Academic literature on the topic 'Price variances'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Price variances.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Price variances"
1
Heny Sidanti and Annisa Istikhomah. "The Effect Of Stock Price, Share Return, Share Trading Volume, And Return Variant On Bid-Ask Spread On Textile And Garment Companies Listed On The Indonesia Stock Exchange, 2019-2020." International Journal of Science, Technology & Management 2, no. 4 (July 23, 2021): 1357–66. http://dx.doi.org/10.46729/ijstm.v2i4.269.
Full textAbstract:
This study aims to obtain empirical evidence of the effect of Stock Price, Stock Return, Stock Trading Volume, and Return Variant on the Bid-Ask Spread of Stocks in Textile and Garment Companies Listed in Indonesia Stock Exchange in 2019-2020. The stock price used is the stock price recorded at the end of each closing period (closing price), stock returns are measured using the difference between returns on the research day and before the study divided by returns on the day before the study, stock trading volume is measured by the number of shares traded at the time of the study. t is divided by the number of shares outstanding at the time of the study, the variance of stock returns is measured using the standard deviation, and the bid-ask spread is measured by the difference between the selling price and the purchase price divided by the difference between the selling price and the purchase price divided by two. The population in this study is 17 textile and garment companies listed on the IDX. Based on the purposive sampling method, a sample of 16 companies was obtained with 309 data. This research data is obtained from the company's monthly data from 2019 to 2020. The results of the analysis show that stock prices and stock trading volumes affect the bid-ask spread, while stock returns and return variances do not affect the bid-ask spread. Meanwhile, simultaneously, stock prices, stock returns, stock trading volume, and return variance affect the bid-ask spread. This research data is obtained from the company's monthly data from 2019 to 2020. The results of the analysis show that stock prices and stock trading volume affect the bid-ask spread, while stock returns and return variances do not affect the bid-ask spread. Meanwhile, simultaneously, stock prices, stock returns, stock trading volume, and return variance affect the bid-ask spread. This research data is obtained from the company's monthly data from 2019 to 2020. The results of the analysis show that stock prices and stock trading volumes affect the bid-ask spread, while stock returns and return variances do not affect the bid-ask spread. Meanwhile, simultaneously, stock prices, stock returns, stock trading volume, and return variance affect the bid-ask spread.
2
Duchin, Ran, and Moshe Levy. "Disagreement, Portfolio Optimization, and Excess Volatility." Journal of Financial and Quantitative Analysis 45, no. 3 (March 31, 2010): 623–40. http://dx.doi.org/10.1017/s0022109010000189.
Full textAbstract:
AbstractDisagreement, a key factor inducing trading, has been receiving ever increasing attention in recent years. Most research has focused on disagreement about the expected returns. Several authors have shown that if the average belief coincides with the true expected return, in the portfolio context prices are unaffected by disagreement. In this paper we study the pricing effects of disagreement about return variances. We show that i) disagreement about variances has systematic and significant pricing effects—more disagreement leads to higher prices, and ii) prices are very sensitive to the degree of disagreement: Even if the average belief about the variance is constant, tiny fluctuations in the disagreement about the variance lead to substantial price fluctuations. This second result may offer an explanation for the excess volatility puzzle: When small changes in the degree of disagreement occur, they induce relatively large price changes. Yet, the changes in disagreement may be hard to directly detect empirically, leading to apparent “excess volatility.”
3
Rahgozar, Reza, and Mary Tichich. "Changes in Financial Variables and Altman’s Z Score on Stock Price: Consideration of Firm Size and Market Risk." Journal of Finance Issues 14, no. 1 (June 30, 2015): 37–50. http://dx.doi.org/10.58886/jfi.v14i1.2288.
Full textAbstract:
The valuation of common stock can be approached in several ways. Some models, known as dividend valuation models, rely solely on expected dividends and other models rely on longrun historical relationships between stock prices, financial variables, and market risk factors. This study, through correlation and regression analyses, identifies the most relevant variables affecting stock price changes of the Standard & Poor’s 500 Index firms. Moreover, by applyingthe Altman financial stress model, the significance of changes in financial stress measures on stock prices is tested. In addition, the study investigates whether the effects of financial factors on stock prices depend on company size. Also, through mean and variance analysis, the equality of means and variances of larger and smaller firms exposed to market risks are examined. Among all financial variables considered, the changes in operating income and the financialstress measure are the most relevant factors affecting stock price variations. The results showed no strong positive relationship between changes in stock prices and dividends. The tests of equality of means and variances failed to support the notion that correlations between changes in stock prices and operating income, financial leverage, and total assets for small and large size firms differ. However, it rejected the hypothesis that variances of market risk of smalarge firms are equal.
4
Białek, Jacek. "Basic Statistics of Jevons and Carli Indices under the GBM Price Model." Journal of Official Statistics 36, no. 4 (December 1, 2020): 737–61. http://dx.doi.org/10.2478/jos-2020-0037.
Full textAbstract:
AbstractMost countries use either the Jevons or Carli index for the calculation of their Consumer Price Index (CPI) at the lowest (elementary) level of aggregation. The choice of the elementary formula for inflation measurement does matter and the effect of the change of the index formula was estimated by the Bureau of Labor Statistics (2001). It has been shown in the literature that the difference between the Carli index and the Jevons index is bounded from below by the variance of the price relatives. In this article, we extend this result, comparing expected values and variances of these sample indices under the assumption that prices are described by a geometric Brownian motion (GBM). We provide formulas for their biases, variances and mean-squared errors.
5
CHEN, Jieh-Haur, Chuan Fan ONG, Linzi ZHENG, and Shu-Chien HSU. "FORECASTING SPATIAL DYNAMICS OF THE HOUSING MARKET USING SUPPORT VECTOR MACHINE." International Journal of Strategic Property Management 21, no. 3 (July 11, 2017): 273–83. http://dx.doi.org/10.3846/1648715x.2016.1259190.
Full textAbstract:
This paper adopts a novel approach of Support Vector Machine (SVM) to forecast residential housing prices. as one type of machine learning algorithm, the proposed SVM encompasses a larger set of variables that are recognized as price-influencing and meanwhile enables recognizing the geographical pattern of housing price dynamics. The analytical framework consists of two steps. The first step is to identify the supporting vectors (SVs) to price variances using the stepwise multi-regression approach; and then it is to forecast the housing price variances by employing the SVs identified by the first step as well as other variables postulated by the hedonic price theory, where the housing prices in Taipei City are empirically examined to verify the designed framework. Results computed by nonparametric estimation confirm that the prediction power of using SVM in housing price forecasting is of high accuracy. Further studies are suggested to extract the geographical weights using kernel density estimates to reflect price responses to local quantiles of hedonic attributes.
6
Funke, Michael, Petar Mihaylovski, and Adrian Wende. "Out of Sync Subnational Housing Markets and Macroprudential Policies in the UK." De Economist 169, no. 4 (October 9, 2021): 445–67. http://dx.doi.org/10.1007/s10645-021-09394-1.
