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Articoli di riviste sul tema "Prices – Statistical methods"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 19 febbraio 2022

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1

Ellingerová, Helena, Zora Petráková, and Ingrida Skalíková. "Statistical Methods in Building Industry to Determine Prices Indices." Tehnički glasnik 14, no. 4 (December 9, 2020): 458–65. http://dx.doi.org/10.31803/tg-20200604105846.

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Tender price is often affected by the location of the construction, which is usually determined by the investor, and it has an impact on the traffic in the particular location. Individual time of supply and the method of realization play an important role as well. They both are determined by the investor along with the designer of the particular construction. Contractors often complain about the lack of time needed for the preparation of their tender prices. Therefore, it is necessary to look for the possibilities how to reliably speed up this process at the same time taking into account all o

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2

Rudko, G. I., M. M. Kurylo, V. V. Bala, and Yu S. Makovskyi. "METHODS FOR PRICE DETERMINATION (JUSTIFICATION) AT ECONOMIC-GEOLOGICAL EVALUATION OF COAL DEPOSITS." Мінеральні ресурси України, no. 4 (December 28, 2018): 45–48. http://dx.doi.org/10.31996/mru.2018.4.45-48.

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The purpose of research is systematization and analysis of methods of price determining for geological and economic assessment of coal deposits in domestic and international practice. Price indicators and income from sale of coal affect significantly reserves value, profitability of their development, and determine industrial significance of reserves. In domestic practice commodity exchanges, contractual, regulated, world and transfer prices are used. In international practice coal prices are formed at the result of futures, spot or stock exchange contracts. Now international coal trade realiz

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3

Riansut, Warangkhana. "Forecasting of Wollongong Prices via the Use of Statistical Methods." Journal of Applied Science 20, no. 2 (September 6, 2021): 65–79. http://dx.doi.org/10.14416/j.appsci.2021.02.007.

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4

Lin, Lisha, Yaqiong Li, Rui Gao, and Jianhong Wu. "The numerical simulation of Quanto option prices using Bayesian statistical methods." Physica A: Statistical Mechanics and its Applications 567 (April 2021): 125629. http://dx.doi.org/10.1016/j.physa.2020.125629.

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5

Gaca, Radosław. "Parametric and Non-Parametric Statistical Methods in the Assessment of the Effect of Property Attributes on Prices." Real Estate Management and Valuation 26, no. 2 (June 1, 2018): 83–91. http://dx.doi.org/10.2478/remav-2018-0018.

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Abstract One of the basic problems in the comparison-based property valuation process is to determine the influence of property attributes on their price differential. Due to the qualitative character of the majority of property attributes as well as to the distributions of both prices and attributes, their effect on the price differential is increasingly often assessed by means of non-parametric statistical methods. As a tool for determining the effect of attributes on prices, many authors propose parametric methods, in particular multiple regression models. The study presents a comparison of

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6

Webster, Michael, and Rory C. Tarnow-Mordi. "Decomposing Multilateral Price Indexes into the Contributions of Individual Commodities." Journal of Official Statistics 35, no. 2 (June 1, 2019): 461–86. http://dx.doi.org/10.2478/jos-2019-0020.

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Abstract This article describes methods for decomposing price indexes into contributions from individual commodities, to help understand the influence of each commodity on aggregate price index movements. Previous authors have addressed the decomposition of bilateral price indexes, which aggregate changes in commodity prices from one time period to another. Our focus is the decomposition of multilateral price indexes, which aggregate commodity prices across more than two time periods or countries at once. Multilateral indexes have historically been used for spatial comparisons, and have recent

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7

Akbulaev, Nurkhodzha, Basti Aliyeva, and Shehla Rzayeva. "Analysis of the Influence of the Price of Raw Oil and Natural Gas on the Prices of Indices and Shares of the Turkish Stock Exchange." Pénzügyi Szemle = Public Finance Quarterly 66, no. 1 (2021): 151–66. http://dx.doi.org/10.35551/pfq_2021_1_8.

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This article is a review on the impact of prices and their dependence on the cost of oil and natural gas on the world stock markets. The main studies and results achieved in the field of the impact of prices on both the stock index and industrial stocks and the dependence on the level of oil prices are presented. The paper presents an econometric study on the choice of offers on the securities market that allows us to identify the main specifics of changes in prices for the stock index and industrial shares in the daily period from 13. 05. 2012 to 01. 12. 2019. The article uses methods for est

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8

Afanasyev, V. N. "Statistical Methods in the Study of Changes in the Structure and Elements of the Cost of Electricity Generation." Vestnik NSUEM, no. 4 (December 29, 2019): 286–303. http://dx.doi.org/10.34020/2073-6495-2019-4-286-303.

