In most road infrastructure networks, the two prevalent types of pavements considered during the pavement type selection (PTS) process are flexible and rigid. Thus, these two structures are the most commonly constructed in the road industry. A consideration of a different pavement alternative is proposed in this study. Composite pavements, which are in essence a combination of a rigid base overlaid with a hot-mix asphalt (HMA) surface course, have the potential to meet the technical and economic requirements that are sought in the PTS process. For that reason, technical and economic evaluations were performed to justify the consideration of composite pavement systems in the PTS process. At the technical level, composite pavement design guidelines from various transportation agencies were obtained and followed to design their respective composite pavement structures. A mechanistic analysis based on the multi-layer linear elastic theory was performed on different composite structures to understand the behavior they present when compared to traditional pavements. In addition, distresses affecting composite pavements such as fatigue (bottom-up and top-down) cracking, rutting, and reflective cracking were modeled and investigated using sensitivity analyses. At the economic level, a deterministic life cycle cost analysis (LCCA) based on Virginia Department of Transportation (VDOT) guidelines was performed. This LCCA compared two proposed composite pavements (one with a cement-treated base [CTB] and the other with a continuously reinforced concrete pavement [CRCP] base) to traditional flexible and rigid pavement structures. Furthermore, sensitivity analyses involving discount rates and traffic volumes were performed to investigate their effect on the present worth (PW) computation of the four pavement alternatives. Results from this study suggest that composite pavements have both the technical and economic potential to be considered during the PTS process. / Master of Science

L'objectif de ma thèse est d'étudier mathématiquement un indicateur de rupture de volatilité très utilisé par les praticiens en salle de marché. L'indicateur bandes de Bollinger appartient à la famille des méthodes dites d'analyse technique et donc repose exclusivement sur l'historique récente du cours considéré et un principe déduit des observations passées des marchés, indépendamment de tout modèle mathématique. Mon travail consiste à étudier les performances de cet indicateur dans un univers qui serait gouverné par des équations différentielles stochastiques (Black -Scholes) dont le coefficient de diffusion change sa valeur à un temps aléatoire inconnu et inobservable, pour un praticien désirant maximiser une fonction objectif (par exemple, une certaine utilité espérée de la valeur du portefeuille à une certaine maturité). Dans le cadre du modèle, l'indicateur de Bollinger peut s'interpréter comme un estimateur de l'instant de la prochaine rupture. On montre dans le cas des petites volatilités, que le comportement de la densité de l'indicateur dépend de la volatilité, ce qui permet pour un ratio de volatilité assez grand, de détecter via l'estimation de la distribution de l'indicateur dans quel régime de volatilité on se situe. Aussi, dans le cas des grandes volatilités, on montre par une approche via la transformée de Laplace, que le comportement asymptotique des queues de distribution de l'indicateur dépend de la volatilité. Ce qui permet de détecter le changement des grandes volatilités. Ensuite, on s'intéresse à une étude comparative entre l'indicateur de Bollinger et l'estimateur classique de la variation quadratique pour la détection de changement de la volatilité. Enfin, on étudie la gestion optimale de portefeuille qui est décrite par un problème stochastique non standard en ce sens que les contrôles admissibles sont contraints à être des fonctionnelles des prix observés. On résout ce problème de contrôle en s'inspirant de travaux de Pham and Jiao pour décomposer le problème initial d'allocation de portefeuille en un problème de gestion après la rupture et un problème avant la rupture, et chacun de ces problèmes est résolu par la méthode de la programmation dynamique . Ainsi, un théorème de verification est prouvé pour ce problème de contrôle stochastique. / The aim of my thesis is to study mathematically an indicator widely used by the practitioners in the trading market, and designed to detect changes in the volatility term . The Bollinger Bands indicator belongs to the family of methods known as technical analysis which consist in looking t the past price movement in order to predict its future price movements independently of any mathematical model. We study the performance of this indicator in a universe that is governed by a stochastic differential equations (Black-Scholes) such that the volatility changes at an unknown and unobservable random time, for a practitioner seeking to maximize an objective function (for instance, the expected utility of the wealth at a certain maturity). Within the framework of the model, Bollinger indicator can be interpreted as an estimator of the time at which the volatility changes its value. We show that in the case of small volatilities, the density behavior of the indicator depends on the value of the volatility, which allows that for large ratio of volatility, to detect via the distribution estimation in which regime of volatility we are. Also , for the case of large volatilities, we show by an approach via the Laplace transform that the asymptotic tails behavior of the indictor depends on the volatility value. This allows to detect a change for large volatilities. Next, we compare two indicators designed to detect a volatility change: the Bollinger bands and the quadratic variation indicators. Finally, we study the optimal portfolio allocation which is described by a non-standard stochastic problem in view of that the admissible controls need to be adapted to the filtration generated by the prices. We resolve this control problem by an approach used by Pham and Jiao to separate the initial allocation problem into an allocation problem after the rupture and an problem before the rupture, and each one of these problems is resolved by the dynamic programming method. Also, a verification theorem is proved for this stochastic control problem.

