Iowa Leading Indicators Index September 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index October 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index, November 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index, December 2009

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index January 2010

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index February 2010

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index March 2010

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Iowa Leading Indicators Index April 2010

The Iowa Leading Indicators Index (ILII) is a tool for monitoring the future direction of the Iowa economy and State revenues. Its eight components include an agricultural futures price index, an Iowa stock market index, average weekly manufacturing hours in Iowa, initial unemployment claims in Iowa, an Iowa new orders index, diesel fuel consumption in Iowa, residential building permits in Iowa, and the national yield spread.

Seasonality and the valuation of commodity options

Price movements in many commodity markets exhibit significant seasonal patterns. However, given an observed futures price, a deterministic seasonal component at the price level is not relevant for the pricing of commodity options. In contrast, this is not true for the seasonal pattern observed in the volatility of the commodity price. Analyzing an extensive sample of soybean, corn, heating oil and natural gas options, we find that seasonality in volatility is an important aspect to consider when valuing these contracts. The inclusion of an appropriate seasonality adjustment significantly reduces pricing errors in these markets and yields more improvement in valuation accuracy than increasing the number of stochastic factors.

Dynamic hedging with stocastic differential utility

In this paper we study the dynamic hedging problem using three different utility specifications: stochastic differential utility, terminal wealth utility, and we propose a particular utility transformation connecting both previous approaches. In all cases, we assume Markovian prices. Stochastic differential utility, SDU, impacts the pure hedging demand ambiguously, but decreases the pure speculative demand, because risk aversion increases. We also show that consumption decision is, in some sense, independent of hedging decision. With terminal wealth utility, we derive a general and compact hedging formula, which nests as special all cases studied in Duffie and Jackson (1990). We then show how to obtain their formulas. With the third approach we find a compact formula for hedging, which makes the second-type utility framework a particular case, and show that the pure hedging demand is not impacted by this specification. In addition, with CRRA- and CARA-type utilities, the risk aversion increases and, consequently the pure speculative demand decreases. If futures price are martingales, then the transformation plays no role in determining the hedging allocation. We also derive the relevant Bellman equation for each case, using semigroup techniques.

Propuestas regulatorias para el diseño de un mercado ibérico a plazo eficiente de la energía = Regulatory proposals for the development of an efficient iberian energy forward market

