Relevant bibliographies by topics / Prices – Statistical methods

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Prices – Statistical methods'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Prices – Statistical methods"

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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 of the specific features of a structure. This article deals with the application of two statistical methods. The Pareto analysis, which can be used during the design of the tender price, and the extrapolation method, which can be used for the estimation of the price development, based on the regression analysis of the time series. The results of the article particularly serve to contractors in the building industry to better prepare their price offers in tenders. The findings of this document may also be applicable in other countries which have a similar economic profile as Slovakia.
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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 realizes in the framework of futures contracts and spot transactions. In recent years, short-term contracts prevail, rarely it’s used medium-term contracts. A sequence of coal pricing for geological and economic assessment has been determined, which is the following: classification of coal by grades and classes in accordance with current standards; statistical analysis of prices by grades and classes, coal enrichment products; determination of a system of discounts/surcharges to the price of each class depending on coal quality; correction of actual producer prices for assessment reserves. The values of surcharges or discounts for individual indicators of coal quality are determined. The sensitivity analysis of reserves value and profitability from changes in selling coal prices has been carried out. The determination of the coal price or enrichment products requires a detailed justification depending on the stage of geological and feasibility study of reserves. For detailed assessment of explored or exploited deposits it is reasonable to use actual prices of coal sales for the previous period and contract prices for future periods in the presence of medium and long-term contracts. For preliminary geological and economic assessment, it is possible to use the price of the analogue deposit, which is developed, or wholesale coal prices with correction by quality.
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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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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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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 the results of property market attribute weight estimation obtained by means of the Spearman rank correlation coefficient with the ceteris paribus adjustment and the multiple regression model based on a set of transactions with built-up land property. In both of the analyzed methods, qualitative variables were modeled with the use of the Osgood semantic differential scale. The results of the analysis show the equivalence of the applied methods. Property attribute weights calculated using the method based on the rank correlation coefficient with the ceteris paribus adjustment and the multiple regression model, both with the same level of relevance, showed almost identical values. This indicates that both parametric and non-parametric methods can be used to estimate weights.
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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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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 estimating the impact of the price of natural gas and WTI crude oil using the Gretl statistical program, taking into account the selection of the main correlation features of the price matrix. Of the 13 proposed research models, only one model showed its statistical insignificance. A paired linear model of the CocaCola share price dependence and its dependence on NGFO prices was presented and analyzed in detail. Based on the results of econometric modeling, linear regression models were constructed for the dependence of stock prices on the NGFO and WTISPOT prices. The Gretl environment allows you to evaluate the situation in the econometric environment and make a forecast based on the obtained models of the dependence of stock prices and make appropriate conclusions.
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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 elements and the cost structure as a whole. Special emphasis is placed on statistical technologies used in predicting changes in individual elements and the cost structure as a whole. The main goal of such a forecast is to develop a strategy for the behavior of the economic entity and formulate of its activity plan.
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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 daily retail price of pork in the South Korean domestic market based on news articles by incorporating deep learning and topic modeling techniques. To do this, we utilized news articles and retail price data from 2010 to 2019. We initially applied a topic modeling technique to obtain relevant keywords that can express price fluctuations. Based on these keywords, we constructed prediction models using statistical, machine learning, and deep learning methods. The experimental results show that there is a strong relationship between the meaning of news articles and the price of pork.
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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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Dissertations / Theses on the topic "Prices – Statistical methods"

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Xin, Ling, and 辛聆. "The statistical properties and effectiveness of filter trading rule." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/196092.

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Filter trading rule is a technical trading strategy that was very popular amongst practitioners and has been used a lot for testing market efficiency. It has been shown that the filter trading rule is mathematically equivalent to the CUSUM quality control test as both are based on change point detection theory via sequential probability ratio tests (SPRT). To study the operating characteristics of the filter trading rule, many results from the CUSUM literature can be applied. However, some interesting operating characteristics of a technical trading rule such as expected profit per day may not be relevant when put into a quality control setting. In this thesis, we derive formulae for computing these operating characteristics. It is well known that just like any other technical trading rule, the filter trading rule is not effective when the asset price follows a random walk. In this thesis, we studied the statistical properties and effectiveness of the filter trading rule under different asset price models including Markov regime switching model and conditional heteroskedasticity model. The properties of the filter trading rule considered include the waiting time for the first signal in filter trading, the duration of a long or a short cycle in filter trading, the profit return derived from a long or a short cycle and the unit time return of long term filter trading. Built on the above results, we consider the problem of optimizing the performance of a filter trading rule by choosing a suitable filter size. For filter trading rule under the conditional heteroskedasticity model, the change point detection methods lead to a new technical trading rule called generalized filter trading rule in this thesis. The generalized filter trading rule is shown to have a better performance over the ordinary filter trading rule when it is applied to the trading of the Hang Seng Index futures contract. Finally, we have applied the filter trading rule to intraday trading on high frequency Hang Seng Index futures data.
published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
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任漢全 and Hon-chuen Yam. "Statistical analysis of some technical trading rules in financial markets." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31213819.

