Changes In Market Prices Research Articles

A Financially Motivated Extension of the Heston Model for a Joint ℙ- and ℚ-Dynamics Analysis of Variance

The empirical, or “ℙ,” distribution determines profits and losses from market price changes, while the risk- neutral “ℚ” distribution is what is embedded in derivatives prices. Expected returns under the ℙ distribution include expected risk premia, while under the ℚ, those risk premia are embedded in the probabilities. Risk-neutral probabilities, and hence market prices for derivatives, move randomly because expectations about true (ℙ-density) probabilities change and also because risk premia are variable too. While changes in the ℚ density are observable in option prices, the breakdown between true expectations and risk premia is not. Although evidence suggests that risk premia may fluctuate as much as probability beliefs do, it is rare for their dynamics to be formally modeled. That is what Rebonato and Ng do in this article looking at exchange rates. Starting with the assumption of a standard Heston model for dynamics under the P measure, they construct a corresponding volatility process under the ℚ measure by modifying the long-term variance level and the reversion speed. Rather than modeling these as constant parameters, they introduce mean-reverting diffusions for both parameters. The effects of these generalizations are explored by holding one constant while the other is varied. After showing the extra flexibility that the “complex Heston” formulation allows, they devise an analytic approximation formula using the average projected parameter values from the dynamic model as the constant parameters in the standard Heston specification and show that the approach works very well. Finally, they take the model to the data for the EURUSD, JPYUSD, and GBPUSD exchange rates and demonstrate that the new model can fit well over time without the need to refit parameter values.

Prediction of construction cost index based on multi variable grey neural network model

The construction cost index can reflect the construction market price changes on the project cost. Due to unsuitable way of management and the consideration of data security, there is the possibility of researchable sample data missing, or the possibility of not enough data. This way many classical prediction models cannot function well in practice. The study compared numerous models. According to the characteristics of poor sample data and numerous factors for construction engineering, the grey model and BP neural network were selected to establish the prediction model. This study built material and machinery shift as independent variables, the construction cost as the dependent variable to establish the grey neural network model. In empirical analysis, data processing, training and simulation were used by MATLAB, the results concluded: compared with other conventional models, the combined forecasting model for poor data is more effective.

The Co-Terminal Swap Market Model with Bergomi Stochastic Volatility

In this article, we apply the forward variance modeling approach by L.Bergomi to the co-terminal swap market model. We build an interest rate model for which all the market price changes of hedging instruments, interest rate swaps and European swaptions, are interpreted as the state variable variations, and no diffusion parameter calibration procedure is required. The model provides quite simple profit and loss (PnL) formula, with which we can easily understand where a material PnL trend comes from when it appears, and consider how we should modify the model parameters. The model has high flexibility to control the model dynamics because parameter calibration is unnecessary and the model parameters can be used solely for the purpose of the model dynamics control. With the model, the position management of the exotic interest rate products, e.g. Bermudan swaptions, can be carried out in a more sophisticated and systematic manner. A numerical experiment is performed to show the effectiveness of the approach for a Canary swaption, which is a special form of a Bermudan swaption.

A Regional Optimization Model for Waste-to-Energy Generation Using Agricultural Vegetative Residuals

The spatial distribution of vegetative agricultural residuals (VAR) makes the economic feasibility of a waste treatment solution particularly sensitive to transportation costs, especially when farmers are the ones being charged for that. This study evaluated a method to design an economic feasible VAR treatment system, analyzing the profitability of the system as a function of logistics and the unknown market prices of the treatment facilities' products. The design method includes optimization modeling followed by a sensitivity analysis of the potential changes in the system’s profitability. The results show that the market price of the treatment facilities’ products has a greater effect on the system’s profitability in compare to transportation costs. In specific, if biochar prices reach the level forecasted by experts, its production requirements will dominate the whole waste treatment system (WTS). The research highlights the importance of the treatment technology selection as part of a WTS design for agriculture and forest residuals. This selection should allow the absorption of market price changes and transport costs into the system’s operational costs, and remove these potential risks from the system’s implementation path.

