Expected Spot Price Research Articles

Strategic logistics service procurement in shipping supply chains

This paper develops a game-theoretic model to explore the strategic procurement of logistics services in a shipping supply chain, where a freight forwarder canvasses orders and provides one-stop service to shippers. The forwarder faces a decision between in-house and outsourcing modes for inland logistics services, as well as the choice to purchase ocean shipping services through a forward agreement or in a spot market. The spot prices of inland logistics and ocean shipping services are positively correlated with shipper demand, meaning that changes in shipper demand can affect the spot prices. Our analysis indicates that the responsiveness of spot prices could be beneficial to the carrier but detrimental to the forwarder. Hence, the forwarder would adopt a forward agreement to purchase ocean shipping service even when the forward price is slightly higher than the expected spot price. Moreover, a forward agreement could be reached if the market size is relatively small. Finally, we show that the forwarder should adopt the in-house mode for inland logistics services, even when the in-house mode cost is higher than the expected outsourcing cost. This study contributes the literature by revealing how the correlation between shipper demand and spot prices for two types of logistics services affects the procurement decisions of a freight forwarder.

Financialization and speculators risk premia in commodity futures markets

J.M. Keynes coined the term normal backwardation, a situation where a futures price for a particular expiry month is less than the expected spot price for that month. He argued hedgers pay speculators a risk premium, giving rise to normal backwardation. We study the behavior of commodity futures before and since financialization of the markets, which started about 20 years ago. We find the poor returns to managed futures in recent years are likely due to the impact of financialization and the associated outside money suppressing the futures risk premium.

The agricultural futures market in low development countries: a policy to respond to the volatility of prices?

This work discusses the possibility, or rather the effectiveness, of the use of agricultural futures as a means of hedging to minimize exposure to price risk. In particular, the analysis refers to "low-development countries" (LDCs), countries in which agricultural products play a prominent role and in which the process of market liberalization, which took place following the removal of state intervention, is determining an increasing exposure to price volatility. Knight's uncertainty is said to make both producers and speculators more risk averse, hence more conservative. In particular, when the futures price is well above the expected spot price (adjusted for the Knightian uncertainty), the optimal position for the producer is a total hedge of his production, while the optimal position for the speculator consists in not operating at all in the market. We can limit ourselves to observing that if a single producer and a single speculator operate in the market, the equilibria that can be reached are three: of complete exchange, of non-exchange and of partial exchange. The possibility of obtaining one of the three equilibria depends on the degree of risk aversion and the degree of Knightian uncertainty possessed by each of the two different subjects. Access to the capital market is a crucial element for the development of agriculture, both in the start-up phase and in the improvement phase. The search for new capital and new tools to facilitate market access requires a high degree of trust on the part of financial market operators, a trust that is often compromised by the low profitability of loans and the high risk associated with them. The exposure to risk of agricultural activities limits, in fact, the interest of traditional finance, reducing the availability of capital to the few remaining resources within the sector itself after the flight to more attractive alternative uses. Hence the need to introduce new financial and insurance techniques and services, such as to guarantee the agricultural sector the capital necessary for growth and, at the same time, attractive return opportunities for investors. Specifically, it is stated that one of the most profitable paths to follow in this regard is implementation within all EU member states of particular agricultural reforms that introduce risk management techniques in agriculture already successfully implemented by the U.S.A.1

The relationship between day-ahead and future prices in electricity markets: An empirical analysis on Italy, France, Germany, and Switzerland

