Taiwan Security Market is a typical order-driven market. The electronic trading system of Taiwan Security Market launched in 1998 significantly reduces the trade matching time (the current matching time is around 20 seconds) and promptly provides updated online trading information to traders. In this study, we establish an online transaction simulation system which can be applied to predict trade prices and study market efficiency. Models are established for the times and volumes of the newly added bid/ask orders on the match list. Exponentially weighted moving average (EWMA) method is adopted to update the model parameters. Match prices are predicted dynamically based on the EWMA updated models. Further, high frequency bid/ask order data are used to find the supply and demand curves as well as the equilibrium prices. Differences between the transaction prices and the equilibrium prices are used to investigate the efficiency of Taiwan Security Market. Finally, EWMA and cusum control charts are used to monitor the market efficiency. In empirical study, we analyze the intra-daily (April, 2005) high frequency match data of Uni-president Enterprises Corporation and Formosa Plastics Corporation.

Radar signal processing techniques aim to suppress clutter to enable target detection. Many clutter suppression techniques have been developed to improve the detection performance in literature. Among these methods, the most widely known is MTI plus coherent integrator, which gives sufficient radar performance in various scenarios. However, when the correlation coefficient of clutter is small or the spectral separation between the target and clutter is small, classical approaches to clutter suppression fall short. In this study, we consider the ARMA spectral estimation performance in sea clutter modelled by compound K-distribution through Monte Carlo simulations. The method is applied for varying conditions of clutter spikiness and auto correlation sequences (ACS) depending on the radar operation. The performance of clutter suppression using ARMA spectral estimator, which will be called ARMA-CS in this work, is analyzed under varying ARMA model orders. To compare the clutter suppression of ARMA-CS with that of conventional methods, we use improvement factor (IF) which is the ratio between the output Signal to Interference Ratio (SIR) and input SIR as performance measure. In all cases, the performance of ARMA-CS method is better than conventional clutter suppression methods when the correlation among clutter samples is small or the spectral separation between target and clutter is small.

Die vorliegende Arbeit beschäftigt sich mit dem Problem der zufälligen Wärmeausbreitung in beschränkten Gebieten. Dieses Phänomen wird dabei durch eine lineare parabolische Randanfangswertaufabe beschrieben, wobei die Anfangsbedingung und die Neumannrandbedingung als zufällige Felder mit gegebener Wahrscheinlichkeitsverteilung angenommen werden. Des Weiteren werden die zufälligen Felder als homogen und epsilon-korreliert mit einer kleinen Korrelationslänge epsilon > 0 vorausgesetzt und sollen glatte Realisierungen besitzen. Zur Lösung der Randanfangswertaufgabe werden sowohl die klassische Formulierung als auch die Variationsformulierung herangezogen und in diesem Zusammenhang die Fourier Methode sowie die Finite-Elemente Methode betrachtet. Die Finite-Elemente Methode und die Fourier-Methode führen auf einen expliziten funktionalen Zusammenhang zwischen der zufälligen Lösung der betrachteten Randanfangswertaufgabe und den Einflussgrößen, so dass Momentenfunktionen davon abgeleitet werden können. Das Hauptinteresse dieser Arbeit liegt auf der Berechnung dieser Momentenfunktionen, welche durch die gewählten Eigenschaften der stochastischen Einflußgrößen bestimmt werden. Basierend auf dem Finite-Elemente Ansatz bzw. dem Fourier Ansatz werden verschiedene Approximationsmöglichkeiten insbesondere für die Korrelationsfunktion erörtert. Des Weiteren wird die Möglichkeit der Simulation des zufälligen Randanfangswertproblems betrachtet. Hierzu wird zur Simulation der zufälligen Einflussgrößen auf die Theorie von Moving Average Feldern zurückgegriffen. Der letzte Teil der Arbeit widmet sich dem Vergleich der erhaltenen analytischen Resultate anhand konkreter numerischer Beispiele.