Made available in DSpace on 2016-04-25T16:44:27Z (GMT). No. of bitstreams: 1 Leandro Augusto Petrokas.pdf: 6508310 bytes, checksum: 436cb5d8e8eaff84b2bf0f56ca3fd7bd (MD5) Previous issue date: 2012-05-07 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This study aims at assessing the technical analysis is capable of producing superior financial results to the model buy and hold, which recommends the purchase and sale of shares in the medium or long term, without the use of specific tools or criteria to guide such decision. The sample was composed of fourteen shares, in eight different sectors of the economy, the survey period was from 2000 to 2010 and the tests were conducted with five key indicators of technical analysis. It was decided to test whether the simple moving average of 233 periods could increase the profitability obtained by the signs. The impact of generating a buy signal in the returns of five actions, through the event study methodology and, finally, estimated the average duration of the operations performed by the signals studied. The results indicated that in a case 350, 61 only in the yield obtained with the signals of the technical analysis was superior to that obtained by the model buy and hold. By means of the chi-square, it was found that this frequency is not statistically equal to half the cases, therefore, conclude that technical analysis was not able to produce superior financial results to the buy and hold. The results showed that there was no significant improvement in profitability with the use of simple moving average of 233 days as a filter rule, therefore, was not statistically significant differences in mean returns obtained by each signal, with and without the filter. The event studies revealed that only one of the five events analyzed was a statistically significant and positive impact on stock returns. The analysis of the duration of the operations indicated that profitable operations have a longer duration when compared to non-profit for all signals except the IFR, when there was an opposite behavior of this pattern / Esta dissertação tem como objetivo principal avaliar se a análise técnica é capaz de produzir resultados financeiros superiores ao modelo buy and hold, o qual preconiza a compra e a venda de ações a médio ou longo prazo, sem utilização de critérios ou ferramentas específicas para nortear esse tipo de decisão. A amostra foi composta por quatorze ações, de oito setores diferentes da economia, o período da pesquisa foi de 2000 a 2010 e os testes foram realizados com cinco dos principais indicadores (sinais) da análise técnica. Optou-se por testar se a média móvel simples de 233 períodos seria capaz de aumentar a rentabilidade obtida pelos sinais. Foi avaliado o impacto da geração de um sinal de compra nos retornos de cinco ações, por meio da metodologia de estudo de eventos e, por fim, avaliou-se a duração média das operações realizadas pelos sinais estudados. Os resultados indicaram que dentro de 350 casos, somente em 61 a rentabilidade obtida com os sinais da análise técnica foi superior à obtida pelo modelo buy and hold. Por meio do teste do qui-quadrado, constatou-se que tal frequência não é estatisticamente igual à metade dos casos, portanto, conclui-se que a análise técnica não foi capaz de produzir resultados financeiros superiores ao buy and hold. Os resultados evidenciaram que não houve melhora significativa na rentabilidade com a utilização da média móvel simples de 233 dias como regra de filtro, pois, não foi constatada diferença estatisticamente significativa nas médias das rentabilidades obtidas por cada sinal, com e sem o filtro. Os estudos de eventos revelaram que somente em um dos cinco eventos analisados ocorreu um impacto positivo e estatisticamente significativo nos retornos das ações. A análise da duração das operações indicou que as operações lucrativas possuem uma duração maior quando comparada às não lucrativas para todos os sinais, exceto no IFR, quando se verificou um comportamento oposto desse padrão

The thesis describes the stock exchange environment, the system and its basic operating principles. The thesis further focuses on the stock exchange data and its analysis. The author describes the development of the technical analysis; he mentions the classical theory and the classical graphical methods, the modern graphical methods, the technical indicators and finally the latest analytical methods, the so-called Artificial Intelligence. The research focuses on the real stock market prediction using the artificial intelligence methods and knowledge of the modern technical analysis.