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The growth of tariffs and prices in the Russian Federation is largely determined by the growth of electricity prices. Need to know why electricity is becoming more expensive. The article presents the analysis of the system of statistical methods used in the study of changes in the structure and elements of the cost of electricity production. Statistical tools are being discussed to identify and measure the factors behind the rise in electricity prices, and to conduct a detailed causal analysis. Special emphasis is placed on statistical technologies used in the study of changes in individual el

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9

Chuluunsaikhan, Tserenpurev, Ga-Ae Ryu, Kwan-Hee Yoo, HyungChul Rah, and Aziz Nasridinov. "Incorporating Deep Learning and News Topic Modeling for Forecasting Pork Prices: The Case of South Korea." Agriculture 10, no. 11 (October 30, 2020): 513. http://dx.doi.org/10.3390/agriculture10110513.

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Knowing the prices of agricultural commodities in advance can provide governments, farmers, and consumers with various advantages, including a clearer understanding of the market, planning business strategies, and adjusting personal finances. Thus, there have been many efforts to predict the future prices of agricultural commodities in the past. For example, researchers have attempted to predict prices by extracting price quotes, using sentiment analysis algorithms, through statistical information from news stories, and by other means. In this paper, we propose a methodology that predicts the

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10

Marushkevych, Dmytro, and Yevheniia Munchak. "Estimation of Parameters and Verification of Statistical Hypotheses for Gaussian Models of Stock Price." Lietuvos statistikos darbai 55, no. 1 (December 20, 2016): 91–101. http://dx.doi.org/10.15388/ljs.2016.13871.

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We construct models of asset prices on the Ukrainian stock market and analyse their applicability by checkingappropriate statistical hypotheses using actual observed data. We also analyse the presence of jumps in the dynamics ofdifferent assets and estimate the Hurst coefficient for the logarithm of the price of the asset by two different methods.

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11

Grigoreva, D. R., G. A. Gareeva, and A. Yu Ishimova. "COMPUTER TECHNOLOGIES IN STATISTICAL METHODS ON THE EXAMPLE OF POLYMER’S PRICES ANALYSIS." Scientific and Technical Volga region Bulletin 7, no. 1 (February 2017): 77–79. http://dx.doi.org/10.24153/2079-5920-2017-7-1-77-79.

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12

Kopytets, Nataliia. "Analysis of the price situation in the cattle meat market." Ekonomika APK 313, no. 11 (November 27, 2020): 52–59. http://dx.doi.org/10.32317/2221-1055.202011052.

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The purpose of the article is to investigate the current price situation in the cattle meat market, taking into account the peculiarities of the beef price chain “production – processing –trade – consumer”. Research methods. The following methods have been used in the research process: abstract and logical, system analysis – for generalize theoretical positions, formulating conclusions; comparative analysis – for compare indicators and identify trends in their change over time; statistical – for assessing the cattle meat market; tabular – for visual representation of the research results; mono

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13

C. Larson, Alexander, Rita L. Reicher, and David William Johnsen. "Threshold effects in pricing of high-involvement services." Journal of Product & Brand Management 23, no. 2 (April 14, 2014): 121–30. http://dx.doi.org/10.1108/jpbm-04-2013-0278.

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Purpose – The purpose of this research is to test for price threshold effects in the demand for high-involvement services for small businesses. Design/methodology/approach – The authors use a stated preference choice-based conjoint study of small business telecommunications demand. Using survey data, individual-level parameter estimates for a demand model are achieved via the Hierarchical Bayes method of estimation. Findings – For demand for small business telecommunications services, the authors find very strong positive impacts of nine-ending and zero-ending prices on the demand for a common

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14

Kokot, Sebastian, and Marcin Bas. "Evaluation of the Applicability of Statistical Methods in Studies on Price Dynamics on the Real Estate Market." Real Estate Management and Valuation 21, no. 1 (May 1, 2013): 49–58. http://dx.doi.org/10.2478/remav-2013-0007.