Detecting abnormal operating conditions, which will lead to faults developing later, has important economic implications for industries trying to meet their performance and production goals. It is unacceptable to wait for failures that have potential safety, environmental and financial consequences. Moving from a “reactive” strategy to a “proactive” strategy can improve critical equipment reliability and availability while constraining maintenance costs, reducing production deferrals, decreasing the need for spare parts. Once the fault initiates, predicting its progression and deterioration can enable timely interventions without risk to personnel safety or to equipment integrity. This work presents an online-integrated condition monitoring and prognostics framework that addresses the above issues holistically. The proposed framework aligns fully with ISO 17359:2011 and derives from the I-P and P-F curve. Depending upon the running state of machine with respect to its I-P and P-F curve an algorithm will do one of the following: (1) Predict the ideal behaviour and any departure from the normal operating envelope using a combination of Evolving Clustering Method (ECM), a normalised fuzzy weighted distance and tracking signal method. (2) Identify the cause of the departure through an automated diagnostics system using a modified version of ECM for classification. (3) Predict the short-term progression of fault using a modified version of the Dynamic Evolving Neuro-Fuzzy Inference System (DENFIS), called here MDENFIS and a tracking signal method. (4) Predict the long term progression of fault (Prognostics) using a combination of Autoregressive Integrated Moving Average (ARIMA)- Empirical Mode Decomposition (EMD) for predicting the future input values and MDENFIS for predicting the long term progression of fault (output). The proposed model was tested and compared against other models in the literature using benchmarks and field data. This work demonstrates four noticeable improvements over previous methods: (1) Enhanced testing prediction accuracy, (2) comparable processing time if not better, (3) the ability to detect sudden changes in the process and finally (4) the ability to identify and isolate the problem source with high accuracy.

Στο πρώτο κεφάλαιο εισάγουμε τις βασικές έννοιες της διπλωματικής εργασίας. Αναφέρουμε τους ορισμούς και τον σκοπό της ανάλυσης χρονολογικών σειρών. Επίσης εισάγονται ορισμένα βασικά χαρακτηριστικά των χρονολογικών σειρών όπως η έννοια της στασιμότητας και της συνάρτησης αυτοσυσχέτισης και αναφέρουμε τις τρεις βασικές κατηγορίες στοχαστικών υποδειγμάτων χρονολογικών σειρών που αφορούν στις στάσιμες στοχαστικές διαδικασίες, οι οποίες θα αναλυθούν στα επόμενα κεφάλαια. Στο δεύτερο κεφάλαιο αναλύουμε τα αυτοπαλίνδρομα υποδείγματα, πρώτης, δεύτερης και γενικά p τάξης. Αναφέρονται παραδείγματα. Στο τρίτο κεφάλαιο αναλύουμε τα υποδείγματα κινητού μέσου πρώτης και γενικά q τάξης καθώς και μεικτά υποδείγματα πρώτης και γενικά (p,q) τάξης. Αναφέρονται παραδείγματα. Στο τέταρτο κεφάλαιο αναλύουμε χρονολογικές σειρές που δεν έχουν τα χαρακτηριστικά στάσιμων στοχαστικών διαδικασιών. Επίσης αναλύουμε την μεθοδολογία Box-Jenkins, η οποία είναι μία μέθοδος εξεύρεσης ενός στατιστικού υποδείγματος (ARIMA). Τέλος εφαρμόζεται η παραπάνω μέθοδος σε ένα παράδειγμα με τη χρήση του SPSS. / At the first chapter we introduce the basic concepts. We present the main definitions and the objectives of the time series analysis. Furthermore, we introduce some basic characteristics of the time series such as the concepts of “stationary process” and “autocorrelation”. Finally we mention three basic categories of time series models that concern stationary stochastic processes. Following in the second chapter we analyze the autoregressive models of first, second and generally “p” order. We present various relative examples. At the third chapter we analyze the moving average models of first and generally “q” order. Additionally, we analyze the mixed models of first and generally (p,q) order. Various relative examples are presented. Finally, at the forth chapter we analyze time series that don’t have the characteristics of stationary stochastic proceedings. Also we analyze the method Box-Jenkins. Furthermore, the later method is studied using the statistic software package SPSS.

