Real Market Prices Research Articles

Impacts of Labour Force of Afghan Women Based on Education in Economics Growth: In Case of Afghanistan

The essence of this research is to reveal that the impacts of the labor force (unemployment and employment) on Afghan women (females) based on educated people have no positive and direct correlation with increasing economic growth in the estimated period of 2020–2022, but women have a U shape or envelope that contributes to developing economic growth in the long run. Though the study tested the labor force total number of females per cent, the labor force females of Afghanistan have no impact on increasing the total real GDP market price of Afghanistan in 2020-2021-2022 due to the p value being greater than 0.05 or 0.989>0.05; hence, H0 is accepted. As a result, there is not a significant labor force number and labor force females in Afghanistan, as it does not have a crucial impact on economic growth. Economic growth has increased in other sectors such as TOT, exports and imports, etc. Moreover, the intermediate education population per cent of Afghanistan impacts the labor force of male and female members under the working population in Afghanistan in 2020–2021, and the p value is greater than 0.05. It makes sense (0.832>0.05); hence, the null hypothesis is accepted; intermediate and advanced educated people have no impact on under-working-age people in Afghanistan in 2020–2021, but nevertheless, it hasn’t increased the economic growth of Afghanistan in 2020–2021. Otherwise, intermediate- and advanced-educated women percent have no impact on the under-working-age population and do not have a positive impact on economic growth due to the fact that the p value is greater than 0.05. It makes sense (0.832>0.05), hence the null hypothesis is accepted. As a result, the intermediate education population per cent of Afghanistan has no impact on the labor force of males and females under the working population in Afghanistan in 2020–2021. Finally, the study discovered that total real GDP market price and female employees have a moderate correlation in 2019–2020.

An IMEX-based approach for the pricing of equity warrants under fractional Brownian motion models

In this paper, the pricing of equity warrants under a class of fractional Brownian motion models is investigated numerically. By establishing a new nonlinear partial differential equation (PDE) system governing the price in terms of the observable stock price, we solve the pricing system effectively by a robust implicit-explicit numerical method. This is fundamentally different from the documented methods, which first solve the price with respect to the firm value analytically, by assuming that the volatility of the firm is constant, and then compute the price with respect to the stock price and estimate the firm volatility numerically. It is shown that the proposed method is stable in the maximum-norm sense. Furthermore, a sharp theoretical error estimate for the current method is provided, which is also verified numerically. Numerical examples suggest that the current method is efficient and can produce results that are, overall, closer to real market prices than other existing approaches. A great advantage of the current method is that it can be extended easily to price equity warrants under other complicated models. doi: 10.1017/S1446181123000159

Energy market manipulation: Criminal law analysis and signs

Article 42 of the Constitution of Ukraine establishes the principles of preventing abuse of a monopoly position in the market and unfair competition in economic activity. Manipulation of the Energy Market – an act that violates the procedure for state regulation of the electric energy market and the natural gas market approved by the current legislation – poses an increased public danger. The purpose of the study is to investigate objective signs of manipulation in the energy market as part of a criminal offence under Article 222-2 of the Criminal Code of Ukraine. Within the framework of the study, a complex of scientific methods was applied: dialectical, hermeneutical, systemic, formal logical, generalisation, system and structural, method of ascent from the abstract to the concrete, analysis, and synthesis. It is proved that the object of manipulation in the energy market is covered by public relations that control the procedure for state regulation of the electric energy market and the natural gas market approved by the current legislation – the implementation by the state of comprehensive measures to manage the demand, prices, and volumes of the wholesale energy market, prevent abuse and violations in this area. The criminal legal content of the concept of “manipulation” is determined by the deliberate activity of a person(s) who violate the conditions of functioning of the wholesale energy market, is carried out by performing a set of illegal actions, the purpose of which is to obtain financial benefits for themselves and third parties, by changing the price of a financial asset. The essence of manipulation of the wholesale energy market is highlighted through its inherent features, which indicate a violation of the conditions necessary for making transactions on the wholesale energy market and a deviation of the asset price from the real market price in the right direction for manipulators (the presence of a process of overstating (underestimating) the total price of the contract, which leads to the loss of its market status). The practical significance of the study lies in the fact that the analysis carried out is of auxiliary importance for law enforcement practice in solving issues related to the legal qualification of manipulation in the energy market

