Market Price Volatility Research Articles

The Effect of Transmission Constraints on Electricity Prices

Electricity prices in an interconnected market are influenced by the occurrence of transmission constraints. Until relatively recently, however, the important effects of transmission constraints on both the trajectory and volatility of electricity prices have not played a large role in empirical models of prices. This paper explores the contribution to price volatility in the Queensland electricity market made by transmission constraints. It is found that robust estimation techniques are necessary to guard against incorrect inference in time series models using electricity price data in which severe price spikes occur. The main empirical lesson is that transmission constraints contribute significantly both to the level and variability of price and consequently the performance of a price forecasting model is likely to be improved by incorporating information on transmission constraints. While the general tenor of this conclusion will come as no surprise, the extent and the importance of these effects found in this paper for forecasting price and for computing summary measures like Value-at-Risk serve as a timely reminder to practitioners.

Electricity market short‐term risk management via risk‐adjusted probability measures

This study presents an iterative algorithm for modelling the mean-risk model with the conditional value at risk (CVaR). The algorithm is based on the Lagrangian relaxation decomposition, and its main advantage is that it allows removing the coupling between the scenarios due to the constraints used to model the risk. At each stage of the algorithm, a risk-neutral stochastic optimisation problem is solved with the risk-adjusted probabilities that substitute the original ones. The study presents the application of the proposed iterative CVaR algorithm to two different short-term problems where the decision makers are exposed to a high volatility of electricity spot market prices. In the first problem, a time horizon of 1 week is taken into account and a future physical contract is employed as a hedging mechanism. The second problem includes a very detailed formulation of the unit commitment problem. The numerical application is based on realistic data of the Iberian electricity market, where the algorithm has shown a good performance in terms of accuracy and computational time. In addition, this study provides a criterion for selecting the value of the parameters used to implement the CVaR model.

Effect of Crude Oil Futures Trading on Spot Market Volatility: A Panel Data–Based Counterfactual Prediction Analysis

ABSTRACTBased on panel data, a recently developed method of counterfactual prediction analysis is used in this article to analyze how the launch of Tokyo and Dubai crude oil futures influences the price volatility in the spot market whose underlying instruments are corresponding futures. Analysis results show that the launch of crude oil futures can speed up information integration into market system and reduce the volatility of the crude oil spot market, although the crude oil futures market is characterized mainly by speculative factors. The offshore underlying instrument does not have substantial influences on future contracts, while the scale of the futures market has a significant effect on the spot market volatility.

Investigating Linkages between U.S. CDS Spreads and Both Equity Market Price and Equity Market Volatility Channels: A Quantile Cointegrating Regression Approach

We investigate the behavior of daily aggregate U.S. CDS spreads during almost six years. Existing linkages between credit and equity markets advocate the use of market price and volatility channels as explanatory factors. In particular, the evolution of CDS spreads is analyzed along with the level of the equity market and a well-chosen implied volatility index. We describe such robust (to spurious correlation) relationship with the quantile (cointegrating) regression approach. It allows for describing distributional patterns of CDS spreads in the light of the equity market’s influence. Going beyond a simple mean relationship, the quantile regression tool quantifies accurately the linkages between credit and market risks. Such powerful econometric approach handles extreme quantiles (i.e. extreme CDS values) and their behavior with respect to the equity market’s impact. Moreover, heteroskedastic patterns such as time-varying variance, but also autocorrelation, skewness and leptokurtosis are captured. Incidentally, the sensitivity of aggregate CDS spreads to equity market price and volatility channels vary across quantiles. Being quantile-dependent, the sensitivity of credit risk with respect to (equity) market risk exhibits asymmetric responses to equity market shocks. A complementing sub-period analysis investigates potential regime shifts in estimated quantile cointegrating regressions. Quantile cointegrating coefficients vary over time and quantiles, and exhibit different magnitudes across sub-periods. However, the nature of the full sample-specific impact of equity market on CDS spreads is mostly preserved across sub-periods. As a result, the assessment of credit risk with respect to the impact of market risk and the nature of corresponding linkages differ from one quantile to another. Such methodology can help enhance risk management processes, among which value-at-risk (VaR) and expected shortfall. In this light, a scenario analysis and risk signaling application are proposed for credit risk management prospects. Under specific risk levels, credit risky situations are described conditional on the equity market’s impact over time, and related expected aggregate CDS spreads are computed.