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Abstract The specific character of the real estate market is the reason why observations of transaction prices seen as statistical variables are taken in a non-standard way. In the traditional approach each time period or specific moments of time are attributed with one observation of a studied variable per one object. In the case of the real estate market, this is not possible since transactions relate to different objects, i.e., properties, and occur at irregular, or even random, moments. This is why traditional methods used to examine the dynamics of economic phenomena must be adapted to sp

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15

Suradi, Jessica Prania, and Selly Eriska Marisa. "ANALISIS DAMPAK HARGA MINYAK MENTAH DUNIA, TINGKAT SUKU BUNGA DAN KURS VALUTA ASING TERHADAP INDEKS HARGA SAHAM PERTAMBANGAN PERIODE 2014 – 2016." Jurnal Bina Manajemen 8, no. 2 (March 31, 2020): 1–17. http://dx.doi.org/10.52859/jbm.v8i2.84.

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This study aims to look at the effect of world crude oil prices, interest rates, and foreign exchange rates on the mining sector stock price index for the 2014-2016 period. The research method used is descriptive statistical methods with quantitative research types. This study also uses analytical methods such as multiple regression analysis through t test and F test. Based on the F test (simultaneous) shows that world oil prices, interest rates, and foreign exchange rates affect simultaneously on the mining sector stock price index for the period 2014-2016 , while the t test (partial) shows t

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16

Bródka, Dawid, and Marcin Chciałowski. "PRICE VOLATILITY IN MACROECONOMIC STRUCTURE OF PRODUCTION IN POLAND." Acta Scientiarum Polonorum. Oeconomia 16, no. 3 (September 30, 2017): 5–14. http://dx.doi.org/10.22630/aspe.2017.16.3.28.

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In this article an empirical analysis of price volatility was conducted, on the basis of Polish macroeconomic data from 2010–2016 and theoretical framework proposed by Austrian School of Economics. The research was carried out using a number of statistical methods used on price indices representing different stages of production. The analysis allowed to establish conclusions about differing degree of price movements throughout Polish economy and its sectors, where prices of goods produced at the beginning of the structure were characterised by higher volatility than those produced in other bra

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17

Öhman, Peter, and Darush Yazdanfar. "The nexus between stock market index and apartment and villa prices." International Journal of Housing Markets and Analysis 10, no. 3 (June 5, 2017): 450–67. http://dx.doi.org/10.1108/ijhma-09-2016-0069.

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Purpose The purpose of this study is to investigate the Granger causal link between the stock market index and housing prices in terms of apartment and villa prices. Design/methodology/approach Monthly data from September 2005 to October 2013 on apartment prices, villa prices, the stock market index, mortgage rates and the consumer price index were used. Statistical methods were applied to explore the long-run co-integration and Granger causal link between the stock market index and apartment and villa prices in Sweden. Findings The results indicate that the stock market index and housing pric

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18

Navickaitė, Roberta. "Application of Statistical Methods to the Assessment of Prices of Klaipeda City Apartments." Lietuvos statistikos darbai 53, no. 1 (December 20, 2014): 64–77. http://dx.doi.org/10.15388/ljs.2014.13896.

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The paper analyses the use of a nonlinear regression model, generalised linear model and generalised additive model(semi-parametric regression model) for creating real estate valuation models. These models are applied to data on transactions inKlaipeda city apartments. The aim is to create real estate valuation regression models applying various statistical methods and tocompare them with each other. The practical aspects of creating regression models are analysed and conclusions are presented in thepaper.

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19

Gupta, Shashi, Himanshu Choudhary, and D. R. Agarwal. "An Empirical Analysis of Market Efficiency and Price Discovery in Indian Commodity Market." Global Business Review 19, no. 3 (February 15, 2018): 771–89. http://dx.doi.org/10.1177/0972150917713882.

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The present article is an attempt to empirically investigate the long-term market efficiency and price discovery in Indian commodity futures market. The study has been conducted with eight commodities which include two agricultural commodities, two industrial commodities, two precious metal and two energy commodities. Sophisticated statistical methods like restricted cointegration and vector error correction model (VECM) are used to analyse the spot and futures prices time series. Restricted cointegration test shows that near-month futures prices for all the commodities are cointegrated with t

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MÜNNIX, MICHAEL C., RUDI SCHÄFER, and THOMAS GUHR. "STATISTICAL CAUSES FOR THE EPPS EFFECT IN MICROSTRUCTURE NOISE." International Journal of Theoretical and Applied Finance 14, no. 08 (December 2011): 1231–46. http://dx.doi.org/10.1142/s0219024911006838.