Full textAbstract:
AbstractWe examine whether regionally differentiated macroprudential policies can address financial stability concerns and moderate house price differences in the UK. We disaggregate both the household sector and the housing stock in a two-region DSGE model with out of sync subnational housing markets and compare four policy types: standard monetary policy, leaning against the wind monetary policy, national macroprudential policy or one that targets region-specific LTV ratios. In terms of reducing variances of house prices, regionally differentiated macroprudential policy performs best, provided the policy authorities are concerned with stabilising output and house prices rather than simply minimising the variance of inflation.
7
Core, John E., Wayne R. Guay, and Robert E. Verrecchia. "Price versus Non-Price Performance Measures in Optimal CEO Compensation Contracts." Accounting Review 78, no. 4 (October 1, 2003): 957–81. http://dx.doi.org/10.2308/accr.2003.78.4.957.
Full textAbstract:
We empirically examine standard agency predictions about how performance measures are optimally weighted to provide CEO incentives. Consistent with prior empirical research, we document that the relative weight on price and non-price performance measures in CEO cash pay is a decreasing function of the relative variances. Agency theory speaks to the weights in total compensation (annual total pay and changes in the CEO's equity portfolio value), however, and we document that very little of CEOs' total incentives come from cash pay. We also document that variation in the relative weight on price and non-price performance measures in CEO total compensation is an increasing function of the relative variances. The conflicting results using total compensation indicate that existing findings on cash pay cannot be interpreted as evidence supporting standard agency predictions. Based on our results, we suggest approaches for future research on performance measure use in CEO total compensation.
8
Rahman, Sajjadur, and Apostolos Serletis. "THE ASYMMETRIC EFFECTS OF OIL PRICE SHOCKS." Macroeconomic Dynamics 15, S3 (November 2011): 437–71. http://dx.doi.org/10.1017/s1365100511000204.
Full textAbstract:
In this paper we investigate the effects of oil price uncertainty and its asymmetry on real economic activity in the United States, in the context of a bivariate vector autoregression with GARCH-in-mean errors. The model allows for the possibilities of spillovers and asymmetries in the variance–covariance structure for real output growth and the change in the real price of oil. Our measure of oil price uncertainty is the conditional variance of the oil price–change forecast error. We isolate the effects of volatility in the change in the price of oil and its asymmetry on output growth and employ simulation methods to calculate generalized impulse response functions and volatility impulse response functions to trace the effects of independent shocks on the conditional means and the conditional variances, respectively, of the variables. We find that oil price uncertainty has a negative effect on output, and that shocks to the price of oil and its uncertainty have asymmetric effects on output.
9
Ekara, Kingsley E., and Anthony Usoro. "Fitting Alternative Autoregressive and Moving Average Models to Nigeria Crude Oil Prices." International Journal of Mathematics and Statistics Studies 12, no. 1 (January 15, 2024): 1–13. http://dx.doi.org/10.37745/ijmss.13/vol12n1113.
Full textAbstract:
The need to compare the efficiency between the Autoregressive Integrated moving average (ARIMA (p,d,q)) models when modelling Crude oil price is the motivation behind this research. The research focuses on different orders of Autoregressive Integrated moving average models. The trend Analysis of the original series were plotted and was observed that crude oil prices were not stationary. The data were transformed by taking a natural log and the series becomes stationary after first differenced. The ACF and PACF of the stationary time series were also plotted which were the basis for the suggested ARIMA models. Error variances for the suggested ARIMA (p,d,q) models were derived and estimated as the basis for model performance comparison. Empirically, Crude Oil Price data spanning from January 2006 to July 2023 were used for the analysis. Findings from the study has revealed that, ARIMA (2,1,1) with the least error variance outperformed the other suggested models. The study further stated the estimated models for forecast of the future value of the crude oil price. The study recommends the use of error variance as a criterion for best model suggestion and ARIMA (2,1,1) was selected as the best model for modelling Nigeria Crude oil price.
10
Wang, Xingchun, Zhiwei Su, and Guangli Xu. "THE VALUATION OF EXECUTIVE STOCK OPTIONS UNDER GARCH MODELS." Probability in the Engineering and Informational Sciences 32, no. 3 (August 11, 2017): 409–33. http://dx.doi.org/10.1017/s0269964817000316.
Full textAbstract:
In this paper, we investigate executive stock options with endogenous departure and time-varying variances. We use a “Generalized Autoregressive Conditional Heteroskedasticity” process to capture the variance process of the log stock price. In addition, we take into consideration the departure risk of the executive and assume that the probability of remaining employed has a power form of stock price ratios. After deriving the closed-form pricing formulae of executive stock options, we illustrate the effects of the departure risk on the values of executive stock options.
Dissertations / Theses on the topic "Price variances"
1
Vù, Thi Minh Hàng. "Analysing the influence of revenue management characteristics on customers' price fairness perception, price acceptance and switching intention in the service industry." Electronic Thesis or Diss., Aix-Marseille, 2022. http://theses.univ-amu.fr.lama.univ-amu.fr/220120_VU_905yeynbv422j202mdju405xmo_TH.pdf.
Full textAbstract:
De nos jours, la gestion des revenus (Revenue Management, RM) a été largement appliquée dans le monde entier pour maximiser les revenus et les bénéfices à court terme des entreprises. Cependant, l'effet du RM sur le profit à long terme reste sans réponse. Afin de contribuer à combler les lacunes de la littérature sur la tarification, la présente étude a d'abord cherché à mettre en lumière les liens entre la perception des clients et les réponses comportementales qui en découlent et qui sont directement associées au profit à long terme des entreprises, notamment la perception de l'équité des prix, l'acceptation des prix et l'intention de changer de fournisseur. Deuxièmement, la présente étude a permis d'élucider la manière dont trois caractéristiques typiques de la variation des prix causée par la pratique de la RM (intensité, vitesse et régularité) influencent la perception de l'équité des prix, l'acceptation des prix et l'intention de changer de fournisseur chez les clients. Troisièmement, nous avons également découvert si le type de variation de prix (une augmentation ou une diminution de prix) modère les influences de l'intensité, de la vitesse et de la régularité sur la perception et les réactions des trois clients. Les résultats de cette étude ont fourni des réponses détaillées aux trois objectifs de recherche. Les contributions théoriques des résultats de la recherche ont été discutées, suivies des suggestions managériales pour établir une stratégie de tarification RM plus efficace pour un développement financier durable à long terme, et des recommandations pour les recherches futuresNowadays, Revenue Management (RM) has been applied widely across industries around the world to maximize the short-term revenue and profit of firms. However, the effect of this pricing strategy on the long-term revenue and profit remains unanswered. In the investigation of the RM practice which discriminates prices for the same customer over time, to contribute to filling the gap in the pricing literature, the present study, firstly, aimed to illuminate the links between customer perception and consequent behavioural responses which are directly associated with the long-term profit of firms, including Price fairness perception, Price acceptance, and Switching intention. Secondly, the present study elucidated how three typical price variance characteristics caused by the RM practice (Intensity, Speed, and Regularity) influence customers’ Price fairness perception, Price acceptance, and Switching intention. Thirdly, whether Type of price variance (a price increase or a price decrease) moderates the influences of the Intensity, Speed, and Regularity on the three customers’ perception and reactions was also discovered in this study. Findings of the current study not only provided the detailed answers for the three research objectives, but also shed light on the interaction effects of Intensity, Speed, and Regularity on customers’ perception and reactions. Theoretical contributions of the research findings were discussed, followed by the managerial suggestions to establish a more efficient RM pricing Strategy for sustainable financial development in the long term, and recommendations for future research
2
Zhao, Xiaolu. "Essays on financial econometrics : variance and covariance estimation using price durations." Thesis, Lancaster University, 2017. http://eprints.lancs.ac.uk/89003/.