Darbe „Akcijų kainų kintamumo analizė“ nagrinėjami ir lyginami Baltijos (Lietuvos, Latvijos, Estijos) bei Lotynų Amerikos (Meksikos, Venesuelos) šalių duomenys. Atliekama pasirinktų akcijų kainų grąžų analizė. Jai naudojami trijų metų kiekvienos dienos duomenys (akcijų kainos). Pirmoje darbo dalyje supažindinama su bendra prognozavimo metodų teorija, aprašomi skirtingi, dažnai literatūroje ir praktikoje sutinkami modeliai. Antrojoje dalyje aprašyti prognozavimo metodai taikomi realiems duomenims, t.y. pasirinktoms akcijoms. Prognozuojama akcijų kainų grąža, kuri po to yra palyginama su realia reikšme, apskaičiuojamos prognozavimo metodų paklaidos. Pagrindinis darbo tikslas – atlikti lyginamąją prognozavimo modelių analizę su pasirinktomis akcijomis ir atrinkti tuos metodus, kurie duoda geriausius rezultatus. Darbo tikslui įgyvendinti naudojama SAS statistinio paketo ekonometrikos ir laiko eilučių analizės posistemė SAS/ETS (Time Series Forecasting System). / Most of empirical surveys in macro and financial economics are based on time series analysis. In this work, data of Baltic and Latin America countries is being analyzed and compared. Analysis of stock price returns is presented using daily long term (three years) period data. In the first part of this work general forecasting theory is presented, also different methods, frequently met in the literature and practice, are described. In the second part, forecasting models are being applied for real data. We present results of forecasting stock returns comparing them with real values. Also a precision of forecasts is being calculated, which let us to decide about propriety of each model. Consequently, the aim of this work is to forecast returns of stock price by various time series models and to choose the best one. The analysis was made using SAS statistical package and its econometrics and Time Series Analysis System (SAS/ETS).

Tiriamajame darbe nagrinėjama techninės analizės metodų pelningumas bei patikimumas, jų praktinė nauda ir veikimo principai mažesnėse akcijų biržose (Vilniaus, Rygos, Talino). Gautų rezultatų palyginimui į tyrimą įtraukiama S&P500 akcijų indeksas. Pagrindinis tyrimo tikslas išnagrinėti du techninės analizės metodus - Santykinio stiprumo indeksą ir Slankiųjų vidurkių metodą, praktiškai juos panaudojant aukščiau paminėtose akcijų biržose, ištirti generuojamų pirkimo – pardavimo signalų patikimumą. Fundamentalios analizės atveju yra nagrinėjama Lietuvos komercinių bankų teikiamų konkrečių įmonių akcijų apžvalgų-rekomendacijų, patikimumas bei praktinė nauda. Pirmoje darbo dalyje aprašoma efektyvios rinkos teorijos prasmė (pamatinė techninės ir fundamentalios analizės teorija), kartu paliečiant pagrindinius fundamentalios ir techninės analizės principus. Plačiau nagrinėjami pasaulyje atlikti techninės analizės tyrimai, gauti jų rezultatai. Antroje darbo dalyje pateikiama metodologija kaip buvo atliktas techninės analizės tyrimas su Baltijos šalių ir JAV akcijų indeksais, nubrėžiamos pagrindinės tyrimo ribos. Trečioje tyrimo dalyje pateikiami rezultatai. Didžiausias metinis pelningumas buvo gautas remiantis Slankiųjų vidurkių metodu (50/200 su OMXV akcijų indeksu) – 24,44 proc., kai tuo tarpu „pirk ir laikyk“ strategijos gautas pelningumas – 22,68 proc. po mokesčių. RSI indekso metodas geriausiai pasiteisino su S&P500 akcijų indeksu. Šio metodo metinė grąža siekė 2,15 proc., o... [toliau žr. visą tekstą] / The profitability and reliability of technical analysis methods is the main theme of this work. The practical value of these methods and main rules of operation are analyzed in smaller markets (Vilnius, Ryga and Tallin) and also in comparison with S&P 500 index. The main purpose of this study is to practically test couple of technical analysis methods (Relative Strength Index – RSI and Dual Moving Average Crossover - DMAC) by applying them in markets mentioned above, explore the signals for buying and selling. The fundamental analysis is evaluated while analyzing the reliability and practical benefits of recommendations provided by the commercial banks of Lithuania. The meaning of efficient market theory (it’s the most basic theory for technical and fundamental analysis) is described in literature analysis part. Also, the main rules of fundamental and technical analysis are described there. All the methodology of the research with Baltic and USA indexes is provided in the second part of the work. The third part is filled with results of the research. The best annual after tax gain providing method was DMAC (Dual Moving Average Crossover) (50/200 with OMXV share index) with 22,44% gain for the shareholder, while “buy and keep” strategy provided only 22,68%. RSI (Relative Strength Index) worked best with S&P500 index. The annual odd of this method was 2,15%, while “buy and keep” strategy was only 0,087. DMAC (20/100) also worked best while analyzing the truthfulness of... [to full text]