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We present two statistical causes for the distortion of correlations on high-frequency financial data. We demonstrate that the asynchrony of trades as well as the decimalization of stock prices has a large impact on the decline of the correlation coefficients towards smaller return intervals (Epps effect). These distortions depend on the properties of the time series and are of purely statistical origin. We are able to present parameter-free compensation methods, which we validate in a model setup. Furthermore, the compensation methods are applied to high-frequency empirical data from the NYSE

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21

Mohapatra, Avilasa, Smruti Rekha Das, Kaberi Das, and Debahuti Mishra. "Applications of neural network based methods on stock market prediction: survey." International Journal of Engineering & Technology 7, no. 2.6 (March 11, 2018): 71. http://dx.doi.org/10.14419/ijet.v7i2.6.10070.

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Financial forecasting is one of the domineering fields of research, where investor’s money is at stake due to the rise or fall of the stock prices which unpredictable and fluctuating. Basically as the demand for stock markets has been rising at an unprecedented rate so its prediction becomes all the more exciting and challenging. Prediction of the forthcoming stock prices mostly Artificial Neural Network (ANN) based models are taken into account. The other models such as Bio-inspired Computing, Fuzzy network model etc., considering statistical measures, technical indicators and fundamental ind

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22

Barańska, Anna, and Beata Śpiewak. "The Influence of Chosen Statistical Methods of Detecting Outliers on Property Valuation Result." Real Estate Management and Valuation 29, no. 1 (March 1, 2021): 87–97. http://dx.doi.org/10.2478/remav-2021-0008.

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Abstract The subject of the thesis concerns the application of selected statistical methods searching for outliers in the process of determining the value of real estate, based on a functional model adjusted to market data. The collected research material consisted of data on land properties, which were the subject of transactions on local markets, for which there was no information regarding the specific conditions of concluding the sale agreement. After the initial selection of data regarding the purpose of the property in the local plan, the type of property rights being sold and the size o

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Cellmer, Radosław. "The Possibilities and Limitations of Geostatistical Methods in Real Estate Market Analyses." Real Estate Management and Valuation 22, no. 3 (October 1, 2014): 54–62. http://dx.doi.org/10.2478/remav-2014-0027.

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Abstract In the traditional approach, geostatistical modeling involves analyses of the spatial structure of regionalized data, as well as estimations and simulations that rely on kriging methods. Geostatistical methods can complement traditional statistical models of property transaction prices, and when combined with those models, they offer a comprehensive tool for spatial analysis that is used in the process of developing land value maps. Transaction prices are characterized by mutual spatial correlations and can be considered as regionalized variables. They can also be regarded as random v

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Astuti, Astuti, Elly Susanti, and Hery Pandapotan Silitonga. "ANALISIS DAMPAK RASIO KEUANGAN PERUSAHAAN TERHADAP HARGA SAHAM PADA PERUSAHAAN YANG TERCATAT PADA JII." Jesya (Jurnal Ekonomi & Ekonomi Syariah) 3, no. 2 (May 31, 2020): 108–217. http://dx.doi.org/10.36778/jesya.v3i2.202.

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The research method uses qualitative data, secondary data sources, using documentation methods, classic data assumption test analysis techniques, coefficient of determination, hypothesis testing. The object of research in companies incorporated in the Jakarta Islamic Index in the period 2014 - 2018. The results of this study by F statistical tests show that all independent variables influence the dependent variable. In statistical test t current ratio has a negative and significant effect on stock prices. Size and Debt to Asset Ratio influence and are not significant on stock prices. Return on

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Gupta, Saloni. "Statistical Arbitrage: Profits through Pairs Trading." Journal of Business Management and Information Systems 2, no. 1 (June 30, 2015): 140–48. http://dx.doi.org/10.48001/jbmis.2015.0201013.

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Statistical arbitrage is a popular device among hedge fund managers and assets management professionals. It refers to simultaneous buying and selling two different capital assets to earn super-normal profit. By identifying persistent anomalies that violate the efficient market hypothesis, statistical methods can be used to create a trading strategy to generate profit with high probability. A pair trading is one such trading strategy which is based on statistical arbitrage process. Pairs trading can be simple in concept, but can be one of the most complex types of trading in practice. The start

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Viviani, Emma, Luca Di Persio, and Matthias Ehrhardt. "Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case." Energies 14, no. 2 (January 11, 2021): 364. http://dx.doi.org/10.3390/en14020364.

