Relevant bibliographies by topics / Aparchai

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  2. Dissertations / Theses
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  5. Conference papers

Academic literature on the topic 'Aparchai'

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Published: 4 June 2021
Last updated: 10 February 2022

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Journal articles on the topic "Aparchai"

1

Blok, Josine. "Sharing with the Gods. Aparchai and Dekatai in Ancient Greece, written by Jim, Th.S.F." Mnemosyne 70, no. 1 (January 20, 2017): 167–69. http://dx.doi.org/10.1163/1568525x-12342283.

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Wagner-Hasel, Beate. "GIFTS FOR THE GODS - T.S.F. Jim Sharing with the Gods. Aparchai and Dekatai in Ancient Greece. Pp. xvi + 373, ills. Oxford: Oxford University Press, 2014. Cased, £80, US$150. ISBN: 978-0-19-870682-3." Classical Review 66, no. 2 (July 20, 2016): 468–70. http://dx.doi.org/10.1017/s0009840x16001177.

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Jim, Theodora Suk Fong. "APARCHAIIN THE GREAT LIST OF THASIANTHEÔROI." Classical Quarterly 64, no. 1 (April 16, 2014): 13–24. http://dx.doi.org/10.1017/s0009838813000505.

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One of the most baffling inscriptions has come down to us from the so-called ‘Passage of theTheôroi’ at Thasos. Situated at the north-eastern entrance of the ancient agora, and consisting originally of two walls on either side of a path paved by marble, the monumental passage way had a long list of names inscribed on the inside of its western wall; this is the so-called ‘great list of Thasiantheôroi’. Two of its constituent lists bear the headings ἐπὶ τῆς πρώτης ἀπαρχῆς and ἐπὶ τῆς δευ[τέρη]ς ἀπαρχῆς| οἵδε ἐθεόρεον. The meaning of the wordaparchêand the nature of thetheôroiin question have been the subject of disagreement among historians. The aim of this article is to contribute further suggestions to existing discussions.
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SIDADADOLOG, JUITA HARYATI, I. WAYAN SUMARJAYA, and NI KETUT TARI TASTRAWATI. "PERAMALAN VOLATILITAS RETURN SAHAM MENGGUNAKAN METODE ASYMMETRIC POWER ARCH (APARCH)." E-Jurnal Matematika 9, no. 3 (September 2, 2020): 157. http://dx.doi.org/10.24843/mtk.2020.v09.i03.p293.

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Model APARCH is one of the asymmetric GARCH models. These models are able to capture the incidence of good news and bad news in the volatility. The APARCH model has an asymmetric coefficient to cope with leverage effect by modeling a leverage that has heteroscedasticity and asymmetric effect condition. The results of this research were obtained by the appropriate APARCH model. The model is the APARCH(1,2) model because all parameters are significant. Thus, proceeds from the volatility of stock return for the next 14 days with the model volatility APARCH(1,2) increased from period one to period fourteen.
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Aurora Luque. "Aparcar es difícil: –Road movie–." Sirena: poesia, arte y critica 2008, no. 2 (2008): 16. http://dx.doi.org/10.1353/sir.0.0031.

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Hidayatullah, Syarif, and Mohammad Farhan Qudratullah. "Analisis Risiko Investasi Saham Syariah Dengan Model Value AT Risk-Asymmetric Power Autoregressive Conditional Heterocedasticity (VaR-APARCH)." Jurnal Fourier 6, no. 1 (April 4, 2017): 37. http://dx.doi.org/10.14421/fourier.2017.61.37-43.