How oil price and exchange rate affect stock price in China using Bayesian Quantile_on_Quantile with GARCH approach

We revisit the links of real exchange rate, oil price and stock market price for China using Bayesian Multivariate Quantile_on_Quantile with GARCH approach over the period of September 14, 2001 to June 17, 2022 (a total of 4051 days). Results indicate both the links between stock price and oil price and between stock price and exchange rate varying under different combinations of quantiles. GARCH model also indicate that yesterday news and persistence measures varying with current conditional variance under different quantiles. We further estimate half-life of a shock to our whole markets and find out the half-life of a shock range from 0.415 to 4.015 days. Result not found in previous study. Our study has important policy implications for the investors, practitioners, and the government.

AN IMEX-BASED APPROACH FOR THE PRICING OF EQUITY WARRANTS UNDER FRACTIONAL BROWNIAN MOTION MODELS

AbstractIn this paper, the pricing of equity warrants under a class of fractional Brownian motion models is investigated numerically. By establishing a new nonlinear partial differential equation (PDE) system governing the price in terms of the observable stock price, we solve the pricing system effectively by a robust implicit-explicit numerical method. This is fundamentally different from the documented methods, which first solve the price with respect to the firm value analytically, by assuming that the volatility of the firm is constant, and then compute the price with respect to the stock price and estimate the firm volatility numerically. It is shown that the proposed method is stable in the maximum-norm sense. Furthermore, a sharp theoretical error estimate for the current method is provided, which is also verified numerically. Numerical examples suggest that the current method is efficient and can produce results that are, overall, closer to real market prices than other existing approaches. A great advantage of the current method is that it can be extended easily to price equity warrants under other complicated models.

Transactive control of air-conditioning systems in buildings for participation in Singapore’s Demand Response market through load curtailment

Air-conditioning and mechanical ventilation (ACMV) systems account for significant electrical demand within buildings. These systems have large thermal time constants and can be utilized as thermal energy storage. This paper is focused on participation of commercial buildings in Singapore’s Demand Response (DR) programme through curtailment in electricity demand of ACMV systems for financial incentive and power grid benefits. A novel Transactive Energy-based virtual market is proposed for a building where multiple air-conditioning zone agents transact to purchase conditioned-air from central ACMV system. These zone agents consider forecasts of occupancy and outdoor temperatures to submit bids for conditioned-air corresponding to increasing electricity market prices, using a novel dynamic programming approach to utilize the temporal flexibility in cooling demand through pre-cooling. ACMV electricity demand bid is calculated based on net conditioned-air bids by using existing accurate building models in whole-building energy modeling (BEM) platforms corresponding to increasing electricity prices for submission to DR market. Case studies are performed in MATLAB–EnergyPlus co-simulation environment on a benchmark five-zone building model representing a small office building. Results show that the proposed control is effective in providing curtailment of ACMV electricity demand for DR according to real Singapore market price signals, while respecting occupants’ thermal comfort preferences and up to 56% reduction in ACMV electrical power demand is possible for 1 h. Further, revenue analysis shows that DR market participation incentive from 1 h participation would be higher than energy costs for ACMV operation for the entire day, which makes the DR market participation commercially lucrative.

A Study on Farmers’ Perception about Uzhavan App in Select Districts of Tamil Nadu

ICT provides more facilities to farmers by introducing agricultural mobile apps and encourage the farmers for effective farming. These mobile apps provide agriculture related information to farmers in timely and cost effective manner. The present study is carried out to find the farmers perception on uzhavan app which is developed by Government of Tamil Nadu. More than 5 lakh farmers have registered in this app and get various benefits. The uzhavan app has been used by many farmers in gaining more information about agricultural activities. Respondents revealed that dissemination of information through the uzhavan app is valuable and user friendly. The major challenges faced by the farmers were network problem mainly during the ATMA training registration, lack of price details of few commodity and in minor problem time consumes to use all services, app is quite difficult to use due to poor content visibility. From the study, it has been found that majority of farmers had good perception about the uzhavan app and they are satisfied with the features that support them in farming and they also expect some other features need to be integrated in uzhavan mobile app. The uzhavan app provides real time market price of some agricultural commodities and it has greater impact in selling farmers produce at fair price in mandis. Meanwhile, the features of e market online platform helps farmers to connects directly with traders and sell their produce at good price. The availability of farm guide in app provides information regarding fertilizer recommendations practices where most of sample respondents adopted recommended usage level and has positive impact in farming by increasing the yield of farmers.