Estimating the cost of pre‐harvest forward contracting corn and soybeans in Illinois before and after 2007

AbstractForward contracting historically has been the principal risk management tool of crop farmers in the United States. We use pre‐harvest forward contract bids from 1977 to 2013 in Illinois to estimate the cost of forward contracting corn and soybeans. Prior to 2007, it cost 1.55% of the October spot price or 3.74 cents/bushel on average to forward contract corn at the end of February. In 2007–2013, a period of high price volatility, the average cost increased to 3.31% or 16.40 cents/bushel. In the soybean market, before 2007 the average cost was 0.77% or 6.26 cents/bushel and thereafter increased to 1.46% or 15.62 cents/bushel. Default risk does not appear to be a determinant of forward contracting cost. However, evidence suggests that the higher cash flow risk associated with volatile market prices is likely to be the main driving cause of increasing forward contracting costs observed after 2007. [EconLit citations: Q11, Q13].

Beyond the day-ahead market – effects of revenue maximisation of the marketing of renewables on electricity markets

The proportion of renewable energy has rapidly increased in many countries during the last few years. Due to the specific characteristics of variable renewables, this development influences the price on electricity markets as well as flexibility requirements in the electricity system. New developments regarding market liberalisation and support schemes for renewables encourage the active participation of renewables in the electricity market. This paper analyses the effects of such a participation of renewables in different electricity market segments. In particular, we investigate how the active marketing of renewables on the day-ahead, intra-day, balancing and futures markets dampen their effects on markets and systems. Using German data for 2013, we determine the effect of direct marketing on average market price levels and price volatility, the possible contribution of renewables to balancing, the profitability of flexible generation from biomass, and the additional revenues that renewables can generate from participating in different markets. Price effects of shifting renewables between markets, and limits in intra-day market liquidity are included in the assessment.

A study on price volatility in the aquaculture market using value-at-Risk (VaR)

ABSTRACTAquaculture production is increasingly important in seafood production and is currently the fastest growing food production technology worldwide. To continue the industry growth, price risk management is an essential part in creating successful projects and sustainable business operations. This research uses trade data on fish and invertebrate prices, and evaluates the relative price uncertainty from farmed and captured products. Moreover, we consider a set of species groups (fish, invertebrates), species’ families (e.g., Salmonidae, white fish and crustaceans), and individual species (e.g., salmon, seabream and prawns), and evaluate their price volatility over time using Value-at-Risk (VaR). The results indicate that the introduction of aquaculture production to a species’ total supply will reduce price volatility. Consequently, incentives and regulations should support research and development of new aquaculture species.

Comportamiento de precios de mercados y análisis de volatilidad, para durazno (<i>Prunus persica</i> [L.] Batsch.) producido en Boyacá, Colombia

En la actualidad, se encuentran diferentes estudios de caducifolios, y en este caso de durazno en temas como producción, cosecha, poscosecha, mercados. Sin embargo, al desarrollar la formulación de los proyectos de inversión, no se conoce el comportamiento del precio de la fruta en los últimos años, en los mercados más representativos del país. Es así como se desarrolló esta investigación centrada en el análisis de los precios de durazno en tres mercados de Colombia: (a) Central de Abastos de Bogotá, (b) Mayorista de Antioquia, Medellín y (c) Retén sur de Tunja, con el objetivo de comprobar si durante el período 2006 al 2011, se ha presentado estacionalidad y volatilidad en los precios de mercados, más aun cuando los pequeños productores manifiestan que cada vez este agronegocio es menos rentable y al elaborar nuevos proyectos para invertir en esta especie, se presenta la dificultad en la asignación de los precios de venta. Este aspecto incrementa el riesgo en la toma de decisiones para los productores. El estudio inició desde el análisis de las generalidades de la producción de caducifolios y del durazno, producto que se concentra principalmente en el departamento de Boyacá, Colombia, en agroempresas de tipo minifundistas, de economía campesina. Continuó con la relación de datos de precios por kg/mes, entre el año 2006 y 2011. En los tres mercados, la metodología utilizada fue un análisis exploratorio de los precios por medio del Análisis Espectral Singular, utilizando el Método de Loess. Además, se empleó la metodología de Box y Jenkins. Se logró determinar el comportamiento de tendencia y estacionalidad en los precios del durazno. De otra parte, se identificó que el comportamiento estacional y de tendencia no está presente en los mercados Corabastos de Bogotá y Central mayorista de Antioquia, sí se encontró estacionalidad en el mercado de Tunja. Cabe resaltar que la volatilidad de los precios no se observó en los tres mercados estudiados, se determinó que el precio promedio actual de duraznos per kg en el mercado de Retén sur de Tunja es de $1.800 (USD 0,60) y de $3.500 (USD 1,17) en los mercados de Bogotá y Medellín.

