This paper presents empirical evidence on the e¢ cacy of forecast averaging using the ALFRED real-time database. We consider averages taken over a variety of di¤erent bivariate VAR models that are distinguished from one another based upon at least one of the following: which variables are used as predictors, the number of lags, using all available data or data after the Great Moderation, the ob...

This paper proposes a novel approach to measure and analyze the effect of temperature on electricity demand. This temperature effect is specified as a function of the density of temperatures observed at a high frequency with a functional coefficient, which we call the temperature response function. This approach contrasts with the usual approach to model the temperature effect as a function of ...

Loss-of-function DJ-1 mutations can cause early-onset Parkinson's disease. The function of DJ-1 is unknown, but an acidic isoform accumulates after oxidative stress, leading to the suggestion that DJ-1 is protective under these conditions. We addressed whether this represents a posttranslational modification at cysteine residues by systematically mutating cysteine residues in human DJ-1. WT or ...

This position paper delineates the structure of some experiments to detect early symptoms of cervical cancer. We are using a large corpora of electronic patient records texts in Swedish from Karolinska University Hospital from the years 2009-2010, where we extracted in total 1,660 patient records with the ICD-10 diagnosis code C53 for cervical cancer. We used a Named Entity Recogniser called Cl...

This paper constructs a composite leading index for business cycle prediction based on vine copulas that capture the complex pattern of dependence among individual predictors. This approach is optimal in the sense that the resulting index possesses the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. The model specification is semi-parametric in nat...

This paper proposes a new method to forecast S&P 500 return distribution by combining quantile regression models using macro-finance variables with volatility-based models including various standard EGARCH and stochastic volatility specifications. 30 density forecasting models are compared and combined in an out-of-sample forecasting exercise. Using macro-finance variables is found to help subs...

This paper shows that out-of-sample forecast comparisons can help prevent data mining-induced overfitting. The basic results are drawn from simulations of a simple Monte Carlo design and a real data-based design similar to those in Lovell (1983) and Hoover and Perez (1999). In each simulation, a general-to-specific procedure is used to arrive at a model. If the selected specification includes a...

We develop two specification tests of predictive densities based on that the generalized residuals of correctly specified predictive density models are i.i.d. uniform. The simultaneous test compares the joint density of generalized residuals with product of uniform densities; the sequential test examines the hypotheses of serial independence and uniformity sequentially based on the copula repre...

We forecast quarterly US in‡ation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We …nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and...

We put forward Value-at-Risk models relevant for commodity traders who have long and short trading positions in commodity markets. In a 5-year out-of-sample study on aluminium, copper, nickel, Brent crude oil and WTI crude oil daily cash prices and cocoa nearby futures contracts, we assess the performance of the RiskMetrics, skewed Student APARCH and skewed student ARCH models. While the skewed...