Optimal Utilization of Renewable Energy in Aquaponic Systems

Aquaponic systems require energy in different forms, heat, solar radiation, electricity etc. Typical actuator components of an aquaponic system include pumps, aerators, heaters, coolers, feeders, propagators, lights, etc., which need electrical energy to operate. Hybrid Energy Systems (HES) can help in improving the economic and environmental sustainability of aquaponic systems with respect to energy aspects. Energy management is one of the key issues in operating the HES, which needs to be optimized with respect to the current and future change in generation, demand, and market price, etc. In this paper, a Decision Support System (DSS) for optimal energy management of an aquaponic system that integrates different energy sources and storage mechanisms according to priorities will be presented. The integrated model consists of photovoltaic and solar thermal modules, wind turbine, hydropower, biomass plant, CHP, gas boiler, energy and heat storage systems and access to the power grid and district heating. The results show that the proposed method can significantly increase the utilization of HES and reduce the exchange with the power grid and district heating and consequently reduce running costs.

Opportunity Cost Pass‐Through from Fossil Fuel Market Prices to Procurement Costs of the U.S. Power Producers

AbstractThis paper investigates the transmission of fossil fuel commodity spot market price changes to procurement costs of U.S. power producers. We measure and compare the speed and magnitude with which spot prices predict procurement costs using restricted access fuel price data. Natural gas spot prices are quickly reflected in procurement costs. Coal spot prices offer very little predictive power to coal procurement costs. Although not causal, the empirical results also show differences across regulatory status. These findings may have implications for the electricity market deregulation literature that creates marginal cost curves as a competitive benchmark.

Does inflation cause gold market price changes? evidence on the G7 countries from the tests of nonparametric quantile causality in mean and variance

ABSTRACTThis article utilizes the newly proposed nonparametric causality-in-quantiles test to examine the predictability of mean and variance of changes in gold prices based on inflation for G7 countries. The causality-in-quantiles approach permits us to test for not only causality in mean but also causality in variance. We start our investigation by utilizing tests for nonlinearity. These tests identify nonlinearity, showing that the linear Granger causality tests are subject to misspecification error. Unlike tests of misspecified linear models, our nonparametric causality-in-quantiles tests find causality in mean and variance from inflation to gold market price changes between the 0.20 quantile and the 0.70 quantile, implying that very low- and high-price changes in gold markets are not related to inflation. These changes should be related to other sources, such as financial shocks and exchange market shocks. We find support that gold serves as a hedge against inflation, but only in the mid-quantile ranges, i.e. quantiles from 0.20 to 0.70. Our results show that gold does not serve as a hedge against inflation during periods when gold market price changes are very low or very high, which are respectively quiet and highly volatile periods.

Impact of Fundamental Factors on Stock Price: A Case of Nepalese Commercial Banks

This study examines the impact of fundamental factors on stock price of Nepalese commercial banks. Return on assets, return on equity, net profit margin, earning per share and dividend per share are the independent variables. And market price per share and change in market price per share are the dependent variables. Data are collected from the Banking and Financial Statistics and Bank Supervision Report published by Nepal Rastra Bank and annual reports of the selected commercial banks. The study is based on 13 commercial banks of Nepal from 2007 to 2014, leading to a total of 104 observations. The regression models are estimated to test the significance and impact of fundamental factors in stock price of Nepalese commercial banks. The result shows that dividend per share (DPS), return on assets (ROA) and earning per share (EPS) are positively related to the stock price (market price per share and change in market price per share). This indicates that higher the DPS, ROA and EPS, higher would be the stock price. However, net profit margin is negatively related to stock price. The regression result shows that the beta coefficients for DPS and EPS are positively significant with market price per share at 5 percent level of significance.