El mercado ibérico de futuros de energía eléctrica gestionado por OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, con sede en Lisboa), también conocido como el mercado ibérico de derivados de energía, comenzó a funcionar el 3 de julio de 2006. Se analiza la eficiencia de este mercado organizado, por lo que se estudia la precisión con la que sus precios de futuros predicen el precio de contado. En dicho mercado coexisten dos modos de negociación: el mercado continuo (modo por defecto) y la contratación mediante subasta. En la negociación en continuo, las órdenes anónimas de compra y de venta interactúan de manera inmediata e individual con órdenes contrarias, dando lugar a operaciones con un número indeterminado de precios para cada contrato. En la negociación a través de subasta, un precio único de equilibrio maximiza el volumen negociado, liquidándose todas las operaciones a ese precio. Adicionalmente, los miembros negociadores de OMIP pueden liquidar operaciones “Over-The-Counter” (OTC) a través de la cámara de compensación de OMIP (OMIClear). Las cinco mayores empresas españolas de distribución de energía eléctrica tenían la obligación de comprar electricidad hasta julio de 2009 en subastas en OMIP, para cubrir parte de sus suministros regulados. De igual manera, el suministrador de último recurso portugués mantuvo tal obligación hasta julio de 2010. Los precios de equilibrio de esas subastas no han resultado óptimos a efectos retributivos de tales suministros regulados dado que dichos precios tienden a situarse ligeramente sesgados al alza. La prima de riesgo ex-post, definida como la diferencia entre los precios a plazo y de contado en el periodo de entrega, se emplea para medir su eficiencia de precio. El mercado de contado, gestionado por OMIE (“Operador de Mercado Ibérico de la Energía”, conocido tradicionalmente como “OMEL”), tiene su sede en Madrid. Durante los dos primeros años del mercado de futuros, la prima de riesgo media tiende a resultar positiva, al igual que en otros mercados europeos de energía eléctrica y gas natural. En ese periodo, la prima de riesgo ex-post tiende a ser negativa en los mercados de petróleo y carbón. Los mercados de energía tienden a mostrar niveles limitados de eficiencia de mercado. La eficiencia de precio del mercado de futuros aumenta con el desarrollo de otros mecanismos coexistentes dentro del mercado ibérico de electricidad (conocido como “MIBEL”) –es decir, el mercado dominante OTC, las subastas de centrales virtuales de generación conocidas en España como Emisiones Primarias de Energía, y las subastas para cubrir parte de los suministros de último recurso conocidas en España como subastas CESUR– y con una mayor integración de los mercados regionales europeos de energía eléctrica. Se construye un modelo de regresión para analizar la evolución de los volúmenes negociados en el mercado continuo durante sus cuatro primeros años como una función de doce indicadores potenciales de liquidez. Los únicos indicadores significativos son los volúmenes negociados en las subastas obligatorias gestionadas por OMIP, los volúmenes negociados en el mercado OTC y los volúmenes OTC compensados por OMIClear. El número de creadores de mercado, la incorporación de agentes financieros y compañías de generación pertenecientes a grupos integrados con suministradores de último recurso, y los volúmenes OTC compensados por OMIClear muestran una fuerte correlación con los volúmenes negociados en el mercado continuo. La liquidez de OMIP está aún lejos de los niveles alcanzados por los mercados europeos más maduros (localizados en los países nórdicos (Nasdaq OMX Commodities) y Alemania (EEX)). El operador de mercado y su cámara de compensación podrían desarrollar acciones eficientes de marketing para atraer nuevos agentes activos en el mercado de contado (p.ej. industrias consumidoras intensivas de energía, suministradores, pequeños productores, compañías energéticas internacionales y empresas de energías renovables) y agentes financieros, captar volúmenes del opaco OTC, y mejorar el funcionamiento de los productos existentes aún no líquidos. Resultaría de gran utilidad para tales acciones un diálogo activo con todos los agentes (participantes en el mercado, operador de mercado de contado, y autoridades supervisoras). Durante sus primeros cinco años y medio, el mercado continuo presenta un crecimento de liquidez estable. Se mide el desempeño de sus funciones de cobertura mediante la ratio de posición neta obtenida al dividir la posición abierta final de un contrato de derivados mensual entre su volumen acumulado en la cámara de compensación. Los futuros carga base muestran la ratio más baja debido a su buena liquidez. Los futuros carga punta muestran una mayor ratio al producirse su menor liquidez a través de contadas subastas fijadas por regulación portuguesa. Las permutas carga base liquidadas en la cámara de compensación ubicada en Madrid –MEFF Power, activa desde el 21 de marzo de 2011– muestran inicialmente valores altos debido a bajos volúmenes registrados, dado que esta cámara se emplea principalmente para vencimientos pequeños (diario y semanal). Dicha ratio puede ser una poderosa herramienta de supervisión para los reguladores energéticos cuando accedan a todas las transacciones de derivados en virtud del Reglamento Europeo sobre Integridad y Transparencia de los Mercados de Energía (“REMIT”), en vigor desde el 28 de diciembre de 2011. La prima de riesgo ex-post tiende a ser positiva en todos los mecanismos (futuros en OMIP, mercado OTC y subastas CESUR) y disminuye debido a la curvas de aprendizaje y al efecto, desde el año 2011, del precio fijo para la retribución de la generación con carbón autóctono. Se realiza una comparativa con los costes a plazo de generación con gas natural (diferencial “clean spark spread”) obtenido como la diferencia entre el precio del futuro eléctrico y el coste a plazo de generación con ciclo combinado internalizando los costes de emisión de CO2. Los futuros eléctricos tienen una elevada correlación con los precios de gas europeos. Los diferenciales de contratos con vencimiento inmediato tienden a ser positivos. Los mayores diferenciales se dan para los contratos mensuales, seguidos de los trimestrales y anuales. Los generadores eléctricos con gas pueden maximizar beneficios con contratos de menor vencimiento. Los informes de monitorización por el operador de mercado que proporcionan transparencia post-operacional, el acceso a datos OTC por el regulador energético, y la valoración del riesgo regulatorio pueden contribuir a ganancias de eficiencia. Estas recomendaciones son también válidas para un potencial mercado ibérico de futuros de gas, una vez que el hub ibérico de gas –actualmente en fase de diseño, con