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Penelitian ini membahas analisis risiko data runtun waktu dengan model Value at Risk- Asymmetric Power Autoregressive Conditional Heteroscedasticity (VaR-APARCH)dalam pasar modal syariah. Metode yang digunakan dalam penelitian ini adalah penerapan kasus.Data yang digunakan adalah harga penutupan harian saham dalam Jakarta Islamic Index (JII)periode 4 Maret 2013 sampai 8 April 2015.Model APARCH yang dipilih berdasarkan nilai Schwarz Criterion (SC).Langkah-langkah dalam penelitian ini adalah menguji kestasioneran data, mengidentifikasi model ARIMA,mengestimasi parameter model ARIMA, menguji diagnostik model ARIMA, mendeteksi ada tidaknya unsur ARCH atau unsur heteroskedastisitas, uji asimetris data saham, mengestimasi model APARCH, menguji diagnostik model APARCH, dan menghitung risiko dengan VaR-APARCH.Model terbaik yang dipilih adalah ARIMA ((3),0,0) dan APARCH (1,1). Model ini valid untuk menganalisis besar risiko investasi dalam jangka waktu 10 hari ke depan.
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Augustine Kutu, Adebayo, and Harold Ngalawa. "Exchange rate volatility and global shocks in Russia: an application of GARCH and APARCH models." Investment Management and Financial Innovations 13, no. 4 (December 29, 2016): 203–11. http://dx.doi.org/10.21511/imfi.13(4-1).2016.06.

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This study examines global shocks and the volatility of the Russian rubble/United States dollar exchange rate using the symmetric Generalized Autoregressive Conditional Heteroscedasticity (GARCH), and Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) models. The GARCH and APARCH are employed under normal (Normal Gaussian) and non-normal (Student’s t and Generalized Error) distributions. Using monthly exchange rate data covering January 1994 – December 2013, the study finds that the symmetric (GARCH) model has the best fit under the non-normal distribution, which improves the overall estimation for measuring conditional variance. Conversely, the APARCH model does not show asymmetric response in exchange rate volatility and global shocks, resulting in no presence of leverage effect. The GARCH model under the Student’s t distribution produces better fit for estimating exchange rate volatility and global shocks in Russia, compared to the APARCH model. Keywords: exchange rate volatility, global Shocks, GARCH and APARCH models. JEL Classification: F30, F31, P33
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Kasse, Irwan, Andi Mariani, Serly Utari, and Didiharyono D. "Investment Risk Analysis On Bitcoin With Applied of VaR-APARCH Model." JTAM (Jurnal Teori dan Aplikasi Matematika) 5, no. 1 (April 17, 2021): 1. http://dx.doi.org/10.31764/jtam.v5i1.3220.

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Investment can be defined as an activity to postpone consumption at the present time with the aim to obtain maximum profits in the future. However, the greater the benefits, the greater the risk. For that we need a way to predict how much the risk will be borne. Modelling data that experiences heteroscedasticity and asymmetricity can use the Asymmetric Power Autoregressive Conditional Heteroscedasticity (APARCH) model. This research discusses the time series data risk analysis using the Value at Risk-Asymmetric Power Autoregressive Conditional Heteroscedasticity (VaR-APARCH) model using the daily closing price data of Bitcoin USD period January 1 2019 to 31 December 2019. The best APARCH model was chosen based on the value of Akaike's Information Criterion (AIC). From the analysis results obtained the best model, namely ARIMA (6,1,1) and APARCH (1,1) with the risk of loss in the initial investment of IDR 100,000,000 in the next day IDR 26,617,000. The results of this study can be used as additional information and apply knowledge about the risk of investing in Bitcoin with the VaR-APARCH model.
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Aparci, Mustafa, and Omer Uz. "Treatment solution by Aparci and Uz." Interactive CardioVascular and Thoracic Surgery 22, no. 5 (April 25, 2016): 699.2–700. http://dx.doi.org/10.1093/icvts/ivw100.

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Laurent, Sébastien. "Analytical Derivates of the APARCH Model." Computational Economics 24, no. 1 (August 2004): 51–57. http://dx.doi.org/10.1023/b:csem.0000038851.72226.76.

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Dissertations / Theses on the topic "Aparchai"

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Jim, Suk Fong. "Gifts to the Gods : Aparchai, Dekatai and related offerings in Archaic and Classical Greece." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:46767d83-0b32-4ebd-8f26-457a785f2478.