Full textAbstract:
Asset variance and covariance are fundamental for financial risk management and many finance applications. With the advent of tick-by-tick high-frequency data, the estimation of univariate variances and multivariate covariance matrices has attracted more attention from econometricians. Many of the proposed high-frequency variance and covariance estimators are based on time-domain measurements. In this thesis, we investigate variance and covariance estimators constructed on the price domain: the price duration based variance and covariance estimators. A price event occurs when the absolute cumulative price change equals or exceeds a pre-specified threshold value. The time taken between two consecutive price events is a price duration. Intuitively, shorter durations are indicative of higher volatility. The duration-based approach provides a new angle to look at the high-frequency data, additionally, the duration based variance and covariance estimators are shown to be more efficient than competing time-domain high-frequency estimators. The information advantage of the duration based approach is demonstrated through two empirical applications, a volatility forecasting exercise and an out-of-sample globalminimum-variance portfolio allocation problem. The duration based estimators are shown to provide both better forecasting performance and better portfolio allocation results. The paper in Chapter 2 is under the first round Revise&Resubmit to the Journal of Business & Economic Statistics. In Chapter 2, we discuss the estimation of univariate variance using price durations. Variance estimation using high-frequency data needs to take into account the effect of market microstructure (MMS) noise, including discrete transaction times, discrete price levels, and bid/ask spreads, as well as price jumps. The price duration estimator has a built-in feature to be robust to large price jumps, while its robustness against the MMS noise is achieved through a careful selection of the threshold value that defines a price event. We discuss the selection of this optimal threshold value through both simulation and empirical evidence. We devise both a non-parametric and a parametric estimator. For the estimation of integrated variance at a daily frequency, the non-parametric duration based variance estimator suffices, while the parametric estimator additionally provides us with an instantaneous variance estimator. As an empirical application to 20 DJIA stocks, we compare the volatility forecasting performance of three classes of volatility estimators, including the realized volatility, the option implied volatility, and the price duration based volatility estimators, on one-day, one-week, and one-month horizons. Forecasting comparisons among individual estimators, as well as in a combination setup, are considered. The duration based estimators, especially the parametric price duration volatility estimator, are found to provide more accurate out-of-sample forecasts. In Chapter 3, we introduce a covariance matrix estimator using price durations. In the multivariate setting, there is the additional issue of nonsynchronous trade arrival times when estimating a high-dimensional variance-covariance matrix using tick-by-tick transaction data. Through simulation, we assess the effects of the lasttick time-synchronization method and MMS noise on the duration based covariance estimator, and compare its accuracy and efficiency with other candidate covariance estimators. Since the covariance matrix is estimated on a pairwise basis, it is not guaranteed to be positive semi-definite (psd). To reduce the number of negative eigenvalues produced by a non-psd matrix, we devise an averaging estimator which is the average of a wide range of duration based covariance matrix estimators. This estimator is applied to a portfolio of 19 DJIA stocks on an out-of-sample global minimum variance portfolio allocation problem where the objective is to minimize the one-day ahead portfolio variance. A simple shrinkage technique is used to improve non-psd and ill-conditioned matrices. The price duration covariance matrix estimator is shown to provide a comparably low portfolio variance while yielding considerably lower portfolio turnover rates than previous estimators.
3
Raval, Vimal. "Arbitrage bounds for prices of options on realised variance." Thesis, Imperial College London, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.529358.
Full text
4
Dahlin, Alexander. "The Price Dynamics of Regional Family Houses in Sweden : Ripple Effect or Not?" Thesis, KTH, Fastigheter och byggande, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254836.
Full textAbstract:
This paper builds on the study Prices on the Second-hand Market for Swedish Family Housesconducted by Lennart Berg, economist and associate professor emeritus from UppsalaUniversity in 2002. This study attempts to identify inter-and intraregional pricedependencies in Sweden for the second hand market for family houses. The house priceindices used in this econometric analysis commences in 1990:1 and ends in 2018:4 for allregions in accordance to NUTS 2 in Sweden.This thesis models the change of the regional prices for one-and two family houses indicatingthat the metropolitan area of Stockholm contributes predominantly to all other regionsthroughout the country. In addition, the capital city also shows cointegrated relationshipswith all regions although not the contrary. Shocks to the housing market of Stockholmindicate that Gothenburg, the Western region and Malmö are affected contemporaneouslyfollowed by the other regions nationwide with a certain time lag leading to say that thecontribution and influence of the capital city´s house price development leads the pricedevelopment throughout the country, Sweden.Detta examensarbete ligger till grund av den tidigare studien Prices on the Second-handMarket for Swedish Family Houses av Lennart Berg, nationalekonom och professor emerituspå Uppsala Universitet, 2002. Denna studie har som mål att finna de inter-och intraregionala pris förhållanden i Sverige på den inhemska andrahandsmarknaden för en-och tvåfamiljhus. Med hjälp av ekonometriska analyser har fastighetsprisindex använts i rapportenmellan år 1990:1 till 2018:4 för samtliga regioner i landet enligt indelning av NUTS 2.Denna uppsats skattar de regionala prisförändringar för en-och två familjehus därindikationer tyder på att Stockholms län verkar vara prisledande i relation till alla andraregioner och storstadsområden i Sverige. Därutöver, visar det sig att huvudstaden harkointegrerande samband med resten av landets regioner dock ej tvärtom. Simuleradeekonomiska chocker på Stockholms län visar att att Stor-Göteborg, Västsverige och Stor-Malmö är påverkade samtidigt med hänsyn till tid följd av de resterande regionerna med ettvisst lag. Detta kan tyda på att Stockholms regionala utveckling samt prispåverkan lederprisutvecklingen i landet.
5
Holt, Andrew James. "On computing discrete logarithms : large prime(s) variants." Thesis, University of Bath, 2003. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425879.
Full text
6
Thierbach, Frank. "Mean variance hedging in the presence of additionally observed market prices /." Aachen : Shaker, 2003. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=010527019&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
Full text
7
Renfroe, Laura A. "The International iPad Index: Price Variants across Countries and Associated Population Factors." Scholarship @ Claremont, 2013. http://scholarship.claremont.edu/cmc_theses/731.