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Ma, Po-yee Pauline, and 馬寶兒. "The heteroscedastic structure of some Hong Kong price series." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31976062.

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Shen, Rujun, and 沈汝君. "Mining optimal technical trading rules with genetic algorithms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47870011.

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In recent years technical trading rules are widely known by more and more people, not only the academics many investors also learn to apply them in financial markets. One approach of constructing technical trading rules is to use technical indicators, such as moving average(MA) and filter rules. These trading rules are widely used possibly because the technical indicators are simple to compute and can be programmed easily. An alternative approach of constructing technical trading rules is to rely on some chart patterns. However, the patterns and signals detected by these rules are often made by the visual inspection through human eyes. As for as I know, there are no universally acceptable methods of constructing the chart patterns. In 2000, Prof. Andrew Lo and his colleagues are the first ones who define five pairs of chart patterns mathematically. They are Head-and-Shoulders(HS) & Inverted Headand- Shoulders(IHS), Broadening tops(BTOP) & bottoms(BBOT), Triangle tops(TTOP) & bottoms(TBOT), Rectangle tops(RTOP) & bottoms( RBOT) and Double tops(DTOP) & bottoms(DBOT). The basic formulation of a chart pattern consists of two steps: detection of (i) extreme points of a price series; and (ii) shape of the pattern. In Lo et al.(2000), the method of kernel smoothing was used to identify the extreme points. It was admitted by Lo et al. (2000) that the optimal bandwidth used in kernel method is not the best choice and the expert judgement is needed in detecting the bandwidth. In addition, their work considered chart pattern detection only but no buy/sell signal detection. It should be noted that it is possible to have a chart pattern formed without a signal detected, but in this case no transaction will be made. In this thesis, I propose a new class of technical trading rules which aims to resolve the above problems. More specifically, each chart pattern is parameterized by a set of parameters which governs the shape of the pattern, the entry and exit signals of trades. Then the optimal set of parameters can be determined by using genetic algorithms (GAs). The advantage of GA is that they can deal with a high-dimensional optimization problems no matter the parameters to be optimized are continuous or discrete. In addition, GA can also be convenient to use in the situation that the fitness function is not differentiable or has a multi-modal surface.
published_or_final_version
Statistics and Actuarial Science
Master
Master of Philosophy
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Li, Chun-wah, and 李振華. "Spatial autocorrelation and liquidity in Hong Kong's real estate market." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B47278006.

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Spatial autocorrelation is commonly found in the Hedonic Pricing model for real estate prices, but little attention has been paid to identify the causes behind. The primary objective of this research is to examine the causes of spatial autocorrelation in housing prices. Observed autocorrelation is often attributable to the omission of important location characteristics in the modelling process. Since it is practically impossible to exhaustively include all location characteristics, some variables may eventually be omitted, leaving spatially autocorrelated residuals in the Hedonic Pricing model. This thesis proposes a new source of spatial autocorrelation: real estate market liquidity. We hypothesize that liquidity affects the geographical boundary within which buyers and sellers search for price information. When the “immediate vicinity” of a property has few transactions, buyers and sellers may have to search for price information from more distant locations. Therefore, low liquidity in the vicinity of a property should strengthen the spatial autocorrelation of real estate prices. A Spatial - Liquidity Hedonic Pricing (SLHP) model is proposed to test the above hypothesis. The SLHP model generalizes traditional spatial autoregressive models by making the spatial process liquidity dependent. When applied to the apartment market in Hong Kong, the model is operationalized by defining “immediate vicinity” as the building where the subject unit locates. Furthermore, the SLHP model recognizes that past transactions may affect current transactions, but not vice versa, so the spatial weight matrix is simply lower triangular. Under this condition, we have shown that the Maximum Likelihood Estimation is equivalent to the Ordinary Least Squares Estimation. This greatly simplifies the estimation procedures and reduces the empirical analysis to a feasible scale. Based on 15 500 transactions of residential units in Taikooshing, Hong Kong from 1992 to 2006, we conclude that while positive spatial autocorrelation is present in housing prices, its magnitude decreases when liquidity, as measured by the past transaction volume in the immediate vicinity of a subject unit, is high. In addition, we found that current prices are spatially correlated with transactions occurred up to the last three months only, reflecting the relatively high information efficiency of Hong Kong’s residential market. All these results are generally robust across a variety of distance, liquidity, and time weight specifications. This study establishes liquidity as a determinant of spatial autocorrelation in real estate prices. This is a new finding contributing to the economic literature on liquidity effects and technical literature on spatial estimation. Our results not only reveal the spatially dependent price formation process in the real estate market, but also have practical applications on the hedonic modelling of real estate prices for mass valuation and index construction.
published_or_final_version
Real Estate and Construction
Doctoral
Doctor of Philosophy
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6