Dividend Policy and Share Price Volatility: A Case of Nepalese Commercial Banks

This study examines the impact of dividend policy on share price volatility of Nepalese commercial banks. The share price volatility, change in market price per share and stock return change are dependent variables. Dividend yield, dividend payout, debt ratio, size, growth and earning volatility are independent variables. The study is based on 18 commercial banks of Nepal from 2009-2014, leading to a total of 108 observations. The data are collected from various issues of Banking and Financial Statistics and Bank Supervision Report published by Nepal Rastra Bank, annual Report of Nepal Stock Exchange and the annual reports of the selected banks. The regression models are estimated to test the significance and impact of dividend policy on share price volatility of Nepalese commercial banks. The study reveals that dividend payout is negatively related to share price volatility (price volatility, change in MPS and stock return volatility). It indicates that increase in dividend payout leads to decrease in share price volatility. However, earning volatility is positively related to share price volatility indicating that higher the earning volatility, higher would be share price volatility. The regression result shows that dividend yield and size have significant positive impact on share price volatility. The beta coefficients for growth and dividend yield are significant at 5 percent level of significance.

Bank Valuation Models – A Comparative Analysis

The Bank valuation model was designed based on objective to fit the most applicable valuation model for banks to help in forecasting bank specific decision and also forecast the market value of share. First study the accuracy and explanatory value of the value estimates from the residual income model compared to the estimates from the Relative valuation model for banks. Empirical evidence suggests that the residual income model is superior to the relative valuation model when it comes to measuring bank shareholder value. The results of the comparison suggest that value estimates from the residual income model are even more reliable for banks. On this basis, we conclude that residual income is an appropriate value estimate for the shareholder value of banks. There was positive significant relationship identified between the intrinsic value of bank share determined by RIV model and Market price of share in all the cases by performing correlation and Regression study. This study will be useful for forecasting the possible changes in market price. It was identified that determinants vary as per the working and regulatory condition as determinants impacting private, public and Indian banks were not similar so panel regression model will vary for each cases. It was also identified that Public Sector Bank in India shows more positive progressive trend as compared to private Sector Bank even after the fact that public Sector Bank has higher regulatory restriction as compared to Private Sector banks. This research will serve very useful for the banker to plan and take decision regarding shareholder value creation by implementing proper valuation model for getting appropriate value estimate and also adopting proper internal performance measure for having accurate and regular check on the process of value creation.

Fueling fiscal interactions: commodity price shocks and local government spending in Colombia

This paper explores fiscal interactions in a developing country. We analyze whether public expenditures in neighboring municipalities influence local spending decisions within a comprehensive set of expenditure categories. Our analysis is based on panel data covering the universe of Colombian municipalities from 2000 to 2010. We offer a quasi-experimental identification strategy exploiting exogenous variation in municipalities’ exposure to changes in the world market price of oil, depending on the municipalities’ endowment with oil resources and controlling for municipality fixed effects. While we find evidence of strong spatial autocorrelation of total local public spending as well as in almost all expenditure categories, the quasi-experimental approach reveals that there are no significant causal fiscal interaction effects between municipalities. This highlights the importance of using additional sources of exogenous variation for the identification of fiscal interactions. In the developing country context, our findings suggest that fiscal decentralization policies do not lead to a race to the bottom in local public expenditures.

Vector autoregressive approach for impact of oil India stock price on fuel price in India

ABSTRACTFinancial market volatility is an important input for investment and financial market regulation. In recent years, the different varieties of models that apparently predict changes in stock market prices have been introduced. Time series modeling has a major role in forecasting of stock market price related issues. The dynamic relationships between dollar rate, crude oil, and fuel price are examined based on a vector autoregressive model with the use of Granger causality test, impulse response function, and variance decomposition for the data. The possible methods for forecasters are emphasized and their relevance for the Efficient Market Hypothesis is also discussed.

