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Ahmadi, Ahmadi, and R. Adisetiawan. "Multivariate Time Series in Macroeconomics." Eksis: Jurnal Ilmiah Ekonomi dan Bisnis 11, no. 2 (November 23, 2020): 151. http://dx.doi.org/10.33087/eksis.v11i2.209.
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Gold is one of the most popular commodities and investment alternatives. Gold prices are thought to be influenced by several other factors such as the US Dollar, oil price, inflation rate, and stock exchange so that gold price modeling is not only influenced by its own value. This research was conducted to determine the best forecasting model and to find out what factors influence the price of gold. This research modeled the price of gold in a multivariate and reviewed the univariate modeling that will be used as a comparison model of multivariate modeling. Univariate modeling is done using ARIMA model where the modeling results state that gold price fluctuations as white noise. Multivariate gold price modeling is done using Vector Error Correction Model with gold, oil, US Dollar and Dow Jones indices, and inflation rate as predictors. The results showed that the VECM model has been able to model the gold price well and all the factors studied influenced the gold price. The US dollar and oil prices are negatively correlated with gold prices, while the inflation rate is positively correlated with gold prices. The Dow Jones index was positively correlated with gold prices in just two periods.
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Yao, Jun, and Harmen Oppewal. "Unit pricing matters more when consumers are under time pressure." European Journal of Marketing 50, no. 5/6 (May 9, 2016): 1094–114. http://dx.doi.org/10.1108/ejm-03-2015-0122.
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Purpose This paper aims to first investigate how unit pricing affects consumers’ grocery purchase decisions and perceptions of the shopping task’s information load. The second goal is to test how time pressure enhances the behavioural and perceptual effects of displaying unit prices. Design/methodology/approach Two on-line experiments were conducted using national samples of shoppers. In Study 1, participants indicated their choices and perceptions in an inter-brand shopping scenario where prepackaged products have conflicting positions on retail price and unit price. In Study 2, participants conducted the same shopping task but now under a condition of time pressure. Findings Study 1 shows that unit pricing shifts consumer choices towards the lower unit priced options and improves their perceptions of task information load. Study 2 shows that when consumers are under time pressure, unit pricing shows stronger effects on choices but not on perceptions. Research limitations/implications The study comprised a fairly homogenous set of low involvement categories and relatively small assortments in a hypothetical purchase setting. Exploration of the role of unit pricing in more complex and more realistic purchase environments pose suitable avenues for future research. Practical implications This study shows that consumers benefit from unit pricing because it makes it easier for them to find the lower unit priced items and to more quickly complete their shopping task. Retailers will benefit from increased customer satisfaction and possibly an improved store image. Social implications The study shows that consumers generally benefit from the presence of unit pricing and that unit price information does not create harmful effects in terms of increasing their information load. Originality/value This study uses a specifically designed and controlled but nevertheless realistic grocery choice task to study the effects of unit pricing in an inter-brand context where there are only small differences in size and price. The study contributes to the literature by showing that in such conditions, unit prices help consumers compare the economic losses associated with product options. Their heuristic role is more pronounced when consumers are under time pressure. The study shows that consumers generally benefit from the presence of unit prices.
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Curry, David J., and Peter C. Riesz. "Prices and Price/Quality Relationships: A Longitudinal Analysis." Journal of Marketing 52, no. 1 (January 1988): 36–51. http://dx.doi.org/10.1177/002224298805200104.
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Though price and quality are recognized as important tactical and strategic variables for a marketing manager, few empirical data are available on the behavior of price or the correspondence between price and quality over time. The authors report results for three hypotheses derived from product life cycle theory, dynamic pricing policy, and economic information theory about price trends, price convergence, and the correspondence between price and quality among brands in 62 durable product forms. Results strongly confirm the hypotheses that prices converge as well as decrease in real terms. The decline in price variation apparently results from a narrowing of prices by all relevant competitors. Brands entering or exiting a category counterbalance one another and are nearly as likely to be priced below as above a category mean. Reduced correspondence between price and quality levels over time suggests that as pricing flexibility declines, competition may occur in the form of promotional expenditures rather than relative quality improvements. Implications of these findings for marketing strategy and consumer welfare are discussed.
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Doucouliagos, Chris. "Price exhaustion and number preference: time and price confluence in Australian stock prices." European Journal of Finance 11, no. 3 (June 2005): 207–21. http://dx.doi.org/10.1080/1351847042000254194.
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Chen, Xi, and Michael Funke. "Real-Time Warning Signs of Emerging and Collapsing Chinese House Price Bubbles." National Institute Economic Review 223 (February 2013): R39—R48. http://dx.doi.org/10.1177/002795011322300105.
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The recent increase in Chinese house prices has led to concerns that China is vulnerable to asset price shocks. In this paper, we apply recently developed recursive unit root tests to spot the beginning and the end of potential speculative bubbles in Chinese house price cycles. Overall, we find that except for 2009–10 actual house prices are not significantly disconnected from fundamentals. Thus, the evidence for speculative house price bubbles in China is in general weak.
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Michaillat, Pascal, and Emmanuel Saez. "Aggregate Demand, Idle Time, and Unemployment *." Quarterly Journal of Economics 130, no. 2 (February 8, 2015): 507–69. http://dx.doi.org/10.1093/qje/qjv006.
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Abstract This article develops a model of unemployment fluctuations. The model keeps the architecture of the general-disequilibrium model of Barro and Grossman (1971) but takes a matching approach to the labor and product markets instead of a disequilibrium approach. On the product and labor markets, both price and tightness adjust to equalize supply and demand. Since there are two equilibrium variables but only one equilibrium condition on each market, a price mechanism is needed to select an equilibrium. We focus on two polar mechanisms: fixed prices and competitive prices. When prices are fixed, aggregate demand affects unemployment as follows. An increase in aggregate demand leads firms to find more customers. This reduces the idle time of their employees and thus increases their labor demand. This in turn reduces unemployment. We combine the predictions of the model and empirical measures of product market tightness, labor market tightness, output, and employment to assess the sources of labor market fluctuations in the United States. First, we find that product market tightness and labor market tightness fluctuate a lot, which implies that the fixed-price equilibrium describes the data better than the competitive-price equilibrium. Next, we find that labor market tightness and employment are positively correlated, which suggests that the labor market fluctuations are mostly due to labor demand shocks and not to labor supply or mismatch shocks. Last, we find that product market tightness and output are positively correlated, which suggests that the labor demand shocks mostly reflect aggregate demand shocks and not technology shocks.