<p>In this thesis, we conduct a case study by applying simple technical trading rules on Chinese stock market. The technical trading rules we tested are moving average rules and trading range breakout rules. The stock indices we tested are SSE A (Shanghai A) and SZSE (Shenzhen A) share, these shares are limited to the Chinese domestic traders. Our main trading rule frameworks are mainly from Brock, Lakonishok& Lebaron (1992), which including the most basic technical trading rules and covered various length of period, however we add the 25 days moving average to our frame work. We obtained our data from DataStream; the data are the daily closing prices of two indices we mentioned above.</p><p>We compared the mean return and Sharpe ratio with buy and hold. We further calculated breakeven transaction costs to test whether the technical trading rules can still add wealth to investors after adjusting the transaction costs. Our results showed that most technical trading rules perform better than buy and hold. VMA perform better than FMA and TRB, short period (25 and 50 days) performed better than longer period. On mean return, our data violated the assumption of parametric statistical test. We performed non-parametric tests, all the trading rules showed statistical significance at 95% level than buy and hold except FMA (1, 25,0), all the trading rules resulted higher Sharpe ratio than buy and hold. On transaction costs, 7 trading rules on SSE A are performed poorer than buy and hold, all the other rules provided positive breakeven transaction costs. Across the entire trading rule, both stock markets offered positive break-even transaction costs, 0.436% for SSE A and 1.369% for SZSE A. and they are both higher than the maximum transaction costs one bears.</p>

Thesis (Ph.D. (Risk Management))--North-West University, Potchefstroom Campus, 2008.

Background: The efficient market hypothesis asserts that one cannot consistently achieve returns in excess of market returns by trading on publicly available information. Since there is no collective market return in the foreign exchange (FX) market, it has generally been perceived as impossible to consistently generate a profit. There is now empirical evidence which seriously call into question the efficiency of the FX market and opens up the possibility to turn a profit on the FX market by ways of analysis.Technical analysis is a method of analysis which by using historical price data tries to deduce future price changes. Technical analysis assumes that financial markets move in sine waves. There are stronger and weaker sine waves simultaneously. An accurate identification of the dominant sine wave gives the investor a good idea about future movement. Most technical trading tools approximate the length of the sine wave by default. This static approach does not consider the specific market or the recent lengths of the dominant sine wave. Spectral analysis will help to identify the dominant cycle, and thus determine the frequency of that cycle making the applied trading rules adaptive to the market. Purpose: The purpose is to investigate whether adding spectral analysis to existing technical analysis tools can create a higher and more stable return on investment on the FX market. Method: An experiment involving four different sets of trading rules was conducted to answer the purpose. In the first test, trades were performed based on a static approach commonly used by technical traders today. In the other three tests different transforms of spectral analysis were applied, thus making the input not static, but adaptive to the market. The four sets of trading rules where coded as an automatic trading algorithm and backtested on data collected for the currency-pair EURGBP during an 11-month period. All four tests were analysed in three different areas; performance, stability of return and crash risk. Results: The study shows that the application of spectral analysis to technical analysis methods on the FX market results in higher return on investment and better stability of returns. The win/lose ratio is significantly higher and the adaptive approach increases profit as well as decreases losses. / Bakgrund: Den effektiva marknadshypotesen stadgar att det inte är möjligt att stadigt generera högre avkastning än marknadens kollektiva avkastning genom att köpa och sälja baserat på tillgänglig information. Eftersom det inte finns någon kollektiv avkastning på valutamarknaden har det länge ansetts omöjligt att generera någon stabil vinst på denna marknad. Det finns numera empiriskt bevis som tydligt ifrågasätter valutamarknadens egentliga effektivitet och som också i sin tur öppnar upp för möjligheten att generera stabil avkastning på valutamarknaden genom analys.Teknisk analys är en analysmetod som genom avläsandet av historisk prisdata försöker utläsa framtida prisförändringar. Teknisk analys antar att finansiella marknader rör sig i sinuskurvor. Det finns starkare och svagare sinuskurvor. En exakt identifikation av den dominanta cykeln ger investeraren en god idé om framtida rörelser. De flesta tekniska analysverktygen uppskattar längden på cykeln statiskt och tar varken hänsyn till den specifika marknaden eller hur den dominanta cykeln har sett ut nyligen. Spektralanalys identifierar den dominanta cykeln varigenom frekvensen av densamma kan bestämmas och analysverktyget görs adaptivt till marknaden. Syfte: Syftet med uppsatsen är att ta reda på huruvida teknisk analys på valutamarknaden kan skapa en högre och mer stabil avkastning på investerat kapital genom användandet av spektralanalys för att mäta den dominanta cykeln. Metod: Ett experiment innehållande fyra olika uppsättningar av analysverktyg gjordes för att besvara syftet. Handel i det första testet baserades på en statisk ansats som normalt används av tekniska analytiker idag. På de andra tre testerna applicerades olika transformer av spektralanalys och gjordes därigenom adaptiva till marknaden. Analysverktygen kodades som en automatisk handelsalgoritm och testades retroaktivt på insamlad data för valutaparet EURGBP under elva månader. Samtliga fyra tester analyserades i tre olika områden; prestation, avkastningsstabilitet och risk att förlora hela kapitalet. Resultat: Studien visar att applikationen av spektralanalys på tekniska analysverktyg på valutamarknaden resulterar i högre avkastning på investerat kapital och högre avkastningsstabilitet. Vinst/förlust ration är väsentligt högre och den adaptiva ansatsen ökar avkastning samtidigt som den minskar förluster.