Ren, JinJuan, and 任錦娟. "Investigating the role of accounting earnings in explaining increasingidiosyncratic volatility." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2004. http://hub.hku.hk/bib/B29851051.

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Mohammadi, Limaei Soleiman. "Economically optimal values and decisions in Iranian forest management /." Umeå : Dept. of Forest Economics, Swedish University of Agricultural Sciences, 2006. http://epsilon.slu.se/200691.pdf.

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Lawrence, Gerald D. "Stumpage price expectations: an empirical analysis of nonindustrial private landowners in the Mid-Atlantic states." Thesis, Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/51894.

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Numerous empirical studies outside of forestry have analyzed the role of price expectations in different decision processes. Empirical studies using price expectations in forestry research is a relatively new field of endeavor. Past studies have typically ignored or given cursory treatment to the role of price expectations. This study provides a review of studies in forestry that have attempted to incorporate price expectations into model formulations. Models are then developed to explain the short-run harvest, and long-run regeneration expenditure decisions by the non-industrial private forest owner, incorporating different distributed lag formulations to account for price expectations. The estimated models for the short-run harvest decision, using cross sectional non-aggregated data, indicates that price expectations play a significant role in this decision process. Therefore, price expectations should be incorporated in some form, (i.e. different forms of distributed lags), to properly specify models. Estimated models for the long-run regeneration expenditure decision indicates a weak link between economic variables and the regeneration decision. For both types of models, estimated coefficients for personal characteristics of landowners are in general considered insignificant, indicating the lack of influence that personal characteristics have on these decision processes
Master of Science
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Du, Toit Cornel. "Non-parametric volatility measurements and volatility forecasting models." Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/50401.

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Assignment (MComm)--Stellenbosch University, 2005.
ENGLISH ABSTRACT: Volatilty was originally seen to be constant and deterministic, but it was later realised that return series are non-stationary. Owing to this non-stationarity nature of returns, there were no reliable ex-post volatility measurements. Subsequently, researchers focussed on ex-ante volatility models. It was only then realised that before good volatility models can be created, reliable ex-post volatility measuremetns need to be defined. In this study we examine non-parametric ex-post volatility measurements in order to obtain approximations of the variances of non-stationary return series. A detailed mathematical derivation and discussion of the already developed volatility measurements, in particular the realised volatility- and DST measurements, are given In theory, the higher the sample frequency of returns is, the more accurate the measurements are. These volatility measurements referred to above, however, all have short-comings in that the realised volatility fails if the sample frequency becomes to high owing to microstructure effects. On the other hand, the DST measurement cannot handle changing instantaneous volatility. In this study we introduce a new volatility measurement, termed microstructure realised volatility, that overcomes these shortcomings. This measurement, as with realised volatility, is based on quadratic variation theory, but the underlying return model is more realistic.
AFRIKAANSE OPSOMMING: Volatiliteit is oorspronklik as konstant en deterministies beskou, dit was eers later dat besef is dat opbrengste nie-stasionêr is. Betroubare volatiliteits metings was nie beskikbaar nie weens die nie-stasionêre aard van opbrengste. Daarom het navorsers gefokus op vooruitskattingvolatiliteits modelle. Dit was eers op hierdie stadium dat navorsers besef het dat die definieering van betroubare volatiliteit metings 'n voorvereiste is vir die skepping van goeie vooruitskattings modelle. Nie-parametriese volatiliteit metings word in hierdie studie ondersoek om sodoende benaderings van die variansies van die nie-stasionêre opbrengste reeks te beraam. 'n Gedetaileerde wiskundige afleiding en bespreking van bestaande volatiliteits metings, spesifiek gerealiseerde volatiliteit en DST- metings, word gegee. In teorie salopbrengste wat meer dikwels waargeneem word tot beter akkuraatheid lei. Bogenoemde volatilitieits metings het egter tekortkominge aangesien gerealiseerde volatiliteit faal wanneer dit te hoog raak, weens mikrostruktuur effekte. Aan die ander kant kan die DST meting nie veranderlike oombliklike volatilitiet hanteer nie. Ons stel in hierdie studie 'n nuwe volatilitieits meting bekend, naamlik mikro-struktuur gerealiseerde volatiliteit, wat nie hierdie tekortkominge het nie. Net soos met gerealiseerde volatiliteit sal hierdie meting gebaseer wees op kwadratiese variasie teorie, maar die onderliggende opbrengste model is meer realisties.
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Lee, Yee-nin, and 李綺年. "On a double smooth transition time series model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31215555.

