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Journal articles on the topic 'Price indexes'

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Published: 4 June 2021

Last updated: 30 July 2024

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1

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 recently received attention from statistical agencies looking to produce temporal price indexes from large and high frequency price data sets, such as scanner data. Methods for decomposing these indexes are of practical relevance. We present decompositions of three multilateral price indexes. We also review methods proposed by other researchers for extending multilateral indexes without revising previously published index levels, and show how to decompose the extended indexes they produce. Finally, we use a data set of seasonal prices and quantities to illustrate how these decomposition methods can be used to understand the influence of individual commodities on multilateral price index movements, and to shed light on the relationships between various multilateral and extension methods.

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2

Fava, Vera Lucia. "Price dispersion and price indexes." Applied Economics 42, no. 1 (January 2010): 23–36. http://dx.doi.org/10.1080/00036840701579168.

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3

Bossert, Walter, and Frank Stehling. "Optimal Price Indexes." Jahrbücher für Nationalökonomie und Statistik 241, no. 4 (August 1, 2021): 477–99. http://dx.doi.org/10.1515/jbnst-2020-0055.

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Abstract We examine the notion of a price index as the solution to the problem of minimizing the distance between the index values and the vector of price ratios. To do so, the choice of a suitable distance function is of crucial importance. We use a generalized least-squares criterion for this purpose and show that the generalized quasilinear functions are the only solutions to the problem of minimizing the distance thus defined. There are numerous special cases that are obtained for specific choices of the requisite functions and weights. In particular, we show that, in addition to the well-established indexes of Laspeyres, Paasche, Marshall-Edgeworth, Walsh, and Törnqvist, the arithmetic-current-period index, the arithmetic-hybrid index, the harmonic-base-period index, and the harmonic-hybrid index can be obtained with suitably chosen distance functions. Furthermore, the logarithmic least-squares criterion is employed to obtain indexes that are based on geometric means.

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4

Hill, Robert J. "Constructing Price Indexes across Space and Time: The Case of the European Union." American Economic Review 94, no. 5 (November 1, 2004): 1379–410. http://dx.doi.org/10.1257/0002828043052178.

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This paper considers the problem of how to construct and reconcile price indexes across space and time. A general taxonomy of panel price index methods, containing four broad classes, is proposed, along with five criteria for discriminating between them. Methods from each of the four classes are then used to compute spatial and temporal price indexes for the 15 countries of the European Union (EU) over the period 1995–2000. Using these panel price indexes, I test whether or not price levels and relative prices converged across the EU over this period.

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5

Feenstra, Robert C. "Exact Hedonic Price Indexes." Review of Economics and Statistics 77, no. 4 (November 1995): 634. http://dx.doi.org/10.2307/2109812.

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6

Bourassa, Steven C., Eva Cantoni, and Martin Hoesli. "Robust hedonic price indexes." International Journal of Housing Markets and Analysis 9, no. 1 (March 7, 2016): 47–65. http://dx.doi.org/10.1108/ijhma-11-2014-0050.

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Purpose – The purpose of this paper is to demonstrate the application of robust techniques to the estimation of hedonic house price indexes. Design/methodology/approach – The authors use simulation analysis to compare an index estimated using ordinary least squares (OLS) with several indexes estimated using robust techniques. The analysis uses sales transactions data from a US city. The authors then explore how robust methods can correct for omitted variables under some circumstances and how they affect the revision problem that occurs when longitudinal hedonic indexes are updated. Findings – Robust methods can resolve missing variable problems in some circumstances and also can substantially reduce the revision problem in longitudinal hedonic indexes. Practical implications – Robust techniques may be preferable to OLS when constructing longitudinal hedonic indexes. Originality/value – This is the first paper to undertake a systematic analysis of the applicability of robust techniques in constructing hedonic house price indexes.

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7

Faryna, Oleksandr, Oleksandr Talavera, and Tetiana Yukhymenko. "What Drives the Difference between Online and Official Price Indexes?" Visnyk of the National Bank of Ukraine, no. 243 (March 29, 2018): 21–30. http://dx.doi.org/10.26531/vnbu2018.243.021.

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This paper examines the associations between online price indexes and official statistics. First, we generate online CPI component sub-indexes, which are later aggregated to an Online Price CPI. This approach is applied to our unique dataset which contains about 3 million observations of online retail prices for consumer goods in Ukraine’s five largest cities. The data span over the period 2016m1 – 2017m12 and cover about 46% of Ukraine’s Consumer Price Inflation basket. We find that online inflation is generally consistent with official estimates, but the matching capability varies across sub-indexes. Although the differences can partially be explained by poor dataset coverage, we find that online prices may indeed represent new information that is not captured by official statistics.

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8

Juszczak, Adam. "The use of web-scraped data to analyze the dynamics of footwear prices." Journal of Economics and Management 43 (2021): 251–69. http://dx.doi.org/10.22367/jem.2021.43.12.