Comparative analysis of the marginal abatement cost modeling for coal-fired power plants in China

Emissions trading system (ETS) is an effective approach to achieve China's “double carbon” targets. An accurate measurement of carbon MAC (marginal abatement cost) serves as the basic evidence for the stability of ETS and market validity. This paper constructs a comprehensive analytical framework, including four parametric and two non-parametric methods, to analyze the efficiency and carbon MAC of 92 large coal-fired power plants in China. Results show that the average technical efficiency and shadow price were 0.92 and 13.63 RMB/ton, respectively. As verified by Monte Carlo simulations, each method has its cons and pros, while the MAC calculated by the parametric stochastic frontier analysis (SFA) is the closest to the real carbon market price. Additional analyses show that the MAC is positively related with plant scale and negatively related to the provincial carbon intensity targets. This result suggests power plants' technological progress and the asymmetric government subsidies.

Simulation of Financial Market Performance and Algorithmic Economic Model based on Complex Network

At present, traditional macro-financial models such as random walk model and log-periodic power law model in academia cannot explain the stylized characteristics of financial markets. So, we propose a microscopic model that produces stylized characteristics of real financial markets. The model integrates the herding effect, the non-linear relationship of investors and the non-linear structure of the system very well. The research results show that the financial market model established in this paper can simulate most of the characteristics of the real financial market price time series relatively accurately. The model helps to understand the internal operating mechanism of the financial system and provides some basis and reference for the establishment of financial market forecasting models.

Data-driven structural modeling of electricity price dynamics

In many countries, electricity prices on day-ahead auction markets result from a market clearing designed to maximize social welfare. For each hour of the day, the market price can be represented as the intersection of a supply and demand curve. Structural market models reflect this price formation mechanism and are widely used in prospective studies guiding long-term decisions (e.g. investments and market design). However, simulating the supply curve in these models proves challenging since estimating the sell orders it comprises (i.e. offer prices and corresponding quantities) typically requires formulating numerous techno-economic hypotheses about power system assets and the behaviors of market participants. Due to imperfect competition, real market prices differ from the theoretical optimum, but modeling this difference is not straightforward. The objective of this work is to propose a model to simulate prices on day-ahead markets that account for the optimal economic dispatch of generation units, while also making use of historical day-ahead market prices. Inferring from historical data is especially important when not all information is made public (e.g. bidding strategies) or due to difficulty in accurately accounting for qualitative notions in quantitative models (e.g. market power). In this paper we propose a method for the parametrization of sell orders associated with production units. The estimation algorithm for this parametrization makes it possible to mitigate the requirement for analytic formulation of all of the above-mentioned aspects and to take advantage of the ever-increasing volume of available data on power systems (e.g. technical and market data). Parametrized orders also offer the possibility to account for various factors in a modular fashion, such as the strategic behavior of market participants. The proposed approach is validated using data related to the French day-ahead market and power system, for the period from 2015 to 2018.

Potential benefits from participating in day-ahead and regulation markets for CHPs

A combined heat and power plant (CHP) has the ability to provide ancillary services and therefore, can contribute to the improvement of flexibility and reliability of the power system. To motivate CHPs to provide flexibility services, this work investigated the potential benefit for CHPs from participating simultaneously in day-ahead and frequency regulation markets. A new CHP model was proposed, which considers both heat recovery from flue gas condensation and thermal energy storage. Based on the multi-market optimization using real market prices, it can be concluded that providing the frequency regulation service in addition to day-ahead trading can increase the annual profit of CHPs, which was 2.75% for the studied CHP. Meanwhile, the benefit was clearly affected by the heat demand as both high and low heat demand seasons (e.g. in winter and summer) can limit the flexibility provided by the CHP. In addition, the sensitivity analysis was carried out to assess the impacts of key factors, including electricity price, heat demand, cost of electricity, and bid size for frequency reserve services, on the benefit from the participation in both markets. The price difference between the day-ahead and frequency regulation markets and the cost of electricity generation were found to have clear impacts on the benefit of the CHP.

