本文改良金融投資技術分析操作方法中, 傳統的「單一移動平均」選股法為「多重移動平均」選股法, 其係以道氏理論上, 所謂的市場同時存在三種趨勢 (主要趨勢, 次級趨勢, 小型趨勢) 為基礎, 建立多重時間架構, 輔以移動平均線為股價趨勢判斷, 以及葛蘭碧八大法則之股價突破 (或跌破) 判斷原則作為操作訊號, 所彚整而提出。實證上, 採用2014年12月31日台灣證券交易所公告之台灣50、中型100, 以及富櫃50成分股為樣本, 並以2001年1月1日至2014年12月31日為回溯期間。在進行策略交易的模擬分析與績效差異檢定後, 實證結果發現, 多重移動平均選股法投資策略績效, 在統計分析上並無法較單一周期投資策略績效為優, 但卻能有效過濾沒必要的交易行為, 使突破買進之假訊號降低, 間接的降低交易次數及減少交易成本。 / This study enhanced from the traditional single period moving average for stock selection into multiple-period moving average counterpart. The theoretical foundation comes from the Dow Theory, which states that there exist three trends simultaneously, that is, major trend, secondary trend, and minor trend. Also, the Granville Rules suggest stock price breaking out may serve as entry and exit signal for trading. Our sample are grouped into three subsamples, Taiwan 50, Mid-Cap 100, Gretai 50. The sample period ranges from 2001/1/1 to 2014/12/31. Our empirical backtesting and performance test suggests that, contrary to our expectations, the multiple period method does not outperform its single period counterpart. However, the multiple period stock selection method may filter out false signals, and thereby reduce not only possible price risk associated with noisy trades but the accompanying transaction costs. / 摘要 I Abstract II 致謝詞 III 目錄 V 圖次 VII 表次 VIII 第一章　緒論 1 第一節　研究背景及動機 1 第二節　研究目的 2 第三節　研究對象與範圍 2 第四節　研究流程 4 第二章　文獻回顧 6 第一節　技術分析理論 6 一、技術分析基本邏輯 6 二、技術分析主要的型態類型 7 第二節　移動平均線的原理 9 一、簡單移動平均線的計算 9 二、移動平均線的常見應用 9 第三節　多重移動平均理論及選股法 11 一、多重移動平均的原理 11 二、多重移動平均的選股模式 11 第四節　相關研究文獻回顧與評析 11 一、過去研究文獻 11 二、文獻評析 16 三、本文假說推論 16 第三章　研究方法 17 第一節　傳統移動平均線選股模式 17 第二節　YC指標選股模式 17 第三節　選股模式績效差異檢定 19 第四節　資料來源與變數選取 19 第四章　實證分析 20 第一節　操作策略績效估計 20 第二節　操作策略績效比較 28 第三節　多重策略模型之適性歸納–由規模的角度 36 第五章　結論與建議 43 參考文獻 44 中文部份 44 英文部份 46 參考網址 46 圖次 圖1-4-1 研究流程圖 5 圖2-1-1 型態類技術理論的基本分類 6 圖2-1-2 市場同時存在三種趨勢 7 圖2-1-3 K線的基本構造 8 圖2-2-1 葛蘭碧(Granville)八大法則概念圖 10 表次 表1-3-1 台股之台灣50成分股 2 表1-3-2 台股之中型100成分股 3 表1-3-3 台股之富櫃50成分股 3 表2-4-1 過去研究文獻的整理 14 表4-1-1 台灣50成份股總交易次數及成本 20 表4-1-2 中型100成份股總交易次數及成本 22 表4-1-3 富櫃50成份股總交易次數及成本 26 表4-1-4 單一與多重模式下交易次數與進出場交易成本彚整 28 表4-2-1 台灣50成份股總報酬及總報酬率 28 表4-2-2 中型100成份股總報酬及總報酬率 30 表4-2-3 富櫃50成份股總報酬及總報酬率 34 表4-2-4 單一與多重策略下的平均總報酬與平均總報酬率彚整 36 表4-3-1 多重策略下總報酬率與市值之迴歸分析 36 表4-3-2 多重策略下總報酬率與股本之迴歸分析 37 表4-3-3 台灣50股本前20%成份股之策略績效及差異比較 37 表4-3-4 台灣50股本後20%成份股之策略績效及差異比較 38 表4-3-5 中型100股本前20%成份股之策略績效及差異比較 39 表4-3-6 中型100股本後20%成份股之策略績效及差異比較 40 表4-3-7 富櫃50股本前20%成份股之策略績效及差異比較 41 表4-3-8 富櫃50股本後20%成份股之策略績效及差異比較 42