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This study is about one of the most ubiquitous and yet little studied aspects of ancient Greek religion, the offering of so-called ‘first-fruits’ (aparchai) and tithes (dekatai) in Archaic and Classical Greece (c.700-300 B.C.). A widespread and traditional custom all over Greece and the Greek Mediterranean, the offering of ‘first-fruits’ and tithes entailed using a portion of the proceeds from a diversity of human activities (such as craft-work, fishing, trade, military expeditions) to present something to the gods. I look at the different kinds of aparchai and dekatai offered to the Greek gods by individuals and states under various circumstances, the various contexts in which the language and practice of making such offerings were used, the deployment of this religious custom in politics, and the transformation of a voluntary practice into a religious obligation. Ultimately, however, my major concern is with questions of religious psychology: why people should bring aparchai and dekatai to the gods, and what motivations and expectations they might have had. Because it was such a commonplace practice, the custom has been taken simply as a given in both ancient and modern scholarship; and no attempt has been made to explain its religious significance. By drawing on current anthropological studies of gift-giving, I argue that that aparchai and dekatai do not merely give to the gods, but give back to the gods some of the benefits granted by the divinities in the first place, reflecting first and foremost a sense of dependence on the divine. I suggest that the offering of aparchai and dekatai may be thought of as a means of settling men’s debts to, and thereby maintaining good relations with, the gods, who were considered the sources of both goods and evils. I challenge the emphasis, common in modern scholarship, on material returns as the central motive behind the act of bringing gifts to the gods. Instead I suggest that the study of gift-giving between humans and the divine should embrace the possibility that psychological feelings of dependence on and gratitude to the gods might also have been involved.
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Ding, Ding. "Modeling of Market Volatility with APARCH Model." Thesis, Uppsala universitet, Analys och tillämpad matematik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-153703.

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Gasparini, Daniela Caetano de Souza. "Verificação da performance de modelos APARCH assimétricos aplicados a dados financeiros." Universidade Federal de São Carlos, 2013. https://repositorio.ufscar.br/handle/ufscar/4567.

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Made available in DSpace on 2016-06-02T20:06:07Z (GMT). No. of bitstreams: 1 5123.pdf: 958057 bytes, checksum: 23f5ad95404afd58fe48eeb517ef5b41 (MD5) Previous issue date: 2013-04-01
Financiadora de Estudos e Projetos
The volatility of financial assets changes over time, indicating the specification of regime change in volatility models. Furthermore, the presence of asymmetry in the returns of the financial market has been recognized in the financial literature of recent decades. In this paper, we present some heteroscedastic models with regime change, considering that the error component of these models follows Skew Laplace distribution, as well as the process of estimating its parameters via maximum likelihood and Bayesian methods.
A volatilidade dos ativos financeiros se altera ao longo do tempo, sinalizando a especificação de mudança de regime para modelos de volatilidade. Além disso, a presença de assimetria nos retornos do mercado financeiro tem sido reconhecida na literatura financeira das últimas décadas. Neste trabalho, apresentamos alguns modelos heterocedásticos com mudança de regime, considerando que a componente do erro desses modelos segue distribuição Laplace assimétrica, bem como o processo de estimação de seus parâmetros via máxima verossimilhança e métodos bayesianos.
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White, Joel R. "Christ, the firstfruits the Old Testament background of [aparchē] in 1 Corinthians 15:20-23 and its function in Paul's argument /." Theological Research Exchange Network (TREN), 2000. http://www.tren.com.

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Thesis (Th. M.)--Gordon-Conwell Theological Seminary, South Hamilton, Mass., 2000.
Abstract and vita. "Aparchē" appears in Greek letters on t.p. Includes bibliographical references (leaves 130-139).
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Higgs, Helen. "Price and volatility relationships in the Australian electricity market." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16404/.