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Zhao, Lu-Tao, Shun-Gang Wang, and Zhi-Gang Zhang. "Oil Price Forecasting Using a Time-Varying Approach." Energies 13, no. 6 (March 17, 2020): 1403. http://dx.doi.org/10.3390/en13061403.
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The international crude oil market plays an important role in the global economy. This paper uses a variable time window and the polynomial decomposition method to define the trend term of time series and proposes a crude oil price forecasting method based on time-varying trend decomposition to describe the changes in trends over time and forecast crude oil prices. First, to characterize the time-varying characteristics of crude oil price trends, the basic concepts of post-position intervals, pre-position intervals and time-varying windows are defined. Second, a crude oil price series is decomposed with a time-varying window to determine the best fitting results. The parameter vector is used as a time-varying trend. Then, to quantitatively describe the continuation of the time-varying trend, the concept of the trend threshold is defined, and a corresponding algorithm for selecting the trend threshold is given. Finally, through the predicted trend thresholds, the historical reference data are selected, and the time-varying trend is combined to complete the crude oil price forecast. Through empirical research, it is found that the time-varying trend prediction model proposed in this paper achieves a better prediction than several common models. These results can provide suggestions and references for investors in the international crude oil market to understand the trends of oil prices and improve their investment decisions.
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Zhang, Jian Hua, Fan Tao Kong, Jian Zhai Wu, Meng Shuai Zhu, Ke Xu, and Jia Jia Liu. "Tomato Prices Time Series Prediction Model Based on Wavelet Neural Network." Applied Mechanics and Materials 644-650 (September 2014): 2636–40. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2636.
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Accurate prediction of agricultural prices is beneficial to correctly guide the circulation of agricultural products and agricultural production and realize the equilibrium of supply and demand of agricultural area. On the basis of wavelet neural network, this paper, choosing tomato prices as study object, tomato retail price data from ten collection sites in Hebei province from January, 1st, 2013 to December, 30th, 2013 as samples, builds the tomato price time series prediction model to test price model. As the results show, model prediction error rate is less than 0.01, and the correlation (R2) of predicted value and actual value is 0.908, showing that the model could accurately predict tomatoes price movements. The establishment of the model will provide technical support for tomato market monitoring and early warning and references for related policies.
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Bulfone, Liliana. "High prices for generics in Australia — more competition might help." Australian Health Review 33, no. 2 (2009): 200. http://dx.doi.org/10.1071/ah090200.
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It is commonly believed that dispensed prices of medicines in Australia are substantially lower than those in other developed countries, particularly the US. This article reports the results of an analysis comparing dispensed prices for the most commonly prescribed and the highest cost items in Australia with dispensed prices in the US. Although a large majority of items are less expensive in Australia than in the US, Australian prices are higher for a substantial number of products, particularly generic drugs. This article examines various policies affecting the pricing of generics in Australia. It is postulated that the main cause for higher prices for a substantial number of generic products is the lack of price competition. This results from government policy which ensures that a price reduction by one company is communicated immediately to all competitors in that market along with an invitation to match the reduced price. The dominant strategy for all suppliers is to only reduce their price in response to a reduction in price by a competitor. The result is a lack of differentiation in pricing across brands of a medicine on the Schedule of Pharmaceutical Benefits. The government could improve the structure of the generics market and encourage greater competition by ceasing to disclose competitor firms? offers to other competitors. The government could conduct pricing reviews of each generic product relatively infrequently (eg, only once annually or every 18 months). At the time of the pricing review, the government would request confidential offers on price for a generic from all players in the market. Brands should then all be listed under the Pharmaceutical Benefits Scheme (PBS) at the offered price. Prices offered by the individual supplier would apply until the next pricing review. The PBS would continue to subsidise up to the price of the lowest priced brand, with brand premiums applying to all brands priced higher than the benchmark price. Such an approach would provide opportunity for players in the market to capture market share by being the lowest priced brand.
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Guan, Xiaodong, Haishaerjiang Wushouer, Mingchun Yang, Sheng Han, Luwen Shi, Dennis Ross-Degnan, and Anita Katharina Wagner. "Influence of government price regulation and deregulation on the price of antineoplastic medications in China: a controlled interrupted time series study." BMJ Open 9, no. 11 (November 2019): e031658. http://dx.doi.org/10.1136/bmjopen-2019-031658.
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BackgroundIn October 2012, the Chinese government established maximum retail prices for specific products, including 30 antineoplastic medications. Three years later, in June 2015, the government abolished price regulation for most medications, including all antineoplastic medications. This study examined the impacts of regulation and subsequent deregulation of prices of antineoplastic medications in China.MethodsUsing hospital procurement data and an interrupted time series with comparison series design, we examined the impacts of the policy changes on relative purchase prices (Laspeyres price index) and volumes of and spending on 52 antineoplastic medications in 699 hospitals. We identified three policy periods: prior to the initial price regulation (October 2011 to September 2012); during price regulation (October 2012 to June 2015); and after price deregulation (July 2015 to June 2016).ResultsDuring government price regulation, compared with price-unregulated cancer medications (n=22, mostly newer targeted products), the relative price of price-regulated medications (n=30, mostly chemotherapeutic products) decreased significantly (β=−0.081, p<0.001). After the government price deregulation, no significant price change occurred. Neither government price regulation nor deregulation had a significant impact on average volumes of or average spending on all antineoplastic medications immediately after the policy changes or in the longer term (p>0.05).ConclusionCompared with unregulated antineoplastics, the prices of regulated antineoplastic medications decreased after setting price caps and did not increase after deregulation. To control the rapid growth of oncology medication expenditures, more effective measures than price regulation through price caps for traditional chemotherapy are needed.
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Avino, Davide, Emese Lazar, and Simone Varotto. "Time varying price discovery." Economics Letters 126 (January 2015): 18–21. http://dx.doi.org/10.1016/j.econlet.2014.09.030.
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Gričar, Sergej, and Štefan Bojnec. "Prices of short-stay accommodation: time series of a eurozone country." International Journal of Contemporary Hospitality Management 31, no. 12 (December 9, 2019): 4500–4519. http://dx.doi.org/10.1108/ijchm-01-2019-0091.