In this thesis, we conduct a case study by applying simple technical trading rules on Chinese stock market. The technical trading rules we tested are moving average rules and trading range breakout rules. The stock indices we tested are SSE A (Shanghai A) and SZSE (Shenzhen A) share, these shares are limited to the Chinese domestic traders. Our main trading rule frameworks are mainly from Brock, Lakonishok&amp; Lebaron (1992), which including the most basic technical trading rules and covered various length of period, however we add the 25 days moving average to our frame work. We obtained our data from DataStream; the data are the daily closing prices of two indices we mentioned above. We compared the mean return and Sharpe ratio with buy and hold. We further calculated breakeven transaction costs to test whether the technical trading rules can still add wealth to investors after adjusting the transaction costs. Our results showed that most technical trading rules perform better than buy and hold. VMA perform better than FMA and TRB, short period (25 and 50 days) performed better than longer period. On mean return, our data violated the assumption of parametric statistical test. We performed non-parametric tests, all the trading rules showed statistical significance at 95% level than buy and hold except FMA (1, 25,0), all the trading rules resulted higher Sharpe ratio than buy and hold. On transaction costs, 7 trading rules on SSE A are performed poorer than buy and hold, all the other rules provided positive breakeven transaction costs. Across the entire trading rule, both stock markets offered positive break-even transaction costs, 0.436% for SSE A and 1.369% for SZSE A. and they are both higher than the maximum transaction costs one bears.

The rapid growth of the Internet has shaped up the global economy. The stock market information is thus more and more transparent. Although the investors can get more helpful information to judge future trend of the stock market, they may get wrong judgments because the stock market data are too huge to be completely analyzed. Therefore, the purpose of this study is to develop an artificial stock market analyst by employing the information technology with high speed and performance, as well as integrating the artificial intelligence techniques. We exploit case-based reasoning to simulate the analysts in using history stock market data, employ the artificial neural network to imitate the analysts in analyzing the macrofactors of stock market, and apply the fuzzy logic to humanize the artificial stock market analyst in making judgments close to the real stock market analysts. The artificial stock market analyst would use the modified case-based reasoning system combined with the artificial neural network, and incorporate the designed membership functions for macrofactors of stock market. We expect the system to improve the accuracy of Taiwan electric stock price prediction by applying macrofactors from the technical analysis indicators and financial crisis factors, and make better stock trading strategies.