Full textAbstract:
The goal of this research was to determine which population factors were associated with iPad pricing differences across countries. Specifically, this paper measured the relationship between iPad prices in a given country and its U.S. dollar exchange rate, amount of income inequality, Gross Domestic Product per capita, luxury good sales growth, Individualism Index score, and population density. Panel data was collected for the iPad 2, the iPad Retina, and the iPad Mini tablets from 38 countries of varying geographic locations, economic paradigms, and political structures. The pooled data set yielded 114 observations in total. Regressing iPad price as a percent of national average income revealed a positive relationship between price and status consciousness as well as cultural individualism. There existed a negative relationship between iPad price and luxury sales growth. These results indicated that the iPad served as a status symbol with higher demand in countries that promoted individualism and exhibited higher degrees of income inequality.
8
Lee, Mou Chin. "An empirical test of variance gamma options pricing model on Hang Seng index options." HKBU Institutional Repository, 2000. http://repository.hkbu.edu.hk/etd_ra/263.
Full text
9
Park, Sungwook. "Three essays on long run movements of real exchange rates." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1180465881.
Full text
10
Issaka, Aziz. "Analysis of Variance Based Financial Instruments and Transition Probability Densities Swaps, Price Indices, and Asymptotic Expansions." Diss., North Dakota State University, 2018. https://hdl.handle.net/10365/31742.
Full textAbstract:
This dissertation studies a couple of variance-dependent instruments in the financial market. Firstly, a number of aspects of the variance swap in connection to the Barndorff-Nielsen and Shephard model are studied. A partial integro-differential equation that describes the dynamics of the arbitrage-free price of the variance swap is formulated. Under appropriate assumptions for the first four cumulants of the driving subordinator, a Ve\v{c}e\v{r}-type theorem is proved. The bounds of the arbitrage-free variance swap price are also found. Finally, a price-weighted index modulated by market variance is introduced. The large-basket limit dynamics of the price index and the ``error term" are derived. Empirical data driven numerical examples are provided in support of the proposed price index. We implemented Feynman path integral method for the analysis of option pricing for certain L\'evy process-driven financial markets. For such markets, we find closed form solutions of transition probability density functions of option pricing in terms of various special functions. Asymptotic analysis of transition probability density functions is provided. We also find expressions for transition probability density functions in terms of various special functions for certain L\'evy process-driven markets where the interest rate is stochastic.
Books on the topic "Price variances"
1
Durlauf, Steven N. Bounds on the variances of specification errors in models with expectations. Cambridge, MA: National Bureau of Economic Research, 1989.
Find full text
2
Campbell, John Y. A variance decomposition for stock returns. London: LSE Financial Markets Group, 1990.
Find full text
3
Campbell, John Y. A variance decomposition for stock returns. Cambridge, MA: National Bureau of Economic Research, 1990.
Find full text
4
Engel, Charles. Some new variance bounds for asset prices. Cambridge, MA: National Bureau of Economic Research, 2004.
Find full text
5
Geert, Bekaert. Conditioning information and variance bounds on pricing kernels. Cambridge, MA: National Bureau of Economic Research, 1999.
Find full text
6
Oomen, Roel C. A. Using high frequency stock market index data to calculate, model & forecast realized return variance. San Domenico: European University Institute, Department of Economics, 2001.
Find full text
7
Campbell, Sean D. A trend and variance decomposition of the rent-price ratio in housing markets. Washington, D.C: Federal Reserve Board, 2006.
Find full text
8
Copeland, Laurence S. Inflation, interest rate risk and the variance of common stock prices. Manchester: Manchester Business School, 1986.
Find full text
9
Allen, D. E. Minimum variance hedge ratios on the Sydney Futures Exchange. Perth, W.A: Edith Cowan University, Faculty of Business, School of Economics and Finance, 1996.
Find full text
10
Engle, R. F. Index-option pricing with stochastic volatility and the value of accurate variance forecasts. Cambridge, MA: National Bureau of Economic Research, 1993.
Find full textBook chapters on the topic "Price variances"
1
Osborne, Martin J., and Ariel Rubinstein. "Monopoly." In Models in Microeconomic Theory, 89–102. 2nd ed. Cambridge, UK: Open Book Publishers, 2023. http://dx.doi.org/10.11647/obp.0362.07.
Full textAbstract:
This chapter studies several variants of a model that fits a very different situation, in which the producer of a single good is the only one serving a market. The variants differ in the type of options the producer can offer potential buyers. In the basic case, the producer can post a price per unit, and each buyer can purchase any amount of the good at that price. In other cases, the producer has other instruments like offering all consumers a set of price-quantity pairs. In each case, every potential buyer chooses the option he most prefers. The producer predicts correctly the buyers’ responses and acts to advance her target (like maximizing profit or increasing production).
2
Privault, Nicolas, and Dichuan Yang. "Variance-GGC Asset Price Models and Their Sensitivity Analysis." In Statistical Methods and Applications in Insurance and Finance, 81–101. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30417-5_3.
Full text
3
Dhankar, Raj S. "Variance Ratio Test, ARIMA Model and Stock Price Behaviour." In India Studies in Business and Economics, 95–112. New Delhi: Springer India, 2019. http://dx.doi.org/10.1007/978-81-322-3950-5_6.
Full text
4
Lachapelle, J. M., and H. I. Maibach. "The Methodology of Prick Testing and Its Variants." In Patch Testing and Prick Testing, 149–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-09215-6_11.
Full text
5
Froeb, Luke M. "Log Spectral Analysis: Variance Components of Asset Prices." In Computational Economics and Finance, 305–29. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4612-2340-5_13.
Full text
6
Resta, Marina. "SOM Variants for the Simulation of Market Price Modeling." In Intelligent Systems Reference Library, 49–67. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21440-5_4.
Full text
7
Lachapelle, Jean-Marie, and Howard I. Maibach. "Methodology of Open (Non-prick) Testing, Prick Testing, and Its Variants." In Patch Testing and Prick Testing, 159–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25492-5_11.
Full text
8
Lachapelle, Jean-Marie, and Howard I. Maibach. "Methodology of Open (Non-prick) Testing, Prick Testing, and Its Variants." In Patch Testing and Prick Testing, 177–91. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27099-5_11.
Full text
9
Kalidindi, Amit Raja, Naga Sudhakar Ramisetty, Srikalpa Sankeerth Kruthiventi, Jayam Sri Harsha Srinivas, and Lekshmi S. Nair. "Comparative Analysis of RNN Variants Performance in Stock Price Prediction." In Advances in Intelligent Systems and Computing, 779–95. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-5443-6_59.
Full text
10
Peng, Jin-Tang, and Chen-Fu Chien. "A Study of Variance of Locational Price in a Deregulated Generation Market." In Multi-Objective Programming and Goal Programming, 383–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-36510-5_55.
Full textConference papers on the topic "Price variances"
1
Melet, Arthur. "Post-Investment Reviews of Oil and Gas Projects: Methodology, Lessons Learnt, and Limitations." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207601-ms.