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Purpose This paper aims to provide a reliable statistical model for time-series prices of short-stay accommodation and overnight stays in a eurozone country. Design/methodology/approach Exploiting the unit root feature, the cointegrated vector autoregressive model solves the problem of misspecification. Subsequently, variables are modelled for a long-run equilibrium with included deterministic variables. Findings The empirical results confirmed that overnight stays for foreign tourists were positively associated with the prices of short-stay accommodation. Research limitations/implications The major limitation lies in the data vector and its time horizon; its extension could provide a more specific view. Practical implications Findings can assist practitioners and hotel executives by providing the information and rationale for adopting seasonal volatility pricing. Structural breaks in price time-series have practical implications for setting seasonal-pricing schemes. Tourists could benefit either from greater price stability or from differentiated seasonal prices, which are important in the promotion of the price attractiveness of the tourist destination. Originality/value The originality of the paper lies in the applied unit root econometrics for tourism price time-series modelling and the prediction of short-stay accommodation prices.
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SAHA, SUBRATA, and MANJUSRI BASU. "INTEGRATED DYNAMIC PRICING FOR SEASONAL PRODUCTS WITH PRICE AND TIME DEPENDENT DEMAND." Asia-Pacific Journal of Operational Research 27, no. 03 (June 2010): 393–410. http://dx.doi.org/10.1142/s0217595910002764.
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In this paper, an inventory model for deteriorating items with ramp-type time and price dependent consumption rate over a finite planning horizon is considered. In contrast to the traditional deterministic inventory model with static price over the entire planning horizon or fixed number of price changes over the finite time horizon, an alternative model is derived in which prices and the number of price change are to be decision variables. We show that the total profit function is concave. With the concavity, a solution procedure is presented to determine optimal prices, optimal number of pricing cycles and optimal lot size and optimal profit. We illustrate the model with numerical examples. Sensitivity analysis of the model is also carried out.
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Björklund, Kicki, John Alex Dadzie, and Mats Wilhelmsson. "Offer price, transaction price and time‐on‐market." Property Management 24, no. 4 (August 2006): 415–26. http://dx.doi.org/10.1108/02637470610671631.
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Hill, Robert J. "Constructing Price Indexes across Space and Time: The Case of the European Union." American Economic Review 94, no. 5 (November 1, 2004): 1379–410. http://dx.doi.org/10.1257/0002828043052178.
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This paper considers the problem of how to construct and reconcile price indexes across space and time. A general taxonomy of panel price index methods, containing four broad classes, is proposed, along with five criteria for discriminating between them. Methods from each of the four classes are then used to compute spatial and temporal price indexes for the 15 countries of the European Union (EU) over the period 1995–2000. Using these panel price indexes, I test whether or not price levels and relative prices converged across the EU over this period.
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OSTROVSKY, DMITRY. "BLACK–SCHOLES–MERTON IN RANDOM TIME: A NEW STOCHASTIC VOLATILITY MODEL WITH PATH DEPENDENCE." International Journal of Theoretical and Applied Finance 10, no. 05 (August 2007): 847–72. http://dx.doi.org/10.1142/s0219024907004421.
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A generalized Black–Scholes–Merton economy is introduced. The economy is driven by Brownian motion in random time that is taken to be continuous and independent of Brownian motion. European options are priced by the no-arbitrage principle as conditional averages of their classical values over the random time to maturity. The prices are path dependent in general unless the time derivative of the random time is Markovian. An explicit self-financing hedging strategy is shown to replicate all European options by dynamically trading in stock, money market, and digital calls on realized variance. The notion of the average price is introduced, and the average price of the call option is shown to be greater than the corresponding Black–Scholes price for all deep in- and out-of-the-money options under appropriate sufficient conditions. The model is implemented in limit lognormal random time. The significance of its multiscaling law is explained theoretically and verified numerically to be a determining factor of the term structure of implied volatility.
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Shabanov, Timofey Yu. "Time deals: optimization of lag." Vegetable crops of Russia, no. 5 (November 7, 2019): 94–97. http://dx.doi.org/10.18619/2072-9146-2019-5-94-97.
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Relevance. In many ways, a successful purchase and sale transaction is determined by the time it takes to complete it. The search for the best deal time is linked to the optimization of the time lag. The purpose of the study is to optimize the time lag of the agricultural market.Methods. This article considered a role of time in business processes for Russian potato market of producer into period 1998-2018.Results. There was trend of annual reduction about 365 thousand tons (1.2...1.7% of total) per year supply of potatoes on Russian domestic market of producers. Some priority of quantity vs price of producer been revealed. There was inverse proportional function between producers` prices and quantity of potatoes. That is than worse harvest that higher producer`s price. Reducing a supply of potatoes 1 million tons from agricultural market perhaps increase in producer prices by $ 8.5 / t (4...5% on average). Offered concept and hypothesis about linearization of equilibrium of market processes into conditions of time shifts of dynamics their parameters were confirmed. There verified assumption about existence of inter-interval time optimum which this linearization maximal business processes. In course of correlation analysis of dynamics of annual indicators of potato market, it revealed month May of current period as optimal time of producer's offers with price restrictions and diminishing returns, and month September with quantity restrictions and increasing returns. If fixation of producer`s prices situation of deals May more likely, in case of crop failure (limited quantity) in September.
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Maia, Emanuella Gomes, Camila Mendes dos Passos, Renata Bertazzi Levy, Ana Paula Bortoletto Martins, Laís Amaral Mais, and Rafael Moreira Claro. "What to expect from the price of healthy and unhealthy foods over time? The case from Brazil." Public Health Nutrition 23, no. 4 (January 15, 2020): 579–88. http://dx.doi.org/10.1017/s1368980019003586.
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AbstractObjective:To measure change in price of food groups over time (1995–2030) in Brazil, considering the Brazilian Dietary Guidelines’ recommendations.Design:Data from the Household Budget Survey (2008–2009 HBS) and the National System of Consumer Price Indexes (NSCPI) were used to create a data set containing monthly prices for the foods and beverages most consumed in the country (n 102), from January 1995 to December 2017. Data on price of foods and beverages from 2008–2009 HBS (referring to January 2009) were used to calculate real price over time using the monthly variation in prices from NSCPI. All prices were deflated to December 2017. Foods and beverages were classified following the Brazilian Dietary Guidelines’ recommendations. The monthly price for each food group and subgroup was used to analyse changes in prices from 1995 to 2017 and to forecast prices up to 2030 using fractional polynomial models.Setting:Brazil.Participants:National estimates of foods and beverages purchased for Brazil.Results:In 1995, ultra-processed foods were the most expensive group (R$ 6·51/kg), followed by processed foods (R$ 6·44/kg), then unprocessed or minimally processed foods and culinary ingredients (R$ 3·45/kg). Since the early 2000s, the price of ultra-processed foods underwent successive reductions, becoming cheaper than processed foods and reducing the distance between it and the price of the other group. Forecasts indicate that unhealthy foods will become cheaper than healthy foods in 2026.Conclusions:Food prices in Brazil have changed unfavourably considering the Brazilian Dietary Guidelines’ recommendations. This may imply a decrease in the quality of the population’s diet.