<p><strong>Background: </strong></p><p>The efficient market hypothesis asserts that one cannot consistently achieve returns in excess of market returns by trading on publicly available information. Since there is no collective market return in the foreign exchange (FX) market, it has generally been perceived as impossible to consistently generate a profit. There is now empirical evidence which seriously call into question the efficiency of the FX market and opens up the possibility to turn a profit on the FX market by ways of analysis.Technical analysis is a method of analysis which by using historical price data tries to deduce future price changes. Technical analysis assumes that financial markets move in sine waves. There are stronger and weaker sine waves simultaneously. An accurate identification of the dominant sine wave gives the investor a good idea about future movement. Most technical trading tools approximate the length of the sine wave by default. This static approach does not consider the specific market or the recent lengths of the dominant sine wave. Spectral analysis will help to identify the dominant cycle, and thus determine the frequency of that cycle making the applied trading rules adaptive to the market.</p><p><strong>Purpose: </strong></p><p>The purpose is to investigate whether adding spectral analysis to existing technical analysis tools can create a higher and more stable return on investment on the FX market.</p><p><strong>Method: </strong></p><p>An experiment involving four different sets of trading rules was conducted to answer the purpose. In the first test, trades were performed based on a static approach commonly used by technical traders today. In the other three tests different transforms of spectral analysis were applied, thus making the input not static, but adaptive to the market. The four sets of trading rules where coded as an automatic trading algorithm and backtested on data collected for the currency-pair EURGBP during an 11-month period. All four tests were analysed in three different areas; performance, stability of return and crash risk.</p><p><strong>Results: </strong></p><p><strong></strong>The study shows that the application of spectral analysis to technical analysis methods on the FX market results in higher return on investment and better stability of returns. The win/lose ratio is significantly higher and the adaptive approach increases profit as well as decreases losses.</p> / <p><strong>Bakgrund: </strong></p><p>Den effektiva marknadshypotesen stadgar att det inte är möjligt att stadigt generera högre avkastning än marknadens kollektiva avkastning genom att köpa och sälja baserat på tillgänglig information. Eftersom det inte finns någon kollektiv avkastning på valutamarknaden har det länge ansetts omöjligt att generera någon stabil vinst på denna marknad. Det finns numera empiriskt bevis som tydligt ifrågasätter valutamarknadens egentliga effektivitet och som också i sin tur öppnar upp för möjligheten att generera stabil avkastning på valutamarknaden genom analys.Teknisk analys är en analysmetod som genom avläsandet av historisk prisdata försöker utläsa framtida prisförändringar. Teknisk analys antar att finansiella marknader rör sig i sinuskurvor. Det finns starkare och svagare sinuskurvor. En exakt identifikation av den dominanta cykeln ger investeraren en god idé om framtida rörelser. De flesta tekniska analysverktygen uppskattar längden på cykeln statiskt och tar varken hänsyn till den specifika marknaden eller hur den dominanta cykeln har sett ut nyligen. Spektralanalys identifierar den dominanta cykeln varigenom frekvensen av densamma kan bestämmas och analysverktyget görs adaptivt till marknaden.</p><p><strong>Syfte: </strong></p><p>Syftet med uppsatsen är att ta reda på huruvida teknisk analys på valutamarknaden kan skapa en högre och mer stabil avkastning på investerat kapital genom användandet av spektralanalys för att mäta den dominanta cykeln.</p><p><strong>Metod: </strong></p><p>Ett experiment innehållande fyra olika uppsättningar av analysverktyg gjordes för att besvara syftet. Handel i det första testet baserades på en statisk ansats som normalt används av tekniska analytiker idag. På de andra tre testerna applicerades olika transformer av spektralanalys och gjordes därigenom adaptiva till marknaden. Analysverktygen kodades som en automatisk handelsalgoritm och testades retroaktivt på insamlad data för valutaparet EURGBP under elva månader. Samtliga fyra tester analyserades i tre olika områden; prestation, avkastningsstabilitet och risk att förlora hela kapitalet.</p><p><strong>Resultat: </strong></p><p><strong></strong>Studien visar att applikationen av spektralanalys på tekniska analysverktyg på valutamarknaden resulterar i högre avkastning på investerat kapital och högre avkastningsstabilitet. Vinst/förlust ration är väsentligt högre och den adaptiva ansatsen ökar avkastning samtidigt som den minskar förluster.</p>