Full textAbstract:
Abstract Objectives/scope Discuss the analytical framework created by ADNOC for the implementation of post-investment reviews (PIR) of previous capital projects, and present an overview of both the results, the lessons learnt and the limitations of such exercises, based on ADNOC's return of experience on PIRs. Without sharing confidential project information, the article will focus on providing actionable insights on ADNOC's chosen approach for PIRs, including best practices in terms of data and stakeholder management. Methods, procedures, process The overall approach can be summarized as follows: Project choice: what are the tangible criteria to be used to focus PIRs on the capital projects with the highest potential in terms of learning opportunity? Data collection: what are the minimum data requirements to conduct a PIR for an O&G project? Variance analysis: what rules need to be followed to be able to generate two economics models (initial vs updated) that can be compared? Root cause analysis: how to organize the analysis process to explain the identified variances? Results, observations, conclusions PIRs can play an important role in the continuous improvement of O&G companies’ operations at the pre-investment stage, capital investment stage, and operation stage: At the investment stage, a PIR can provide insights into the effectiveness of the decision-making and, specifically, help to identify improvement areas in the valuation (project economics), assumptions, risk management, and decision-making processes. At the execution stage, PIRs can be useful to quantify the impact of project delays and cost overruns on the overall project economics, and associate such variances with the relevant underlying causes. At the operation stage, PIRs be useful to quantify the impact of OPEX, production, and price variances (actual – forecast) on overall project economics, and associate such variances with the relevant underlying causes. Limitations of PIRs Uncertainty on what projects are likely to yield the best learning opportunities. Subjectivity: PIRs are partly subjective, as the results are largely dependent on data availability and methodological choices. Applicability of recommendations and acceptance from key stakeholders
2
Nissanka, Nipunika, and Tilanka Wijesinghe. "REGIONAL RELEVANCY OF THE CIDA PRICE INDICES UNDER THE RESTRICTIONS URGED BY THE COVID-19 PANDEMIC." In The SLIIT International Conference on Engineering and Technology 2022. Faculty of Engineering, SLIIT, 2022. http://dx.doi.org/10.54389/dcgt7296.
Full textAbstract:
CIDA price fluctuation formula and price indices provide considerable relief to the estimators in mitigating the risk due to the fluctuation of the price of construction inputs during project execution. But there is a huge outcry that the CIDA indices does not appropriately reflect the actual fluctuation of market prices especially during the period of pandemic. The aim of this research was to identify the appropriateness of CIDA indices in ascertaining the price fluctuation of construction material prices across the regions especially under the restrictions imposed by the Covid-19 pandemic. The study was limited to analysis the regional behavior of material prices based on the significant materials. Market price of construction materials was collected from suppliers, constructors, and construction professionals who are currently involved in construction projects. The market prices were collected from nine provinces of the country for eight different types of significant materials during the period of pandemic. Collected data were first observed for its behavior within and across the provinces to check the appropriateness to be represented by country wide common indices. This was done through the analysis of variance and through the checking of null hypothesis i.e., “always there is no difference in means between the provincial prices of a given material”. Thereafter the fluctuation of provincial prices of given inputs were compared to the variation of respective CIDA indices with the corresponding time to check the parallelism and correlation. In this research, it has been concluded that, there is a requirement for establishing regional monthly indices for construction inputs. KEYWORDS: CIDA indices, Construction materials, Province, Regional
3
Qian, Li, and David Ben-Arieh. "Joint Pricing and Platform Configuration in Product Family Design With Genetic Algorithm." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86110.
Full textAbstract:
Manufacturers add numerous product variants to address different customer preferences for mass customization. One approach to implement the mass customization is to develop or produce products based on the platform architecture. A platform is a set of common components, modules or parts shared by product variants in one product family. One product variant makes use of the platform as the starting point and then add or remove components to change features of the product. The problem of determining the platform configuration is considered as maximizing the overall profit under the price-dependent demand market environment while satisfying the part assembly constraints. Platform configuration and sale prices are decision variables in the problem. A strategy based on Genetic Algorithm is proposed to solve the illustrating problem involving the product family of cordless drills. Results manifest that the sale price decision could have significant influence on the product family design, e.g. the platform configuration and the profitability of one product family.
4
Tekin, Bilgehan, and Seda Nur Bastak. "The Relationship of Stock Prices and Stock Market Performance Ratios in Companies Trading on Borsa Istanbul: An Application in Companies with the Highest Trading Volume." In International Conference on Eurasian Economies. Eurasian Economists Association, 2021. http://dx.doi.org/10.36880/c13.02599.
Full textAbstract:
In this study, the effect of certain ratios that investors pay attention to on stock prices in Borsa Istanbul is examined. For this purpose, 30 of the stocks with which the investors traded the most were taken as a sample. In the study, 30 companies with the highest average trading volume in the analysis period were selected according to their transactions in Borsa Istanbul. The study covers the period between 2010: 1Q-2019: 4Q. Variables included in the study are stock market price, P/E ratio, trading volume, market to book ratio, beta, free float percentage. In this study, it has been tried to understand at what level the stock market prices of companies' publicly traded stocks are affected by the indicators that emerge as a result of the transactions realized in the stock exchange, rather than the ratios discussed within the scope of financial analysis and ratio analysis, examples of which are very common in the literature. Panel regression analysis was performed in the study. Before proceeding to the panel regression analysis, preliminary tests were carried out and the model was tried to be given its most suitable form. For this purpose, multicollinearity tests, cross section dependency test, second generation unit root tests, varying variance test, panel regression model selection were made. The model created in the last stage was estimated. As a result of the study, it was seen that the Price/Earnings, Transaction Volume, Market Value/Book Value and Beta variables were significantly effective on the stock market prices of the companies' stocks. Among these variables, BETA affects negatively, while other variables affect positively. The variable with the highest effect on the share price is the negative BETA coefficient and the positive direction is the trading volume.
5
Suleman, Shafic, Godfred Kwaku Ennin, Omowumi Iledare, and Constantine Kojo-Mawenena Kudzedzi. "Impact of Crude Oil Price Volatilities on Petroleum Revenue Collection and Allocation in Ghana." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/217257-ms.
Full textAbstract:
Abstract The abundance of resources is a blessing, but the price volatility of those resources is a curse (Luciani, 2011). Price variations and its corresponding impact on petroleum revenues is of great importance to industry players. This study adopted a quantitative approach to analyse secondary data collected from multiple sources including Public Interest and Accountability Committee (PIAC), Bank of Ghana and not limited to the Ministry of Finance to examine the extent to which crude oil fluctuations influence petroleum revenue collection and allocation in Ghana. The main statistical method employed for this research was regression and descriptive analysis. For robustness check, three post estimations were conducted. These are the Cameron and Trivedi test for heteroskedasticity, Ramsey test for omitted variables, and variance inflation factors (VIF). All three postestimation results showed that the regression estimates are robust. The study finds that at a 1% significance level, the Price of Crude Oil (PCO) and the Petroleum Revenues (PR) are statistically significant. This emphasises the crucial influence of oil prices on petroleum revenues to the state. The study also finds that factors, other than oil price, could to an extent affect petroleum revenues collection and allocation. Such includes allocations to the Ghana National Petroleum Corporation, the Annual Budget Funding Amount (ABFA), Ministerial discretions and volumes of crude oil produced and among others. Against these findings, the study recommends that some reforms be made to the PRMA to do away with ministerial discretions on capping the Ghana stabilization fund and also where necessary, consider hedging as a security against unexpected crude oil price falls.