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In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods for point forecast, comparing their performance in terms of efficiency, accuracy, and reliability, and we then exploit Neural Networks approaches to derive a hybrid model for probabilistic type forecasting. We show that our solution reaches the highest standard both in terms of efficiency and precision by testing its output on German electricity prices data.

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Viviani, Emma, Luca Di Persio, and Matthias Ehrhardt. "Energy Markets Forecasting. From Inferential Statistics to Machine Learning: The German Case." Energies 14, no. 2 (January 11, 2021): 364. http://dx.doi.org/10.3390/en14020364.

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In this work, we investigate a probabilistic method for electricity price forecasting, which overcomes traditional ones. We start considering statistical methods for point forecast, comparing their performance in terms of efficiency, accuracy, and reliability, and we then exploit Neural Networks approaches to derive a hybrid model for probabilistic type forecasting. We show that our solution reaches the highest standard both in terms of efficiency and precision by testing its output on German electricity prices data.

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Jasińska, Elżbieta, and Edward Preweda. "Statistical Modelling of the Market Value of Dwellings, on the Example of the City of Kraków." Sustainability 13, no. 16 (August 20, 2021): 9339. http://dx.doi.org/10.3390/su13169339.

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The analysis of a city’s spatial development, in terms of a location that meets the needs of its inhabitants, requires many approaches. The preliminary assessment of the collected material showed that there was real estate in the database whose price did not have market characteristics. For the correct formulation of the valuation model, it is necessary to detect and eliminate or reduce the impact of these properties on the valuation results. In this study, multivariate analysis was used and three methods of detecting outliers were verified. The database of 8812 residential premises traded on

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Ehrlich, Gabriel, John Haltiwanger, Ron Jarmin, David Johnson, and Matthew D. Shapiro. "Minding Your Ps and Qs: Going from Micro to Macro in Measuring Prices and Quantities." AEA Papers and Proceedings 109 (May 1, 2019): 438–43. http://dx.doi.org/10.1257/pandp.20191004.

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Key macro indicators such as output, productivity, and inflation are based on a complex system across multiple statistical agencies using different samples and levels of aggregation. The Census Bureau collects nominal sales, the Bureau of Labor Statistics collects prices, and the Bureau of Economic Analysis constructs nominal and real GDP using these data and other sources. The price and quantity data are integrated at a high level of aggregation. This paper explores alternative methods for reengineering key national output and price indices using item-level data. Such reengineering offers the

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Zawojska, Aldona, and Beata Horbowiec. "Ryzyko cenowe na rynku produktów rolno-żywnościowych: źródła, skutki i sposoby zarządzania." Zeszyty Naukowe SGGW - Ekonomika i Organizacja Gospodarki Żywnościowej, no. 115 (September 30, 2016): 37–57. http://dx.doi.org/10.22630/eiogz.2016.115.31.

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This paper aims to identify the causes and consequences of price risk in agri-food market as well as its mitigation methods. The research uses the scientific literature review approach and statistical analysis, applying the coefficients of variation of price indices for the global agricultural production and for the procurement of particular agricultural products in Poland over the period from 1995 to 2013. The price data is derived from the Central Statistical Office of Poland (GUS). Our study confirms the findings of other investigators that crop production is characterised by larger price f

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Faliński, Przemysław. "INVESTMENT RISK MANAGEMENT BASED ON QUOTATIONS OF OIL COMPANIES, OIL AND DOLLAR." Zeszyty Naukowe Uniwersytetu Przyrodniczo-Humanistycznego w Siedlcach. Seria: Administracja i Zarządzanie, no. 53(126) (January 27, 2021): 37–45. http://dx.doi.org/10.34739/zn.2020.53.04.

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With the non-random movement of the prices of exchange trading objects in mind, by means of the methods and tools of chaos theory, it is possible to show that price changes are subject to the laws of deterministic chaos. This is a new look at this subject compared to the statistical methods that have been used for years, which in most cases assume that the distribution of the rate of returns of the examined series is normal. The aim of the study is to determine the nature of the changes in oil, dollar and Polish fuel prices: whether they are random or determined. In addition, the second aim is

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Zyga, Jacek. "Connection Between Similarity and Estimation Results of Property Values Obtained by Statistical Methods." Real Estate Management and Valuation 24, no. 3 (September 1, 2016): 5–15. http://dx.doi.org/10.1515/remav-2016-0017.