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HULT, HENRIK, FILIP LINDSKOG, and JOHAN NYKVIST. "A SIMPLE TIME-CONSISTENT MODEL FOR THE FORWARD DENSITY PROCESS." International Journal of Theoretical and Applied Finance 16, no. 08 (December 2013): 1350048. http://dx.doi.org/10.1142/s0219024913500489.
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In this paper, a simple model for the evolution of the forward density of the future value of an asset is proposed. The model allows for a straightforward initial calibration to option prices and has dynamics that are consistent with empirical findings from option price data. The model is constructed with the aim of being both simple and realistic, and avoid the need for frequent re-calibration. The model prices of n options and a forward contract are expressed as time-varying functions of an (n + 1)-dimensional Brownian motion and it is investigated how the Brownian trajectory can be determined from the trajectories of the price processes. An approach based on particle filtering is presented for determining the location of the driving Brownian motion from option prices observed in discrete time. A simulation study and an empirical study of call options on the S&P 500 index illustrate that the model provides a good fit to option price data.
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Mohd Azman, Nur Azrina, Md Pauzi Abdullah, Mohammad Yusri Hassan, Dalila Mat Said, Faridah Hussin, Norzanah Rosmin, and Siti Maherah Hussin. "Impact of Different Time of Use Electricity Pricing Structure on Residential Consumer." Indonesian Journal of Electrical Engineering and Computer Science 10, no. 3 (June 1, 2018): 1053. http://dx.doi.org/10.11591/ijeecs.v10.i3.pp1053-1060.
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<span>Load profile for residential users is different from commercial users where peak load occurs outside of work hours compared to working hours. Consequently, the Time of Use-based electricity price must be different not only in terms of price, but also in terms of time block structure. This paper examines the impacts of different TOU structures on TOU prices and load profiles of residential consumer. Four TOU structures are tested on the real load profile for a selected residential consumer area in Malaysia. Two elasticity factors are used for each structure to represent two different groups of users, a group that responds highly to price changes and a group that does not. The TOU price set for each structure is determined optimally subject to the following constraints; the price difference between the TOU and a fixed price per hour should be minimized and the amount of difference between price increase and price drop should be equal. From the analysis, the TOU structure with 12-time blocks provides better price signals and peak load reduction.</span>
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Niyimbanira, Ferdinand. "Fuel price and exchange rate dynamics in South Africa: A time series analysis." Corporate Ownership and Control 12, no. 4 (2015): 185–93. http://dx.doi.org/10.22495/cocv12i4c1p2.
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This paper empirically examined the relationship between fuel price and exchange rate in South Africa. Monthly data spanning over the period of January 2001 to December 2013 was used while adopting the cointegration method. The Augumented Dickey Fuller (ADF) test showed that all variables (Fuel Price, Exchange rate and New Vehicle sales) became stationary after the first difference. The results from Johansen cointegration test indicated no cointegrating equation, indicating that series were not cointegrated.The findings show that fuel price is affected by at least its two previous month prices. Both explanatory variable coefficients (0.541228 and -0.368649), show that fuel price will be increased by 20 cents Rand due to its previous two month prices. The results from impulsive test confirmed VAR test results. This paper provided evidence that there was a causal link from the exchange rates to petrol price during last one sub-period. The implication therefore is that in South Africa an increase of the fuel price is a response to the Rand value fluctuations ceteris paribus. Based on the findings of the study, policy implications and suggestion for future research are made.
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Dewi, Syanti, and Ishak Ramli. "OPSI SAHAM PADA PASAR MODAL DI INDONESIA (STUDI PASAR OPSI SAAT PASAR OPSI MASIH BERLANGSUNG DI BURSA EFEK INDONESIA)." Jurnal Muara Ilmu Ekonomi dan Bisnis 2, no. 2 (March 28, 2019): 300. http://dx.doi.org/10.24912/jmieb.v2i2.1001.
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Stock option exchange market is not working anymore in the Indonesian Stock Exchange, using the data option exchange market for the running period 2007-2008, we analyzed the effect of stock price, strike price, time to maturity, volatility and risk- free interest rate on the stock option’s price of listed stock call or put option trading at the Indonesian Stock Exchange during 2007-2008. The results found that the stock price, strike price, time to maturity, volatility and risk-free interest rate are positive significantly affecting the stock option price either the buying option price or the selling option price in Indonesia Stock Exchange 2007-2008 period. While there were no variables that significantly affected the call option during the periode 2007-2008, furthermore stock prices and strike prices significantly affected the put option prices. Time to maturity, Volatility, and risk free interest rate did not significantly affect the put option prices.That is why the stock option exchange market stop since the investor were not sure to the stock option price versus the risk of the volatility, time to maturity, and riskfree rate.
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Jiang, Chun, Yi-Fan Wu, Xiao-Lin Li, and Xin Li. "Time-frequency Connectedness between Coal Market Prices, New Energy Stock Prices and CO2 Emissions Trading Prices in China." Sustainability 12, no. 7 (April 2, 2020): 2823. http://dx.doi.org/10.3390/su12072823.
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This paper aims to examine whether there is inherent dynamic connectedness among coal market prices, new energy stock prices and carbon emission trading (CET) prices in China under time- and frequency-varying perspectives. For this purpose, we apply a novel wavelet method proposed by Aguiar-Conraria et al. (2018). Specifically, utilizing the single wavelet power spectrum, the multiple wavelet coherency, the partial wavelet coherency, also combined with the partial phase difference and the partial wavelet gains, this paper discovers the time-frequency interaction between three markets. The empirical results show that the connectedness between the CET market price and the coal price is frequency-varying and mainly occur in the lower and higher frequency bands, while the connectedness between the CET market price and the new energy stock price mainly happen in the middle and lower frequency bands. In the high-frequency domain, the CET market price is mainly affected by the coal price, while the CET market price is dominated by the new energy stock price in the middle frequency. These uncovered frequency-varying characteristics among these markets in this study could provide several implications. Main participants in these markets, such as polluting industries, governments and financial actors, should pay close attention to the connectedness under different frequencies, in order to realize their goal of the production, the policymaking, and the investment.