reuniones mensuales de los agentes desde enero de 2013 en el grupo de trabajo liderado por el regulador energético español– esté operativo. El hub ibérico de gas proporcionará transparencia al atraer más agentes y mejorar la competencia, incrementando su eficiencia, dado que en el mercado OTC actual no se revela precio alguno de gas. ABSTRACT The Iberian Power Futures Market, managed by OMIP (“Operador do Mercado Ibérico de Energia, Pólo Português”, located in Lisbon), also known as the Iberian Energy Derivatives Market, started operations on 3 July 2006. The market efficiency, regarding how well the future price predicts the spot price, is analysed for this energy derivatives exchange. There are two trading modes coexisting within OMIP: the continuous market (default mode) and the call auction. In the continuous trading, anonymous buy and sell orders interact immediately and individually with opposite side orders, generating trades with an undetermined number of prices for each contract. In the call auction trading, a single price auction maximizes the traded volume, being all trades settled at the same price (equilibrium price). Additionally, OMIP trading members may settle Over-the-Counter (OTC) trades through OMIP clearing house (OMIClear). The five largest Spanish distribution companies have been obliged to purchase in auctions managed by OMIP until July 2009, in order to partly cover their portfolios of end users’ regulated supplies. Likewise, the Portuguese last resort supplier kept that obligation until July 2010. The auction equilibrium prices are not optimal for remuneration purposes of regulated supplies as such prices seem to be slightly upward biased. The ex-post forward risk premium, defined as the difference between the forward and spot prices in the delivery period, is used to measure its price efficiency. The spot market, managed by OMIE (Market Operator of the Iberian Energy Market, Spanish Pool, known traditionally as “OMEL”), is located in Madrid. During the first two years of the futures market, the average forward risk premium tends to be positive, as it occurs with other European power and natural gas markets. In that period, the ex-post forward risk premium tends to be negative in oil and coal markets. Energy markets tend to show limited levels of market efficiency. The price efficiency of the Iberian Power Futures Market improves with the market development of all the coexistent forward contracting mechanisms within the Iberian Electricity Market (known as “MIBEL”) – namely, the dominant OTC market, the Virtual Power Plant Auctions known in Spain as Energy Primary Emissions, and the auctions catering for part of the last resort supplies known in Spain as CESUR auctions – and with further integration of European Regional Electricity Markets. A regression model tracking the evolution of the traded volumes in the continuous market during its first four years is built as a function of twelve potential liquidity drivers. The only significant drivers are the traded volumes in OMIP compulsory auctions, the traded volumes in the OTC market, and the OTC cleared volumes by OMIClear. The amount of market makers, the enrolment of financial members and generation companies belonging to the integrated group of last resort suppliers, and the OTC cleared volume by OMIClear show strong correlation with the traded volumes in the continuous market. OMIP liquidity is still far from the levels reached by the most mature European markets (located in the Nordic countries (Nasdaq OMX Commodities) and Germany (EEX)). The market operator and its clearing house could develop efficient marketing actions to attract new entrants active in the spot market (e.g. energy intensive industries, suppliers, small producers, international energy companies and renewable generation companies) and financial agents as well as volumes from the opaque OTC market, and to improve the performance of existing illiquid products. An active dialogue with all the stakeholders (market participants, spot market operator, and supervisory authorities) will help to implement such actions. During its firs five and a half years, the continuous market shows steady liquidity growth. The hedging performance is measured through a net position ratio obtained from the final open interest of a month derivatives contract divided by its accumulated cleared volume. The base load futures in the Iberian energy derivatives exchange show the lowest ratios due to good liquidity. The peak futures show bigger ratios as their reduced liquidity is produced by auctions fixed by Portuguese regulation. The base load swaps settled in the clearing house located in Spain – MEFF Power, operating since 21 March 2011, with a new denomination (BME Clearing) since 9 September 2013 – show initially large values due to low registered volumes, as this clearing house is mainly used for short maturity (daily and weekly swaps). The net position ratio can be a powerful oversight tool for energy regulators when accessing to all the derivatives transactions as envisaged by European regulation on Energy Market Integrity and Transparency (“REMIT”), in force since 28 December 2011. The ex-post forward risk premium tends to be positive in all existing mechanisms (OMIP futures, OTC market and CESUR auctions) and diminishes due to the learning curve and the effect – since year 2011 – of the fixed price retributing the indigenous coal fired generation. Comparison with the forward generation costs from natural gas (“clean spark spread”) – obtained as the difference between the power futures price and the forward generation cost with a gas fired combined cycle plant taking into account the CO2 emission rates – is also performed. The power futures are strongly correlated with European gas prices. The clean spark spreads built with prompt contracts tend to be positive. The biggest clean spark spreads are for the month contract, followed by the quarter contract and then by the year contract. Therefore, gas fired generation companies can maximize profits trading with contracts of shorter maturity. Market monitoring reports by the market operator providing post-trade transparency, OTC data access by the energy regulator, and assessment of the regulatory risk can contribute to efficiency gains. The same recommendations are also valid for a potential Iberian gas futures market, once an Iberian gas hub – currently in a design phase, with monthly meetings amongst the stakeholders in a Working Group led by the Spanish energy regulatory authority since January 2013 – is operating. The Iberian gas hub would bring transparency attracting more shippers and improving competition and thus its efficiency, as no gas price is currently disclosed in the existing OTC market.