We evaluate the relationship between electricity day-ahead and future prices following the hedging pressure theory, which explains the difference between future prices and expected spot prices regarding market players’ risk aversion. We calculate the sign and intensity of the ex-post risk premia in the electricity market of Italy, France, Switzerland, and Germany during the last decade and for all products traded: monthly, quarterly, and yearly futures and distinguish between base-load and peak-price futures. We test the impact of the trading period on the risk premia in panel regressions, controlling for seasonality and the impact of financial markets’ trades and primary energy prices. We show that, in all countries, there is no convergence of future prices to the underlying day-ahead ones; moreover, for most future contracts, the premium rises as contracts approach delivery. In addition, for Italy and Switzerland, there is an inversion of the sign of the premia (mostly for base-load products). Risk premia are negative at the beginning of the trading period and positive as the delivery period approaches. This indicates that, in these countries, premia are, on average, paid by power producers at the beginning of the period and by suppliers (i.e. power buyers) close to delivery. In contrast, in France and Germany, risk premia are both positive at the beginning and at the end of the trading period, signalling that, on average, buyers are willing to pay a premium to cover price volatility.

Analysis of futures and spot electricity markets under risk aversion

We analyze the procurement problem in the electricity supply chain, focusing on the interaction between futures and spot prices. The supply chain network analyzed in our study includes risk-averse generators and retailers, both with the ability to use conditional value at risk (CV@R) in their decision processes. In this supply chain, the futures price is computed to clear the futures market, without imposing the constraint that the expected spot price equals the futures price. As major methodological contributions: we compute the Nash equilibrium of the problem using CV@R and considering conjectural variations; we derive analytical relationships between the futures and the spot market outcomes and study the implications of demand and marginal cost uncertainty, as well as the level of the players’ risk aversion, on market equilibrium; we introduce the concept of risk-adjusted expectation to derive the futures market price as a function of the players’ expected losses or profits in the spot market; and we use consistent spot and wholesale price derivatives to calculate the players’ reaction functions. Finally, we illustrate our model with several numerical examples in the context of the Spanish electricity market, studying how the shape of the forward curve and the relationship between spot and futures prices depend on seasonality, risk aversion, generators’ market power, and hydrological resources. Surprisingly we observed that risk aversion increases the profit and reduces firms’ risk, and that the consumer utility is higher in the scenarios in which retailers behave a la Cournot in the wholesale market.

Commodity index risk premium

Increasingly commodities have become an asset class in a process called financialization. Many institutional investors, looking for ways to expand their diversification opportunities, are holding positions in a commodity futures index and use them as a performance benchmark. Thus, institutional commodity holdings in commodities has expanded significantly.In this paper we estimate the risk premium of a commodity index using analyst’s forecasts and futures prices of each of the commodities included in the index. We estimate futures and expected spot price curves using a no-arbitrage multifactor stochastic pricing model and a Kalman Filter. The model includes time-varying risk premia thus allowing for the exploration of macro variables that could explain their time variation for each family of commodities.The proposed model has already shown to be effective for single commodities, such as oil and copper, but this paper extends its use to analyze indices of the four main commodity sectors: energy, industrial metals, precious metals and agriculture, as well as a global portfolio that mimics the S&P GSCI Index. This allows for a better understanding of how some macro variables affect different commodity sectors providing useful information for institutional investors of a commodity index.

Expected prices, futures prices and time-varying risk premiums: The case of copper

A three-factor no-arbitrage stochastic commodity pricing model is calibrated to copper using analysts' predictions provided by Bloomberg's Commodity Price Forecast and futures prices from the COMEX and LME metals exchanges. The model generates futures prices, expected spot prices and time-varying risk premiums for different maturities. Results show that between October 2010 and June 2018 both exchanges exhibit a positive average risk premium for each maturity. The risk premiums for both exchanges are also shown to be stochastic, with short maturities having higher average values and greater volatility. In addition, the futures prices of COMEX values were greater than those LME with a mean difference of 0.477% and the LME exhibits higher averages values than COMEX for expected spot prices and risk premiums, with differences of 0.438% and 0.354%, respectively. As for risk premium volatility, the estimate for COMEX is 0.993% greater than that for LME. Statistically significant evidence is also given for the cointegration of the two markets. An empirical analysis shows that the main determinants of the variation in copper risk premiums are variations in COMEX inventories, hedging pressure, the default premium, the Chicago Board Options Exchange Volatility Index and the return on the NASDAQ Emerging Market Index. Finally, the approach is used for estimating expected copper spot prices, thus making it a useful tool for practitioners and policy makers who use expected copper prices as the basis for their investment and risk-management decisions.