有鑑於台灣銀行保險市場重要性之提升，金融各界皆高度關注銀行保險市場的發展，然而國內尚缺乏專業客觀的指標以全面地衡量銀行保險市場，僅能就每月公布之新契約保費收入數據觀察銀行保險市場。因此本研究目的為建置多元化銀行保險市場指標，分別為總體經濟因素指標、銀行保險業務趨勢指標與市場專業意見指標，以提供市場各界評估銀行保險市場之發展。 　 總體經濟因素指標部分，本研究利用多元迴歸模型，分析對於我國銀行保險市場有顯著影響力的因子，包括一年期定存利率、景氣對策信號分數、超額儲蓄率、金融保險業從業人員數與台灣整體銀行分行數等，並據以建置總體經濟因素指標。銀行保險業務趨勢指標部分，本研究利用移動平均法，觀測銀行保險市場的業務趨勢，以長短期均線比較方式，用以建構評估銀行保險業務變動趨勢。　　市場專業意見指標部分，本研究蒐集彙整銀行保險市場專業經理人及從業人員之意見，以建構市場專業意見指標，透過上述三項指標提供市場更完整專業的市場資訊與預測工具，使本研究建置之指標不僅於量化數據而兼顧質化意見。 / Bancassurance is unquestionably one of the most important trend in Taiwan’s financial market, and has received much attention from both researchers and policymakers. The aim of this article is to construct bancassurance indicators for Taiwan, which provide more diverse and professional ways to measure and predict bancassurance market. We build three indicators, they are about the influence of macroeconomic factors, the trend in bancassurance, and the professional advice from bancassurance experts, and we name them Macro-indicator, Trend-indicator, and Expert-indicator respectively. Every indicator are built with different methods, the Macro-indicator is constructed by creating a multiple regression model that is using first year premium for bancassurance as a dependent variable with macroeconomic factors as predictor variables, which are 1-year interest rate, monitoring indicator, excess saving rate, number of employees in financial market, and number of bank branches in Taiwan. Also, we use the concept of moving average method in technical analysis to develop the Trend-indicator, which can be used to examine trends and patterns as well as infer future trends by observing the momentum in bancassurance market. To　provide the market more insights, we set up an electronic platform to collect professional advices and ideas from bancassurance experts so that we could understand bancassurance market condition and direction more objectively.