Electricity balancing markets in South East Europe — Investigation of the level of development and regional integration

The development and regional integration of the balancing markets is expected to enhance the use and reduce costs of frequency support services. This is becoming increasingly important as the exploitation of variable renewable energy sources (RES) for electricity generation leads to higher balancing costs.The aim of this paper is to analyse the current state of the legislation related to balancing markets as well as balancing practices in the region of South East Europe (SEE), identify the main barriers, and propose recommendations for development and regional integration of the balancing markets. The investigation was conducted in close cooperation with the Transmission System Operators (TSOs) from eight countries in SEE that are responsible for establishment and operation of the balancing markets in these countries. It consists of six segments addressing various elements of the electricity balancing markets implementation, current practices of reserves/balancing energy procurement, pricing and settlement, as well as the anticipated near future developments. Such a scope of research is unique in the related literature, as most analyses are related to the situation either to EU member states or to Western Balkan (WB) countries. Namely, the region of SEE is distinctive because it is consisted of both EU and non-EU countries. This region faces many challenges in the development of the wholesale electricity and balancing markets and their regional integration.An important conclusion of this research is that low competition and secondary legislation protecting national resources are major obstacles to progress. The creation of a regional balancing market could facilitate competition and allow the creation of real market prices, which in turn would incentivize investment in RES and advanced technologies.

Optimal energy bidding for renewable plants: A practical application to an actual wind farm in Spain

Finding an optimal bidding strategy for a wind farm in the electricity market is not straightforward due to the wind variability. This issue is becoming more relevant as renewable plants are more exposed to market signals. Considering the characteristics of the European markets, operators must submit the energy bidding between 12 and 36 h ahead the actual delivery time. This bidding can be adjusted later in any session of the intraday markets, but sometimes this is not enough to reduce significantly the deviation risk. This paper presents a practical application of a method to analytically calculate the optimal bidding of a wind power plant, based on the maximisation of the income function. The results show that, given the characteristics of the deviation markets in Spain, the optimal bidding strategy depends essentially on the deviation of the system. The proposed technique has been tested and validated in a real application by considering actual data for energy production and forecasts for an operating wind farm in Spain, as well as real market deviations and prices provided by the Spanish system and market operators; analysing the advantages of the proposed optimal bidding strategy over the most plausible option, based on bidding the forecasted energy.

Optimal Design Model for a Residential PV Storage System an Application to the Spanish Case

Self-consumption of photovoltaic energy is being promoted as an effective way for energy consumption in residential households. The European Directive 944/2019 promotes the use of green energy and battery energy storage systems (BESS) for self-consumption and, in Spain, the 244/2019 Royal Decree of the Spanish electrical regulatory framework allows the self-consumption of energy with a photovoltaic (PV) facility for residential use, as well as the injection of the surplus energy into the grid for which compensation will be received. At the same time, new developments in PV and BESS technologies reduce the costs of facilities, a fact that can increase the profitability of self-consumption through PV energy. This study evaluates the profitability of a household PV facility with BESS using a model based on real market prices, hourly data from user smart meters, and their own location; especially, the model gives the best configuration of PV panels power and BESS capacity. The financial indicators taken as reference for the results and conclusions are the Net Present Value (NPV), Internal Rate of Return (IRR), and Investment Return (IR). Our method examines also the effect of the BESS and PV panel costs on the profitability of the facility. Unlike other studies, our model is based on actual (not simulated) demand and price data, and it can be easily extended to other locations and market prices.

Evaluation of Equity-linked structured products and pricing

Based on a unique data set, this research paper examines the pricing of equity-linked structured products in the market. The following section of this paper look at examining a few popular products available in the market, describing their key characteristics, and identifying one such product which will be examined closely for the purposes of determining if the issuing institution has priced the same fairly. The daily closing prices of a large variety of structured products are compared to theoretical values derived from the prices of options traded on the Eurex (European Exchange). This research paper also provides a brief background on the pricing of equity-linked structured products (‘products’) and issues around valuation of these products and look in detail fair pricing of the zero-coupon bond and the basket option. Comparing this with the market price of the instrument I could draw conclusions based on how close the real market price of the instrument is with the recomputed price.