Crowdfunding, Financing Constraints, and Real Effects

We study the feasibility and optimal design of presale crowdfunding contracts where participating consumers pay a premium above the future expected spot price and financially constrained entrepreneurs balance the potential product–market distortions introduced through presale crowdfunding against the cost of traditional external financing. Our analysis shows how such crowdfunding contracts enable the execution of projects that could not be otherwise undertaken and highlights novel interactions between the cost of capital, demand uncertainty, and production. Tighter financing constraints reduce the ability of the monopolist to extract surplus but, contrary to the usual result, may increase production. We evaluate how uncertainty and market size reduce the price-discriminating power of the monopolist and affect the optimal contract regime. Nevertheless, we show how such presale price-discriminating contracts are implementable even when the number of potential consumers is relatively high and their individual demand is stochastic. This paper was accepted by Gustavo Manso, finance.

The risk markup of intermittent renewable supply in German electricity forward markets

Renewable energy sources such as wind or solar power currently make up a large share of the total German electricity supply as a result of the German energy transition. This paper presents an empirical analysis of how power shocks resulting from intermittent renewables affect the forecast error of the forward premium in German electricity markets. We extend the existing literature by investigating determinants of forward premiums, focusing on both wind and solar power. We find positive monthly wind shock effects on forecast errors, ie, a specific risk markup on forward prices. These findings underline the need to introduce wind power futures at the European Energy Exchange (EEX) in order to reduce the risk markup for participants in forward markets. No daily wind shock or solar shock effects are found. One explanation for this could be the almost perfect approximations of the expected spot price. This is in line with the EEX’s strategy, which does not create wind power futures for contracts with maturities of days. The wind shock effect on monthly peak-load premium is larger than that on base-load premiums. This is likely due to higher differences in marginal costs on the right-hand side of the merit order curve.

Risk premia in commodity price forecasts and their impact on valuation

Commodity price driven valuation models require a stochastic price input if the value of managerial flexibility, such as the option to defer investment until the optimal time and the option to abandon a project, is to be estimated. The risk-neutral version of the stochastic price model is typically used in academic work; however, risk-adjusted models of the expected spot price are often used in practice. These two approaches are connected by a risk premium which is unfortunately often difficult to estimate. In this work, we use natural gas futures prices in a Kalman filter approach with maximum likelihood estimation to parameterize the Schwartz and Smith (2000) stochastic price model, and then apply an asset pricing model to address the large uncertainty of the risk premia parameter estimates. To evaluate the impact of the risk premia and other parameters in the two-factor price model on project valuation, we apply the price model to a prototypical shale gas investment, both for a base reference case as well as for cases where there are real options to optimally time decisions to invest or to abandon the project. Using this approach, we are able to determine the implied risk-adjusted discount rate that would be used with the spot price forecast, given the two-factor model risk premia, and we also discuss the impact of the risk premia on project value relative to other model parameters.

Estimating and forecasting the real prices of crude oil: A data rich model using a dynamic model averaging (DMA) approach

Given that oil price fluctuations have been of great interest for macroeconomics in the recent years due to its' important implications for future inflation, economic growth, and policy making, the aim of this paper is to estimate and forecast West Texas Intermediate (WTI) crude oil prices using a large monthly dataset, that covers the period from March 1983 to December 2011. To achieve this aim, forecasting with factor models offers a usual approach that utilizes large datasets, however; a forecasting model which simply includes all factors in state space equation and does not allow for time varying may be not suitable with a highly volatile market such as oil market. To overcome these limitations, an approach that accounts both for parameter and model uncertainty is employed. In particular, this study uses the Dynamic Model Averaging (DMA) approach suggested by Koop and Korobilis (2012). The key element of the DMA approach is that it allows both for model and parameter to vary at each point of time. By doing so, the DMA is robust to structural breaks. Empirical findings show that DMA approach outperforms any other alternative model used in the forecasting exercise. Results also show that there is model but not parameter variation in this oil price forecasting exercise. Finally, the findings suggest that the DMA approach provides a better proxy of expected spot prices than future prices.