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Aim/purpose – Web-scraping is a technique used to automatically extract data from websites. After the rise-up of online shopping, it allows the acquisition of information about prices of goods sold by retailers such as supermarkets or internet shops. This study examines the possibility of using web-scrapped data from one clothing store. It aims at comparing known price index formulas being implemented to the web-scraping case and verifying their sensitivity on the choice of data filter type. Design/methodology/approach – The author uses the price data scrapped from one of the biggest online shops in Poland. The data were obtained as part of eCPI (electronic Consumer Price Index) project conducted by the National Bank of Poland. The author decided to select three types of products for this analysis – female ballerinas, male shoes, and male oxfords to compare their prices in over one-year time period. Six price indexes were used for calculation – The Jevons and Dutot indexes with their chain and GEKS (acronym from the names of creators – Gini–Éltető–Köves–Szulc) versions. Apart from the analysis conducted on a full data set, the author introduced filters to remove outliers. Findings – Clothing and footwear are considered one of the most difficult groups of goods to measure price change indexes due to high product churn, which undermines the possibility to use the traditional Jevons and Dutot indexes. However, it is possible to use chained indexes and GEKS indexes instead. Still, these indexes are fairly sensitive to large price changes. As observed in case of both product groups, the results provided by the GEKS and chained versions of indexes were different, which could lead to conclu- sion that even though they are lending promising results, they could be better suited for other COICOP (Classification of Individual Consumption by Purpose) groups. Research implications/limitations – The findings of the paper showed that usage of filters did not significantly reduce the difference between price indexes based on GEKS and chain formulas. Originality/value/contribution – The usage of web-scrapped data is a fairly new topic in the literature. Research on the possibility of using different price indexes provides useful insights for future usage of these data by statistics offices. Keywords: inflation, CPI, web-scraping, online shopping, big data. JEL Classification: C43, C49.

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9

Hsieh, Heng-Hsing, Kathleen Hodnett, and Paul Van Rensburg. "Fundamental Indexation For Global Equities: Does Firm Size Matter?" Journal of Applied Business Research (JABR) 28, no. 1 (July 17, 2012): 105. http://dx.doi.org/10.19030/jabr.v28i1.7154.

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Market capitalization is often used as the weighting methodology for broad market indexes to reflect the performances of large established firms in the market. The market capitalization of a firm is a price-sensitive measure of firm size that self-adjusts to reflect the firms intrinsic value in an efficient capital market. In the presence of investor overreaction, the price-sensitive cap-weighted indexes cease to be mean-variance efficient in that they overweigh overvalued assets and under weigh undervalued assets. Fundamental indexation, proposed by Arnott, Hsu and Moore (2005), argue that fundamental values of a firm such as book value, revenues and earnings are price-insensitive, and hence are not subject to the systematic overshooting of asset prices through noise trading. The aim of this paper is to test whether fundamental-weighted indexes are more mean-variance efficient proxies for large established firms in the global equity market compared to cap-weighted indexes over an extensive 18-year period from 1991 to 2008. Test results show that fundamental-weighted indexes outperform cap-weighted indexes over two sub-periods as well as the overall examination period, during an expansionary market and in turbulent times. A strong negative relationship between the degree of index concentration and the index performance is detected for cap-weighted indexes while no such relationship is detected for the fundamental-weighted indexes. Our results suggest that price-insensitive fundamental-weighted indexes are more mean-variance efficient proxies for the performances of large firms for global equities relative to cap-weighted indexes. By removing the price-element in measuring firm size, the small firm anomaly is not present in fundamental-weighted indexes.

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10

Kokot, Sebastian. "COMPARATIVE ANALYSIS OF HEDONIC AND FILTERED INDEXES IN SELECTED CITIES." Real Estate Management and Valuation 25, no. 3 (September 26, 2017): 40–50. http://dx.doi.org/10.1515/remav-2017-0021.

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Abstract Property price indexes are difficult to determine both from the substantive and technical/organizational points of view. Various methods of constructing such indexes have been developed in order to overcome these difficulties. To this end, the author compares two types of indexes: hedonic indexes and ones termed filtered for the purpose of this particular paper. Hedonic index values come from Polish National Bank (NBP) publications, while the filtered indexes have been computed with the use of the 4253H filter on the basis of the NBP announcements on mean property prices. Thus, the results are comparable as both types of indexes are derived from the same input databases. The analysis covers both the comparison of the obtained results as well as a discussion of substantive and technical problems encountered when building the property price indexes.

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11

Dubey, Amaresh, and Palmer-Jones Richard. "Prices, Price Indexes and Poverty Counts in India during 1980s and 1990s: Calculation of Unit Value Consumer Price Indexes." Artha Vijnana: Journal of The Gokhale Institute of Politics and Economics 47, no. 3-4 (December 1, 2005): 223. http://dx.doi.org/10.21648/arthavij/2005/v47/i3-4/115623.

