn-D2) of alteration is associated with Cu mineralisation and occurs as a zoned quartz-dolomite system. Distal alteration consists of S2-Silicified Pyritic Shale where quartz+ sphalerite+ galena+ chalcopyrite and cuhedral pyrite ~verprint framboidal pyrite beds in the pyrite marker bed and immediate deposit footwall. Inward is a progressive sequence of interbedded/banded SJ-Hydrothermal Quartz-Dolomite and unaltered shale beds. The SJ-Hydrothermal Quartz-Dolomite alteration first appears as spots and veins with 2-4mm light grey alteration margins in lhe footwall followed by coalesced spots. An Fe-rich variant of hydrothermal dolomite occurs where minor SJ-Chloritic Shale was observed on the distal margin of Fe-rich quartz-dolomite altered rocks. Further inward and proximal to the highest ore grade is S4-Silicified Dolomitic Shale (dolostone) lhat grades into S5-Biack Silica in the centre of the ore body. S5 alteration consists of fine-grained quartz + chalcopyrite + apatite + carbonaceous material and replaces host rock and earlier siliceous alteration. Cu grade has a strong positive correlation with intensity of alteration. Minor concentrations of Pb and Zn are associated with bedding parallel quartz flooding + chalcopyrite + euhedral pyrite of S2-Silicified Pyritic Shale. Sphalerite and galena replace pyrite framboids. A new method of calculating mass balance change in compositions during alteration has been developed. This method uses a log transform of the element of interest divided by an immobile element. The logratio method is scale invariant and therefore avoids the unit sum problem. This melhod has been applied to Nifty multi-element data from host rock lithologies and alteration phases. Mass balance calculations suggests that during intense alteration (S4 and S5) the central core of the deposit was enriched in Cu, Si02, As, Zn, Pb, Sn, Ni, U, Fez03 andY. Depletion has occurred in Ba, Sr, and Rb. The outer halo of the deposit experienced similar additions but of a smaller magnitude. An implication of the mass balance analysis is that there has been a significant volume change during alteration and mineralisation. The highest concentration of Cu occurs within hydrothermally altered rocks of the upper and lower units of the Nifty member while Pb and Zn occur in silicified pyrite shales in the pyrite marker bed and footwall beds. High concentrations of Zn also occur in shale above the upper carbonate beds. This distribution of base-metals has resulted in a vertical metal zonation of Cu~Pb~Zn. New galena Pb isotope data from the Nifty Cu deposit and other regional prospects have been combined with existing galena data to constrain the source of Pb. Pb isotope data from Throssell Group deposits and prospects plot as a linear trend in 206PbP04Pb vs 206PbP04Pb space. The Warrabarty Pb-Zn prospect plots at the least radiogenic end, Maroochydore Cu deposit at the most radiogenic end, and lhe Nifty Cu deposit plots towards the least radiogenic end of the trend. The Throssell Group linear trend suggests mixing between two Pb sources. Potential sources of Pb are I) Rudall Complex, 2) Pilbara Craton, or 3) internally sourced Pb leached from Throssell Group sediments. The Rudall Complex Pb signature is poorly defined as shown by initial Pb-Pb ratios of K-feldspars separates. Galena Pb isotope data from deposits in the Pilbara Craton plot on a Pb evolution trend similar to the growth curve of Cumming and Richards (1975). A source-mixing model is proposed where Pb from a magmatic source (J.t:=9.88) is mixed with crustal Pb (J.t:=l0.55): The position of deposits and prospects along the linear trend suggests that the Pb in the Warrabarty Pb-Zn prospect was dominated by magmatic Pb and that Pb at the • Maroochydore Cu deposit has a crustal source. Pb in the Nifty Cu deposit appears to have a mixed source. Syn-mincralisation fluid inclusions are small (commonly <5-lOJ.lm) and consist a simple two phase petrology of liquid and vapour. Fluid inclusion trapping temperatures of mineralising fluids at Nifty range between 270-457°C (median 358°C) and salinity of 8-27 eq. wt.% NaCl (median 15 eq. wt.% NaCI). Post mineralisation inclusions have trapping temperatures between 18I-269°C (median 190°C) and salinity of 11-15 eq. wt.% NaCI (median 13 eq. wt.% NaCl). Sulphur isotope data from framboidal pyrite ranges between o34ScoT of -27 and + 16%o, suggesting that the source of framboidal pyrite sulphur is a combination of reduced seawater sulphate and evaporite sulphate. Chalcopyrite o34ScoT ranges between -6 and +6%o and o34ScoT for euhcdral, syn-mineralisation pyrite ranges between - 12 to+ 12%o. The range of syn-mineralisation sulphide data suggest that source of sulphur at Nifty was homogenous and that syn-mineralisation sulphides did not utilise existing sulphur from sedimentary pyrite. The o34S range of -6 to +6%o for chalcopyrite also suggests a reduced magmatic hydrothermal source of sulphur. Carbon and oxygen isotopic data from host rock carbonates, pre-, syn-, and post-mineralisation vein stages have lighter oxygen and carbon values than other deposits in the region. Results from the various vein stage carbonates overlap, with o13Cvpo8 values from approximately 6 to -13%o and o180vsMow values from approximately 15 to 20%o. Carbon and oxygen isotope trend modelling suggests that fluid mixing and fluid/rock interaction are potential precipitation mechanisms. A model for the formation of the Nifty Cu deposit is proposed whereby compression associated with the Miles Orogeny caused the expulsion hydrothermal fluids from deep in the Yeneena Basin. Fluid expulsion was driven by 1ithostatic loading due to overriding thrust sheets. Hydrothermal fluids travelled along a basement decollement and then ascend D2 thrust faults toward zones of low pressure. During tightening of the Nifty syncline thrust faulting penetrated carbonaceous and dolomitic shales allowing hydrothermal fluids to enter the Nifty member. Early fluid pulses were weakly oxidised and contained low concentrations of base metals. These fluids altered the host rock and precipitated £2-Green Quartz. Later hydrothermal fluid changed, increasing the concentration of base metals, became hotter, more saline, reduced and moderately acidic. On encountering the Nifty member, hydrothermal fluids reacted with dolomite-dominated beds forrning the dolomitic alteration textures and in turn, siliceous replacement of carbonaceous shale and dolomitic mudstone. Chalcopyrite precipitation was controlled mainly by changes in pH and /02 caused by the reaction of acidic, hydrothermal fluids with the dolomite-bearing host rock.

