Reduce Price Volatility Research Articles

Safe haven between European ESG and energy sector under Russian-Ukraine war: Role of sustainable investments for portfolio diversification

The shortage of oil and gas supply to Europe during the Russia-Ukraine conflict has triggered a price hike in the European energy sector. To mitigate the impact of higher energy prices on consumers, the EU introduced a price ceiling mechanism to curb gas prices from exceeding market norms. This interplay between supply shortages and price controls further heightened volatility in energy market prices. Consequently, our study aims to explore the efficacy of ESG indices as a safe haven against the highly volatile European oil and gas sectors to reduce portfolio losses during conflict. Using advanced analytical techniques such as cross-quantilogram to predict directional predictability, we find that bullish ESG markets are a safe haven against the bearish oil and gas markets in short, medium, and long-term investment horizons. Further, to identify the net receiver/transmitter of spillover between ESG indices and oil and gas sectors, our quantile time-frequency connectedness analysis shows ESG is a net receiver of spillover before the conflict and during wartime. Additionally, we explored the indicator of uncertainty that influences quantile spillover between ESG indices and European oil and gas sectors. We find that uncertainty's role in quantile spillover is significant and asymmetric, and it becomes more volatile during wartime. This feature tends to be amplified during short and long-term spillovers. Finally, the portfolio rebalance strategy suggests that a safe haven portfolio based on a one-month investment horizon yields positive returns during wartime. Hence, this study suggests investors include ESG indices as safe haven assets at times of crisis and for policymakers to understand the role of uncertainties in reducing price volatility and risk contagion among ESG and energy markets.

Can night trading reduce price volatility? Evidence from China's corn and corn starch futures markets

AbstractSince 2013, China's futures exchanges have implemented night trading for agricultural futures to reduce the overnight risk and price jump of futures products by extending trading hours. This study uses difference‐in‐differences (DID) to examine the impacts of night trading on daytime price volatility in corn and corn starch futures markets. On the basis of tick‐by‐tick data for these futures, we find that night trading has significantly reduced daytime volatility and contributed to price volatility stability in the corresponding futures market. Moreover, we make DID estimations for separate daytime sessions and find that the reduction of the daytime volatility takes place mainly during the first trading session. Robustness and placebo tests further support our main conclusions. Our results provide valuable guidance for futures exchanges and regulators seeking to formulate night trading policies for futures and options.

Does public information facilitate price consensus? Characterizing USDA announcement effects using realized volatility

The provision of public information in commodity markets is justified in part by the idea that public information generates consensus among market participants about the fundamental value of the commodity and reduces price volatility. Significant reductions in options-implied volatility following report releases have been presented as evidence of this market-calming effect. We scrutinize this finding in more detail by comparing implied volatility to realized volatility measures from intraday price data. We show that while implied volatility does indeed fall after report releases, realized volatility does not decrease. We measure realized volatility using intraday data and find evidence of much higher volatility on report days only within minutes of the report release. This pattern is consistent with changes in implied volatility being driven by the resolution of uncertainty about the information contained in the report, rather than changes in volatility expectations that may reflect the consensus among traders about forthcoming price volatility.

Risk-managed operation of community integrated energy systems in day-ahead and real-time markets based on portfolio theory

Operation strategy is a critical issue for the community integrated energy system (CIES) to improve its economic performance. However, the uncertainties in energy markets may result in severe deviation and fluctuation in the operation cost. It is challenging to balance the cost and risk in the operation optimization of CIES. This paper proposes a risk-managed operation optimization method based on portfolio theory for the CIES in day-ahead and real-time electricity markets. First, both kinds of markets are modeled as risky investment markets, whose returns and risks are described by the mean value and the variance of the electricity price. Second, the power purchase of the CIES from different markets is modeled as risky investment activities, in which the Markowitz portfolio theory is employed to balance the risk and cost. Third, the optimal portfolio can be obtained by solving the operation optimization problem of the CIES considering the risk preference of the owner. The case studies show that the CIES can reduce price volatility by 10.11% with only a 3.46% increase in cost in the day-ahead market. The proposed method provides a balance between different returns and risk fluctuations according to user preferences, which verified the validity and feasibility.