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This thesis presents a collection of papers that has been published, accepted or submitted for publication. They assess price, volatility and market relationships in the five regional electricity markets in the Australian National Electricity Market (NEM): namely, New South Wales (NSW), Queensland (QLD), South Australia (SA), the Snowy Mountains Hydroelectric Scheme (SNO) and Victoria (VIC). The transmission networks that link regional systems via interconnectors across the eastern states have played an important role in the connection of the regional markets into an efficient national electricity market. During peak periods, the interconnectors become congested and the NEM separates into its regions, promoting price differences across the market and exacerbating reliability problems in regional utilities. This thesis is motivated in part by the fact that assessment of these prices and volatility within and between regional markets allows for better forecasts by electricity producers, transmitters and retailers and the efficient distribution of energy on a national level. The first two papers explore whether the lagged price and volatility information flows of the connected spot electricity markets can be used to forecast the pricing behaviour of individual markets. A multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model is used to identify the source and magnitude of price and volatility spillovers within (intra-relationship) and across (inter-relationship) the various spot markets. The results show evidence of the fact that prices in one market can be explained by their own price lagged one-period and are independent of lagged spot prices of any other markets when daily data is employed. This implies that the regional spot electricity markets are not fully integrated. However, there is also evidence of a large number of significant ownvolatility and cross-volatility spillovers in all five markets indicating that shocks in some markets will affect price volatility in others. Similar conclusions are obtained when the daily data are disaggregated into peak and off-peak periods, suggesting that the spot electricity markets are still rather isolated. These results inspired the research underlying the third paper of the thesis on modelling the dynamics of spot electricity prices in each regional market. A family of generalised autoregressive conditional heteroskedasticity (GARCH), RiskMetrics, normal Asymmetric Power ARCH (APARCH), Student APARCH and skewed Student APARCH is used to model the time-varying variance in prices with the inclusion of news arrival as proxied by the contemporaneous volume of demand, time-of-day, day-of-week and month-of-year effects as exogenous explanatory variables. The important contribution in this paper lies in the use of two latter methodologies, namely, the Student APARCH and skewed Student APARCH which take account of the skewness and fat tailed characteristics of the electricity spot price series. The results indicate significant innovation spillovers (ARCH effects) and volatility spillovers (GARCH effects) in the conditional standard deviation equation, even with market and calendar effects included. Intraday prices also exhibit significant asymmetric responses of volatility to the flow of information (that is, positive shocks or good news are associated with higher volatility than negative shocks or bad news). The fourth research paper attempts to capture salient feature of price hikes or spikes in wholesale electricity markets. The results show that electricity prices exhibit stronger mean-reversion after a price spike than the mean-reversion in the normal period, suggesting the electricity price quickly returns from some extreme position (such as a price spike) to equilibrium; this is, extreme price spikes are shortlived. Mean-reversion can be measured in a separate regime from the normal regime using Markov probability transition to identify the different regimes. The fifth and final paper investigates whether interstate/regional trade has enhanced the efficiency of each spot electricity market. Multiple variance ratio tests are used to determine if Australian spot electricity markets follow a random walk; that is, if they are informationally efficient. The results indicate that despite the presence of a national market only the Victorian market during the off-peak period is informationally (or market) efficient and follows a random walk. This thesis makes a significant contribution in estimating the volatility and the efficiency of the wholesale electricity prices by employing four advanced time series techniques that have not been previously explored in the Australian context. An understanding of the modelling and forecastability of electricity spot price volatility across and within the Australian spot markets is vital for generators, distributors and market regulators. Such an understanding influences the pricing of derivative contracts traded on the electricity markets and enables market participants to better manage their financial risks.
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Mohammed, Ansarullah Ridwan. "Analysis of Islamic Stock Indices." Thesis, 2009. http://hdl.handle.net/10012/4355.

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In this thesis, an attempt is made to build on the quantitative research in the field of Islamic Finance. Firstly, univariate modelling using special GARCH-type models is performed on both the FTSE All World and FTSE Shari'ah All World indices. The AR(1) + APARCH(1,1) model with standardized skewed student-t innovations provided the best overall fit and was the most successful at VaR modelling for long and short trading positions. A risk assessment is done using the Conditional Tail Expectation (CTE) risk measure which concluded that in short trading positions the FTSE Shari'ah All World index was riskier than the FTSE All World index but, in long trading positions the results were not conclusive as to which is riskier. Secondly, under the Markowitz model of risk and return the performance of Islamic equity is compared to conventional equity using various Dow Jones indices. The results indicated that even though the Islamic portfolio is relatively less diversified than the conventional portfolio, due to several investment restrictions, the Shari'ah screening process excluded various industries whose absence resulted in risk reduction. As a result, the Islamic portfolio provided a basket of stocks with special and favourable risk characteristics. Lastly, copulas are used to model the dependency structure between the filtered returns of the FTSE All World and FTSE Shari'ah All World indices after fitting the AR(1) + APARCH(1,1) model with standardized skewed student-t innovations. The t copula outperformed the others and a demonstration of forecasting using the copula-extended model is done.
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Yun-Shyang, Yo, and 游雲翔. "The Effect of Distribution of Financial Assets at Higher Order Moments to VaR –Application of APARCH model." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/33151329562869593463.