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Books on the topic "Prices – Statistical methods"

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Duqing, Liu, and Zhang Gengqiu, eds. Jia ge tong ji. Beijing: Zhongguo cai zheng jing ji chu ban she, 1987.

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Valʹtukh, K. K. Dinamika otnositelʹnykh t︠s︡en: Teorii︠a︡, statisticheskie issledovanii︠a︡. Novosibirsk: "Nauka", 2002.

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Bryan, Michael F. Asset prices in the measurement of inflation. Cambridge, MA: National Bureau of Economic Research, 2002.

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Bryan, Michael F. Asset prices in the measurement of inflation. Amsterdam: De Nederlandsche Bank, 2001.

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Gousen, Sarah. Producer price measurement--concepts and methods. [Washington, D.C.]: U.S. Dept. of Labor, Bureau of Labor Statistics, 1986.

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Demecs, Lászlóné. A Fogyasztóiár-statisztika módszere. Budapest: Központi Statisztikai Hivatal, 2000.

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Programme, International Comparison. International Comparison Programme (ICP) phase VI: Report of conduct of surveys and analysis in Nigeria. Lagos, Nigeria: Federal Office of Statistics, 1996.

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Linz, Stefan. Handbook on the application of quality adjustment methods in the Harmonised Index of Consumer Prices: Developed within the European project "CENEX HICP Quality Adjustment". Wiesbaden: Federal Statistical Office of Germany, 2009.

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Schmidt, Bernd. Die Preisindex für die Lebenshaltung aller privaten Haushalte in Gestalt eines Kettenindex: Beurteilung aus praktischer, empirischer und theoretischer Sicht. Stuttgart: Metzler-Poeschel, 1997.

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Mendoza, Meyra Sebello. Pricing behavior in Philippine corn markets: Implications for market efficiency. Washington, D.C: International Food Policy Research Institute, 1995.

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Book chapters on the topic "Prices – Statistical methods"

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Mashhoudy, Houshang. "Individualised Assignments on Modelling Car Prices using Data from the Internet." In Assessment Methods in Statistical Education, 247–57. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470710470.ch21.

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Bencivenga, Cristina, Giulia Sargenti, and Rita L. D’Ecclesia. "Energy markets: crucial relationship between prices." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 23–32. Milano: Springer Milan, 2010. http://dx.doi.org/10.1007/978-88-470-1481-7_3.

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Caporin, Massimiliano, Luca Corazzini, and Michele Costola. "Measuring the Impact of Behavioural Choices on the Market Prices." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 53–56. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05014-0_12.

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Braione, Manuela, and Davide De Gaetano. "Modelling the Australian Electricity Spot Prices: A VAR-BEKK Approach." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 191–97. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_35.

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Yoshikawa, Hiroshi. "Stock Prices and the Real Economy: The Different Meaning of Efficiency." In Complexity, Heterogeneity, and the Methods of Statistical Physics in Economics, 3–19. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4806-2_1.

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Ma, Xiaojuan, and Sergey Utev. "Modelling the share prices as a hidden random walk on the lamplighter group." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 263–70. Milano: Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2342-0_31.