Oil Market Stabilization: The Performance of OPEC and Its Allies

We examine the influence of OPEC+ on the level and volatility of oil prices. By extending Pierru et al.’s (2018, 2020) modeling framework, we are able to distinguish OPEC’s particular role and impact from that of its Allies—those countries who joined with OPEC at the end of 2016 in the attempt to stabilize the market. In addition to corroborating earlier results regarding the impact of OPEC’s management of spare capacity prior to 2017, we now present an analysis of how the concerted actions by the larger community of OPEC+ members have affected prices, including during the tumultuous period in which the COVID-19 pandemic took hold. We find that OPEC+’s efforts to stabilize the market reduced price volatility by up to one half, both before and during the pandemic. We attribute most of that reduction to OPEC’s own actions whereas the impact of the Allies’ efforts was mostly to support the price level. In that vein, OPEC+’s management of spare capacity barely impacted the average price over the pre-pandemic period, but, by countering the price collapse caused by the pandemic demand shock, lifted the average price by $35.70 from May 2020 through August 2021.

A modelling framework to quantify the power system benefits from ocean energy deployments

It is understood that electricity generation from the waves and tides can be temporally and spatially offset from other, more established variable renewables, such as wind and solar. However, it is less well understood how this offsetting can impact on power system operation. A novel modelling framework has been developed to quantify the potential benefit of including higher proportions of ocean energy within large-scale electricity systems. Economic dispatch modelling is utilised to model hourly supply–demand matching for a range of sensitivity runs, adjusting the proportion of ocean energy within the generation mix. The framework is applied to a 2030 case study of the power system of Great Britain, testing installed wave or tidal stream capacities ranging from 100 MW to 10 GW. For all sensitivity runs it has been found that ocean energy increases renewable dispatch, reduces dispatch costs, reduces generation required from fossil fuels, reduces system carbon emissions, reduces price volatility, and captures higher market prices. For example, including 1 GW of wave displaces up to £137M and 128 ktCO2 over the year of dispatch modelled. Similarly, 1 GW of tidal stream displaces up to £95M and 87 ktCO2. When including 10 GW of ocean energy, dispatch costs reduce by up to 7% and carbon emissions reduce by up to 29%. This analysis has included the development and publication of open source models of the Great British power system.

The role of the emissions trading scheme 2 in the policy mix to decarbonize road transport in the European Union

This article analyzes the recently decided EU-wide emission trading scheme for road transport and heating fuels. The so-called ETS2 is part of the ‘Fit for 55’ policy package, which also includes tighter vehicle emission standards, a reform of energy taxation, provisions to enhance advanced fuel infrastructure and a Social Climate Fund to alleviate financial pressure for low-income households. We argue that the ETS2 should be understood as an element of a broader policy mix, which considers multiple market failures, fairness both within and across EU member states within the institutional constraints of EU policy making. We conclude by discussing specific potential modifications to the design of the ETS2 that could help achieve the EU's climate target in an efficient and equitable way. These include linking ETS and ETS2, reducing price volatility, increasing the size of the Social Climate fund, and clarifying penalties for countries missing targets under the Effort Sharing Regulation.

Challenges in Assessing the Behaviour of Nodal Electricity Prices in Insular Electricity Markets: The Case of New Zealand

In this new era of energy transition, access to reliable and correctly functioning electricity markets is a huge concern for all economies. The restructuring path taken by most electricity markets involves the movement towards green generation structures and the increasing integration of wind and solar photovoltaic energy sources. Furthermore, it involves the electrification of energy systems, which implies a substantial increase in electricity demand levels. It is also important to add that electricity use has been pivotal in achieving efficient productivity levels in many sectors and is thus crucial to boosting economic activity. Nevertheless, this shift in generation structures has raised several challenges in electricity markets, mainly because the electricity produced from wind and solar photovoltaics is intermittent. In turn, adopting green power sources has been claimed to increase electricity price volatility and thus increase pricing risks. Therefore, to ensure that the right market signals are being sent to investors, the behaviour of electricity prices should be carefully assessed. There are three main types of pricing mechanisms commonly used in electricity markets: zonal, uniform and nodal. This study provides a short literature survey on these three pricing mechanisms. Our analysis has revealed that the assessment of the behaviour of nodal electricity price volatility is rarely studied in the literature. This fact has motivated the exploration of this topic and the consideration of the New Zealand electricity market case. The New Zealand electricity market is an energy-only system with no interconnections with other electricity markets. Furthermore, it has plenty of electricity produced from hydropower, which has a high potential to reduce price volatility through its backup role. The nodal pricing mechanism is complex, and data on it are hard to process. This paper elucidates the main challenges in processing electricity big data. Three different procedures to make this data more useable are described in detail. The main conclusions of this paper highlight the need to access easy-to-manage data and identify certain variables that significantly affect nodal prices for data which are unavailable.