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12

Hill, George R., and Joseph M. Boonin. "Music Price Indexes: 1985 Update." Notes 42, no. 3 (March 1986): 518. http://dx.doi.org/10.2307/897329.

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13

Hill, George R., and Joseph M. Boonin. "Music Price Indexes: 1986 Update." Notes 43, no. 3 (March 1987): 544. http://dx.doi.org/10.2307/898198.

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14

Hill, R. Carter, J. R. Knight, and C. F. Sirmans. "Estimating Capital Asset Price Indexes." Review of Economics and Statistics 79, no. 2 (May 1997): 226–33. http://dx.doi.org/10.1162/003465397556818.

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15

Nowak, Adam D., and Patrick S. Smith. "Quality-Adjusted House Price Indexes." American Economic Review: Insights 2, no. 3 (September 1, 2020): 339–56. http://dx.doi.org/10.1257/aeri.20190337.

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The constant-quality assumption in repeat-sales house price indexes (HPIs) introduces a significant time-varying attribute bias. The direction, magnitude, and source of the bias varies throughout the market cycle and across metropolitan statistical areas (MSAs). We mitigate the bias using a data-driven textual analysis approach that identifies and includes salient text from real estate agent remarks in the repeat-sales estimation. Absent the text, MSA-level HPIs are biased downward by as much as 7 percent during the financial crisis and upward by as much as 20 percent after the crisis. The geographic concentration of the bias magnifies its effect on local HPIs. (JEL C43, E31, R11, R31)

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16

Clements, Kenneth W., H. Y. Izan, and Yihui Lan. "Volatility and stock price indexes." Applied Economics 45, no. 22 (August 2013): 3255–62. http://dx.doi.org/10.1080/00036846.2012.703315.

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17

Nordhaus, William D. "Quality Change in Price Indexes." Journal of Economic Perspectives 12, no. 1 (February 1, 1998): 59–68. http://dx.doi.org/10.1257/jep.12.1.59.

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Price indexes provide the fundamental building blocks for measuring the general price level along with real incomes and real output. But the most important single price index for the United States, the CPI, has been criticized as significantly underestimating the pace of quality change. This paper sketches the issues involved in the measurement of quality change in price indexes. It reviews the theory of quality change, discusses how the Bureau of Labor Statistics deals with quality change, and provides examples of measurement issues in practice. It concludes with a proposal to resolve the massive uncertainties in this area.

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18

Collins, Alan, Antonello Scorcu, and Roberto Zanola. "Reconsidering hedonic art price indexes." Economics Letters 104, no. 2 (August 2009): 57–60. http://dx.doi.org/10.1016/j.econlet.2009.03.025.

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19

Majewska, Agnieszka. "Using Sectoral Indexes to Discount the Exercise Price of Employee Stock Options." Folia Oeconomica Stetinensia 16, no. 1 (December 1, 2016): 174–85. http://dx.doi.org/10.1515/foli-2016-0010.

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Abstract Employee stock options (ESOs) are an instrument in compensating top management of corporations. In the literature, they are described as a variable component of remuneration of a long-term character (Borkowska, 2012). There are six characteristic elements of the ESO: a grant date, the ESO plan duration, employees entitled to receive options, vesting criteria, a vesting period, and an exercise price. The article refers to the exercise price. The remuneration of employees is determined by the option’s intrinsic value, i.e. the difference between the current stock price and the exercise price. This difference affects the costs incurred by a company in relation with their incentive stock option plan. In this connection, the exercise price of stock options needs to be analysed. The literature shows that usually the strike price is equal to the stock market’s value at the time the option is granted. The options issued with an exercise price equal to the market value of the company’s stock on the date of the grant usually lead to at-the-money options. Walker (2009) mentions that almost all options issued by US firms have been such type of options. Hence, the options with exercise prices less than the prices of the underlying assets have been rarely observed. One of the solutions can be discounting the exercise price by using sectoral indexes, which are sensitive to changes on a particular market. The purpose of this paper is to address several aspects of specifying the exercise price in ESOs. The research shows how sector indexes can be used to discount it. Using sectoral indexes in determining the exercise price can partly limit the unreasonably high profits from the ESO. The literature does not provide ready-made formulas of exercise prices based on specific variables. The aim of the research is to present and apply the formula of the exercise prices in which sectoral indices are used to discount. The data are from the Warsaw Stock Exchange (WSE) and include those companies that revealed the information concerning their incentive programs in 1999–2013. The relevant data come from annual reports, current reports, supervisory boards’ resolutions, and press announcements.

