Unspanned Stochastic Volatility and the Pricing of Commodity Derivatives

We conduct a comprehensive analysis of unspanned stochastic volatility in commodity markets in general and the crude-oil market in particular. We present model-free results that strongly suggest the presence of unspanned stochastic volatility in the crude-oil market. We then develop a tractable model for pricing commodity derivatives in the presence of unspanned stochastic volatility. The model features correlations between innovations to futures prices and volatility, quasi-analytical prices of options on futures and futures curve dynamics in terms of a low-dimensional affine state vector. The model performs well when estimated on an extensive panel data set of crude-oil futures and options.

A General Stochastic Volatility Model for the Pricing and Forecasting of Interest Rate Derivatives

We develop a tractable and flexible stochastic volatility multi-factor model of the term structure of interest rates. It features correlations between innovations to forward rates and volatilities, quasi-analytical prices of zero-coupon bond options and dynamics of the forward rate curve, under both the actual and risk-neutral measure, in terms of a finite-dimensional affine state vector. The model has a very good fit to an extensive panel data set of interest rates, swaptions and caps. In particular, the model matches the implied cap skews and the dynamics of implied volatilities. The model also performs well in forecasting interest rates and derivatives.

An Empirical Analysis of the Swaption Cube

We use a comprehensive database of inter-dealer quotes to conduct the first empirical analysis of the dynamics of the swaption cube. Using a model independent approach, we establish a set of stylized facts regarding the cross-sectional and time-series variation of conditional volatility and skewness of the swap rate distributions implied by the swaption cube. We then develop and estimate a dynamic term structure model that is consistent with these stylized facts, and use it to infer volatility and skewness of the risk-neutral and physical swap rate distributions. Finally, we investigate the fundamental drivers of these distributions. In particular, we find that volatility, volatility risk premia, skewness, and skewness risk premia are significantly related to the characteristics of agents’ belief distributions for the macroeconomy, with GDP beliefs the most important factor in the USD market, and inflation beliefs the most important factor in the EUR market. This is consistent with differences in monetary policy objectives in the two markets.

The term structure of interbank risk

We infer a term structure of interbank risk from spreads between rates on interest rate swaps indexed to the London Interbank Offered Rate (LIBOR) and overnight indexed swaps. We develop a tractable model of interbank risk to decompose the term structure into default and non-default (liquidity) components. From August 2007 to January 2011, the fraction of total interbank risk due to default risk, on average, increases with maturity. At short maturities, the non-default component is important in the first half of the sample period and is correlated with measures of funding and market liquidity. The model also provides a framework for pricing, hedging, and risk management of interest rate swaps in the presence of significant basis risk. (c) 2013 Elsevier B.V. All rights reserved

Uncovering predictability in the evolution of the WTI oil futures curve

Accurately forecasting the price of oil, the world's most actively traded commodity, is of great importance to both academics and practitioners. We contribute by proposing a functional time series based method to model and forecast oil futures. Our approach boasts a number of theoretical and practical advantages including effectively exploiting underlying process dynamics missed by classical discrete approaches. We evaluate the finite-sample performance against established benchmarks using a model confidence set test. A realistic out-of-sample exercise provides strong support for the adoption of our approach with it residing in the superior set of models in all considered instances.Comment: 28 pages, 4 figures, to appear in European Financial Managemen

Comparison of estimated energy intake from 2×24-hour recalls and a seven-day food record with objective measurements of energy expenditure in children

The objective of the present study was to evaluate energy intake (EI) estimated from two non-consecutive 24-hour recalls (24-HDRs) and a pre-coded seven-day food record (7-dFR) against objective measurements of energy expenditure (EE) in children.A total of 67 7–8 year-olds and 64 12–13 year-olds completed the 2×24-HDRs, the 7-dFR, and wore ActiReg® (PreMed AS, Oslo, Norway), a combined position and motion recording instrument, during the same seven days as the 7-dFR was filled in.In the 7–8 year-olds, EI from the 2×24-HDRs (EI2×24-HDR) was overestimated with 3% compared to EE (not significantly different), while EI from the 7-dFR (EI7-dFR) was underestimated with 7% compared to EE (P=0.001). In the 12–13 year-olds, the corresponding figures was underestimation by 10% with the 2×24-HDRs (P<0.001) and by 20% with the 7-dFR (P<0.001). For both age groups combined, the 95% limits of agreement were −4·38 and 3.52 MJ/d for the 2×24-HDRs, and −5.90 and 2.94 MJ/d for the 7-dFR. Pearson correlation coefficients between EI and EE were 0.51 for EI2×24-HDR and 0.29 for EI7-dFR, respectively. The proportion classified in the same or adjacent quartiles was 76% for EI2×24-HDR and 73% for EI7-dFR in the 7–8 year-olds, and 83% for EI2×24-HDR and 70% for EI7-dFR in the 12–13 year-olds.Misreporting of EI seemed modest with both the 2×24-HDRs and the 7-dFR in the 7–8 year-olds when compared to EE measured with ActiReg®. Under-reporting appeared to be more evident in the 12–13 year-olds, especially with the 7-dFR. Compared to measurements of EE, the 2×24-HDRs seemed to perform slightly better than the 7-dFR in terms of ranking of individuals according to EI

Intervention effects on dietary intake among children by maternal education level: results of the Copenhagen School Child Intervention Study (CoSCIS)

Dietary intake among Danish children, in general, does not comply with the official recommendations. The objectives of the present study were to evaluate the 3-year effect of a multi-component school-based intervention on nutrient intake in children, and to examine whether an intervention effect depended on maternal education level. A total of 307 children (intervention group: n 184; comparison group: n 123) were included in the present study. All had information on dietary intake pre- and post-intervention (mean age 6·8 and 9·5 years for intervention and comparison groups, respectively) assessed by a 7-d food record. Analyses were conducted based on the daily intake of macronutrients (energy percentage (E%)), fatty acids (E%), added sugar (E%) and dietary fibre (g/d and g/MJ). Analyses were stratified by maternal education level into three categories. Changes in nutrient intake were observed in the intervention group, mainly among children of mothers with a short education ( < 10 years). Here, intake of dietary fibre increased (β = 2·1 g/d, 95 % CI 0·5, 3·6, P= 0·01). Intake of protein tended to increase (β = 0·6 E%, 95 % CI − 0·01, 1·2, P= 0·05), while intake of fat (β = − 1·7 E%, 95 % CI − 3·8, 0·3, P= 0·09) and SFA (β = − 0·9, 95 % CI − 2·0, 0·2, P= 0·10) tended to decrease. Also, a significant intervention effect was observed on the intake of SFA among children of mothers with a long education (β = − 0·8, 95 % CI − 1·5, − 0·03, P= 0·04). This multi-component school-based intervention resulted in changes in the dietary intake, particularly among children of mothers with a short education. As the dietary intake of this subgroup generally differs most from the recommendations, the results of the present study are particularly encouraging