Fuel prices impacts on stock market of metallurgical industry under the EU emissions trading system

Metallurgical industry is among the largest industrial users of fossil fuels in the Spanish economy and it is one of the industries under the European Union emissions trading system. This study examines the long-run equilibrium relations and short-run interactions between fuels and European Union carbon emissions allowances price changes and the corporate value of Spanish iron and steel industry.From a multifactor market model specification, a cointegrated Vector Error Correction model is employed for the period covering 1st January 2013 to 15th September 2015 to embrace the analysis. Moreover, by using a panel data econometric approach, it is tested if the relationship of European Union carbon emissions allowances and fuel prices variations with stock returns are firm-specific.The results indicate a negative stable long-run relation between gas prices and stock market price changes of metallurgy sector and firm-specific effects. Regarding the EUA price change effect on aggregated stock market return, the VECM estimation did not find a significant long-run linkage. However, the results of EUA price change impact at firm level showed evidence for heterogeneity in this effect.

Durum Wheat Cover Analysis in the Scope of Policy and Market Price Changes: A Case Study in Southern Italy

Agricultural land systems are the result of human interactions with the natural environment, and subjective evidence of socio-economic and environmental interactions has been demonstrated. Nevertheless, it is still difficult to analyze empirically the link between agricultural market and policy, as well as the environmental response due to changes in crop management by local stakeholders. In this study, we propose a cross investigation and analysis to bring the link between vegetation cover, policy, market and farmer’s behavior to light. Our methodology is a combination of a rational positive and analogical approach between the quantifiable and non-quantifiable agents on a temporal basis. The method is applied to a dominant mono-crop agricultural watershed in Southern Italy that has been dedicated to durum wheat cultivation. In this region, we studied the relationship between the Common Agricultural Policy (CAP), durum wheat market price, vegetation cover and land allocation. As a first step, we conducted a separate analysis for each factor, exploiting Moderate Resolution Imaging Spectroradiometer (MODIS) satellite observed Leaf Area Index (LAI) to analyze the land vegetation space–time distribution over the period 2000–2014 and three Land Satellite (Landsat) validated images as check-points for the agricultural pattern and CAP’s reforms. We used the Farm Accountancy Data Network (FADN) and Eurostat data to investigate the on-farm accountancy and the durum wheat market price changes, respectively. Based on the study period, we developed a storyline of the major relevant CAP’s policy changes. In a second step, we conducted a comparative analysis where the CAP’s reforms were used as interpretational support, the land allocation and the on-farm accountability for CAP’s implementation, the price of durum wheat and the LAI for analytical comparison. We found interesting insights regarding the non-agronomic driving forces of LAI dynamics. The behavior of the individual farmers is influenced by the CAP policy that has been implemented by using profitability as the stimulus for the decision making of the farmer. This explains the correlation of the trend between the market price, the LAI of durum wheat and their associated dynamics.

Pricing European Put Option in a Geometric Brownian Motion Stochastic Volatility Model

Stochastic volatility models were introduced because option prices have been mis-priced using Black-Scholes model. In this work, focus is made on pricing European put option in a Geometric Brownian Motion (GBM) stochastic volatility model with uncorrelated stock and volatility. The option is priced using two numerical methods (Crank-Nicolson and Alternating Direction Implicit (ADI) finite difference). Numerical schemes were considered because the closed form solution to the model could not be obtained. The change in option value due to changes in volatility, maturity time and market price of volatility risk are considered and comparison between the efficiency of the numerical methods by computing the CPU time was made.

Loss function analysis of private forest owners’ timber price change expectations

ABSTRACTLoss function analysis was introduced to timber market price analysis. Methods found in Bayesian statistical decision analysis were applied to expectations of market price changes. These were obtained from a forest owner survey conducted in Finland in 2009. Forecast errors of heterogeneous price expectations of the individual private forest owners were derived with observed price changes in six different timber price regions. The forecast errors were complemented with random number simulations to control for unobserved response heterogeneity. The properties and estimation of generalized loss functions – LIN-EX and flexible loss functions – allowing for asymmetry in individual forecast errors were introduced into the analysis. Estimation results for different price regions implied that forest owners’ perceived costs related to positive forecast errors of negative price changes that took place in 2009 were larger than those related to negative errors. This under-prediction vs. over-prediction asymmetry was large in some price regions. The forest owners exhibited an aversion to losses reflected in price expectations errors in the year 2009. The observed loss aversion means that forest owners were cautious in their selling decisions during periods of declining market prices. This has a negative impact on the recovery of slack timber markets.