Corporate bond trading in Indonesia: an empirical study of the role of volume and volatility

We examine the relationship between trading activity and price volatility in Indonesia corporate bond market using 2010-2014 data. We also investigate the role of liquidity and credit quality in this relationship. We find that volume and trading frequency have a positive and significant correlation to bond volatility, which is consistent with the information-based model. The results also suggest that liquidity plays an important role in their relationship, in which illiquidity causing stronger relationship between trading volume and price volatility. Credit quality, however, do not have similar effects on volatility where AAA-rated bonds tend to have higher volatility.

Small Systems, Big Targets: Power Sector Reforms and Renewable Energy Development in Small Electricity Systems

The dominant focus of much policy attention of late has been on the suitability of electricity market reform carried out under the ‘standard’ or prescriptive approach – the end point of which is market liberalization – for the integration of intermittent renewables. There is now a growing consensus around the argument that traditional energy-only electricity markets where prices are based on system marginal cost cannot function efficiently with both fossil fuels and renewables, potentially resulting in market disruptions and price volatility. Consequently, most policy discussion has focused on finding ways to successfully integrate the two through adopting advanced competitive solutions (such as the use of capacity markets in addition to energy-only markets) in larger systems. We however argue that the effectiveness of competition is limited by the size of the system – i.e., there is a minimum threshold size (and other characteristics such as tropical locations, lack of access, and the prevalence of remote consumers) under which competition will not produce expected outcomes, and require distinctive policy solutions. This paper contributes to the policy discourse by discussing the reform of small electricity systems to integrate renewable energy via the means of three case studies: Nicaragua, El Salvador, and their application to Australia’s Northern Territory. The paper draws some policy lessons that can be considered for other small electricity systems in island economies and territories across Africa, the Caribbean, and the Asia-Pacific, that are pursuing a triad of objectives including electricity sector reform, large-scale renewables development and improving energy access.

ТНЕ WORLD OIL MARKET: THE SEARCH FOR BALANCE IN THE NEW "OIL" REALITY

The article provides an analysis of change of the world oil market in the face of new "oil" reality. Factors of formation of new "oil" reality in the global world defined. Scientific background and current state of research of the problem are described. It is shownthat in the Russian and foreign literature the considerable attention is paid to the analysis of dynamics of the quantitative variables characterizing fluctuations and shocks in the oil market. At the same time the search for balance in the new "oil" reality are not considerably investigated yet. The proposed approach allows toreveal the substance of the transformation of the world oil market, to assess the changes in the oil market with the development of rhenium in terms of efficiency and functioning of the mechanism, the prospects of price volatility in the oil market. The main directions of transformation of the oil market are follows. Development of a subject basis of the oil market due to changes of a role of the main market players whose structure includes the USA, Saudi Arabia, Russia now. The impact of regulatory factors complex in the oil market towards equilibrium, which include activity of OPEC, supply of shale oil, future market,activity of the uniform regulator and national regulators. Transformation of the oil market in the direction of perfection of the competitive relations, achievement of optimum market balance as a result of coordination and interaction of interests of participants of the global oil market.