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Dixit, Alok. "Pricing efficiency of S & P CNX Nifty index options: a study in Indian securities market." Thesis, 2009. http://localhost:8080/iit/handle/2074/4664.

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Books on the topic "NIFTY"

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Palmer, Carolann. Nifty ninepatches. [Bothell, WA]: That Patchwork Place., 1992.

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Rasmussen, Greta. Nifty fifty. Stanwood, WA: Tin Man, 1988.

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Eldridge, Roy. The nifty cat. New York: New World Records, 1986.

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Avery, Virginia. Virginia Avery's nifty neckwear. Lafayette, Calif: C&T Pub., 1994.

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Eric, Ladizinsky, and Yamamoto Neal ill, eds. 50 nifty science experiments. Los Angeles: Lowell House Juvenile, 1992.

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Eric, Ladizinsky, and Yamamoto Neal, eds. 50 nifty science experiments. Lincolnwood, Ill: NTC Publishing, 1992.

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ill, Yamamoto Neal, ed. 50 nifty magic tricks. Los Angeles: Lowell House Juvenile, 1992.

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Sharon, McCoy, Olexiewicz Charlene ill, Yamamoto Neal ill, and Staunton James ill, eds. 150 nifty super crafts. Los Angeles, Calif: Lowell House Juvenile, 2000.

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Bartkowski, Alli. 50 nifty quilled cards. New York: Lark Books, 2008.

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Stewart, Melissa. Nifty noses up close. Berkeley Heights, NJ: Enslow Publishers, 2011.

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Book chapters on the topic "NIFTY"

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Dlugos, Jenn, and Charlie Hatton. "A Nifty Trip from Crypt to Tip." In You under the Microscope, 46. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781003292111-30.

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Alexander, Rhoda, and Husam Aldin Al-Malkawi. "The Impact of Macroeconomic Factors on the Nifty Auto Index." In Lecture Notes in Civil Engineering, 11–21. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27462-6_2.

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AbstractThe aim of the paper is to investigate the association between selected macroeconomic variables like crude price, exchange rate, index of industrial production, inflation, interest rate, repo rate, gold price and the auto index of the National Stock Exchange (NSE) of India during a time when the automotive sector in India witnessed the sharpest dip in sales. The study adopts Autoregressive Distributed Lag (ARDL) co-integration approach and performs suitable diagnostic tests. Results indicate that, exchange rate has a significant negative relationship with Nifty auto index in the long run. Additionally, crude price, index of industrial production and repo rates are statistically significant determinants of Nifty auto index. On the contrary, first lag of crude price is found to be a possible predictor of the index in the short run. The study provides important implications for researchers, corporations, portfolio managers, investors, and government. Despite the availability of a large body of literature exploring the association between macro-economic factors and stock market in India, research exploring the association between the former and Indian auto indices has been sparse. Hence, this study is intended to fill this gap in the literature.

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Balaji, Lavanya, H. B. Anita, and Balaji Ashok Kumar. "Volatility Clustering in Nifty Energy Index Using GARCH Model." In Intelligent Communication Technologies and Virtual Mobile Networks, 667–81. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1844-5_53.