The master’s thesis deals with trading the currency market. The aim of thesis is the creation of an automated trading system based on technical analysis. This thesis is divided into several parts. The theoretical aspects and analysis of current situation are followed by automated trading system proposal. The system is designed on basis of technical indicators and tested on historical data and then optimized.

A modelagem de processos espaço-temporais é de suma importância para dados climatológicos, visto que o clima sofre influência temporal e espacial. A classe de modelos STARMA, autorregressivo e de médias móveis espaço-temporal, adequa-se a esses processos, porém, não há, na literatura, um estudo sobre o melhor método para quantificar a dependência espacial, e não é sabido se há uma diferença entre os métodos para esses modelos. Logo, neste trabalho, é realizado um estudo de simulações do modelo STAR, utilizando-se diferentes formas para obter os pesos espaciais. Após concluir as simulações é realizado o ajuste de um modelo STARIMA para um conjunto de dados de médias mensais de temperaturas mínimas diárias coletadas em uma mesorregião localizada no Oeste do Estado do Paraná. Este trabalho é separado em dois artigos e ambos são realizados utilizando-se o programa R. O primeiro é o estudo de simulações, chegando-se à conclusão de que o método para determinar a dependência espacial interfere no resultado da modelagem e depende da região em estudo. No segundo artigo, conclui-se que o inverso da distância é a melhor opção para a matriz de pesos e um modelo STARIMA sazonal tem o melhor ajuste para o conjunto de dados em questão. / Process modeling spatio-temporal is of great importance for climatological data, once that the climate undergoes spatial and temporal influence. The class of models STARMA, autoregressive models and spatio-temporal moving averages, are suitable to the these processes, however, for these models, there is not a study about the best method to quantify the spatial dependence, and/or it is not known whether there is a difference between the methods for these models. In this thesis, a study simulations of the STAR model using different forms for the spatial weights is performed. After the simulation procedure, the STARIMA model is fitted to the real dataset of monthly mean daily minimum temperatures collected in a mesoregion located to the west of the state of Paraná. This thesis is separated into two papers and both are performed using the statistical software R. The first one is the simulation study that concludes that the method for determining the spatial dependence interferes with results of the modeling and depends on the region under study. In the second paper, it is concluded that the inverse distance is the best option for the weight matrix and a seasonal STARIMA model has the best fit for the data set.

<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>

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 focus of this paper is to evaluate if forecast produced by the Central Bank of Sweden (Riksbanken) for the 12 month change in the consumer price index is unbiased? Results shows that for shorter horizons (h &lt; 12) the mean forecast error is unbiased but for longer horizons its negatively biased when inference is done by Maximum entropy bootstrap technique. Can the unbiasedness be improved by strict ap- pliance to econometric methodology? Forecasting with a linear univariate model (seasonal ARIMA) and a multivariate model Vector Error Correction model (VECM) shows that when controlling for the presence of structural breaks VECM outperforms both prediction produced Riksbanken and ARIMA. However Riksbanken had the best precision in their forecast, estimated as MSFE

Accurate forecasting is a real problem at many companies and that includes Alfa Laval in Lund. Alfa Laval experiences problems forecasting for future raw material demand. Management is aware that the forecasting methods used today can be improved or replaced by others. A change could lead to better forecasting accuracy and lower errors which means less inventory, shorter cycle times and better customer service at lower costs. The purpose of this study is to analyze Alfa Laval’s current forecasting models for demand of raw material used for pressed plates, and then determine if other models are better suited for taking into consideration trends and seasonal variation.