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Shapiro, Stephen L., and Joris Drayer. "A New Age of Demand-Based Pricing: An Examination of Dynamic Ticket Pricing and Secondary Market Prices in Major League Baseball." Journal of Sport Management 26, no. 6 (November 2012): 532–46. http://dx.doi.org/10.1123/jsm.26.6.532.
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In 2010, the San Francisco Giants became the first professional team to implement a comprehensive demand-based ticket pricing strategy called dynamic ticket pricing (DTP). In an effort to understand DTP as a price setting strategy, the current investigation explored Giants’ ticket prices during the 2010 season. First, the relationship between fixed ticket prices, dynamic ticket prices, and secondary market ticket prices for comparable seats were examined. In addition, seat location and price changes over time were examined to identify potential effects on ticket price in the primary and secondary market. Giants’ ticket price data were collected for various games throughout the 2010 season. A purposive selection of 12 games, which included (N= 1,316) ticket price observations, were chosen in an effort to include a multitude of game settings. Two ANOVA models were developed to examine price differences based on pricing structure, market, section, and time. Findings showed significant differences between fixed ticket prices, dynamic ticket prices, and secondary market ticket prices, with fixed ticket prices on the low end and secondary market ticket prices on the high end of the pricing spectrum. Furthermore, time was found to have a significant influence on ticket price; however, the influence of time varied by market and seat location. These findings are discussed and both theoretical and practical implications are considered.
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Melching, Konstantin, and Tristan Nguyen. "On the Impact of Dividend Payments on Stock Prices - an Empirical Analysis of the German Stock Market." Studies in Business and Economics 16, no. 1 (April 1, 2021): 255–69. http://dx.doi.org/10.2478/sbe-2021-0020.
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Abstract This paper examines the relation between dividend payments and stock prices of all firms in the German prime standard DAX 30 in the time period from 2012 to 2019. The irrelevance theory introduced by Miller and Modigliani states that dividend payments must not have an impact on stock prices in a perfect market. In contrast, the signaling theory and the dividend puzzle indicate that dividend payments are likely to have a profound impact on the stock price. According to our findings the ex-dividend decrease of stock prices was significantly smaller than the dividend payment. Nevertheless, the results support the impact of the dividend payment on the share price. Firstly, the existence of the ex-dividend markdown is a proof that dividend payments cause share price losses. Secondly, the study explains in particular that high dividend payments result in high share prices over the examined period. Thirdly, our analysis demonstrates a positive correlation between the dividend and the stock price development according to the signaling theory. Considering the above- mentioned results, we can conclude that the share price of a company is highly affected by the decision making of the company regarding the dividend policy.
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Nilsen, Øivind A., Per Marius Pettersen, and Joakim Bratlie. "Time-Dependency in Producers’ Price Adjustments: Evidence from Micro Panel Data." Review of Economics 69, no. 2 (August 28, 2018): 147–68. http://dx.doi.org/10.1515/roe-2018-0012.
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Abstract Existing micro evidence of firms’ price changes tends to show a downward sloping hazard rate – the longer the price of a product has remained the same, the less likely it is that the price will change. Using a panel of Norwegian plant- and product-specific prices, we also find a downward sloping hazard when applying a Kaplan–Meier model. After having controlled for both observed and unobserved characteristics, we find flat hazards with spikes in the first and twelfth months. This suggests time-dependent price-setting by at least some of the producers. The spike after 12 months might be explained by seasonal demand effects, but also by the pricing season effect related to information acquisition and processing, negotiation and signing of price contracts. The revealed price adjustment pattern is at odds with the predictions of the Calvo model, a central element in many dynamic stochastic general equilibrium models, as this assumes constant frequencies of price adjustments over time. Our empirical findings instead point to a modified Calvo model where firms in some periods experience lower menu costs. Finally, the empirical findings may have implications for the effectiveness of monetary policy interventions.
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Wilmot, Neil A. "Heavy Metals: Might as Well Jump." International Journal of Financial Studies 7, no. 2 (June 17, 2019): 33. http://dx.doi.org/10.3390/ijfs7020033.
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Financial times series, and commodity prices in particular, are known to exhibit fat tails in the distribution of prices. As with many natural resources price series, the arrival of new information can lead to unexpectedly rapid changes—or jump—in prices. This suggests that natural resource commodity prices should follow a more complex process than geometric Brownian motion (GBM), which is linked to the Gaussian distribution. The presence of jumps (discontinuities) in several heavy metal price series is investigated, as well as time-varying volatility. The results demonstrate that allowing for jumps and time-varying volatility provides statistically important improvements in the modelling or prices, relative to GBM. These complex processes contributed to the fatness of the tails in the distribution of heavy metal price returns.
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EKSTRÖM, ERIK, and BING LU. "SHORT-TIME IMPLIED VOLATILITY IN EXPONENTIAL LÉVY MODELS." International Journal of Theoretical and Applied Finance 18, no. 04 (June 2015): 1550025. http://dx.doi.org/10.1142/s0219024915500259.
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We show that a necessary and sufficient condition for the explosion of implied volatility near expiry in exponential Lévy models is the existence of jumps towards the strike price in the underlying process. When such jumps do not exist, the implied volatility converges to the volatility of the Gaussian component of the underlying Lévy process as the time to maturity tends to zero. These results are proved by comparing the short-time asymptotics of the Black–Scholes price with explicit formulas for upper and lower bounds of option prices in exponential Lévy models.
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Wang, Jun, Huopo Pan, and Fajiang Liu. "Forecasting Crude Oil Price and Stock Price by Jump Stochastic Time Effective Neural Network Model." Journal of Applied Mathematics 2012 (2012): 1–15. http://dx.doi.org/10.1155/2012/646475.
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The interacting impact between the crude oil prices and the stock market indices in China is investigated in the present paper, and the corresponding statistical behaviors are also analyzed. The database is based on the crude oil prices of Daqing and Shengli in the 7-year period from January 2003 to December 2009 and also on the indices of SHCI, SZCI, SZPI, and SINOPEC with the same time period. A jump stochastic time effective neural network model is introduced and applied to forecast the fluctuations of the time series for the crude oil prices and the stock indices, and we study the corresponding statistical properties by comparison. The experiment analysis shows that when the price fluctuation is small, the predictive values are close to the actual values, and when the price fluctuation is large, the predictive values deviate from the actual values to some degree. Moreover, the correlation properties are studied by the detrended fluctuation analysis, and the results illustrate that there are positive correlations both in the absolute returns of actual data and predictive data.