6
Harrant, Manuel, Thomas Nirmaier, Jerome Kirscher, Christoph Grimm, and Georg Pelz. "Monte Carlo based post-silicon verification considering automotive application variances." In 2013 9th Conference on Ph.D. Research in Microelectronics and Electronics (PRIME). IEEE, 2013. http://dx.doi.org/10.1109/prime.2013.6603132.
Full text
7
Zyskowski, Matthew, and Quanyan Zhu. "Price and variance of anarchy in mean-variance cost density-shaping stochastic differential games." In 2013 IEEE 52nd Annual Conference on Decision and Control (CDC). IEEE, 2013. http://dx.doi.org/10.1109/cdc.2013.6760130.
Full text
8
Dias, Rui, Hortense Santos, Paulo Alexandre, Paula Heliodoro, and Cristina Vasco. "RANDOM WALKS AND MARKET EFFICIENCY TESTS: EVIDENCE FOR US AND AFRICAN CAPITAL MARKETS." In 5th International Scientific Conference – EMAN 2021 – Economics and Management: How to Cope With Disrupted Times. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2021. http://dx.doi.org/10.31410/eman.s.p.2021.17.
Full textAbstract:
The 2020 Russia-Saudi Oil Price War was an economic war triggered in March 2020 by Saudi Arabia in response to Russia’s refusal to reduce oil production to keep oil prices at a moderate level. This economic conflict resulted in a sharp drop in the price of oil in 2020, as well as crashes in international markets. In the light of these events, our aim was to test the efficient market hypothesis, in its weak form, in the stock markets of Botswana (BSE), Egypt (EGX 100), Kenya (NSE 20), Moroccan All Shares (MASI), Tunisia (Tunindex), and the MARKET of the USA (DOWJONES INDUSTRIALS), in the period of Septem¬ber 2, 2019 to January 11, 2021. The results therefore support the evidence that the random walk hypoth¬esis is not supported by the financial markets analyzed in this period of global pandemic. The values of variance ratios are lower than the unit, which implies that the yields are autocorrelated in time and, there is reversal to the mean. In order to validate the results, we estimate the model αDFA that shows that the stock markets NSE 20 (0.75), TUNINDEX (0.69), MASI (0.63), EGX 100 (0.64), BSE (0.61), DOW JONES (0.58) show autocorrelation in their profitability, that is, these markets show signs of (in) efficiency, in its weak form, persistence in profitability, validating the results of the variance test by Rankings and Wright Signs. In conclusion we can show that the U.S. stock market has more market efficiency when compared to the African stock markets analyzed. The authors consider that the results achieved are of interest to investors looking for opportunities for portfolio diversification in these regional stock markets.
9
Yaşar, Aysu, and Kenan Terzioğlu. "Long Memory in Exchange Rate Volatility." In International Conference on Eurasian Economies. Eurasian Economists Association, 2021. http://dx.doi.org/10.36880/c13.02560.
Full textAbstract:
Considering rapidly evolving technology and effective markets, wherein information and news are quickly and effectively reflected in financial asset prices, the positions of investors trading in financial markets regarding financial asset prices vary according to the continuous stream of information coming to the market. However, markets are not fully efficient in terms of maintaining a long memory that enables future pricing estimates based on the past market price of the financial asset. Revealing the existence of a long memory structure is essential to the development of monetary policies since exchange rates that tend to return to average exert high resistance. In this study, the exchange rate’s long-range dependence is determined in the scope of the log-periodogram estimator and using a fractional model structure, the average model, and the variance model structure related to the exchange rate between February 22, 2001–March 16, 2020 are examined. In this context, the parameters in the model allow an examination of the long memory process. According to the fractionally integrated exponential generalized autoregressive conditional heteroskedasticity model, it is determined that the effects of shocks in the exchange rate market continue and persist for a long period. Policy suggestions within the scope of exchange rates are evaluated within model outputs.
10
Antoniuk, Kateryna, and Filip Škultéty. "Modification of the of the Viper SD-4 braking system." In Práce a štúdie. University of Žilina, 2023. http://dx.doi.org/10.26552/pas.z.2023.1.02.
Full textAbstract:
The Viper SD-4 is an excellent example of a Light Sport Aircraft (LSA) category of training aeroplanes. It is produced in Slovakia and used in several European countries and also in the United States of America. It is a very high-quality made aircraft, but some of the pilots say that it has one not very convenient component, which is the operation of the brake system. In this article researched how the brake system can be modified based on data from other brake systems used for the LSA category. The result of this research is the possible variants of the anticipated modifications and the analysis of the relevance of such changes.
Reports on the topic "Price variances"
1
Dew-Becker, Ian, Stefano Giglio, Anh Le, and Marius Rodriguez. The Price of Variance Risk. Cambridge, MA: National Bureau of Economic Research, May 2015. http://dx.doi.org/10.3386/w21182.
Full text
2
Galindo, Arturo, and Victoria Nuguer. Fuel-Price Shocks and Inflation in Latin America and the Caribbean. Inter-American Development Bank, March 2023. http://dx.doi.org/10.18235/0004724.
Full textAbstract:
We estimate the impact of fuel-commodity price shocks on inflation and inflation expectations for eight Latin American countries in which monetary policy follows inflation-targeting frameworks. We use Bayesian Vector Autoregressive models (BVARs) and data from 2005 and up to 2022 to quantify these impacts. We find that the fuel-price shocks are significant in all cases and the response ranges between 0.01 and 0.04 percentage points of inflation, following a 1 p.p. shock to fuel prices. A variance decomposition exercise shows that more than 50% of the outburst in inflation that these countries experienced in 2021 and 2022 can be attributed to the shock in global fuel prices. These results are robust to changes in the specification that include additional controls, different commodity price measures, different lag structures, and alternative ordering.
3
Cochrane, John. Explaining the Variance of Price Dividend Ratios. Cambridge, MA: National Bureau of Economic Research, November 1989. http://dx.doi.org/10.3386/w3157.
Full text
4
Engel, Charles. Some New Variance Bounds for Asset Prices. Cambridge, MA: National Bureau of Economic Research, December 2004. http://dx.doi.org/10.3386/w10981.
Full text
5
Beckman, Jayson, and Thomas Hertel. Validating Energy-Oriented CGE Models. GTAP Working Paper, February 2009. http://dx.doi.org/10.21642/gtap.wp54.