Unia Europejska wobec bezpieczeństwa żywnościowego

The main objective of this paper is to present the attitude of the European Union to the issue of food security. Price volatility in the global market has a significant impact on the economic security of the participants. This particulary applies to commodity price volatility. Excessive volatility in commodity price effects both producers and consumers has a serious implication for food security. In the context of globalisation in a period characterized by sudden changes in food prices, such as for 2007–2008, the food situation in many poor developing countries worsend. It was expected that the increase in food prices in 2010 may lead to the further spread of the phenomenon of malnutrition and further intensification of tensions and unrest among the weaker consumers in the world. An important role in changing this situation can be played by the World Trade Organisation (WTO) and European Union. Food security issues also for the European Union are very important and actual both from theoretical and practical point of view.

Asset Market Linkages in a Regime Switching Environment: Evidence from Commodity and Stock Markets in India

(ProQuest: ... denotes formulae omitted.)1.IntroductionCommodities have emerged as a significant mode of alternative investment today all over the world. While they have been in existence in many of the developed markets, commodities, in Indian context have seen a brisk growth in the last few years, which is quite visible in the volumes of contracts traded. Majority of the Literature on Indian commodity markets has focused on the issue of market efficiency, price volatility, price discovery, market integration, Contango and Normal backwardation and a number of studies have been done in this context. These markets were found to be efficient and doing well on price discovery Ahuja (2006); Bose(2008); Karande (2006); Sahi & Raizada (2006); Nath & Lingareddy (2008) ,Brajesh Kumar(2009); Srinivasan (2012) but relatively poorly on hedging effectiveness (Bose (2009); Kumar (2010); Yaganti and Kamaiah 2012);Gupta & Singh(2007); Aggarwal N, Jain S, Thomas S (2014). During the crises of 2008, when the stock markets were performing badly and the SENSEX was giving a return of 0.7%, agricultural and metal indices of MCX were providing returns to the extent of 18% and 17% respectively. It was during that time commodity markets attracted the attention of the Indian investors and garnered an image of a separate asset class that provided diversification benefits. Thus, it becomes imperative to delve deep into commodities and investigate its linkages with other asset classes in the Indian Context.In context of developed commodity markets, a number of researchers have confirmed that commodity prices tends to move in opposite direction with equity markets and exhibit zero or very low correlation with them Bodie & Rosansky(1980); Edwards & Park (1996); Lee,Leuthold. & Cordier(1986) ; Schneeweis and Spurgin (2000); Jensen et al. (2002) ;Henry G. Jarecki 2007); Anson & Mark (1999) Jensen, Johnson & Mercer,(2009); McCown and Zimmerman (2006);Gorton & Rouwenhorst(2006); Jalil, Ghani, Daud, & Ibrahim (2009); Park & Ratti, (2008); Wang, Wang, & Huan (2010). In addition, several researchers have also confirmed that returns for commodities show positive correlation with unexpected inflation and exhibit better performance under high inflation times Greer (1978); Bodie (1983); Halpern and Warsager (1998); and Gorton, Hayashi & Rouwenhorst (2007). However, in Indian context, this concept of the comovement of Commodity and equity markets remains relatively unexplored. The only studies in this context was done by Mishra (2008) and Brajesh kumar (2008) who investigated the portfolio performance of Indian commodity markets and found favourable results in context of diversification benefits of commodities.One of the major drawbacks of the aforementioned studies is that they have assumed a symmetric and linear relationship between commodity and equity markets and examined their co-movement solely on the basis of correlation. These studies assume the presence of uniform economic state throughout the duration of the study. Researches done by Hui-Ming Zhu , Keming Yu (2012); Hsiang-Tai Lee(2010); Ramaprasad & Shawkat (2011) ; Levy& Kaplanski (2015) confirmed that the returns from commodity futures and stock market do not show a continuous trend but exhibit time varying behaviour i.e. the returns of stocks might be higher in certain economic conditions while it may fall as the economic environment changes due to financial crises, oil price rise, rupee depreciation etc. Similarly the returns from commodities is also subject to variation with changes in economic conditions Wai Mun Fong , Kim Hock See (2002); Minh T. (2009); Nikos & Panos (2011); Kuang-Liang Chang (2012) ; Shiu-Sheng Chen (2010); Lin & Wesseh (2013) ; Gargano,, Pettenuzzo, & Timmermann (2014) due to which the basic assumptions of stationary and linearity of time series models gets refuted.Although in context of developed commodity markets, recently a number of researchers has ve pointed out that correlations between commodity and other asset classes is time varying and different in bearish and bullish markets, restrictive and expansive monetary policy, pre and post crises ,time varying interest rates Jensen et al. …