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Makarov, Igor, and Antoinette Schoar. "Price Discovery in Cryptocurrency Markets." AEA Papers and Proceedings 109 (May 1, 2019): 97–99. http://dx.doi.org/10.1257/pandp.20191020.
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We ask which markets drive bitcoin prices and how price discovery happens across different exchanges. Does the greater exuberance for cryptocurrencies outside the United States affect prices only on local markets or does it impact price formation on global cryptocurrency markets? We document significant heterogeneity in which price formation happens across exchanges and time. When markets are more integrated, shocks to prices on all exchanges contribute to price discovery. However, when markets become segmented, those exchanges that have large arbitrage spreads relative to the US price, i.e. where investors are more exuberant become much less important for price discovery.
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Cahill, Nathanial, Michael Popp, Charles West, Alexandre Rocateli, Amanda Ashworth, Rodney Farris, and Bruce Dixon. "Switchgrass Harvest Time Effects on Nutrient Use and Yield: An Economic Analysis." Journal of Agricultural and Applied Economics 46, no. 4 (November 2014): 487–507. http://dx.doi.org/10.1017/s1074070800029060.
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This article analyzes economic tradeoffs among harvest date, fertilizer applied, nutrient removal, and switchgrass yield as they vary with respect to input and output prices. Economic sensitivity analyses suggest that higher biomass prices lead to earlier harvest. Optimal harvest time occurs beyond time of maximum yield because nutrient removal in the biomass is an important economic consideration. Switchgrass price premia that reflect the cost of non-optimal harvest time are driven by standing crop yield loss, nutrient removal, storage loss, and opportunity cost. These price premia could provide a mechanism to compensate producers for alternative harvest times and aid with logistics management.
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Feldman, Naomi E. "Time is Money: Choosing between Charitable Activities." American Economic Journal: Economic Policy 2, no. 1 (February 1, 2010): 103–30. http://dx.doi.org/10.1257/pol.2.1.103.
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This paper analyzes the impact of a preferential tax-price for monetary donations on the joint decision to donate time (volunteer) and money. The methodological approach takes into account that consumption of each charitable good affects consumption of the other. Using data from a national survey on household charitable giving, the results show that donations of time and money are substitutes. However, a decrease in the tax-price of monetary donations also has a positive effect on donations of time that acts outside the change in relative prices. This more than offsets the substitution effect leading to an overall positive correlation between the two charitable goods. (JEL D64, H24, H31)
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Hanna, Richard C., Scott D. Swain, and Paul D. Berger. "Optimizing time-limited price promotions." Journal of Marketing Analytics 4, no. 2-3 (July 2016): 77–92. http://dx.doi.org/10.1057/s41270-016-0006-y.
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Malik, Obaid Ullah, Robert J. Hilderman, Howard J. Hamilton, and Richard Dosselmann. "Retail price time series imputation." International Journal of Business Intelligence and Data Mining 11, no. 1 (2016): 49. http://dx.doi.org/10.1504/ijbidm.2016.076426.
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Ata, Barış, and James D. Dana. "Price discrimination on booking time." International Journal of Industrial Organization 43 (November 2015): 175–81. http://dx.doi.org/10.1016/j.ijindorg.2015.06.002.
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Frijns, Bart, and Peter Schotman. "Price discovery in tick time." Journal of Empirical Finance 16, no. 5 (December 2009): 759–76. http://dx.doi.org/10.1016/j.jempfin.2009.07.002.
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NGUYỄN MINH, ĐỨC. "Price Transmission in the Value Chain of Hard Clam in Vietnam." Journal of Asian Business and Economic Studies 219 (January 1, 2014): 127–43. http://dx.doi.org/10.24311/jabes/2014.219.1.06.
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Using data collected from 2007-2010, this study identifies price linkages and then forecasts vertical price transmission elasticities between markets (farm, wholesale, retail and export) in the value chain of hard clam (Meratrix lyrata) in Vietnam. After doing necessary tests to make sure that all price data are stationary, Seemingly Unrelated Regression (SUR) and Error Correction Model (ECM) are employed to examine short-time and long-time effects of hard clam price in one market on the other market in its value chain. The seemingly unrelated regression results show that hard clam prices seem not depend on seasons. Farm price of hard clam is transmitted completely to wholesale price while the price in retail market causes negative effect on farm price in the short run. Wholesale price of hard clam is transmitted to both prices in farm and retail markets. The export price of hard clam is estimated not to be affected in the short run by prices in other markets except retail price in domestic markets. Error correction models confirm the independence of hard clam price on annual seasons. The transmission elasticities of prices between the markets are also identified based on model estimation.
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Fang, Xian Wen, Yan Ni Zou, and Qian Jin Zhao. "An Efficient Web Service Composition Method Based on the Price-Time Petri Net." Advanced Materials Research 268-270 (July 2011): 1421–26. http://dx.doi.org/10.4028/www.scientific.net/amr.268-270.1421.
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At present, developers can rapidly generate applications through Web service composition, the quality of service (QoS) of web service composition is important, but most of the existing composition methods are difficult to balance the QoS indexes (Such as time and price). In this paper, a web service composition method based on the price-time Petri net is proposed, the minimum cost can be obtained by modeling based on price time Petri net, and presents a method of priced state class to analyze the cost of web service composition model. Theoretical analysis and case analysis show that the price-time Petri net method is feasible to study Web service composition with the minimum cost.
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Baumeister, Christiane, and Gert Peersman. "Time-Varying Effects of Oil Supply Shocks on the US Economy." American Economic Journal: Macroeconomics 5, no. 4 (October 1, 2013): 1–28. http://dx.doi.org/10.1257/mac.5.4.1.
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Using time-varying BVARs, we find a substantial decline in the short-run price elasticity of oil demand since the mid-1980s. This finding helps explain why an oil production shortfall of the same magnitude is associated with a stronger response of oil prices and more severe macroeconomic consequences over time, while a similar oil price increase is associated with smaller output effects. Oil supply shocks also account for a smaller fraction of real oil price variability in more recent periods, in contrast to oil demand shocks. The overall effects of oil supply disruptions on the US economy have, however, been modest. (JEL E31, E32, Q41, Q43)
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Jang, Peter Y., and Mario G. Beruvides. "Time-Varying Influences of Oil-Producing Countries on Global Oil Price." Energies 13, no. 6 (March 17, 2020): 1404. http://dx.doi.org/10.3390/en13061404.