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20

Cavallo, Alberto, and Roberto Rigobon. "The Billion Prices Project: Using Online Prices for Measurement and Research." Journal of Economic Perspectives 30, no. 2 (May 1, 2016): 151–78. http://dx.doi.org/10.1257/jep.30.2.151.

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A large and growing share of retail prices all over the world are posted online on the websites of retailers. This is a massive and (until recently) untapped source of retail price information. Our objective with the Billion Prices Project, created at MIT in 2008, is to experiment with these new sources of information to improve the computation of traditional economic indicators, starting with the Consumer Price Index. We also seek to understand whether online prices have distinct dynamics, their advantages and disadvantages, and whether they can serve as reliable source of information for economic research. The word “billion” in Billion Prices Project was simply meant to express our desire to collect a massive amount of prices, though we in fact reached that number of observations in less than two years. By 2010, we were collecting 5 million prices every day from over 300 retailers in 50 countries. We describe the methodology used to compute online price indexes and show how they co-move with consumer price indexes in most countries. We also use our price data to study price stickiness, and to investigate the “law of one price” in international economics. Finally we describe how the Billion Prices Project data are publicly shared and discuss why data collection is an important endeavor that macro- and international economists should pursue more often.

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21

Ruzgar, Nursel Selver, and Clare Chua-Chow. "Behavior of Banks’ Stock Market Prices during Long-Term Crises." International Journal of Financial Studies 11, no. 1 (February 6, 2023): 31. http://dx.doi.org/10.3390/ijfs11010031.

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Countries are drastically impacted by financial and fiscal crises. Financial crises have the worst impact on not only society, but also the economy. The Canadian economy underwent financial crises and recessions several times during the last century. In this paper, daily closing stock prices of five large Canadian banks were studied during the last five crisis periods. It is aimed to determine the most effective or dominant index prices on the daily closing stock price of the banks during the crisis periods. The five periods were selected from secondary data from January 1975 to December 2020 by using the graphs and the crises in the literature. Multiple linear regression was performed to analyze the impact of price indexes during crisis periods. Findings show that “price index—financials” had a positive impact on the daily closing price of banks during the last five economic crises in Canada. Since the banks have different investment tools in their portfolio, the impacts of price indexes on the daily closing prices depend on these portfolios, which ultimately could have led to the economic crises.

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22

Fast, Don, Susan E. Fleck, and Dominic A. Smith. "Unit Value Indexes for Exports – New Developments Using Administrative Trade Data." Journal of Official Statistics 38, no. 1 (March 1, 2022): 83–106. http://dx.doi.org/10.2478/jos-2022-0005.

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Abstract U.S. import and export price indexes replaced unit value indexes forty years ago, given quality concerns of mismeasurement due to unit value bias. The administrative trade data underlying the unit values have greatly improved since that time. The transaction records are now more detailed, available electronically, and compiled monthly with little delay. The data are used by academic researchers to calculate price measures, and unit value indexes based on trade data are used by other national statistical offices (NSOs). The U.S. Bureau of Labor Statistics is now evaluating whether replacing price indexes with unit value indexes for homogeneous products calculated from administrative trade data could expand the number of published official import and export price indexes. Using export transactions, the research calculates detailed unit value indexes from 200 + million trade records from 2012–2017 for 123 export product categories. Results show that 27 of the 123 unit value indexes are homogeneous and closely comparable to published official price indexes. This article presents the concepts and methods considered to calculate and evaluate the unit value indexes and to select the product categories that are homogeneous. Compared to official price indexes, export unit value indexes for the 27 5-digit BEA (U.S. Bureau of Economic Analysis) end-use product categories would deflate real exports of these goods by 13 percentage points less over the period. Incorporating these 27 indexes into the top-level XPI would increase the value of real exports of all merchandise goods by 2.6 percentage points at the end of 2017.

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23

Poluan, Ferdhyo Natanael, and Gabriel Yosep Maximilianus Koyongian. "Hubungan harga minyak dunia dan indeks pasar Indonesia selama isu geopolitik." Manajemen Bisnis dan Keuangan Korporat 1, no. 1 (July 16, 2023): 9–15. http://dx.doi.org/10.58784/mbkk.35.

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The continuation of world geopolitical issues still tends to have an impact on fluctuations in world oil prices. Such circumstances motivated this study to find out how the world oil price relates to the market index in Indonesia. Observations are made from 1 January 2023 to 30 April 2023 with samples of market indexes in Indonesia and world oil prices. This study finds that market indexes in Indonesia tend to have similar returns even though some indexes are indicated to be negative. In addition, this study also finds that all indexes have less than optimal risk reward. The main finding of this study is that changes in world oil prices tend not to be followed by changes in market indexes in Indonesia.

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24

Mazuecos, Belén Mazuecos, and Marilena Vecco. "Contextual Art and Hedonic Price Indexes." International Journal of the Arts in Society: Annual Review 4, no. 6 (2010): 111–24. http://dx.doi.org/10.18848/1833-1866/cgp/v04i06/35773.