In quality control applications, Time-Between-Events (TBE) type observations may be monitored by using Exponentially Weighted Moving Average (EWMA) control charts. A widely accepted model for the TBE processes is the exponential distribution, and hence TBE EWMA charts are designed under this assumption. Nevertheless, practical applications do not always conform to the theory and it is common that the observations do not fit the exponential model. Therefore, control charts that are robust to departures from the assumed distribution are desirable in practice. In this thesis, robustness of the lower-sided TBE EWMA charts to the assumption of exponentially distributed observations has been investigated. Weibull and lognormal distributions are considered in order to represent the departures from the assumed exponential model and Markov Chain approach is utilized for evaluating the performance of the chart. By analyzing the performance results, design settings are suggested in order to achieve robust lower-sided TBE EWMA charts.

<p>Accurate forecasting is a real problem at many companies and that includes Alfa Laval in Lund. Alfa Laval experiences problems forecasting for future raw material demand. Management is aware that the forecasting methods used today can be improved or replaced by others. A change could lead to better forecasting accuracy and lower errors which means less inventory, shorter cycle times and better customer service at lower costs.</p><p>The purpose of this study is to analyze Alfa Laval’s current forecasting models for demand of raw material used for pressed plates, and then determine if other models are better suited for taking into consideration trends and seasonal variation.</p>

Im Mittelpunkt dieser Arbeit steht die Untersuchung des stochastischen Verhaltens von Lösungen parabolischer Randanfangswertprobleme mit zufälligen Koeffizienten. Aufgaben dieser Art entstehen beispielsweise bei der mathematischen Modellierung von Wärmeleitprozessen in Materialien, deren Wärmeleitfähigkeit als zufällige Größe bzw. als zufällige Funktion angesehen werden kann. Die Modellierung dieser stochastischen Einflüsse erfolgt u. a. mit Hilfe von epsilon-korrelierten Funktionen. Um stochastische Charakteristiken wie Erwartungswert-, Korrelations- und Varianzfunktion der Lösung des Randanfangswertproblems näherungsweise zu ermitteln, werden die Ansätze der Finite-Elemente-Methode (FEM), der Fouriermethode sowie der Stochastischen Simulation gewählt. Die beiden erstgenannten Verfahren erfahren eine Kombination mit der Methode der Störungsrechnung, wodurch sich jeweils Entwicklungen der gesuchten Charakteristiken bis zur zweiten Ordnung bezüglich eines Störungsparameters ergeben. Konkrete Ergebnisse werden für einfache ein- und zweidimensionale Gebiete ermittelt. Die Anwendung der Störungsrechnung wird im Fall der FEM zudem analytisch gerechtfertigt. Die Methode der Stochastischen Simulation nutzt die Approximation der eingehenden zufälligen Funktion durch Moving-Average-Felder. Für die Auswertung der auftretenden Integrale bei Anwendung der FEM werden explizite Formeln angegeben. Für einige Beispiele im ein- und zweidimensionalen Fall erfolgt die numerische Umsetzung sowie die grafische Präsentation der Ergebnisse sowie deren Vergleich für die verschiedenen eingesetzten Methoden. / This work focuses on the stochastic behavior of solutions of parabolic initial value problems with random coefficients. This sort of tasks is a result of modeling heat conduction processes on material whose heat conductivity can be considered as a random value or a random function. Stochastic influences are modeled, among others, by epsilon correlated functions. In order to determine stochastic characteristics like expectation value function, correlation function, and variance function of the problems solution approximately, the finite element method (FEM), the Fourier method, and the Monte Carlo Simulation are chosen. The first two methods are combined with perturbation techniques. This leads to expansions of the characteristics up to the second order with respect to a perturbation parameter. Results are determined for cases of one and two dimensional domains. The applicability of perturbation methods is verified for the FEM-based solution. The Monte Carlo Simulation uses the approximation of random functions by moving average fields. Explicit formulas are given for the evaluation of integrals which appear by applying the FEM. The work ends with the presenting of numerical examples for the one and two dimensional case.