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This paper aims to investigate the time-varying influences of major crude oil-producing countries on Brent oil prices, with seven-panel data over the observation years of 1998 to 2018. We create seven panels with 36 monthly data for each and estimate the contributions of individual producing countries to oil price changes with a multivariate regression technique of ordinary least squares. Most existing researches have focused on identifying relationships among oil price, market fundamental factors, macroeconomic variables, and geopolitical events in broad perspectives. However, this paper undertakes a longitude/panel analysis of nine oil producers’ influences, with the Organisation for Economic Co-operation and Development (OECD) consumption and the U.S. Dollar Index (USDX) on oil prices in each panel and intends to identify which producers have statistically significant influencing weights on oil prices. We believe that this research contributes to the body of knowledge in better understanding the relative impacts of major oil-producing countries. Results show empirical evidences that the Organization of the Petroleum Exporting Countries (OPEC) production stayed as the greatest negative influence on the oil price in the periods of Panel 2 (2001–2003) and Panel 7 (2016–2018) only, while the U.S. Dollar Index took over the OPEC’s influencing role in most of the other periods, followed by Iran, the U.S., and China.
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Siklar, Ilyas, Umit Yildiz, and Sinan Cakan. "The Time - Varying Natural Rate of Interest and Its Fundamental Determinants: Time Series Evidence from Turkey." Business and Economic Research 6, no. 2 (December 18, 2016): 390. http://dx.doi.org/10.5296/ber.v6i2.10303.
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In this study, by estimating the natural rate of interest, its relationship with key macroeconomic variables is analyzed using the time series data obtained from Turkey. As a first step, together with the natural rate of interest, the potential levels of output, prices and foreign exchange rate are estimated by using the Kalman Filter algorithm and then the related gap levels of each variable representing the deviations from their potentials are determined. As a second step of the study, the effects of output, price and exchange rate gaps on the interest rate gap are analyzed by using cointegration and error correction methodologies and the causality relationship among variables are examined. The main conclusion of the current study is that there is significant causality relationship between the interest rate gap, output, price and exchange rate gaps.
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Park, Minseok, Kyungsub Lee, and Geon Ho Choe. "Distribution of Discrete Time Delta-Hedging Error via a Recursive Relation." East Asian Journal on Applied Mathematics 6, no. 3 (July 20, 2016): 314–36. http://dx.doi.org/10.4208/eajam.010116.220516a.
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AbstractWe introduce a new method to compute the approximate distribution of the Delta-hedging error for a path-dependent option, and calculate its value over various strike prices via a recursive relation and numerical integration. Including geometric Brownian motion and Merton's jump diffusion model, we obtain the approximate distribution of the Delta-hedging error by differentiating its price with respect to the strike price. The distribution from Monte Carlo simulation is compared with that obtained by our method.
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Boyer, Christopher N., Kelsey Campbell, Andrew P. Griffith, Karen L. DeLong, Justin Rhinehart, and David Kirkpatrick. "Price Determinants of Performance-Tested Bulls over Time." Journal of Agricultural and Applied Economics 51, no. 02 (March 25, 2019): 304–14. http://dx.doi.org/10.1017/aae.2019.3.
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AbstractWe estimate the values of bull phenotypic traits, performance measurements, and expected progeny differences (EPDs) over time using bull sale data from an auction in Tennessee from 2006 to 2016. Moreover, we determine how a state partial-cost reimbursement program for bulls with certain EPDs affects bull sale price. Purebred seed stock producers in this region should focus on selling large, fast-growing, mature bulls that produce lighter calves for reduced calving stress. The state cost-share payment did not significantly increase bull prices in most years, meaning this payment was retained by cow-calf producers in most years.
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Cortes, Armando, Megan Park, and Bryan C. McCarthy. "Drug purchase price volatility in an academic medical center." American Journal of Health-System Pharmacy 78, Supplement_2 (March 16, 2021): S33—S37. http://dx.doi.org/10.1093/ajhp/zxaa422.
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Abstract Purpose Inpatient drug purchase price trends at an 811-bed academic medical center are described. Summary Recent highly publicized drug price increases by pharmaceutical manufacturers have generated public interest in regulatory solutions to reduce drug costs. Monitoring drug price changes through internal dashboards has been demonstrated to aid in purchasing decisions to reduce the impact of drug price changes on inpatient pharmacy drug budgets. In this research, University of Chicago Medicine created an internal dashboard to detail specific inpatient drug purchase price trends. Dashboard data input included all medications purchased through the organization’s group purchasing organization over a 25-month time frame. A total of 69,245 drug purchases of 2,432 unique medications and/or dosage strengths were analyzed in the study. Within the 25-month time period, 706 medications (29%) had a net drug purchase price increase, while 898 (37%) had a net drug purchase price decrease. The range of net price percentage changes for medications with price increases was 0.01% to 733.6%; the range for medications with price decreases was 0.01% to 97.5%. Conclusion Relative to previous purchase prices, drug purchase prices decreased or remained the same more often than they increased over a 25-month time frame. However, drug purchase price percentage changes were far greater for medications whose prices increased rather than decreased.
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Babirath, Julia, Karel Malec, Rainer Schmitl, Kamil Maitah, and Mansoor Maitah. "Forecasting based on spectral time series analysis: prediction of the Aurubis stock price." Investment Management and Financial Innovations 17, no. 4 (December 4, 2020): 215–27. http://dx.doi.org/10.21511/imfi.17(4).2020.20.
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The attempt to predict stock price movements has occupied investors ever since. Reliable forecasts are a basis for investment management, and improved forecasting results lead to enhanced portfolio performance and sound risk management. While forecasting using the Wiener process has received great attention in the literature, spectral time series analysis has been disregarded in this respect. The paper’s main objective is to evaluate whether spectral time series analysis can produce reliable forecasts of the Aurubis stock price. Aurubis poses a suitable candidate for an investor’s portfolio due to its sound economic and financial situation and the steady dividend policy. Additionally, reliable management contributes to making Aurubis an investment opportunity. To judge if the achieved forecast results can be considered satisfactory, they are compared against the simulation results of a Wiener process. After de-trending the time series using an Augmented Dickey-Fuller test, the residuals were compartmentalized into sine and cosine functions. The frequencies, amplitude, and phase were obtained using the Fast Fourier transform. The mean absolute percentage error measured the accuracy of the stock price prediction, and the results showed that the spectral analysis was able to deliver superior results when comparing the simulation using a Wiener process. Hence, spectral time series can enhance stock price forecasts and consequently improve risk management.
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EVERTSZ, CARL J. G. "FRACTAL GEOMETRY OF FINANCIAL TIME SERIES." Fractals 03, no. 03 (September 1995): 609–16. http://dx.doi.org/10.1142/s0218348x95000539.