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Singh, Dilip, and Bhupendra Kumar Gupta. "Closing Price Prediction of Nifty Stock Using LSTM with Dense Network." In Lecture Notes in Networks and Systems, 382–92. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-4807-6_37.

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Kumar, Bhupendra, and Neha Yadav. "NIFTY-50 Index Forecasting Using CEEMDAN Decomposition and Deep Learning Models." In Proceedings on International Conference on Data Analytics and Computing, 349–58. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3432-4_27.

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Chhikara, Yashasvi, and Parth Desai. "Regression Analysis on Macroeconomic Factors and Dividend Yield on Bank Nifty Index Returns." In Lecture Notes in Networks and Systems, 419–27. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9689-6_45.

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Mondal, Bhaskar, Om Patra, Ashutosh Satapathy, and Soumya Ranjan Behera. "A Comparative Study on Financial Market Forecasting Using AI: A Case Study on NIFTY." In Advances in Intelligent Systems and Computing, 95–103. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9927-9_10.

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Deepika, N., and P. Victer Paul. "Analyzing Effect of Political Situations on Sensex-Nifty-Rupee—A Study Based on Election Results." In Proceedings of the Third International Conference on Computational Intelligence and Informatics, 811–19. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1480-7_75.

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Murali, Ranjani. "Analysis of COVID-19 Pandemic and Lockdown Effects on the National Stock Exchange NIFTY Indices." In Cybernetics, Cognition and Machine Learning Applications, 313–21. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6691-6_35.

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Sen, Jaydip, and Abhishek Dutta. "A Comparative Study of Hierarchical Risk Parity Portfolio and Eigen Portfolio on the NIFTY 50 Stocks." In Computational Intelligence and Data Analytics, 443–60. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3391-2_34.

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Conference papers on the topic "NIFTY"

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Suen, Caroline, Sandy Huang, Chantat Eksombatchai, Rok Sosic, and Jure Leskovec. "NIFTY." In the 22nd international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2488388.2488496.

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Parlante, Nick, Jeffrey Popyack, Stuart Reges, Stephen Weiss, Scott Dexter, Chaya Gurwitz, Joseph Zachary, and Grant Braught. "Nifty assignments." In the 34th SIGCSE technical symposium. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/611892.611914.

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Parlante, Nick, Thomas P. Murtagh, Mehran Sahami, Owen Astrachan, David Reed, Christopher A. Stone, Brent Heeringa, and Karen Reid. "Nifty assignments." In the 40th ACM technical symposium. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1508865.1509031.

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Parlante, Nick, Julie Zelenski, Josh Hug, John Nicholson, John DeNero, Antti Laaksonen, Arto Vihavainen, Frank McCown, and Kevin Wayne. "Nifty assignments." In the 45th ACM technical symposium. New York, New York, USA: ACM Press, 2014. http://dx.doi.org/10.1145/2538862.2538995.

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Parlante, Nick, Julie Zelenski, Keith Schwarz, Dave Feinberg, Michelle Craig, Stuart Hansen, Michael Scott, and David J. Malan. "Nifty assignments." In the 42nd ACM technical symposium. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1953163.1953305.

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Parlante, Nick, Julie Zelenski, Michelle Craig, John DeNero, Mark Guzdial, David J. Malan, Aditi Muralidharan, Eric Roberts, and Kevin Wayne. "Nifty assignments." In Proceeding of the 44th ACM technical symposium. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2445196.2445356.

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Parlante, Nick, Julie Zelenski, Zachary Dodds, Wynn Vonnegut, David J. Malan, Thomas P. Murtagh, Todd W. Neller, Mark Sherriff, and Daniel Zingaro. "Nifty assignments." In the 41st ACM technical symposium. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1734263.1734425.

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Parlante, Nick, Julie Zelenski, Daniel Zingaro, Kevin Wayne, Dave O'Hallaron, Joshua T. Guerin, Stephen Davies, Zachary Kurmas, and Keen Debby. "Nifty assignments." In the 43rd ACM technical symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2157136.2157274.

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Parlante, Nick, David Matuszek, Jeff Lehman, David Reed, John K. Estell, and Donald Chinn. "Nifty assignments." In the 35th SIGCSE technical symposium. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/971300.971318.

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Parlante, Nick, Steven A. Wolfman, Lester I. McCann, Eric Roberts, Chris Nevison, John Motil, Jerry Cain, and Stuart Reges. "Nifty assignments." In the 37th SIGCSE technical symposium. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1121341.1121516.

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Reports on the topic "NIFTY"

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Powell, J., H. Ludewig, M. Todosow, and M. Reich. NIFTI and DISCOS: New concepts for a compact accelerator neutron source for boron neutron capture therapy applications. Office of Scientific and Technical Information (OSTI), June 1995. http://dx.doi.org/10.2172/432936.

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