På bullriga arbetsplatser använder personal ofta hörselskydd med inbyggda högtalare för att lyssna på exempelvis musik i underhållningssyfte. Om användaren lyssnar på höga ljudnivåer under långa perioder kan bullerskador uppstå i dennes öron. Enligt lagstiftning måste nivån därför begränsas i förebyggande syfte. Bullernivån är ett genomsnitt av de ljudnivåer användaren exponerats för under en arbetsdag. Användaren måste vila öronen om gränsvärdet för bullernivån nås.Om man utnyttjar att det är ett genomsnitt kan användaren tillåtas lyssna på en hög ljudnivå under en begränsad tid för att sedan sänka den. Det går att bevara både säkerheten och lyssningsupplevelsen om en sänkning införs långsamt. Detta arbete beskriver hur en algoritm till en digital signalprocessor kan konstrueras för att reglera ljudnivån.Målsättningen var att algoritmen skulle skydda användarens hörsel utan att försämra lyssningsupplevelsen, och utan att förbruka mer energi än nödvändigt. I algoritmen ingick en prediktor som predikterar mängden buller användaren riskerar att utsättas för, om denne fortsätter lyssna på samma nivå.Långsamma sänkningar av ljudnivån kan då utföras i tid innan gränsvärdet nås. Det visade sig att algoritmen endast behövde ett fåtal samplingar per sekund för att skatta och reglera ljudnivån tillräckligt precist, vilket reducerade energiförbrukningen.Resultatet visar möjligheten att kombinera målen för säkerhet, lyssningsupplevelse och energieffektivitet i hörselskydd. Algoritmen implementerades inte på ett skarpt system.Den hade enbart tillgång till ljudsignalen användaren ämnade lyssna på i underhållningssyfte. / In noisy workplaces the staff are often using hearing protectors with built-in speakers for entertainment purposes. Prolonged exposure to loud sound levels can cause damage to the user’s ears. The legislation requires therefore a limiting mechanism for the speakers. The noise level is defined as the average of the sound levels the user has been exposed to during a working day. If the noise threshold is reached the user has to rest his ears. This definition can be exploited to allow the user to listen to a loud sound level for a limited time and then lowering it. If the sound level is lowered slowly, it is possible to preserve both safety and listening experience. This work describes how an algorithm can be designed for a digital signal processor with the purpose of controlling the sound level. The aim was to protect the user's hearing without spoiling the listening experience, and without consuming more power than necessary. The algorithm design included a predictor that predicts the amount of noise the user risk being subjected to, if he continues to listen at the same level. Slow reduction of the sound level can then be carried out in time before the noise threshold is reached. It turned out that the algorithm only needed a few samples per second to estimate and control the sound level sufficiently precisely, this reduced the power consumption. The results show that it is possible to combine the objectives for safety, listening experience and power consumption in hearing protectors. The algorithm was not implemented in a real system. The algorithm had only access to the audio signal which the user intended to listen to for entertainment purposes.

In this thesis two different problems in distributed sensor networks are considered. Part I involves optimal quantiser design for decentralised estimation of a two-state hidden Markov model with dual sensors. The notion of optimality for quantiser design is based on minimising the probability of error in estimating the hidden Markov state. Equations for the filter error are derived for the continuous (unquantised) sensor outputs (signals), which are used to benchmark the performance of the quantisers. Minimising the probability of filter error to obtain the quantiser breakpoints is a difficult problem therefore an alternative method is employed. The quantiser breakpoints are obtained by maximising the mutual information between the quantised signals and the hidden Markov state. This method is known to work well for the single sensor case. Cases with independent and correlated noise across the signals are considered. The method is then applied to Markov processes with Gaussian signal noise, and further investigated through simulation studies. Simulations involving both independent and correlated noise across the sensors are performed and a number of interesting new theoretical results are obtained, particularly in the case of correlated noise. In Part II, the focus shifts to the detection of faults in helicopter transmission systems. The aim of the investigation is to determine whether the acoustic signature can be used for fault detection and diagnosis. To investigate this, statistical change detection algorithms are applied to acoustic vibration data obtained from the main rotor gearbox of a Bell 206 helicopter, which is run at high load under test conditions.