Optimal combined purchasing strategies for a risk-averse manufacturer under price uncertainty

Purpose: The purpose of our paper is to analyze optimal purchasing strategies when a manufacturer can buy raw materials from a long-term contract supplier and a spot market under spot price uncertainty. Design/methodology/approach: This procurement model can be solved by using dynamic programming. First, we maximize the DM’s utility of the second period, obtaining the optimal contract quantity and spot quantity for the second period. Then, maximize the DM’s utility of both periods, obtaining the optimal purchasing strategy for the first period. We use a numerical method to compare the performance level of a pure spot sourcing strategy with that of a mixed strategy. Findings: Our results show that optimal purchasing strategies vary with the trend of contract prices. If the contract price falls, the total quantity purchased in period 1 will decrease in the degree of risk aversion. If the contract price increases, the total quantity purchased in period 1 will increase in the degree of risk aversion. The relationship between the optimal contract quantity and the degree of risk aversion depends on whether the expected spot price or the contract price is larger in period 2. Finally, we compare the performance levels between a combined strategy and a spot sourcing strategy. It shows that a combined strategy is optimal for a risk-averse buyer. Originality/value: It’s challenging to deal with a two-period procurement problem with risk consideration. We have obtained results of a two-period procurement problem with two sourcing options, namely contract procurement and spot purchases. Our model incorporates the buyer’s risk aversion factor and the change of contract prices, which are not addressed in early studies.

Bidding behavior in the Chilean electricity market

Contracts in power markets are usually obscure. From recently public auctions of long-term supply contracts we can obtain information on how contract prices are determined. To understand generators' bidding behavior, this paper examines the Chilean experience from 2006 to 2011. Using a divisible good auction model we provide a theoretical framework that explains bidding behavior in terms of expected spot prices and contracting positions. Empirical estimations indicate heterogeneity in the cost of over-contracting depending on incumbency, bringing evidence of significant barriers to entry.

Comparison of commodity future pricing approaches with cointegration techniques

Commodity future prices are explained either by price expectations and a risk premium in the theory of normal backwardation or with the theory of storage in a cost of carry valuation. Both approaches are compared in separate equations with Johansen cointegration tests. The data sample contains five LME metals with maturities of 3–27 months and real inventory data. It is found that expected spot prices explain only short maturity future prices. But the cost of carry approach, with the inventory level-dependent convenience yield, explains prices for all maturities.

Equilibrium Commodity Trading

We develop an equilibrium model of commodity spot and futures markets in which commodity production, consumption, and speculation are endogenously determined. Speculators facilitate hedging by the commodity suppliers. The entry of new speculators thus increases the supply of the commodity and decreases the expected spot prices, to the benefits of the end-users. However, this entry may be detrimental to the producers, as they do not internalize the price reduction due to greater aggregate supply. In the presence of asymmetric information, speculation on the futures market serves as a learning device. The futures price and open interest reveal different pieces of private information regarding the supply and demand side of the spot market, respectively. When the accuracy of private information is low, the entry of new speculators makes both production and spot prices more volatile. The entry of new speculators typically increases the correlation between financial and commodity markets.

Equilibrium forward risk premiums in electricity markets

This paper develops an equilibrium electricity forward pricing model which explicitly accounts for constrained capacity. The model is able to reproduce the price spikes observed in wholesale electricity markets using reasonable parameter values. The equilibrium forward premium, defined as the forward price minus the expected spot price, decreases in spot price variance when the expected spot price is less than the retail price, but increases in spot price variance when the expected spot price is greater than the retail price. The forward premium is an increasing function of the ratio of the expected spot price to the retail price.