Does the Sleman Chili Auction Market Affect the Local, Regional and National Market Prices in Indonesia?

Promoting the horticultural auction market as an alternative outlet is becoming more popular. The horticultural auction market has some benefits, such as reducing price volatility and controlling inflation. This research used a case study in Sleman Regency, which established a horticultural auction market to manage volatile chili prices. The daily price data with ECM-GARCH analysis was used to investigate market integration between the Sleman chili auction market and other markets. The result showed that the Sleman auction market had a beneficial impact on the price decline in the local markets. This impact indicated that the auction market controls inflation at the regional level. However, only 5% to 13% of daily variations of the long-term equilibrium of the auction market to other markets were adjusted. There was information efficiency of the chili prices in Indonesia based on the GARCH model. This study proves that auction markets promote control of macro inflation. This study was the first to manage horticultural product price risk from a chili auction market perspective. Moreover, the model applied in this study expands the ECM-GARCH model to improve the validity of an ECM's significance tests and the efficiency of standard ECM parameter estimation.

Dividen dan Volatilitas Harga Saham saat PSBB di Indonesia : Peran Moderasi Cash Holding

The Large-Scale Social Restrictions Policy (PSBB) as an effort to deal with Covid 19 in Indonesia, has weakened the JCI and triggered share price volatility. Companies use cash holdings to strengthen the ability of dividends to reduce share price volatility for a sustainable negative impact on the company. The aim of the research is to provide empirical evidence of the moderating role of cash holding on the relationship between dividends and share price volatility after the PSBB in Indonesia. The research population is all non-financial companies listed on the IDX in 2020, with a final sample of 223 companies, which were analyzed using moderated regression analysis (MRA). The results of the study show that when the business environment is uncertain due to PSBB, cash holding shows that companies are careful in using cash, creates positive sentiment from investors, strengthens positive signals formed by dividends and reduces price volatility in the capital market.
 Keywords: Dividends; Volatility Stock Price; Cash Holding; Covid 19

Government intervention model based on behavioral heterogeneity for China’s stock market

Active government intervention is a striking characteristic of the Chinese stock market. This study develops a behavioral heterogeneous agent model (HAM) comprising fundamentalists, chartists, and stabilizers to investigate investors’ dynamic switching mechanisms under government intervention. The model introduces a new player, the stabilizer, into the HAM as a proxy for the government. We use the model to examine government programs during the 2015 China stock market crash and find that it can replicate the dynamics of investor sentiment and asset prices. In addition, our analysis of two simulations, specifically the data-generating processes and shock response analysis, further corroborates the key conclusion that our intervention model not only maintains market stability but also promotes the return of risk asset prices to their fundamental values. The study concludes that government interventions guided by the new HAM can alleviate the dilemma between reducing price volatility and improving price efficiency in future intervention programs.

Real-Time Electricity Retail Pricing Dual Optimization With Context-Based Fuzzy Optimal Algorithm

Despite its bright prospect to promote affordable energy, one of the main concerns of real-time retail pricing for electricity is price volatility that would create potential bill shocks especially for low-income consumers. This would demotivate consumers to participate in real-time pricing scheme or to act as responsive participants to reduce peak demand. As a motivation to address this concern, this article proposes dual optimization method with fuzzy optimal algorithm to solve the optimization problem presented in the real-time pricing model with the aims to reduce price volatility and to lower the minimum price further. The fuzzy optimal algorithm applies a context-based fuzzy inferencing and a gradient adjustment to arrive at the optimal retail price for every time interval. Context-based fuzzy inferencing allows fuzzy value redefinition so that the desired level of precision is preserved. Gradient adjustment simplifies the derivation of the optimal retail price via a series of iterations. Simulation results reveal that price fluctuations are able to be reduced which would create stability and avoid undesired price spikes. At the same time, the results confirm that further reduction in the minimum retail price can be achieved which would improve welfare benefits while maintaining the desired level of consumer satisfaction.