Full textAbstract:
Although CGE models have received heavy usage, they are often criticized as being insufficiently validated. Key parameters are often not econometrically estimated, and the performance of the model as a whole is rarely checked against historical outcomes. As a consequence, questions frequently arise as to how much faith one can put in CGE results. In this paper, we employ a novel approach to the validation of a widely utilized global CGE model – GTAP-E. By comparing the variance of model generated petroleum price distributions -- driven by historical demand and supply shocks to the model-- with observed five-year moving average price distributions, we conclude that energy demand in GTAP-E is far too price-elastic over this time frame. After incorporating the latest econometric estimates of energy demand and supply elasticities, we revisit the validation question and find the model to perform more satisfactorily. As a further check, we compare a deterministic global general equilibrium simulation, based on historical realizations over the 2001-2006 period during which petroleum prices rose sharply, along with growing global energy demands. As anticipated by the stochastic simulations, the revised model parameters perform much better than the original GTAP-E parameters in this global, general equilibrium context.
6
Jamilov, Rustam, Hélène Rey, and Ahmed Tahoun. The Anatomy of Cyber Risk. Institute for New Economic Thinking Working Paper Series, May 2023. http://dx.doi.org/10.36687/inetwp206.
Full textAbstract:
This paper employs computational linguistics to introduce a novel text-based measure of firm-level cyber risk exposure based on quarterly earnings conference calls of listed firms. Our quarterly measures are available for more than 13,000 firms from 85 countries over 2002-2021. We document that cyber risk exposure predicts cyber attacks, affects stock returns and profits, and is priced in the equity option market. The cost of option protection against price, variance, and tail risks is greater for more cyber-exposed firms. Cyber risks spill over across firms and persist at the sectoral level. The geography of cyber risk exposure is well approximated by a gravity model extended with cross-border portfolio flows. Back-of-the-envelope calculations suggest that the global cost of cyber risk is over $200 billion per year.
7
Missbach, Leonard, Jan Christoph Steckel, and Adrien Vogt-Schilb. Cash transfers in the context of carbon pricing reforms in Latin America and the Caribbean. Inter-American Development Bank, November 2022. http://dx.doi.org/10.18235/0004568.
Full textAbstract:
One reason carbon prices are difficult to implement is that they might imply high additional costs on poor and vulnerable households. In response, studies often highlight that recycling revenues through cash transfers can render carbon pricing reforms progressive. This neglects that existing cash transfer programs target households from low-income groups often imperfectly and that impacts of a carbon price are heterogeneous within income groups. In this study we analyze the role of existing cash transfer schemes to alleviate distributional effects of carbon pricing in 16 Latin American and Caribbean countries. We find carbon pricing to be regressive in 11 countries, progressive in 5, and show that differences within income groups exceed differences between them. Beyond total household expenditures, car ownership and cooking fuel explain the variance in carbon pricing impacts. We show that households who are most affected by carbon pricing, some of them poor, do not necessarily have access to existing cash transfer programs. Governments aiming to compensate households may broaden coverage of existing cash transfer programs or consider complementing instruments such as in-kind transfers or removing existing distortionary taxes.
8
Fernandez, Andres, Andres Gonzalez, and Diego Rodriguez. Sharing a Ride on the Commodities Roller Coaster: Common Factors in Business Cycles of Emerging Economies. Inter-American Development Bank, December 2015. http://dx.doi.org/10.18235/0011716.
Full textAbstract:
Fluctuations in commodity prices are an important driver of business cycles in small emerging market economies (EMEs). This paper documents how these fluctuations correlate strongly with the business cycle in EMEs. A commodity sector is then embedded into a multi-country EMEs business cycle model where exogenous fluctuations in commodity prices follow a common dynamic factor structure and coexist with other driving forces. The estimated model assigns to commodity shocks 42 percent of the variance in income, of which a considerable part is linked to the common factor. A further amplification mechanism is a spillover effect from commodity prices to risk premia.
9
Monetary Policy Report - January 2022. Banco de la República, March 2022. http://dx.doi.org/10.32468/inf-pol-mont-eng.tr1-2022.
Full textAbstract:
Macroeconomic summary Several factors contributed to an increase in projected inflation on the forecast horizon, keeping it above the target rate. These included inflation in December that surpassed expectations (5.62%), indexation to higher inflation rates for various baskets in the consumer price index (CPI), a significant real increase in the legal minimum wage, persistent external and domestic inflationary supply shocks, and heightened exchange rate pressures. The CPI for foods was affected by the persistence of external and domestic supply shocks and was the most significant contributor to unexpectedly high inflation in the fourth quarter. Price adjustments for fuels and certain utilities can explain the acceleration in inflation for regulated items, which was more significant than anticipated. Prices in the CPI for goods excluding food and regulated items also rose more than expected. This was partly due to a smaller effect on prices from the national government’s VAT-free day than anticipated by the technical staff and more persistent external pressures, including via peso depreciation. By contrast, the CPI for services excluding food and regulated items accelerated less than expected, partly reflecting strong competition in the communications sector. This was the only major CPI basket for which prices increased below the target inflation rate. The technical staff revised its inflation forecast upward in response to certain external shocks (prices, costs, and depreciation) and domestic shocks (e.g., on meat products) that were stronger and more persistent than anticipated in the previous report. Observed inflation and a real increase in the legal minimum wage also exceeded expectations, which would boost inflation by affecting price indexation, labor costs, and inflation expectations. The technical staff now expects year-end headline inflation of 4.3% in 2022 and 3.4% in 2023; core inflation is projected to be 4.5% and 3.6%, respectively. These forecasts consider the lapse of certain price relief measures associated with the COVID-19 health emergency, which would contribute to temporarily keeping inflation above the target on the forecast horizon. It is important to note that these estimates continue to contain a significant degree of uncertainty, mainly related to the development of external and domestic supply shocks and their ultimate effects on prices. Other contributing factors include high price volatility and measurement uncertainty related to the extension of Colombia’s health emergency and tax relief measures (such as the VAT-free days) associated with the Social Investment Law (Ley de Inversión Social). The as-yet uncertain magnitude of the effects of a recent real increase in the legal minimum wage (that was high by historical standards) and high observed and expected inflation, are additional factors weighing on the overall uncertainty of the estimates in this report. The size of excess productive capacity remaining in the economy and the degree to which it is closing are also uncertain, as the evolution of the pandemic continues to represent a significant forecast risk. margin, could be less dynamic than expected. And the normalization of monetary policy in the United States could come more quickly than projected in this report, which could negatively affect international financing costs. Finally, there remains a significant degree of uncertainty related to the duration of supply chocks and the degree to which macroeconomic and political conditions could negatively affect the recovery in investment. The technical staff revised its GDP growth projection for 2022 from 4.7% to 4.3% (Graph 1.3). This revision accounts for the likelihood that a larger portion of the recent positive dynamic in private consumption would be transitory than previously expected. This estimate also contemplates less dynamic investment behavior than forecast in the previous report amid less favorable financial conditions and a highly uncertain investment environment. Third-quarter GDP growth (12.9%), which was similar to projections from the October report, and the fourth-quarter growth forecast (8.7%) reflect a positive consumption trend, which has been revised upward. This dynamic has been driven by both public and private spending. Investment growth, meanwhile, has been weaker than forecast. Available