Health Effects of Short-Term Fluctuations in Macroeconomic Conditions: The Case of Hypertension for Older Americans.

We investigate the health effects of short-term macroeconomic fluctuations as described by changes in unemployment rate, house, and stock market price indexes. The 'Great Recession' provides the opportunity to conduct this analysis as it involved contemporaneous shocks to the labor, housing, and stock markets. Using panel data from the Health and Retirement Study over the period 2004-2010, we relate changes in hypertension status to changes in state-level unemployment rate and house prices and to changes in stock market prices. We consider hypertension, a disease related to stress and of high prevalence among older adults, that has received little attention in the literature linking macroeconomic conditions to individual health. Our analysis exploits self-reports of hypertension diagnosis as well as directly measured blood pressure readings. Using both measures, we find that the likelihood of developing hypertension is negatively related to changes in house prices. Also, decreasing house prices lower the probability of stopping hypertension medication treatment for individuals previously diagnosed with the condition. We do not observe significant associations between hypertension and either changes in unemployment rate or stock market prices. We document heterogeneity in the estimated health effects of the recession by gender, education, asset ownership, and work status. Copyright © 2016 John Wiley & Sons, Ltd.

DYNAMIC ECONOMIC RELATIONS AMONG STEEL PRICE INDICES

Bulk shipping is now a globalized industry, with market prices entirely dependent on the world's economic climate. For the bulk shipping market, the steel price index is a crucial standard of reference. In a global industry, the ability to understand the international relationship between changes in information and their effects on economics can help to reduce losses caused by the uncertainty of risk. Because the types of ships and contracts used in bulk shipping are wide-ranging, market participants tend to have difficulty in determining market price changes and trends, and are therefore forced to face greater market uncertainty and volatility. Because steel price is one of the leading indicators used in the bulk shipping market, a clear understanding of steel price index fluctuations can help to reduce the risks associated with bulk shipping. This study uses the vector autoregressive moving-average model as the principle method of analysis to determine how three major economic variables representative of Asian Steel Price Index (ASI), European Steel Price Index (ESI), and North American Steel Price Index (NASI) might influence one another. The results are as follows: (1) ASI is affected by its own positive changes as well as those of NASI, whereas the ESI is only affected by its own moving average. (2) The ASI and NASI are considered as leading indicators. This study aims to provide bulk shipping participants with additional ideas to determine the ideal time to enter the market.

Formation and adaptation of reference prices in grain marketing: an experimental study

This study aimed to explore how producers’ reference prices are formed and adapt over time, and how they affect marketing decisions. Results indicate that producers focus on three major variables to form their reference prices: the current market price, the highest price to date, and their expectation about price behavior. Further, they update their reference prices during the marketing season mainly in response to changes in current market prices, their own expectations about price behavior, and the general price trend. Finally, our findings suggest that producers’ marketing decisions are based on the spread between current market price and reference price, the general market trend and price expectation.

How do agricultural markets respond to radiation risk? Evidence from the 2011 disaster in Japan

Since the explosion of the Fukushima Daiichi Nuclear Power Plant in March 2011, public anxiety surrounding the radioactive contamination of food and the environment has become widespread. This article examines how vegetable prices in the Tokyo Metropolitan Central Wholesale Market were affected in the wake of the nuclear accident. This study exploits the quasi-experimental condition generated by this accident to test market price changes using monthly panel data on the price of six types of fresh vegetables from each of the 47 prefectures in Japan. Our estimation results show that the prices of vegetables grown in Fukushima Prefecture decreased by 10–36% after the disaster compared with the counter-factual estimates in the absence of a perceived radiation risk. This effect has persisted even after radioactive detection tests showed negative results in subsequent years. The consumer behavior of avoiding vegetables from Fukushima and instead buying vegetables grown in other areas may explain the price gap.