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25

White, Alan G. "Measurement Biases in Consumer Price Indexes." International Statistical Review / Revue Internationale de Statistique 67, no. 3 (December 1999): 301. http://dx.doi.org/10.2307/1403708.

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26

Frost, Stephen. "Experimental price indexes for financial services." Statistical Journal of the United Nations Economic Commission for Europe 21, no. 2 (May 18, 2005): 179–89. http://dx.doi.org/10.3233/sju-2004-21209.

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27

Primont, Daniel, Franklin M. Fisher, and Karl Shell. "Economic Analysis of Production Price Indexes." Southern Economic Journal 66, no. 4 (April 2000): 1016. http://dx.doi.org/10.2307/1061545.

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28

Haurin, Donald R., and Patric H. Hendershott. "House Price Indexes: Issues and Results." Real Estate Economics 19, no. 3 (September 1991): 259–69. http://dx.doi.org/10.1111/1540-6229.00552.

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Haurin, Donald R., Patric H. Hendershott, and Dongwook Kim. "Local House Price Indexes: 1982-1991." Real Estate Economics 19, no. 3 (September 1991): 451–72. http://dx.doi.org/10.1111/1540-6229.00562.

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30

Bianconi, Marcelo, and Joe A. Yoshino. "House price indexes and cyclical behavior." International Journal of Housing Markets and Analysis 6, no. 1 (March 2013): 26–44. http://dx.doi.org/10.1108/17538271311305995.

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31

Students, Zvi Griliches, and Daniel S. Hamermesh. "Hedonic price indexes for personal computers." Economics Letters 44, no. 4 (April 1994): 353–57. http://dx.doi.org/10.1016/0165-1765(94)90102-3.

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32

Zhen, Chen, Eric A. Finkelstein, Shawn A. Karns, Ephraim S. Leibtag, and Chenhua Zhang. "Scanner Data‐Based Panel Price Indexes." American Journal of Agricultural Economics 101, no. 1 (June 18, 2018): 311–29. http://dx.doi.org/10.1093/ajae/aay032.

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33

Oulton, Nicholas. "Do UK Price Indexes Overstate Inflation?" National Institute Economic Review 152 (May 1995): 60–75. http://dx.doi.org/10.1177/002795019515200105.

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Official price indexes may overstate (or understate) inflation for a number of reasons. These include substitution bias, outlet bias, failure to allow properly for quality change, and failure to allow for new goods. This note finds that substitution and outlet bias are probably not significant sources of error in the UK. The other two sources most probably do lead to significant overstatement, but the size of the upward bias cannot at the moment be quantified.‘Since, with technological advance, the quality of products tends to improve, the estimates of consumers' expenditure tend to understate the true growth in standards of consumption’. (CSO a 985, p. 72).‘The Producer Price Indices … make some allowance for changes in models and specifications when these can be identified in terms of changes of cost or in technical performance…. [Allowances for quality change] are necessarily somewhat rough and seldom fully satisfactory’. (CSO 1985, p. 40, emphasis added).

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White, Alan G. "Measurement Biases in Consumer Price Indexes." International Statistical Review 67, no. 3 (December 1999): 301–25. http://dx.doi.org/10.1111/j.1751-5823.1999.tb00451.x.

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35

Dunn, Abe, Anne Hall, and Seidu Dauda. "Are Medical Care Prices Still Declining? A Re‐Examination Based on Cost‐Effectiveness Studies." Econometrica 90, no. 2 (2022): 859–86. http://dx.doi.org/10.3982/ecta17635.

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More than two decades ago, a well‐known study on heart attack treatments provided evidence suggesting that, when appropriately adjusted for quality, medical care prices were actually declining (Cutler, McClellan, Newhouse, and Remler (1998)). Our paper revisits this subject by leveraging estimates from more than 8000 cost‐effectiveness studies across a broad range of conditions and treatments. We find large quality‐adjusted price declines associated with treatment innovations. To incorporate these quality‐adjusted indexes into an aggregate measure of inflation, we combine an unadjusted medical‐care price index, quality‐adjusted price indexes from treatment innovations, and proxies for the diffusion rate of new technologies. In contrast to official statistics that suggest medical care prices increased by 0.53 percent per year relative to economy‐wide inflation from 2000 to 2017, we find that quality‐adjusted medical care prices declined by 1.33 percent per year over the same period.

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36

Chiang-Lin, Tsung-Jui, Yong-Shiuan Lee, Tzong-Hann Shieh, Chien-Chang Yen, and Shang-Yueh Tsai. "Study of Asian indexes by a newly derived dynamic model." PLOS ONE 17, no. 5 (May 2, 2022): e0266600. http://dx.doi.org/10.1371/journal.pone.0266600.