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Abstract The article discusses the topic of the application range of statistical methods in estimating property value on the grounds of a comparative approach. The analysis of application effects to estimate the unitary value of properties, respectively similar and dissimilar sets of market properties, by using the method of least squares and a linear price model. The prepared test set was developed from a priori assumed explanatory variable values as well as deterministically specified dependent variables (simulated prices) which were subjected to additional modification by a random factor. O

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Nataraj, S., C. Alvarez, L. Sada, A. A. Juan, J. Panadero, and C. Bayliss. "Applying Statistical Learning Methods for Forecasting Prices and Enhancing the Probability of Success in Logistics Tenders." Transportation Research Procedia 47 (2020): 529–36. http://dx.doi.org/10.1016/j.trpro.2020.03.128.

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Gani, Walid. "Can statistical methods help prove excessiveness of dominant firm's prices Evidence from the Tunisian Competition Council." International Journal of Economics and Business Research 20, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijebr.2020.10030419.

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Henri Drouhin, Pierre-Arnaud, and Arnaud Simon. "Are property derivatives a leading indicator of the real estate market?" Journal of European Real Estate Research 7, no. 2 (July 29, 2014): 158–80. http://dx.doi.org/10.1108/jerer-08-2013-0014.

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Purpose – This paper aims to analyze the statistical characteristics of changes in property forward prices. As highlighted in a survey conducted at the MIT Center for Real Estate in 2006, the relatively weak understanding in their prices is one of the most important barriers in their use. In this context, the analysis of the forward price term structure is essential. Do the short- and long-term forward prices behave similarly? Do property derivatives behave like other derivative assets or other related assets? This study also investigates the lead–lag relationship between spot and forward retu

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Vochozka, Marek, Jakub Horak, and Tomas Krulicky. "Innovations in Management Forecast: Time Development of Stock Prices with Neural Networks." Marketing and Management of Innovations, no. 2 (2020): 324–39. http://dx.doi.org/10.21272/mmi.2020.2-24.

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Accurate prediction of stock market values is a challenging task for over decades. Prediction of stock prices is associated with numerous benefits including but not limited to helping investors make wise decisions to accumulate profits. The development of the share price is a dynamic and nonlinear process affected by several factors. What is interesting is the unpredictability of share prices due to the global financial crisis. However, classical methods are no longer sufficient for the application of share price development prediction.However, over-relying on prediction data can lead to losse

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Lutz, Jack, Theodore E. Howard, and Paul E. Sendak. "Stumpage Price Reporting in the Northern United States." Northern Journal of Applied Forestry 9, no. 2 (June 1, 1992): 69–73. http://dx.doi.org/10.1093/njaf/9.2.69.

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Abstract Data collection, processing, and dissemination methods of stumpage price reports in the northern United States vary considerably among the states due to differing objectives, markets, traditions, and budget constraints. Data are collected primarily from limited segments of the market with little quality control exerted by the compiling agencies. Prices are reported in terms of species, timber quality, and major product, and range from detailed lists to gross aggregates. Important areas for improving the price reports include more rapid dissemination, broader sampling of transactions,

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Kobylińska, Katarzyna, and Radosław Cellmer. "The Use of Indicator Kriging for Analyzing Prices in the Real Estate Market." Real Estate Management and Valuation 24, no. 4 (December 1, 2016): 5–15. http://dx.doi.org/10.1515/remav-2016-0025.

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Abstract The patterns and relations between real estate prices and the factors which shape them can be presented, among others, in the form of traditional statistical models, as well as by means of geostatistical methods. In the case of research involving the diagnosis and prediction of transaction prices, the key role is played by the spatial aspect, hence the particular significance of geostatistical methods using spatial information. The main goal of the conducted research is to determine the probability of the occurrence of a price in a given location in space by means of geostatistical si

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LOFFREDO, MARIA I. "ON THE STATISTICAL PHYSICS CONTRIBUTION TO QUANTITATIVE FINANCE." International Journal of Modern Physics B 18, no. 04n05 (February 20, 2004): 705–13. http://dx.doi.org/10.1142/s021797920402432x.