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碩士
東海大學
財務金融學系
95
This research discusses how the behavior of the volatility and non-normality affects the performance of VaR by using the equity index data of East Asian Tigers(Hong Kong, Taiwan, Singapore and South Korea). I employ GJR-GARCH model and APARCH model to investigate whether the long memory characteristics play the significant role on VaR. Second, I replace the normal distribution assumption of GARCH family models with Student t and skewed Student t distribution to analyze the properties of higher order moments, specifically, fat tail and skewness, to VaR performance. Empirical result shows that the GARCH family models based on normal distribution has poor performance in the description of extreme left tail, which can be alleviated by considering a long-memory based conditional variance model or taking a more flexible distribution instead. Of interesting, the finding also indicates the potential conservative problem caused by the symmetrical distribution, such as fat-tail Student t distribution, could be improved by adopting an asymmetrical general distribution, such as skewed Student t distribution.
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Malandala, Kajingulu. "Analysis of dependence structure between the Rand/U.S Dollar exchange rate and the gold/platinum prices." Diss., 2018. http://hdl.handle.net/10500/25239.

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Copulas functions are a flexible tool for modelling the dependence structure between variables. The joint and marginal distributions of Copulas are not constrained by the assumptions of normality. This study examines the dependence structure between the gold, platinum prices and the ZAR/U.S.D exchange rate using Copulas. The study found that marginal distributions of Copulas follows the ARMA (1, 1)-EGARCH (1, 1) and ARMA(1, 1)-APARCH (1, 1) models under different error terms including the normal, the student-t and the skew student-t error terms. It used the Normal, the Student-t, the Gumbel, the rotated Gumbel, the Clayton, the rotated Clayton, the Plackett, the Joe Clayton and the Normal time varying Copulas to analyse the dependence structure between returns prices of gold, platinum and ZAR/U.S.D exchange rate. The results showed evidence of a positive strong dependence between the returns prices of gold, platinum and returns on the Rand/U.S.D exchange rate for constant and time varying Copulas. The result also showed a co-movement of exchange rates and gold and platinum prices during a rise or declining prices of gold and platinum. The results imply that fluctuations in gold and platinum prices generate Rand/U.S.D exchange rate volatility.
Statistics
M. Sc. (Statistics)
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Books on the topic "Aparchai"

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Rabinowitch, David. Aparchai drawings, 1985-86. Zürich: Annemarie Verna Galerie, 1987.

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Zōrzos, Grēgorēs. Aparchai: Ho anthrōpos ston Theo. Athēnai: Ideotheatron, 1998.

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Manousakas, M. I. Hoi Aparches tēs Hellēnikēs typographias. Athēna: Hetaireia Spoudōn Neoellēnikou Politismou & Genikēs Paideias, 1989.

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Geōrgēs, Giōrgos. Stis aparches tēs Hellēnikēs exōterikēs politikēs. Athēna: Ekdoseis Kastaniōtē, 1995.

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Polytechneio 1973: Hē aparchē tou autonomou kinēmatos. Thessalonikē: Nēsides, 2013.

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Tafrali, Oreste. Hē Thessalonikē: Apo tis aparches ston 14o aiōna. Athēna: Trochalia, 1994.

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Agriantōnē, Christina. Hoi aparches tēs ekviomēchanisēs stēn Hellada ton 19. ai. Athēna: Historiko Archeio, Emporikē Trapeza tēs Hellados, 1986.