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Nardon, Martina, and Paolo Pianca. "Extracting implied dividends from options prices: Some applications to the Italian derivatives market." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 315–22. Milano: Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2342-0_37.

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Nardon, Martina, and Paolo Pianca. "The Effects of Curvature and Elevation of the Probability Weighting Function on Options Prices." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 149–52. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05014-0_35.

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Crosato, Lisa, Luigi Grossi, and Fany Nan. "Forecasting the Volatility of Electricity Prices by Robust Estimation: An Application to the Italian Market." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 279–83. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89824-7_50.

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Arratia, Argimiro, Gustavo Avalos, Alejandra Cabaña, Ariel Duarte-López, and Martí Renedo-Mirambell. "Sentiment Analysis of Financial News: Mechanics and Statistics." In Data Science for Economics and Finance, 195–216. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66891-4_9.

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AbstractThis chapter describes the basic mechanics for building a forecasting model that uses as input sentiment indicators derived from textual data. In addition, as we focus our target of predictions on financial time series, we present a set of stylized empirical facts describing the statistical properties of lexicon-based sentiment indicators extracted from news on financial markets. Examples of these modeling methods and statistical hypothesis tests are provided on real data. The general goal is to provide guidelines for financial practitioners for the proper construction and interpretation of their own time-dependent numerical information representing public perception toward companies, stocks’ prices, and financial markets in general.
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Conference papers on the topic "Prices – Statistical methods"

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Radzikowski, Bartosz, and Adam Śmietanka. "Online CASE CPI." In CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/carma2016.2016.3133.

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Online CASE CPI is an example of using Big data in public statistics. In principle, it is a consumer price index based entirely on online prices: a combination of Central Statistical Office of Poland’s methodology and online data sets. An innovative method of data collection – data scrapping – allowed us to substantially reduce a time delay between data collection and a publication of results. A short, nine-month period of data collection has not given rise to make important conclusions, hence the aims of this paper are: to discuss a general framework of measuring consumer inflation online, to present preliminary results for Poland and to highlight the strengths and weaknesses of this approach. Finally, we believe that online consumer price indices have a complementary nature to conventional inflation measurement, but it might be a serious alternative, having in mind a huge growth potential of e-commerce in coming years.
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Butryn, Krzysztof, and Edward Preweda. "Analysis of the Impact of Quantitative and Qualitative Price-setting Attributes on a Market of Real Estate Intended for the Purpose of the Transformer Stations on the Example of Krakow." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.177.

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Based on appraisal reports, obtained from the City Office of Krakow, there were formulated base of real estate properties on which is situated the building of transformer station or which are intended for such purpose. The base consists of 90 properties located in the administrative boundaries of the city of Krakow. Most of these properties are the plots of very small areas, mainly in the range from 30 to 70 square meters. Based on the completed database, there were conducted a statistical analysis of the relevant market the property. In order to determine the relationship between the attributes and the price of real estate, there were calculated coefficients of the Pearson complete correlation and coefficients of the Spearman correlation. The analysis showed significant differences between quantitative and qualitative correlation coefficients for some variables. In order to improve the consistency of the database, using statistical methods eliminated property turned out. Finally, the analysis considered two bases, numbering respectively 90 and 77 real estates. In the following values, there were defined standardized regression coefficients (scale 9), the partial correlation coefficients for the dependent variable (price) relative to the rest of variables and coefficients of determination. On the basis of calculations and analysis, there have been drawn conclusions on the impact of each attribute on the market prices of these unusual properties.
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Ecer, Fatih. "Comparision of Hedonic Regression Method and Artificial Neural Networks to Predict Housing Prices in Turkey." In International Conference on Eurasian Economies. Eurasian Economists Association, 2014. http://dx.doi.org/10.36880/c05.01150.

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Owner-occupied housing is both a place to live and also the most important asset in many households’ portfolio. Accurately predicting of house prices is therefore of great interest to the general public. This paper aims to compare the housing price prediction accuracies of Hedonic Model (HM) and Artificial Neural Networks (ANNs). In order to achieve this aim, two techniques’ prediction results were compared by using four performance criteria: RMSE, MAE, MAD, and Theil’s U statistic. This study uses the HM and ANNs to empirically determine the house prices in Turkey. HM is the standard technique for modeling the behavior of house prices over the past three decades and is based on micro economic theory. The non-linear relationship between house price and its determinants can be modeled by an ANN, so it is employed in this paper as an alternative method. Empirical results revealed that ANNs performed better than HM in house price predictions, indicating that ANNs could be useful for prediction of house prices. More clearly, the performance criteria from the ANNs are smaller than those from the HM by roughly 60-90%. For instance, the ANN model has about 77 percent lower RMSE, 91 percent lower MAE, 64 percent lower MAD, and 77 percent lower Theil’s U statistic than those of the HM.
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Shrestha, G. B., and Songbo Qiao. "Statistical characterization of electricity price in competitive power markets." In 2010 IEEE 11th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS). IEEE, 2010. http://dx.doi.org/10.1109/pmaps.2010.5529006.