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A short review is given of some research topics recently developed in the framework of quantitative finance and which can be referred to the effort of adapting methods and technologies of statistical physics to the analysis of economic systems. In particular we emphasize the role of a different, new perspective, in approaching financial problems, originated within the theory of complex systems and based on concepts like universality, scaling and correlation properties. Once applied to the time evolution of prices and volatility, this approach allows for the recognition of long-range and nonlin

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Caporale, Guglielmo Maria, and Alex Plastun. "Daily abnormal price changes and trading strategies in the FOREX." Journal of Economic Studies 48, no. 1 (September 9, 2020): 211–22. http://dx.doi.org/10.1108/jes-11-2019-0503.

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PurposeThis paper explores abnormal price changes in the FOREX by using both daily and intraday data on the EURUSD, USDJPY, USDCAD, AUDUSD and EURJPY exchange rates over the period 01.01.2008–31.12.2018.Design/methodology/approachIt applies a dynamic trigger approach to detect abnormal price changes and then various statistical methods, including cumulative abnormal returns analysis, to test the following hypotheses: the intraday behaviour of hourly returns on overreaction days is different from that on normal days (H1), there are detectable patterns in intraday price dynamics on days with abn

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Bradic-Martinovic, Aleksandra. "Stock market prediction using technical analysis." Ekonomski anali 51, no. 170 (2006): 125–46. http://dx.doi.org/10.2298/eka0670125b.

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Technical analysis (TA) is a form of analyzing market encompassing supply and demand of securities according to the study of their prices and trading volume. Using the appropriate methods, TA aims to identify price movements in the stock market, futures or currencies. In short, TA analysis is the process by which "future price movements are formulated according to the price history". TA originates from the work of Charles Dow and his conclusions about the global behavior of the market, as well as from Elliot Wave Theory. Dow did not regard its theory as a tool for stock market movement predict

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Bildirici, Melike, Nilgun Guler Bayazit, and Yasemen Ucan. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM." Energies 13, no. 11 (June 10, 2020): 2980. http://dx.doi.org/10.3390/en13112980.

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Under the influence of the COVID-19 pandemic and the concurrent oil conflict between Russia and Saudi Arabia, oil prices have exhibited unusual and sudden changes. For this reason, the volatilities of the West Texas Intermediate (WTI), Brent and Dubai crude daily oil price data between 29 May 2006 and 31 March 2020 are analysed. Firstly, the presence of chaotic and nonlinear behaviour in the oil prices during the pandemic and the concurrent conflict is investigated by using the Shanon Entropy and Lyapunov exponent tests. The tests show that the oil prices exhibit chaotic behavior. Additionally

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Annisa, Mutiara Lusiana, and Rizki Fitri Amalia. "PENGARUH STRUKTUR MODAL DAN PROFITABILITAS TERHADAP HARGA SAHAM (Studi Kasus Pada Perusahaan Asuransi yang Terdaftar Di Bursa Efek Indonesia Periode 2015 sampai dengan 2017)." BALANCE Jurnal Akuntansi dan Bisnis 3, no. 2 (November 1, 2018): 308. http://dx.doi.org/10.32502/jab.v3i2.1252.

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This research purpose to know and explaining the effect of capital structure and profitability stock prices case of studies at the insurance companies that listed on the Indonesia Stock Exchange from period time of 2015 untul 2017. The type of research used is explanatory causality research with quantitative approach. Based on sampling technique “purposive sampling” researcher used 11 companies that meets the criteria. The method of analysis used in this research is statistical descriptive analysis multiple linear analysis. The result of the methods show that the capital structure and profitab

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Parengkuan, Frangky Christoffel. "Analisis Sentimen Perubahan Harga Emas Dunia, Nilai Tukar Rupiah dan Indeks Harga Saham Gabungan terhadap Keputusan Membeli Produk Reksadana Saham." Jurnal Ilmiah Magister Managemen 4, no. 2 (December 1, 2018): 1–17. http://dx.doi.org/10.34010/jimm.v4i2.3768.

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The objective of this study are (1) to describe the exchange of world gold price, USD/IDR exchage rate, the movement in Indonesian Stocks Exchange Indexs (IHSG) and investor’s sentiment to buy Equity Fund (2) to verify the corelation against the world gold price, USD/IDR exchange rate and movement of Indonesian Stocks Exchange Indexs (3) to calculate how they will make effect to decision of buying Equity Fund. The Equity Funds come from all funds that sold by Bank Danamon Region 8 Jawa Barat with minimum existing for more than 10 years performance. Analytical tools that used in this study is p

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Ani, Dorothy Patience, Emmanuel Adah Onoja, and Isaac Terna Humbe. "Partial Fuel Subsidy Removal in Nigeria." International Journal of Social Ecology and Sustainable Development 12, no. 1 (January 2021): 98–114. http://dx.doi.org/10.4018/ijsesd.2021010108.