Futures basis, inventory and commodity price volatility: an empirical analysis

We employ a large dataset of physical inventory data on 21 different commodities for the period 1993–2011 to empirically analyze the behavior of commodity prices and their volatility as predicted by the theory of storage. We examine two main issues. First, we analyze the relationship between inventory and the shape of the forward curve. Low (high) inventory is associated with forward curves in backwardation (contango), as the theory of storage predicts. Second, we show that price volatility is a decreasing function of inventory for the majority of commodities in our sample. This effect is more pronounced in backwardated markets. Our findings are robust with respect to alternative inventory measures and over the recent commodity price boom.

Futures trading, spot price volatility and market efficiency: evidence from European real estate securities futures

In 2007 futures contracts were introduced based upon the listed real estate market in Europe. Following their launch they have received increasing attention from property investors, however, few studies have considered the impact their introduction has had. This study considers two key elements. Firstly, a traditional Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model, the approach of Bessembinder & Seguin (1992) and the Gray’s (1996) Markov-switching-GARCH model are used to examine the impact of futures trading on the European real estate securities market. The results show that futures trading did not destabilize the underlying listed market. Importantly, the results also reveal that the introduction of a futures market has improved the speed and quality of information flowing to the spot market. Secondly, we assess the hedging effectiveness of the contracts using two alternative strategies (naïve and Ordinary Least Squares models). The empirical results also show that the contracts are effective hedging instruments, leading to a reduction in risk of 64 %.

Tests of non-linearity using LIFFE futures transactions price data

This paper presents and implements a number of tests for non-linear dependence and a test for chaos using transactions prices on three LIFFE futures contracts: the Short Sterling interest rate contract, the Long Gilt government bond contract, and the FTSE 100 stock index futures contract. While previous studies of high frequency futures market data use only those transactions which involve a price change, we use all of the transaction prices on these contracts whether they involve a price change or not. Our results indicate irrefutable evidence of non-linearity in two of the three contracts, although we find no evidence of a chaotic process in any of the series. We are also able to provide some indications of the effect of the duration of the trading day on the degree of non-linearity of the underlying contract. The trading day for the Long Gilt contract was extended in August 1994, and prior to this date there is no evidence of any structure in the return series. However, after the extension of the trading day we do find evidence of a non-linear return structure.

Are price limits on futures markets that cool? evidence from the brazilian merchantile & futures exchange

This paper investigates the impact of price limits on the Brazil- ian future markets using high frequency data. The aim is to identify whether there is a cool-off or a magnet effect. For that purpose, we examine a tick-by-tick data set that includes all contracts on the São Paulo stock index futures traded on the Brazilian Mercantile and Futures Exchange from January 1997 to December 1999. Our main finding is that price limits drive back prices as they approach the lower limit. There is a strong cool-off effect of the lower limit on the conditional mean, whereas the upper limit seems to entail a weak magnet effect on the conditional variance. We then build a trading strategy that accounts for the cool-off effect so as to demonstrate that the latter has not only statistical, but also economic signifi- cance. The resulting Sharpe ratio indeed is way superior to the buy-and-hold benchmarks we consider.