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A comparative study of approaches to forecast the correct trading actions
Get PDFThis paper addresses the problem of decision making in the context of financial markets, more specifically, the problem of forecasting the correct trading action for a certain future horizon. We study and compare two alternative ways of addressing these forecasting tasks: (a) using standard numeric prediction models to forecast the variation on the prices of the target asset and, on a second stage, transform these numeric predictions into a decision according to some predefined decision rules; and (b) use models that directly forecast the right decision thus ignoring the intermediate numeric forecasting task. The objective of our study is to determine if both strategies provide identical results or if there is any particular advantage worth being considered that may distinguish each alternative in the context of financial markets
A chemometrics approach applied to Fourier transform infrared spectroscopy (FTIR) for monitoring the spoilage of fresh salmon (Salmo salar) stored under modified atmospheres
No full textThe aim of this work was to investigate the potential of Fourier transform infrared spectroscopy (FTIR) to detect and predict the bacterial load of salmon fillets (Salmo salar) stored at 3, 8 and 30 degrees C under three packaging conditions: air packaging (AP) and two modified atmospheres constituted by a mixture of 50%N-2/40%CO2/10%O-2 with lemon juice (MAPL) and without lemon juice (MAP). Fresh salmon samples were periodically examined for total viable counts (TVC), specific spoilage organisms (SSO) counts, pH, FTIR and sensory assessment of freshness. Principal components analysis (PCA) allowed identification of the wavenumbers potentially correlated with the spoilage process. Linear discriminant analysis (LDA) of infrared spectral data was performed to support sensory data and to accurately identify samples freshness. The effect of the packaging atmospheres was assessed by microbial enumeration and LDA was used to determine sample packaging from the measured infrared spectra. It was verified that modified atmospheres can decrease significantly the bacterial load of fresh salmon. Lemon juice combined with MAP showed a more pronounced delay in the growth of Brochothrix thermosphacta, Photobacterium phosphoreum, psychrotrophs and H2S producers. Partial least squares regression (PLS-R) allowed estimates of TVC and psychrotrophs, lactic acid bacteria, molds and yeasts, Brochothrix thermosphacta, Enterobacteriaceae, Pseudomonas spp. and H2S producer counts from the infrared spectral data: For TVC, the root mean square error of prediction (RMSEP) value was 0.78 log cfu g(-1) for an external set of samples. According to the results, FTIR can be used as a reliable, accurate and fast method for real time freshness evaluation of salmon fillets stored under different temperatures and packaging atmospheres
Assessing arsenic and selenium in a single nail clipping using portable X-ray fluorescence
No full textThe feasibility of measuring arsenic and selenium contents in a single nail clipping was investigated using a small-focus portable X-ray fluorescence (XRF) instrument with monochromatic excitation beams. Nail clipping phantoms supplemented with arsenic and selenium to produce materials with 0, 5, 10, 15, and 20 mu g/g were used for calibration purposes. In total, 10 different clippings were analyzed at two different measurement positions. Energy spectra were fit with detection peaks for arsenic K-alpha, selenium K-alpha, arsenic K-beta, selenium K-beta, and bromine K-alpha characteristic X-rays. Data analysis was performed under two distinct conditions of fitting constraint. Calibration lines were established from the amplitude of each of the arsenic and selenium peaks as a function of the elemental contents in the clippings. The slopes of the four calibration lines were consistent between the two conditions of analysis. The calculated minimum detection limit (MDL) of the method, when considering the Ka peak only, ranged from 0.210 +/- 0.002 mu g/g selenium under one condition of analysis to 0.777 +/- 0.009 mu g/g selenium under another. Compared with previous portable XRF nail clipping studies, MDLs were substantially improved for both arsenic and selenium. The new measurement technique had the additional benefits of being short in duration (similar to 3 min) and requiring only a single nail clipping. The mass of the individual clipping used did not appear to play a major role in signal strength, but positioning of the clipping is important
Probabilistic price forecasting for day-ahead and intraday markets: Beyond the statistical model
Get PDFForecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 €/MWh for day-ahead market and a maximum value of 2.53 €/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions. © 2017 by the authors
New Metrics for Evaluating Technical Benefits and Risks of DGs Increasing Penetration
No full textIncreasing penetration of distributed generation (DG), may be interesting from several points of view, but it raises important challenges about distribution system operation and planning practices. To optimal allocation of DG, which play an important role in construction of microgrids, the benefits and risks should be qualified and quantified. This paper introduces several probabilistic indices to evaluate the potential operational effects of increasing penetration of renewable DG units such as wind power and photovoltaic on rural distribution network with the aid of evaluating technical benefits and risks tradeoffs. A probabilistic generation-load model is suggested to calculate these indices which combine a large number of possible operating conditions of renewable DG units with their probabilities. Temporal and annual indices of voltage profile and line flow-related attributes such as interest voltage rise, risky voltage rise, risky voltage down, line loss reduction, line loss increment, and line overload flow are introduced using probability and expected values of their occurrence. Also, to measure the overall interests and risks of installing DG, composite indices are presented. The implementation of the proposed framework in a 4-bus and IEEE 33-bus radial distribution systems shows the effectiveness of the benefits and risks assessment technique with the proposed metrics
An optimization-simulation approach to the network redesign problem of pharmaceutical wholesalers
No full textThe pharmaceutical industry operates in a very competitive and regulated market The increased pressure of pharmacies to order fewer products and to receive them more frequently is overcharging the pharmaceutical's distribution network Furthermore, the tight margins and the continuous growth of generic drugs consumption are pressing wholesalers to optimize their supply chains. In order to survive, wholesalers are rethinking their strategies to increase competitiveness. This paper proposes an optimization-simulation approach to address the wholesalers network redesign problem, trading off the operational costs and customer service level. Firstly, at a strategic-tactical level, the supply chain network redesign decisions are optimized via a mixed integer programming model. Here, the number, location, function and capacity of the warehouses, the allocation of customers to the warehouses and the capacity and function of the distribution channels are defined. Secondly, at an operation level, the solution found is evaluated by means of a discrete event simulation model to assess the impact of the redesign in the wholesaler's daily activities. Computational results on a pharmaceutical wholesaler case-study are discussed and the benefits of this solution approach exposed
Effect of Risk Aversion on Reserve Procurement With Flexible Demand Side Resources From the ISO Point of View
No full textIn this study, a two-stage stochastic programming joint day-ahead energy and reserve scheduling model to address uncertainty in wind power generation is developed. Apart from the generation side, the demand side is also eligible as a reserve resource and is modeled through responsive load aggregations, as well as large industrial loads that directly participate in the scheduling procedure. The main contribution of this paper is the inclusion of a risk metric, namely the conditional value-at-risk, which renders a conceptually different resource scheduling framework. The proposed model is employed in order to analyze the behavior of energy and reserve scheduling by both generation and demand for a risk-averse independent system operator. To reach practical conclusions, the proposed methodology is tested on the real non-interconnected insular power system of Crete, Greece, which is characterized by a significant penetration of wind power generation