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Sophia, Daskalopoulou, ed. Stis aparches tēs Neoellēnikēs ideologias: To chroniko tēs Dropolēs. Athēna: Ekdoseis Aphōn. Tolidē, 1999.

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Agriantōnē, Christina. Oi aparches tēs ekviomēchanisēs stēn Ellada ton 19. ai. Athēna: Istoriko Archeio, Emporikē Trapeza tēs Ellados, 1986.

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To Byzantio kai oi aparches te s Euro pe s. Athe na: Ethniko Idryma Ereuno n, 2004.

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Book chapters on the topic "Aparchai"

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da Conceição Costa, Maria, Manuel G. Scotto, and Isabel Pereira. "Integer-Valued APARCH Processes." In Time Series Analysis and Forecasting, 189–202. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28725-6_15.

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Jim, Theodora Suk Fong. "A Network of Aparchai." In Sharing with the Gods, 203–49. Oxford University Press, 2014. http://dx.doi.org/10.1093/acprof:oso/9780198706823.003.0008.

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Osagie Adenomon, Monday. "Financial Time Series Analysis via Backtesting Approach." In Linked Open Data - Applications, Trends and Future Developments. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.94112.

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This book chapter investigated the place of backtesting approach in financial time series analysis in choosing a reliable Generalized Auto-Regressive Conditional Heteroscedastic (GARCH) Model to analyze stock returns in Nigeria. To achieve this, The chapter used a secondary data that was collected from www.cashcraft.com under stock trend and analysis. Daily stock price was collected on Zenith bank stock price from October 21st 2004 to May 8th 2017. The chapter used nine different GARCH models (standard GARCH (sGARCH), Glosten-Jagannathan-Runkle GARCH (gjrGARCH), Exponential GARCH (Egarch), Integrated GARCH (iGARCH), Asymmetric Power Autoregressive Conditional Heteroskedasticity (ARCH) (apARCH), Threshold GARCH (TGARCH), Non-linear GARCH (NGARCH), Nonlinear (Asymmetric) GARCH (NAGARCH) and The Absolute Value GARCH (AVGARCH) with maximum lag of 2. Most the information criteria for the sGARCH model were not available due to lack of convergence. The lowest information criteria were associated with apARCH (2,2) with Student t-distribution followed by NGARCH(2,1) with skewed student t-distribution. The backtesting result of the apARCH (2,2) was not available while eGARCH(1,1) with Skewed student t-distribution, NGARCH(1,1), NGARCH(2,1), and TGARCH (2,1) failed the backtesting but eGARCH (1,1) with student t-distribution passed the backtesting approach. Therefore with the backtesting approach, eGARCH(1,1) with student distribution emerged the superior model for modeling Zenith Bank stock returns in Nigeria. This chapter recommended the backtesting approach to selecting reliable GARCH model.
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Jim, Theodora Suk Fong. "The Vocabulary of Aparche, Aparchesthai, and Related Terms." In Sharing with the Gods, 28–58. Oxford University Press, 2014. http://dx.doi.org/10.1093/acprof:oso/9780198706823.003.0002.

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Conference papers on the topic "Aparchai"

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Deng, Ze-Hui. "Volatility Forecasting Using APARCH with Skewed Conditional Distributions." In 2010 International Conference on E-Business and E-Government (ICEE). IEEE, 2010. http://dx.doi.org/10.1109/icee.2010.1338.

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Nugroho, Didit Budi, and Bambang Susanto. "Volatility modeling for IDR exchange rate through APARCH model with student-t distribution." In THE 4TH INTERNATIONAL CONFERENCE ON RESEARCH, IMPLEMENTATION, AND EDUCATION OF MATHEMATICS AND SCIENCE (4TH ICRIEMS): Research and Education for Developing Scientific Attitude in Sciences And Mathematics. Author(s), 2017. http://dx.doi.org/10.1063/1.4995120.

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Yanxiang Chen and Jianying Luo. "Notice of Retraction: Risk measurement of Chinese SMEB stock market: An APARCH-SKST approach." In 2010 IEEE International Conference on Advanced Management Science (ICAMS). IEEE, 2010. http://dx.doi.org/10.1109/icams.2010.5553214.

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