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We take the stock prices as a dynamic system and characterize its movements by a newly derived dynamic model, called the new Price Reversion Model (nPRM), for which the solution is derived and carefully analyzed under different circumstances. We also develop a procedure of applying the nPRM to real daily closing prices of a stock index. This proposed procedure brings a different perspective to the study of stock prices based on thermodynamics, and the time varying coefficients in the nPRM offer economic meanings of the stock movements. More specifically, the average of smoothed historical data A in the nPRM, analogous to the environment temperature in the Newton’s law of cooling, represent an implied equilibrium price. The heat transfer coefficient κ is adapted to be either negative or positive, which illustrates the speed of convergence or divergence of stock prices, respectively. The empirical study of ten Asian stock indexes shows that the nPRM accurately characterizes and forecasts the market values.

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37

Wang, Zijun. "Predicting the rise and fall of Shanghai composite index based on artificial intelligence." E3S Web of Conferences 235 (2021): 03063. http://dx.doi.org/10.1051/e3sconf/202123503063.

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Shanghai composite index reflects the changes of stock prices, and the methods for various models to predict the stock index emerge one after another, and artificial intelligence is also widely used in various fields due to its stability and accuracy. In this paper, artificial intelligence is applied to Shanghai composite index to predict the stock index. A total of 3422 Shanghai composite indexes from January 1, 2005 to January 1, 2019 were collected, including five indexes: opening price, maximum price, closing price, minimum price and trading volume. Then MA, KDJ and MACD were selected as technical indexes, and their application methods and advantages in Shanghai composite index were analyzed in detail. In addition, in this paper, logistic regression and support vector machine (SVM) in artificial intelligence model were adopted to predict the ups and downs. Finally, it indicates that the support vector basis method based on radial basis is more suitable for stock index prediction model. In this paper, a framework of index prediction is provided by combining technical indicators with artificial intelligence.

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38

Widłak, Marta. "Metody wyznaczania hedonicznych indeksów cen jako sposób kontroli zmian jakości dóbr." Wiadomości Statystyczne. The Polish Statistician 2010, no. 9 (September 28, 2010): 1–25. http://dx.doi.org/10.59139/ws.2010.09.1.

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The aim of the article is to present and classify construction methods of hedonic price indexes being a way to control quality good changes in price indexes. Main differences between methods are pointed as well as conclusions drawn from their comparison. Theoretical literature and international empirical surveys are base of the study. The cited examples concern mainly hedonic price indexes of dwellings. Construction methods of hedonic price indexes may be classified as direct and indirect (by the classify criterion of using hedonic function). Direct methods are used for high heterogenic goods, where it is very difficult to determine a fixed basket of representatives. Indirect methods are used as additional to basket approach in the price dynamics survey.

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Ericson, Lars-Erik, Han-Suck Song, Jakob Winstrand, and Mats Wilhelmsson. "REGIONAL HOUSE PRICE INDEX CONSTRUCTION – THE CASE OF SWEDEN." International Journal of Strategic Property Management 17, no. 3 (September 23, 2013): 278–304. http://dx.doi.org/10.3846/1648715x.2013.822032.

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The academic literature on the construction of regional house price indexes usually uses geographic areas whose boundaries are administratively drawn. However such administrative regions might not be optimal for the construction of regional price indexes. When producing housing price indexes, we often encounter problems with insufficient number of observations. One way to remedy this problem is to estimate a quarterly index instead of a monthly index. Another possible way to mitigate the thin markets problem is to construct indexes for geographically aggregated regions. However, the literature that discusses methods of dealing with the problem of thin markets and especially geographical aggregation is very rare. The goal of this paper is to construct a housing price index for a major part of Sweden, and to construct price index series for a number of regions. The number of regions, and how their boundaries should be created in order to construct reliable regional price indexes, is however an open question. We apply traditional hedonic methodology in order to estimate house price indexes for both predefined regions whose boundaries are based on a division of labor markets in Sweden, as well as a division of regions based on statistical cluster analysis. The results from this study suggest that regions should be clustered together based on regional price levels and/or price development as clustering variables. If only geographical proximity is used as clustering variable, our computations show that there is a high risk that we end up with some clusters having large standard errors, which in turn might result in inaccurate indexes.

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Pakes, Ariel. "A Reconsideration of Hedonic Price Indexes with an Application to PC’s." American Economic Review 93, no. 5 (November 1, 2003): 1578–96. http://dx.doi.org/10.1257/000282803322655455.

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This paper compares hedonic to matched model indexes. Matched model indexes are averages of the price changes of goods that remain on sampled stores’ shelves. Since goods that disappear tend to have falling market values, matched model indexes select from the right tail of price changes. The BLS can construct hedonic indexes that correct for this selection and are justified by standard arguments. In an empirical study of PC’s hedonics produce sharp price declines while matched model indexes are near zero. Also, though there are modifications to hedonics that seem desirable, they are not those in current use.