Informed trading, market efficiency and volatility

We establish relationships that have proved difficult to capture in financial markets, between informed trading, efficiency and volatility. We examine the efficiency and volatility of market prices in 6058 parallel horserace betting exchange and bookmaker markets (1.8 million price points). We find that informed trading is associated with increased efficiency and volatility.

Volatility Dynamics in Oil and Oilseeds Spot and Futures Market in India

Executive Summary India occupies the fifth position in the vegetable oil economy of the world. The demand for oilseeds and vegetable oil has far exceeded the domestic output necessitating huge imports. Futures market helps to bring price stability for the development of the underlying physical market. The present study investigates the volatility dynamics in spot and futures markets of select oil and oilseeds commodities. The objectives of this article are to study (a) the information transmission process between spot and futures markets, also called volatility spillover and (b) the impact of futures trading activity on the volatility of physical market prices. The commodities selected from oil and oilseeds segment are refined soya oil, mustard seed, crude palm oil, and mentha oil. The study uses basic Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model to capture volatility in prices of the selected commodities. Bivariate GARCH model makes use of information in the history of two different markets for testing volatility spillover between two markets of the same underlying commodity. The relationship between futures trading activity and spot price volatility is investigated for examining the impact of futures trading activity on the volatility of underlying spot market. Two variables, viz., futures trading volume and open interest are decomposed into expected and unexpected components and are taken as a proxy for the level of trading activity. The contemporaneous and dynamic relationships are studied with the help of augmented GARCH model and Granger causality, respectively. It is observed that there is an efficient transmission of information between spot and futures markets but it is the spot market which leads to the flow of information to futures and hence causes greater spillover of volatility. The spot market has a greater impact on the volatility of futures market, indicating that informational efficiency of oilseeds spot market is stronger than that of the futures market. The contemporaneous and dynamic relationship between spot price volatility and futures trading activity tested with econometric models provide evidence of the destabilizing impact of an unexpected increase in futures trading activity (volume or open interest) on the spot price volatility in three out of four commodities studied. This indicates that badly informed traders present in futures market are destabilizing the underlying spot market by inducing noise and lowering the information content of prices.

Mixed-integer Programming of Stochastic Hydro Self-scheduling Problem in Joint Energy and Reserves Markets

This article presents a stochastic model for self-scheduling of a purely hydro generating company participating in the day-ahead joint energy and reverse market aimed at maximizing the profit. In the proposed framework, the mixed-integer non-linear programming of the hydro self-scheduling problem is converted into mixed-integer programming. The hydro self-scheduling problem with uncertainties, such as outages of generation units and volatile market prices, is modeled as a stochastic mixed-integer programming problem. Random 24-hr scenarios are generated using Roulette wheel mechanism and lattice Monte Carlo simulation methods. Afterward, the proposed stochastic model is decomposed into deterministic optimization sub scenarios. For great accuracy, multi-performance curves are employed in the modeling stage. Moreover, wide-ranging parameters are taken that result in an absolutely real outcome, e.g., head dependent reservoirs, start-up cost, water discharge limits, initial and final volume, water balance constraints, spinning and non-spinning reserve, spillage of reservoir, and a cascade hydro plant. Finally, for a test system with eight hydro plants, the bilateral contracts are evaluated in terms of performance indices to demonstrate the effectiveness of proposed model.