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Gong, Yongshun, Zhibin Li, Jian Zhang, Wei Liu, Bei Chen, and Xiangjun Dong. "A Spatial Missing Value Imputation Method for Multi-view Urban Statistical Data." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/182.

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Large volumes of urban statistical data with multiple views imply rich knowledge about the development degree of cities. These data present crucial statistics which play an irreplaceable role in the regional analysis and urban computing. In reality, however, the statistical data divided into fine-grained regions usually suffer from missing data problems. Those missing values hide the useful information that may result in a distorted data analysis. Thus, in this paper, we propose a spatial missing data imputation method for multi-view urban statistical data. To address this problem, we exploit an improved spatial multi-kernel clustering method to guide the imputation process cooperating with an adaptive-weight non-negative matrix factorization strategy. Intensive experiments are conducted with other state-of-the-art approaches on six real-world urban statistical datasets. The results not only show the superiority of our method against other comparative methods on different datasets, but also represent a strong generalizability of our model.
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Yu, Shujian, Ammar Shaker, Francesco Alesiani, and Jose Principe. "Measuring the Discrepancy between Conditional Distributions: Methods, Properties and Applications." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/385.

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We propose a simple yet powerful test statistic to quantify the discrepancy between two conditional distributions. The new statistic avoids the explicit estimation of the underlying distributions in high-dimensional space and it operates on the cone of symmetric positive semidefinite (SPS) matrix using the Bregman matrix divergence. Moreover, it inherits the merits of the correntropy function to explicitly incorporate high-order statistics in the data. We present the properties of our new statistic and illustrate its connections to prior art. We finally show the applications of our new statistic on three different machine learning problems, namely the multi-task learning over graphs, the concept drift detection, and the information-theoretic feature selection, to demonstrate its utility and advantage. Code of our statistic is available at https://bit.ly/BregmanCorrentropy.
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Lambkin, David, Ian Wade, and Robin Stephens. "Estimating Operational Weather Downtime: A Comparison of Analytical Methods." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95367.

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Abstract Weather downtime (WDT) is a logistical and financial risk when planning operations or offering services. Such risk is typically identified and managed in advance using statistical predictions based on historical weather data. Estimates of programme and cost for offshore construction work may vary, not because of the nature of a task, or the environment at the location, or the capability and price of a vessel, but because estimates of WDT have been calculated in different ways. Estimates of WDT are required in order to develop a realistic programme for complex and long duration projects. Therefore, a good understanding of the analytical options and a feel for the implications of the many and varied approaches is key to finding optimal solutions regarding WDT assessments. In this paper we consider a number of variants to the two principal approaches (namely ‘Weather Windows’ and ‘Simulation Based’ WDT analysis) to the derivation of WDT statistics. WDT estimates calculated using the same environmental input data, but alternative approaches are presented. The presentation highlights the potential variation in downtime statistics that can result from the alternative analyses, aiming to improve awareness of the application of such statistics when estimating project programme and cost at the planning stages.
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Cerjan, Marin, Ivana Krzelj, Marko Vidak, and Marko Delimar. "A literature review with statistical analysis of electricity price forecasting methods." In IEEE EUROCON 2013. IEEE, 2013. http://dx.doi.org/10.1109/eurocon.2013.6625068.

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Nor, Abu Hassan Shaari Md, Tamat Sarmidi, and Ehsan Hosseinidoust. "Forecasting of palm oil price in Malaysia using linear and nonlinear methods." In STATISTICS AND OPERATIONAL RESEARCH INTERNATIONAL CONFERENCE (SORIC 2013). AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4894340.

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Hegland, Markus. "An Approximate Maximum a Posteriori Method with Gaussian Process Priors." In Proceedings of the International Statistics Workshop. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812772466_0020.

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