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Mattingly, T. Joseph, Gerard F. Anderson, and Joseph F. Levy. "Comparison of Price Index Methods and Drug Price Inflation Estimates for Hepatitis C Virus Medications." JAMA Health Forum 4, no. 6 (June 9, 2023): e231317. http://dx.doi.org/10.1001/jamahealthforum.2023.1317.

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ImportanceMeasuring drug price inflation is challenging because new drugs continually enter the market, some drugs transition from branded to generic, and current inflation indexes do not account for these market basket changes. Instead, they measure the price increases after new drugs have been launched. Therefore, the public pays the higher costs of newer and usually more expensive drugs, but the inflation indexes do not reflect the increases over existing drugs previously used to treat the same conditions.ObjectiveTo assess how price index methods can affect estimates of drug price inflation using a case study of hepatitis C virus (HCV) medication and to explore other approaches for constructing a price index.Design, Setting, and ParticipantsThis cross-sectional study used data from outpatient pharmacies to compile a list of all HCV medications that were ever on the market (brand and generic) from 2013 to 2020. Using National Drug Codes of HCV drugs, a 20% nationally representative sample of Medicare Part D claims from 2013 to 2020 was queried. Alternative drug price indexes, including product-level vs class-level product and quantity definitions were developed in which gross vs net price definitions were used and an adjustment was created and applied to capture treatment duration because newer drugs often required a shorter duration.Main Outcomes and MeasuresPrice index value and rate of inflation from 2013 to 2020 for each methodologic approach to constructing a drug pricing index.ResultsIn all, 27 different HCV drug regimens were identified in Medicare Part D claims in 2013 to 2020. A product-level approach for measuring inflation estimated a 10% gross drug price increase from 2013 to 2020 for HCV drugs, whereas a class-level approach including the higher prices of the new drugs showed a 31% gross price increase. After adjusting for manufacturer rebates to estimate net prices, the findings showed that HCV drug prices fell by 31% from 2013 to 2020.Conclusions and RelevanceThe findings of this cross-sectional study indicate that the current product-level methods to estimate drug price inflation underestimated price increases for HCV drugs by failing to include the high launch prices of new market entrants. Using a class-level approach, the index captured higher spending on new products at launch. Prescription-level analyses, which did not consider shorter durations of treatment, overestimated price increases.

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Zapata, Hector O., Joshua D. Detre, and Tatsuya Hanabuchi. "Historical Performance of Commodity and Stock Markets." Journal of Agricultural and Applied Economics 44, no. 3 (August 2012): 339–57. http://dx.doi.org/10.1017/s1074070800000468.

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This paper examines two interrelated issues in commodity markets, namely, the cyclical relationship between stocks and commodities and the function of commodity and agribusiness indexes in portfolios. A high negative correlation has existed between stock and commodity prices over the past 140 years. Moreover, the two markets have alternated in price leadership with 29-32-year cycles. The recent price dominance in agricultural commodities started in 2000, a result supported by the empirical results of the portfolio allocation analysis. For a risk-averse investor, irrespective of the period analyzed, placing funds in agribusiness and/or agricultural commodity indexes was sound investing.

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Depari, Genesis Sembiring. "MACROECONOMICS FACTOR: THE IMPACT ON STOCK PRICE INDEX." Klabat Accounting Review 3, no. 2 (September 30, 2022): 23. http://dx.doi.org/10.60090/kar.v3i2.880.23-32.

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The objective of this study is to determine the link between macroeconomic variables and JCI, STI, and KLSE which are the stock price indexes of Indonesia, Singapore, and Malaysia stock price indexes. Multiple linear regression is used to investigate the influence of four macroeconomic factors on the stock market composite index, namely GDP growth, broad money (money supply), inflation, and interest rate spread. The finding indicates that inflation has a negative effect, while interest rate spread positively affecting the stock price Indexes. Investors may profit from this situation by purchasing blue chips when inflation and interest rates are rising. Keywords: GDP growth, inflation, interest rate spread, money supply, stock price indexes

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Horowitz, Stanley, and Bruce Harmon. "Inflation and Price Escalation Adjustments in Estimating Program Cost: F-35 Case Study." Defense Acquisition Research Journal 27, no. 92 (April 1, 2020): 194–217. http://dx.doi.org/10.22594/dau.19-836.27.02.

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Applying price indexes presents a challenge in estimating the costs of new defense systems. An inappropriate price index—one not closely linked to the inputs to the systems being costed—can introduce errors in both development of cost estimating relationships (CER) and in development of out-year budgets. To help cost analysts understand the impacts of different price indexes, this article applies two sets of price indexes to the F-35 program. Using hedonic price indexes derived from CERs, the authors isolate changes in price due to factors other than changes in quality by developing a “Baseline” CER model using data on historical tactical aircraft programs available early in the F-35 program. The focus of the work is to improve estimates of acquisition costs. All the data used in the econometric analysis are acquisition cost data. Better cost estimates should improve projections of budget requirements.