Impact of electricity price forecasting errors on bidding: a price‐taker's perspective

Electricity price forecasting is very important for market participants in a deregulated market. However, only a few papers investigated the impact of forecasting errors on the market participants' behaviours and revenues. In this study, a general formulation of bidding in the electricity market is considered and the participant is assumed to be a price-taker which is general for most of the participants in power markets. A numerical method for quantifying the impact of forecasting errors on the bidding curves and revenues based on multiparametric linear programming is proposed. The forecasted prices are regarded as exogenous parameters for both deterministic and stochastic bidding models. Compared with the existing method, the proposed method can calculate how much improvement will be achieved in the cost or revenue of the bidder if he reduces the price forecasting error level, and such calculation does not require any predefined forecasting results. Numerical results and discussions based on real-market price data are conducted to show the application of the proposed method.

Incorporating Production Task Scheduling in Energy Management of an Industrial Microgrid: A Regret-Based Stochastic Programming Approach

In this paper, a regret-based risk-averse stochastic production task and energy management (PTEM) model for industrial microgrid is proposed, which is applied to a battery manufacturing plant (BMP) microgrid. We incorporate production task scheduling with production constraints in the energy management of industrial microgrid. The general PTEM of industrial microgrids is analyzed and the production processes and energy requirements of a BMP multi-energy microgrid prosumer are presented, in which thermostatically controlled loads (TCLs) in buildings are considered. Then, the regret-based risk-averse PTEM model is formulated as a mixed-integer linear programming (MILP) problem based on stochastic programming considering uncertainties of day-ahead electricity market price and photovoltaic (PV) power output. Conditional value-at-risk (CVaR) is introduced for risk control and utilized for minimizing the expected regret. Numerical studies are carried out to validate the proposed model by comparing with risk-neutral approach and deterministic model based on real market prices from PJM electricity market. The results show that the proposed PTEM approach is effectively risk-averse. In addition, the impacts of total target production task and risk-control parameter on expected cost and regret are analyzed.

Non-parametric Pricing and Hedging of Exotic Derivatives

ABSTRACT In the spirit of Arrow–Debreu, we introduce a family of financial derivatives that act as primitive securities in that exotic derivatives can be approximated by their linear combinations. We call these financial derivatives signature payoffs. We show that signature payoffs can be used to non-parametrically price and hedge exotic derivatives in the scenario where one has access to price data for other exotic payoffs. The methodology leads to a computationally tractable and accurate algorithm for pricing and hedging using market prices of a basket of exotic derivatives that has been tested on real and simulated market prices, obtaining good results.

Stochastic Optimal Energy Management and Pricing for Load Serving Entity With Aggregated TCLs of Smart Buildings: A Stackelberg Game Approach

With the development of demand-side management in the smart grid, load-serving entity (LSE) plays a more important role for consumers, which purchases energy from the electricity market and sells it to consumers. Moreover, aggregated thermostatically controlled loads (TCLs) in smart buildings can provide additional demand response capacities and require efficient energy management methods. This article proposes a stochastic optimal energy management and pricing model for LSE with aggregated TCLs and energy storage based on the Stackelberg game and stochastic programming. The energy management and pricing problem are formulated as a bilevel optimization model. The upper level model aims to maximize LSE's expected profit under market price uncertainties and determines the offering prices to consumers. According to the offering price from upper level model, the lower level model optimizes the power purchasing pattern for consumers of two types of buildings with TCLs: factory and office buildings. The nonlinear bilevel model is reformulated and converted into mixed-integer linear programming using a strong duality theory. The proposed model is validated by numerical studies based on real market prices from the PJM electricity market. In addition, the impacts of energy storage, number of buildings, comfortable indoor temperature limits, and offering price limits on LSE's profit are analyzed.

Usage of P/E earning models as a tool for valuation of shares in condition of global market

With the rapid development of computational technology, non-traditional mathematical and statistical methods have also parallely developed to help simplify and accelerate the computation of certain tasks, or even to solve problems that are usually unsolvable. The aim of this paper is to get closer to the P/E earning models and briefly summarize their calculation and usage options. In the first part of our paper we briefly worked out the theoretical basis of these models. Furthermore, we focused on a detailed description of their calculation and use in calculating the value of shares. In the second part of the work we focused on the application of the calculation of the selected P / E model to Apple inc. in the course of 2018 and compared the data obtained with another instrument to identify the intrinsic value of the action. In the last part we focused on the interpretation and summary of the results of the application. We consider the greatest added value of our contribution to be a theoretical comparison of different types of calculation and deeper application of the selected model to real market prices of Apple inc. with the interpretation of the results obtained. We can conclude that the aim we have set is met and we believe that our article will be a valuable addition to the issue in this area.