This thesis deals with problems of automatic trading system for trading on commodity exchange. Automated trading system for the purpose of this thesis is based on the principle of adaptive moving average. This principle is processed initially at a theoretical level, then the thesis analyzes the problem of making automated trading system and risks of online trading. The final section describes implementation and testing of automatic trading system.

No description available.

No description available.

No description available.

As time passes, change occurs. With this change comes the need for surveillance. One may be a technician on an assembly line and in need of a surveillance technique to monitor the number of defective components produced. On the other hand, one may be an administrator of a hospital in need of surveillance measures to monitor the number of patient falls in the hospital or to monitor surgical outcomes to detect changes in surgical failure rates. A natural choice for on-going surveillance is the control chart; however, the chart must be constructed in a way that accommodates the situation at hand. Two scenarios involving attribute control charting are investigated here. The first scenario involves Poisson count data where the area of opportunity changes. A modified exponentially weighted moving average (EWMA) chart is proposed to accommodate the varying sample sizes. The performance of this method is compared with the performance for several competing control chart techniques and recommendations are made regarding the best preforming control chart method. This research is a result of joint work with Dr. William H. Woodall (Department of Statistics, Virginia Tech). The second scenario involves monitoring a process where items are classified into more than two categories and the results for these classifications are readily available. A multinomial cumulative sum (CUSUM) chart is proposed to monitor these types of situations. The multinomial CUSUM chart is evaluated through comparisons of performance with competing control chart methods. This research is a result of joint work with Mr. Lee J. Wells (Grado Department of Industrial and Systems Engineering, Virginia Tech) and Dr. William H. Woodall (Department of Statistics, Virginia Tech). / Ph. D.

We examine some of the methodologies implemented by the Centers for Disease Control and Prevention's (CDC) BioSense program. The program uses data from hospitals and public health departments to detect outbreaks using the Early Aberration Reporting System (EARS). The EARS method W2 allows one to monitor syndrome counts (W2count) from each source and the proportion of counts of a particular syndrome relative to the total number of visits (W2rate). We investigate the performance of the W2r method designed using an empiric recurrence interval (RI) in this dissertation research. An adaptive threshold monitoring method is introduced based on fitting sample data to the underlying distributions, then converting the current value to a Z-score through a p-value. We compare the upper thresholds on the Z-scores required to obtain given values of the recurrence interval for different sets of parameter values. We then simulate one-week outbreaks in our data and calculate the proportion of times these methods correctly signal an outbreak using Shewhart and exponentially weighted moving average (EWMA) charts. Our results indicate the adaptive threshold method gives more consistent statistical performance across different parameter sets and amounts of baseline historical data used for computing the statistics. For the power analysis, the EWMA chart is superior to its Shewhart counterpart in nearly all cases, and the adaptive threshold method tends to outperform the W2 rate method. Two modified W2r methods proposed in the dissertation also tend to outperform the W2r method in terms of the RI threshold functions and in the power analysis. / Ph. D.

Engineers of off-road equipment, on-road vehicles, pavement, and tires must assess the roughness of a terrain surface for the design of their products. The International Roughness Index (IRI), a standardized means of assessing longitudinal road roughness, quantifies roughness based on the average suspension travel for a particular vehicle at a prescribed speed. The Discrete Roughness Index (DRI) developed in this work address fundamental limitations of the IRI. Specifically, the DRI is calculated for each discretely measured location along a terrain surface and is applicable to vehicles traveling at varying speeds and using parameters other than the Golden Quarter-Car on which the IRI is based. The development of the DRI begins with a consistent discretization of the terrain surface, vehicle response, and the IRI. Next the Fractional Response Coefficient is developed, the properties of which are critical in the development of the DRI. The DRI is developed and its properties are discussed through theory and simulation of the ASTM E1926-08 profile. One important property of the average DRI is that it converges to the IRI as the distance between sampled points becomes smaller, for the particular case when the Golden Quarter-Car model is simulated at 80 kph. The DRI is not an alternative to the standard IRI, therefore, but a widely applicable roughness measure of which the standard IRI is a single specialized application. / Master of Science

The thesis evaluates several hundred one-day-ahead VaR forecasting models in the time period between the years 2004 and 2009 on data from six world stock indices - DJI, GSPC, IXIC, FTSE, GDAXI and N225. The models model mean using the AR and MA processes with up to two lags and variance with one of GARCH, EGARCH or TARCH processes with up to two lags. The models are estimated on the data from the in-sample period and their forecasting ac- curacy is evaluated on the out-of-sample data, which are more volatile. The main aim of the thesis is to test whether a model estimated on data with lower volatility can be used in periods with higher volatility. The evaluation is based on the conditional coverage test and is performed on each stock index sepa- rately. Unlike other works in this eld of study, the thesis does not assume the log-returns to be normally distributed and does not explicitly select a partic- ular conditional volatility process. Moreover, the thesis takes advantage of a less known conditional coverage framework for the measurement of forecasting accuracy.

<p>Syftet är att konstruera en handelsstrategi baserad på Contracts-For-Difference (CFD) för att utnyttja de möjliga samband som föreligger mellan oljepris och SEK/USD växlingskurs.</p><p>Uppsatsen baseras på en induktiv ansats med kvantitativ metod. Slutsatser dras från utifrån de data som har bearbetats.</p><p>Korrelationen mellan olja och valutan SEK/USD är starkt negativ. Funktionaliteten hos ”Moving Average” som indikator för trendskiften bedöms som relativt hög. Handelsstrategin som har konstruerats uppvisar positivt resultat efter fem års simulerad handel. Handelsstrategin skulle kunna automatiseras och automatisering av denna bedöms som mindre komplicerat.</p> / <p>The purpose is to construct a trading strategy based on Contracts-For-Difference (CFD) to exploit the possible correlations between oil price and SEK/USD spot rate.</p><p>The thesis is based on an inductive approach with a quantitative methodology. Conclusions are drawn from the data that has been processed.</p><p>The correlation between oil and currency SEK/USD has a strong negative value. The functionality of "Moving Average" as an indicator for showing trend shifts are assessed as relatively high. The constructed trade strategy gave positive results after five years of simulated trading. The trade strategy could be automated and the automation of this is considered less complicated.</p>

Syftet är att konstruera en handelsstrategi baserad på Contracts-For-Difference (CFD) för att utnyttja de möjliga samband som föreligger mellan oljepris och SEK/USD växlingskurs. Uppsatsen baseras på en induktiv ansats med kvantitativ metod. Slutsatser dras från utifrån de data som har bearbetats. Korrelationen mellan olja och valutan SEK/USD är starkt negativ. Funktionaliteten hos ”Moving Average” som indikator för trendskiften bedöms som relativt hög. Handelsstrategin som har konstruerats uppvisar positivt resultat efter fem års simulerad handel. Handelsstrategin skulle kunna automatiseras och automatisering av denna bedöms som mindre komplicerat. / The purpose is to construct a trading strategy based on Contracts-For-Difference (CFD) to exploit the possible correlations between oil price and SEK/USD spot rate. The thesis is based on an inductive approach with a quantitative methodology. Conclusions are drawn from the data that has been processed. The correlation between oil and currency SEK/USD has a strong negative value. The functionality of "Moving Average" as an indicator for showing trend shifts are assessed as relatively high. The constructed trade strategy gave positive results after five years of simulated trading. The trade strategy could be automated and the automation of this is considered less complicated.