fourth-quarter data suggest that consumption spending for the period would have exceeded estimates from October, thanks to three consecutive months that included VAT-free days, a relatively low COVID-19 caseload, and mobility indicators similar to their pre-pandemic levels. By contrast, the most recently available figures on new housing developments and machinery and equipment imports suggest that investment, while continuing to rise, is growing at a slower rate than anticipated in the previous report. The trade deficit is expected to have widened, as imports would have grown at a high level and outpaced exports. Given the above, the technical staff now expects fourth-quarter economic growth of 8.7%, with overall growth for 2021 of 9.9%. Several factors should continue to contribute to output recovery in 2022, though some of these may be less significant than previously forecast. International financial conditions are expected to be less favorable, though external demand should continue to recover and terms of trade continue to increase amid higher projected oil prices. Lower unemployment rates and subsequent positive effects on household income, despite increased inflation, would also boost output recovery, as would progress in the national vaccination campaign. The technical staff expects that the conditions that have favored recent high levels of consumption would be, in large part, transitory. Consumption spending is expected to grow at a slower rate in 2022. Gross fixed capital formation (GFCF) would continue to recover, approaching its pre-pandemic level, though at a slower rate than anticipated in the previous report. This would be due to lower observed GFCF levels and the potential impact of political and fiscal uncertainty. Meanwhile, the policy interest rate would be less expansionary as the process of monetary policy normalization continues. Given the above, growth in 2022 is forecast to decelerate to 4.3% (previously 4.7%). In 2023, that figure (3.1%) is projected to converge to levels closer to the potential growth rate. In this case, excess productive capacity would be expected to tighten at a similar rate as projected in the previous report. The trade deficit would tighten more than previously projected on the forecast horizon, due to expectations of an improved export dynamic and moderation in imports. The growth forecast for 2022 considers a low basis of comparison from the first half of 2021. However, there remain significant downside risks to this forecast. The current projection does not, for example, account for any additional effects on economic activity resulting from further waves of COVID-19. High private consumption levels, which have already surpassed pre-pandemic levels by a large margin, could be less dynamic than expected. And the normalization of monetary policy in the United States could come more quickly than projected in this report, which could negatively affect international financing costs. Finally, there remains a significant degree of uncertainty related to the duration of supply chocks and the degree to which macroeconomic and political conditions could negatively affect the recovery in investment. External demand for Colombian goods and services should continue to recover amid significant global inflation pressures, high oil prices, and less favorable international financial conditions than those estimated in October. Economic activity among Colombia’s major trade partners recovered in 2021 amid countries reopening and ample international liquidity. However, that growth has been somewhat restricted by global supply chain disruptions and new outbreaks of COVID-19. The technical staff has revised its growth forecast for Colombia’s main trade partners from 6.3% to 6.9% for 2021, and from 3.4% to 3.3% for 2022; trade partner economies are expected to grow 2.6% in 2023. Colombia’s annual terms of trade increased in 2021, largely on higher oil, coffee, and coal prices. This improvement came despite increased prices for goods and services imports. The expected oil price trajectory has been revised upward, partly to supply restrictions and lagging investment in the sector that would offset reduced growth forecasts in some major economies. Elevated freight and raw materials costs and supply chain disruptions continue to affect global goods production, and have led to increases in global prices. Coupled with the recovery in global demand, this has put upward pressure on external inflation. Several emerging market economies have continued to normalize monetary policy in this context. Meanwhile, in the United States, the Federal Reserve has anticipated an end to its asset buying program. U.S. inflation in December (7.0%) was again surprisingly high and market average inflation forecasts for 2022 have increased. The Fed is expected to increase its policy rate during the first quarter of 2022, with quarterly increases anticipated over the rest of the year. For its part, Colombia’s sovereign risk premium has increased and is forecast to remain on a higher path, to levels above the 15-year-average, on the forecast horizon. This would be partly due to the effects of a less expansionary monetary policy in the United States and the accumulation of macroeconomic imbalances in Colombia. Given the above, international financial conditions are projected to be less favorable than anticipated in the October report. The increase in Colombia’s external financing costs could be more significant if upward pressures on inflation in the United States persist and monetary policy is normalized more quickly than contemplated in this report. As detailed in Section 2.3, uncertainty surrounding international financial conditions continues to be unusually high. Along with other considerations, recent concerns over the potential effects of new COVID-19 variants, the persistence of global supply chain disruptions, energy crises in certain countries, growing geopolitical tensions, and a more significant deceleration in China are all factors underlying this uncertainty. The changing macroeconomic environment toward greater inflation and unanchoring risks on inflation expectations imply a reduction in the space available for monetary policy stimulus. Recovery in domestic demand and a reduction in excess productive capacity have come in line with the technical staff’s expectations from the October report. Some upside risks to inflation have materialized, while medium-term inflation expectations have increased and are above the 3% target. Monetary policy remains expansionary. Significant global inflationary pressures and the unexpected increase in the CPI in December point to more persistent effects from recent supply shocks. Core inflation is trending upward, but remains below the 3% target. Headline and core inflation projections have increased on the forecast horizon and are above the target rate through the end of 2023. Meanwhile, the expected dynamism of domestic demand would be in line with low levels of excess productive capacity. An accumulation of macroeconomic imbalances in Colombia and the increased likelihood of a faster normalization of monetary policy in the United States would put upward pressure on sovereign risk perceptions in a more persistent manner, with implications for the exchange rate and the natural rate of interest. Persistent disruptions to international supply chains, a high real increase in the legal minimum wage, and the indexation of various baskets in the CPI to higher inflation rates could affect price expectations and push inflation above the target more persistently. These factors suggest that the space to maintain monetary stimulus has continued to diminish, though monetary policy remains expansionary. 1.2 Monetary policy decision Banco de la República’s board of directors (BDBR) in its meetings in December 2021 and January 2022 voted to continue normalizing monetary policy. The BDBR voted by a majority in these two meetings to increase the benchmark interest rate by 50 and 100 basis points, respectively, bringing the policy rate to 4.0%.
10
Asian Development Outlook 2021 Update: Transforming Agriculture in Asia. Asian Development Bank, September 2021. http://dx.doi.org/10.22617/fls210352-3.
Full textAbstract:
This report forecasts growth in developing Asia of 7.1% in 2021 and 5.4% in 2022 in an uneven recovery caused by divergent growth paths. Its theme chapter explores sustainable agriculture. Growth forecasts are revised up for East Asia and Central Asia from the projections made in April, but down for South Asia, Southeast Asia, and the Pacific. This reflects differences in vaccination progress and control of domestic COVID-19 outbreaks but also other factors, including rising commodity prices and depressed tourism. Inflation is expected to remain under control. The main risks to the economic outlook come from the COVID-19 pandemic, including the emergence of new variants, slower-than-expected vaccine rollouts, and waning vaccine effectiveness. Sustainable food production and agricultural systems that are resilient to climate change will be crucial for developing Asia. To transform agriculture in the region, its economies must tackle challenges from changing consumer demand, changing demographics, and a changing and more fragile environment.