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Kirikkaleli, Dervis, and Ibrahim Darbaz. "The Causal Linkage between Energy Price and Food Price." Energies 14, no. 14 (July 11, 2021): 4182. http://dx.doi.org/10.3390/en14144182.

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This paper aims to reveal the causal relationship between energy prices and food prices and whether this relationship is similar in the food sub-groups forming the food price index used. As food prices more than doubled during the 2008 economic crisis, this relationship has received considerable attention from researchers. Many researches have been conducted to determine the causes and consequences of the 2008 food price crisis. Researches are mainly focused on crude oil and bio-energy in terms of “energy”. This research is not only differentiated by the data used but also by the methodology employed. The study attempts to add new findings to the empirical food price literature by utilizing relatively newly developed methods, namely Toda–Yamamoto causality, Fourier Toda–Yamamoto causality, and spectral BC causality tests. The spectral BC causality test clearly reveals that there is bidirectional causality between the energy price index and food price indexes (grains, other food, and oils) at different frequencies.

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Goetzmann, William, and Liang Peng. "Estimating House Price Indexes in the Presence of Seller Reservation Prices." Review of Economics and Statistics 88, no. 1 (February 1, 2006): 100–112. http://dx.doi.org/10.1162/003465306775565783.

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Goetzmann, William, and Liang Peng. "Estimating House Price Indexes in the Presence of Seller Reservation Prices." Review of Economics and Statistics 88, no. 1 (February 2006): 100–112. http://dx.doi.org/10.1162/rest.2006.88.1.100.

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Huseynli, Nigar. "Causality between Selected Energy Companies’ Price Indexes and Barel Oil Prices." International Journal of Energy Economics and Policy 13, no. 1 (January 22, 2023): 235–40. http://dx.doi.org/10.32479/ijeep.13579.

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Energy production and consumption have an important place in the world. Due to the increase in demand, it reveals the result of the valuation of the companies in this sector. The main purpose of this study is to analyze the relationship between brent oil prices in the world and the index prices of energy companies, which are among the world's most important and top 10 companies. The research covers the period between January 2011 and July 2022. The time series was created by considering the data in the selected time period on a monthly basis. Co-integration analysis was applied to the series and the relationship between the variables was tried to be determined. Short-term relationships were examined by applying the VAR model. At this stage, causality was carried out with Granger causality analysis. As a result of the analysis, it was concluded that brent oil prices, which were formed as a result of events in the world, had an effect on the index prices of two important energy companies, Exxon Mobile and Gazprom. In other words, there is a causal relationship between these variables. This bilateral causality relationship between Brent oil prices and Exxon Mobile is realized unilaterally with the other two energy companies. In short, there is a Granger causality relationship between these variables.

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Pu, Chengyi, Yueyun (Bill) Chen, and Xiaojun Pan. "Weather indexes, index insurance and weather index futures." Insurance Markets and Companies 9, no. 1 (August 31, 2018): 32–40. http://dx.doi.org/10.21511/ins.09(1).2018.04.

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This paper compares the weather insurance, weather index insurance and index futures and focuses on why China needs to develop weather indexes and adopt and trade weather index futures. It further discusses how to construct the indexes and futures and how to price them. Different from the Heating Degree Days (HDDs) and Cooling Degree Days (CDDs) used at Chicago Mercantile Exchange (CME), it develops the Extremely Heating Days (EHDs) and Extremely Cooling Days (ECDs) to derive relevant temperature-based weather index futures. Recently China has started using weather index insurance to cover farmers’ risk. Through comparisons of weather index futures with index insurance, this study shows the necessity and importance of using the weather index futures to better protect farmers and better develop China’s financial markets.

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Corrado, Carol, David Martin, and Qianfan Wu. "Innovation α: What Do IP-Intensive Stock Price Indexes Tell Us about Innovation?" AEA Papers and Proceedings 110 (May 1, 2020): 31–35. http://dx.doi.org/10.1257/pandp.20201056.

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Patents and other intellectual property (IP) have grown in relative importance in investments and market capitalizations of public firms (e.g., Corrado and Hulten 2010). This paper illustrates the construction of IP-intensive stock price indexes, focusing on a network analysis tool (Martin 2001, Winer et al. 2003, Luse and Martin 2014) that helps pinpoint firms that are most likely to generate value from their intangible assets. The analysis finds that (a) stock price indexes constructed using the tool yield above-average returns and (b) stock prices of US companies in two tech-driven sectors outperform non-US firms despite lower average patent portfolio valuations.

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