Beyond CAPM: estimating the cost of equity considering idiosyncratic risks

The present study proposes a new evaluation approach aimed at estimating the cost of equity through standardized models which consider an innovative set of firm-specific information on the main unsystematic risks which are typical of any business. Our objective is extending the Capital Asset Pricing Model (CAPM) by defining a standard formula for quantifying the premium for certain idiosyncratic risks as a function of a new set of firm-specific quantitative information. We define two econometric models, for listed and non-listed firms respectively, which consider five idiosyncratic risk factors: firm size, value factor, operating risks, financial structure and stock market price volatility. The models were tested on a sample of European non-financial companies. The empirical results show that while the CAPM systematically underestimates the cost of equity, the proposed models correctly estimate its expected value; furthermore, they show a slight improvement also in terms of estimates’ volatility. Due to their efficacy and ease of use, the proposed models represent a valid practical tool for investors, analysts and professional evaluators. This work contributes to the existing literature by proposing a typologically innovative extension of the CAPM set of explanatory variables, defining and testing new models for the estimation of the unsystematic risks’ spread of the cost of equity based on an original set of firm-specific accounting and market information.

A closer insight into the causality between short selling trades and volatility

This study addresses the Granger causality between short selling activities and stock price volatility in the US stock market, utilizing daily data and advanced methodologies.The results denote a bilateral causality between the short selling trades and the volatility of price changes in the US stock market at individual stock as well as at market level. The bilateral causality relationship persists during different market conjunctures.The findings imply that measures to curb excess price volatility stemming from short selling trades were relatively ineffective and the policy-makers need to impose more stringent restrictions to prevent market destabilization.

機会制約付き最適化問題におけるFractile modelを用いた市場価格変動リスクを考慮した小売業者の電力調達問題

This paper presents a stochastic decision making framework of the retailer for the power procurement in the deregulated electricity market taking into account the risk induced by the volatile market prices. Unlike conventional related literature, the paper incorporates the three types of trades, which are a forward contract, a spot market, and a real-time market for adjusting the imbalance, in the transaction model with rational responses of the consumers to the selling prices offered by the retailer. For the risk hedge using the forward contract, it is quite significant to reflect the risk attitude of the retailer on decision making in market transactions. In the literature, the weighting method is often used to formulate the retailer's decision making for the power procurement. In the weighting method, however, it is difficult to determine both the weighting coefficients and the confidential level associated with the risk so as to reflect the risk attitude of the retailer adequately, particularly in the bi-level programming problem. In this paper, in order to naturally model the retailer's decision making, we employ the fractile model in which the target variable is maximized subject to the probability that the profit is not less than the target variable exceeds a given assured level given by the retailer according to the risk attitude. Through the computational experiments, we demonstrate the retailer's behavior with satisfactory level for the profit and risk in the deregulated electricity market.

Volatility Modelling in Crude Oil and Natural Gas Prices

Abstract This study analysis the return volatility of spot market prices of crude oil (WTI) and natural gas (Henry Hub) for two different terms which cover 02.01.2009 – 28.04.2014 and 04.01.2010-28.04.2014 with different version of the GARCH class models such as GARCH, IGARCH, GJRGARCH, EGARCH, FIGARCH, FIAPARCH. In particular, the main idea of employing various GARCH models is to determine which one of these linear and nonlinear asymmetric models perform more accurate in terms of ingroups and intergroups activities. Therefore, the main purpose of the paper is to determine a model which ensures to get a maximum return with response to the minimum loss for returns of the investments held by individual investors and fund managers, private sector budget planning decision makers, and state agencies forecasting about macroeconomic indicators. To do this, the ten-days out-of-sample volatility forecasts of Loss Functions to capture the forecasting performance of GARCH class models and to prevent forecasting errors with efficiency hedge ratio in energy market are being considered. For two periods, asymmetric and integrated GARCH models give relatively more accurate performance than other available models. Respectively, for the first period, minimum loss model is FIGARCH-BBM (SST) and for the second period, is EGARCH(GED) for WTI crude oil series in consideration of MSE and MAE criterion. Similarly, for the first period minimum loss model is FIGARCH-BBM (SST) and for the second period, is EGARCH(GED) for Henry Hub natural gas series in consideration of MSE and MAE criterion. This study has potential recommendations for investors from developed and developing countries, which differs it from the current studies.