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The ripple effects of the petrol crisis on the Nigerian economy is multi-faceted: price distortions, volatilities, dutch-disease, corruption, and inefficiencies. This study assessed the effects of partial fuel subsidy removal on agricultural sector and Nigerian economy. The study made use of secondary data obtained from Central Bank of Nigeria Statistical Bulletins, Petroleum Product Price Regulatory Agency (PPPRA), National Bureau of Statistics, Benue State Agricultural and Rural Development Authority (BNARDA), and FAO. Johansen co-integration model and t-test were the analytical tools used.

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Žmuk, Berislav. "Capabilities of Statistical Residual-Based Control Charts in Short- and Long-Term Stock Trading." Naše gospodarstvo/Our economy 62, no. 1 (March 1, 2016): 12–26. http://dx.doi.org/10.1515/ngoe-2016-0002.

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Abstract The aim of this paper is to introduce and develop additional statistical tools to support the decision-making process in stock trading. The prices of CROBEX10 index stocks on the Zagreb Stock Exchange were used in the paper. The conducted trading simulations, based on the residual-based control charts, led to an investor’s profit in 67.92% cases. In the short run, the residual-based cumulative sum (CUSUM) control chart led to the highest portfolio profits. In the long run, when average stock prices were used and 2-sigma control limits set, the residual-based exponential weighted movin

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Palát, M., Š. Dvořáková, and N. Kupková. " Consumption of beef in the Czech Republic." Agricultural Economics (Zemědělská ekonomika) 58, No. 7 (July 23, 2012): 308–14. http://dx.doi.org/10.17221/72/2011-agricecon.

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The paper is aimed at the demand for beef. Its objective is to evaluate the development of beef consumption in the market of the Czech Republic, and particularly to identify the factors affecting the level of demand for beef. It refers to the analysis of the development of beef consumption in the Czech Republic depending on its price and costs of the selected kinds of its near substitutes, when their relationships are evaluated through their relationships are evaluated methods of regression and correlation analysis. The paper proves statistically the existence of relations among these crucial

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Mansfield, Sarah J. "Generic drug prices and policy in Australia: room for improvement? A comparative analysis with England." Australian Health Review 38, no. 1 (2014): 6. http://dx.doi.org/10.1071/ah12009.

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Objective To assess the degree to which reimbursement prices in Australia and England differ for a range of generic drugs, and to analyse the supply- and demand-side factors that may contribute to these differences. Methods Australian and English reimbursement prices were compared for a range of generic drugs using pricing information obtained from government websites. Next, a literature review was conducted to identify supply- and demand-side factors that could affect generic prices in Australia and England. Various search topics were identified addressing potential supply-side (e.g. market a

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Horváth, József, and Sándor Kovács. "The Examination of the Effects of Value Modifying Factors on Dairy Farms." Acta Agraria Debreceniensis, no. 24 (October 11, 2006): 36–40. http://dx.doi.org/10.34101/actaagrar/24/3222.

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We wish to present a method to quantify the value modifying effects when comparing animal farms. To achieve our objective, multi-variable statistical methods were needed. We used a principal component analysis to originate three separate principal components from nine variables that determine the value of farms. A cluster analysis was carried out in order to classify farms as poor, average and excellent. The question may arise as to which principal components and which variables determine this classification.After pointing out the significance of variables and principal components in determini

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McCord, Michael James, John McCord, Peadar Thomas Davis, Martin Haran, and Paul Bidanset. "House price estimation using an eigenvector spatial filtering approach." International Journal of Housing Markets and Analysis 13, no. 5 (November 14, 2019): 845–67. http://dx.doi.org/10.1108/ijhma-09-2019-0097.

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Purpose Numerous geo-statistical methods have been developed to analyse the spatial dimension and composition of house prices. Despite these advances, spatial filtering remains an under-researched approach within house price studies. This paper aims to examine the spatial distribution of house prices using an eigenvector spatial filtering (ESF) procedure, to analyse the local variation and spatial heterogeneity. Design/methodology/approach Using 2,664 sale transactions over the one year period Q3 2017 to Q3 2018, an eigenvector spatial filtering approach is applied to evaluate spatial patterns

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