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A simple quantitative measure of the self-similarity in time-series in general and in the stock market in particular is the scaling behavior of the absolute size of the jumps across lags of size k. A stronger form of self-similarity entails that not only this mean absolute value, but also the full distributions of lag-k jumps have a scaling behavior characterized by the above Hurst exponent. In 1963, Benoit Mandelbrot showed that cotton prices have such a strong form of (distributional) self-similarity, and for the first time introduced Lévy’s stable random variables in the modeling of price records. This paper discusses the analysis of the self-similarity of high-frequency DEM-USD exchange rate records and the 30 main German stock price records. Distributional self-similarity is found in both cases and some of its consequences are discussed.
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Vochozka, Marek, Jakub Horak, and Tomas Krulicky. "Innovations in Management Forecast: Time Development of Stock Prices with Neural Networks." Marketing and Management of Innovations, no. 2 (2020): 324–39. http://dx.doi.org/10.21272/mmi.2020.2-24.
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Accurate prediction of stock market values is a challenging task for over decades. Prediction of stock prices is associated with numerous benefits including but not limited to helping investors make wise decisions to accumulate profits. The development of the share price is a dynamic and nonlinear process affected by several factors. What is interesting is the unpredictability of share prices due to the global financial crisis. However, classical methods are no longer sufficient for the application of share price development prediction.However, over-relying on prediction data can lead to losses in the case of software malfunction. This paper aims to innovate the prediction management when predicting the share price development over time by the use of neural networks. For the contribution, the data on the prices of CEZ, a.s. shares obtained from the Prague Stock Exchange database. The stock price data are available for the period 2012-2017. In the case of Statistica software, the multilayer perceptron networks (MLP) and the radial basis function networks (RBF) are generated. In the case of Matlab software, the Support Vector Regression (SVR) and the Back-Propagation Neural Network (BPNN) are generated. The networks with the best characteristics are retained and based on the statistical interpretation of the results, and all are applicable in practice. In all data sets, MLP networks show stable performance better than in the case of SVR and BPNN networks. As for the final assessment, the deviation of 2.26% occurs in the most significant differential of the maximal and the minimal prediction. It is not necessarily significant regarding the price of one stock. However, in the case of purchasing or selling a large number of stocks, the difference may seem significant. Therefore, in practice, the application of two networks is recommended: MLP 1-2-1 and MLP 1-5-1. The first network always represents a pessimistic, minimal prediction. The second one of the recommended networks is an optimistic, maximal prediction. The actual situation should correspond to the interval of the difference between the optimistic and pessimistic prediction. Keywords: Statistica software, Matlab software, stock price development, neural networks, prediction.
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EL QALLI, YASSINE. "RECURSIVE BAYESIAN ESTIMATION IN FORWARD PRICE MODELS IMPLIED BY FAIR PRICING." International Journal of Theoretical and Applied Finance 13, no. 02 (March 2010): 301–33. http://dx.doi.org/10.1142/s0219024910005784.
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In this paper we describe a recursive Bayesian algorithm for the estimation of forward price models. The forward price is modeled within the benchmark framework for a forward price volatility function which includes a stochastic variable; a forward price with a liquidly traded maturity. A relationship between the bond price, the spot price and certain forward prices is stated. We set up the stochastic real world dynamics for these discretely compounded market observed forward prices. We propose a dynamic Bayesian estimation algorithm for a Monte Carlo time-discretized version of the resulting forward prices dynamics. The parameter to be estimated is a vector consisting of the forward price volatility parameters and the benchmarked bond price volatility parameters.
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Liu, Yue, Pierre Failler, Jiaying Peng, and Yuhang Zheng. "Time-Varying Relationship between Crude Oil Price and Exchange Rate in the Context of Structural Breaks." Energies 13, no. 9 (May 11, 2020): 2395. http://dx.doi.org/10.3390/en13092395.
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This paper examines the dynamic relationship between crude oil prices and the U.S. exchange rate within the structural break detection context. Based on monthly data from January 1996 to April 2019, this paper identifies structural breaks in movements of oil price and examines the dynamic relationship between crude oil prices and the U.S. exchange rate movement by introducing the economic policy uncertainty and using the TVP-VAR (Time-Varying Parameter-Vector Auto Regression ) model. Empirical results indicate that shocks to crude oil prices have immediate and short-term impacts on movements in the exchange rate which are emphasized during the confidence intervals of structural breaks. Oil price shocks and economic policy uncertainty are interrelated and influence movements in the U.S. exchange rate. Since the U.S. dollar is the main currency of the international oil market and the U.S. has become a major exporter of crude oil, the transmission of price shocks to the U.S. exchange rate becomes complicated. In most cases, the relationship between oil prices and the U.S. exchange rate movements is negative.
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Hamulczuk, Mariusz, and Oksana Makarchuk. "Time-varying relationship between Ukrainian corn and world crude oil prices." Economic Annals-ХХI 184, no. 7-8 (September 10, 2020): 49–57. http://dx.doi.org/10.21003/ea.v184-05.
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Corn belongs to the most important feed and industrial grains in the world being utilized for bioethanol production. Ukraine does not produce biofuels and does not pursue an active renewable energy policy. However, due to significant share of exports, corn prices in Ukraine can be shaped under the influence of biofuel policies pursued by developed countries, as well as under the influence of world energy markets. Therefore, the aim of the paper is to investigate the mechanisms linking Ukrainian export corn prices with Brent oil prices, as well as to quantitatively assess the nature of this relationship. We were especially interested in possible time-varying relationship between the prices. The price analysis was carried out on the basis of monthly data for the period 2001-2020 with the use of rolling correlation technique and rolling causality tests. The results of this research indicate on time-varying co-movements of Ukrainian corn and Brent crude oil prices. The strongest positive correlations and significant bidirectional causality were observed in 2007-2011. However, in most of sub-periods there were no significant relationships between these prices. Among factors strengthening the price linkages are the low corn-oil price ratios, dynamic increase of corn utilized for ethanol production and depletion of the world corn stocks. The conducted analysis confirmed that changes in biofuel demand in other countries can affect Ukrainian corn market due to horizontal integration of grain markets worldwide. Biofuel policy reforms in the EU aiming at decreasing mandatory blending of conventional biofuels in favor of advanced biofuels can lead to decrease in demand for corn in Ukraine after 2021, leading, in turn, to further weakening of linkage between corn and crude oil prices.