The forward premium in electricity futures

Understanding the nature of the forward premium is particularly crucial, but rather elusive, for a non-storable commodity such as wholesale electricity. Whilst forward prices emerge as the expectation of spot plus, or minus, an ex ante premium for risk, the manifestation and empirical analysis must focus upon realised ex post premiums. This presents modelling requirements to control for shocks to the spot expectation as well as the endogeneity of ex post premia with spot price outcomes. In addition, because electricity is a derived commodity in the sense that market prices are often set by technologies that convert gas or coal into power, it is an open question whether much of the premia in power may actually be a pass-through of the premia in gas (or coal). Using a four dimensional VAR model we are able to distinguish fundamental and behavioural aspects of price formation in both the daily and monthly forward premia from the British market. We present new evidence on daily and seasonal sign reversals, associated with demand cycles, the greater importance of behavioural adaptations in the risk premia than fundamental or spot market risk measures, and the substantial fuel risk pass-through. We also show the value of a nonlinear specification in this context. • Futures for electricity are analysed through forward premia on expected spot prices. • These premia differ by time of day (peak and off-peak) and according to many drivers. • Behavioural drivers play a greater part in the peak periods. • Fundamental drivers are more influential in off-peak periods.

A Square-Root T Hedging Rule for Nonstorable Products

This note derives a hedging rule under the assumption of noisy forward prices. Forward prices are assumed to be noisy due to non-storability of the underlying product and the resulting lack of carry arbitrage. The minimum-variance hedge ratio increases nonlinearly with decreasing time to maturity of the forward contract, as more information about the expected spot price arrives and the forward price becomes less noisy. If the noise component follows a process similar to a random walk, the precision of the forward price increases as a square-root function of the remaining trading time. By setting the initial hedge ratio according to hypothetically efficient prices, a producer overhedges and the minimum-variance hedge is not achieved.

Panamax 4TC Rate Forecasting: A Kalman-Filter Approach

This paper compares a series of Vector Autoregressive Models, Vector Error Coerrection Models and ARIMA to State space models using the Kalman filter routine to Forecast Spot Panamax 4TC rates. The null hypothesis of this investigation is that VAR and ARIMA models with lagged spot and Forward Freight Agreements (FFA) returns provide the best forecast for spot rates. The alternative hypothesis is that they do not. In that respect, if the null the hypothesis holds then VAR or ARIMA models calculated through a Maximum likelihood OLS will be the best estimates of expected spot prices. The second Null hypothesis is that the FFA returns can be used to provide better forecasts than regressing the spot returns to its lagged first differences i.e. either through OLS or not. Although it is found that FFAs do contain information about the spot, as indicated by past literature, linear dynamic models of lagged spot returns exhibit a lower Root Mean Squared error and directional forecasting Accuracy than all other models for daily forecasts. However, results of weekly and monthly forecasts are mixed, indicating that incremental reduction in RMSE is higher when including forward contracts of longer maturities as explanatory variables. In addition, it is found that chained timeseries of contracts with longer maturity contain more information about the spot.

An Analysis of the Main Determinants of Electricity Forward Prices and Forward Risk Premia

The liberalisation of energy markets entails the appearance of market risks which must be borne by market participants: producers, retailers and final consumers. Some of these risks can be managed by participating in the forward markets and transferring it to other agents who are willing to bear it and command a compensation for it. Thus, forward prices are made up of two components: the expected spot price at a future date and the forward risk premium. In this chapter we analyse the factors influencing the evolution of electricity forward prices in Spain. These factors include the forward prices for natural gas and CO2 emission rights, as well as the electricity forward prices in Germany and in France and spot prices in Spain. We also analyse the behaviour of the ex-post electricity forward risk premia in Germany, France and Spain, and in particular we find a positive correlation between ex-post electricity risk premia in these three countries as well as between risk premia for electricity and natural gas futures prices.