Structural policy priorities in agriculture of Russia

The goal is to analyze the current state of Russian agriculture and the main problems of its further development. Designate indicators and parameters of macroeconomics that must be taken into account when assessing structural changes. Propose an algorithm for the formation of structural policy in Russian agriculture, justify the need and main problems of its implementation. Methods – the work on the article was carried out on the basis of the application of general scientific empirical methods in the framework of comparative, logical and statistical analysis, as well as through the analysis of structure and dynamics, tabular and graphical interpretation of information, etc. Relevance – it is noted that by 2020, the recovery growth in agricultural economy, which began at the turn of the century, has been completed, which made it possible to overcome the decline in production in the 1990s, ensure the country's food independence and create conditions for the transition to export-oriented development. At the same time, the indicators of the country's self-sufficiency in a number of products (milk, vegetables and melons, potatoes, fruits and berries), which were established by the Food Security Doctrine of the Russian Federation, have not been achieved. The share of spending on food in the family consumer budgets remains high. The development of agriculture is highly dependent on the supply of foreign technologies, machinery and equipment, seeds and breeding material, which creates risks for food security. The growth of agricultural production has little effect on the solution of social problems of the countryside. The intensification of agricultural production leads to the aggravation of environmental problems. Results – in the framework of this article, the directions of structural policy in Russian agriculture are considered, according to which the strategic documents of industry development are being adjusted. The author also considers the main directions of agricultural and rural policy aimed to solve these problems: stimulating investment in the industry; improvement of scientific and technical support for agriculture; measures to reduce price volatility in agri-food market; overcoming the departmental approach to rural development and diversifying the rural economy; measures to improve soil fertility and ecological situation in agriculture. Conclusions – the areas of improvement of agricultural policy which are considered in the framework of the article, the work on which is actively being carried out today by AIC management bodies, will play an important role in the development of agro-industrial complex of Russia. At the same time, it is necessary to ensure compliance between the tasks set for AIC to achieve the country's food security, increasing export potential of domestic agri-food products, sustainable development of rural areas and envisaged measures, as well as financial resources which are allocated for the development.

Food price volatility and household food security: Evidence from Nigeria

Food prices vary seasonally, particularly in areas with rainfed agricultural production and imperfect markets, and are also subject to volatility arising from macroeconomic and climatic shocks, such as global supply shocks and abrupt policy changes. The specific nature of these relationships remains a pressing empirical question, particularly in contexts where food insecurity is prevalent, prices are subject to diverse sources of variation, and governments are seeking policy options to reduce price volatility. We use panel data from Nigeria to investigate the effects of non-seasonal food price volatility, in particular unexpected increases in prices, on household food security. Accounting for substitution effects and focusing on both domestic and imported rice—key components of the Nigerian diet—we find that imported rice price increases are damaging to both dietary diversity (downward impact) and the food share of consumption expenditure (upward impact), while impacts of domestic rice price volatility are ambiguous. We find differential effects by wealth status that vary across indicators of food security: an increase in the price of imported rice increases food share more among poor households than rich households, and decreases dietary diversity more among rich households than poor households. Our findings point toward the importance of improving food security by mitigating the effects of global shocks on imported food prices, and also highlight the data challenges and complexity involved in developing precise answers to these important policy questions.

Potential for Nd and Dy Recovery from End-of-Life Products to Meet Future Electric Vehicle Demand in the U.S.

Rare earth elements (REEs) such as Neodymium (Nd) and Dysprosium (Dy) are used in Rare Earth Permanent Magnets (REPMs). Neodymium-iron-boron (NdFeB) magnets offer the strongest magnetic field per volume among all the magnets available in the market, which enables lightweight and compact product designs. NdFeB magnets have thus become indispensable in emerging clean technologies such as wind turbines and electric vehicles (EVs). Global demand for these renewables is increasing due to environmental considerations, energy security, and consumer demand. However, China’s dominance in REE production and processing technology has led to concerns pertaining to supply chain risks. This is especially the case for the automotive industry that is experiencing a major shift from traditional internal combustion engines to EVs that employ these REPMs. The number of EVs on U.S. roads is projected to reach more than 18 million in 2030 up from 1.4 million in 2019. In order to mitigate supply chain brittleness, and thereby potentially reduce price volatility, secondary REE supply sources from end-of-life (EoL) products may be a viable option. This study quantifies the recycling potential of Nd and Dy from EoL EVs, HDDs and MRIs in the U.S. Factors used in the analysis were number of units manufactured each year, NdFeB magnet mass in each unit and REE composition of magnets employed. Using EV production forecasts, we estimate how much of the future Nd and Dy demands can be met by secondary supply from EoL products.

A Coordination Mechanism For Reducing Price Spikes in Distribution Grids

Recently, given the increased integration of renewables and growing uncertainty in demand, the wholesale market price has become highly volatile. Energy communities connected to the main electricity grid may be exposed to this increasing price volatility. Additionally, they may also be exposed to local network congestions, resulting in price spikes. Motivated by this problem, in this paper, we present a coordination mechanism between entities at the distribution grid to reduce price volatility. The mechanism relies on the concept of duality theory in mathematical programming through which explicit constraints can be imposed on the local electricity price. Constraining the dual variable related to price enables the quantification of the demand-side flexibility required to guarantee a certain price limit. We illustrate our approach with a case study of a congested distribution grid and an energy storage system as the source of the required demand-side flexibility. Through detailed simulations, we determine the optimal size and operation of the storage system required to constrain prices. An economic evaluation of the case study shows that the business case for providing the contracted flexibility with the storage system depends strongly on the chosen price limit.

Performance evaluation of the Bayesian and classical value at risk models with circuit breakers set up

Circuit breakers, like price limits and trading suspensions, are used to reduce price volatility in security markets. When returns hit price limits or missed, observed returns deviate from equilibrium returns. This creates a challenge for predicting stock returns and modelling value at risk (VaR). In Tehran Stock Exchange (TSE), the circuit breakers are applied to control for the excess price volatilities. This paper intend to address which models and what methodology should be applied by risk analysts to calculate the VaR when the returns are unobservable. To this end, we extend Wei's (2002) model, in the framework of Bayesian Censored and Missing-GARCH approach, to estimate VaR for a share index in TSE. Using daily data over June 2006 to June 2016, we show that the Censored and Missing- GARCH model with student-t distribution outperforms the other VaR estimation metods. Kullback-Leibler (KLIC), Kupic (1995) test and Lopez score (1998) outcomes show that estimated VaR by Censored and missing- GARCH model with student-t distribution is of the most accuracy among the other GARCH family estimated models.

Performance evaluation of the Bayesian and classical value at risk models with circuit breakers set up

Circuit breakers, like price limits and trading suspensions, are used to reduce price volatility in security markets. When returns hit price limits or missed, observed returns deviate from equilibrium returns. This creates a challenge for predicting stock returns and modelling value at risk (VaR). In Tehran Stock Exchange (TSE), the circuit breakers are applied to control for the excess price volatilities. This paper intend to address which models and what methodology should be applied by risk analysts to calculate the VaR when the returns are unobservable. To this end, we extend Wei's (2002) model, in the framework of Bayesian Censored and Missing-GARCH approach, to estimate VaR for a share index in TSE. Using daily data over June 2006 to June 2016, we show that the Censored and Missing- GARCH model with student-t distribution outperforms the other VaR estimation metods. Kullback-Leibler (KLIC), Kupic (1995) test and Lopez score (1998) outcomes show that estimated VaR by Censored and missing- GARCH model with student-t distribution is of the most accuracy among the other GARCH family estimated models.

Effects of Stockholding Policy on Maize Prices: Evidence from Zambia

Abstract Many countries in the developing world use public stockholding programs to stabilize prices for both farmers and consumers. Governments directly purchase and store staple grains, and then sell them to processors or consumers, often at heavily subsidized prices. Despite the substantial costs of these stockholding programs, little is known about their effectiveness in mitigating retail price swings. This paper estimates the effects of purchase and sales activities of the Zambian Food Reserve Agency (FRA) on monthly maize market prices across more than thirty markets in Zambia from 2003 to 2008. To deal with the endogeneity in purchases and sales, we use predicted FRA purchase and sales targets as instrumental variables. Controlling for other policies, we find evidence that FRA activities stabilize retail prices in major district markets within the cropping year. Results show that FRA purchases raise local prices for surplus maize producers about 5 % on average at the time of harvest, and that FRA sales help lower the prices to consumers during the lean season up to 7 %. However, we find limited evidence that the FRA is able to reduce price volatility between years.

The Influence of Supply Management on Farmland Values in Ontario

AbstractSupply management programs for Canada's dairy and poultry sectors are intended to reduce price volatility and provide fair returns for producers. However, the reduced risk and higher returns for these producers may contribute to higher farmland values. This paper estimates the impact of supply management on farmland values in the Canadian province of Ontario using a hedonic approach based on over 25,000 farmland sales. The results indicate that farmland values have been positively impacted by supply‐managed livestock density. In addition, a recent policy change ‐ a cap on the price of dairy quota ‐ is found to further contribute to increased farmland values.