TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS


 Allyson Smith
 3 years ago
 Views:
Transcription
1 TEMPORAL PATTERN IDENTIFICATION OF TIME SERIES DATA USING PATTERN WAVELETS AND GENETIC ALGORITHMS RICHARD J. POVINELLI AND XIN FENG Deparmen of Elecrical and Compuer Engineering Marquee Universiy, P.O. ox 88, Milwaukee, WI , USA Ph: Fx: ASTRACT: A new mehod for emporal paern maching of a ime series is developed using paern waveles and geneic algorihms. The paern wavele is applied o he maching of an embedded ime series. A problemspecific finess facor is inroduced in he new algorihm, which is useful o consruc a finess funcion of he feaure space. A wosep process discovers he paern wavele ha yields high finess value. The bes emporal paern maches are found hrough a hresholding process. These maches are kep and he fuure ime series daa poin is used in he geneic algorihm's finess funcion. The algorihm has been successfully applied o he idenificaion of saisically significan emporal paerns in financial ime series daa. Keywords: Temporal Paern Idenificaion, Geneic Algorihms, Paern Recogniion, Time Series Analysis, Waveles INTRODUCTION Daa mining is he exploraion of daa wih he goal of discovering hidden srucure. In many realworld applicaions, i is imporan o sudy he change of emporal feaures of a nonsaionary ime series, and idenify he ones ha are represening he significance of ime insances. For example, i is criical in sock marke applicaions ha he paerns relaing o sudden sock price changes be idenified. Generally such ime series are considered nonsaionary. Tradiional ime series analysis employs saisical mehods o model and explain he daa and predic fuure values of he ime series. I is no easy, however, o idenify he criical emporal paerns of he ime series using hese radiional mehods. Using a se of observaions, in his paper, we presen a new mehod for ime series daa mining. y inroducing a paern wavele along wih he use of a geneic algorihm (GA), emporal paerns can be effecively revealed in nonsaionary ime series. The paper is organized as follows. Afer presening he problem saemen, radiional ARMA modeling is reviewed. The ideas of emporal paern maching
2 and he paern wavele are hen discussed. Nex, a deailed discussion of he new algorihm is provided. Finally, a presenaion of he resuls and conclusions is given. PROLEM STATEMENT Le Z {z,,, N} be he nonsaionary arge ime series, whose emporal feaures evolve over ime. The ask is o find an approach o characerize hese changing emporal feaures. Applying radiional ime series modeling o his problem involves finding soluions o he oxjenkins difference equaion (owerman and O'Connell 993). ( z ) φ δ + θ a, p q where φ p () is he nonseasonal auoregressive operaor of order p, θ q () is he nonseasonal moving average operaor of order q, z is he ime series, a is a sequence of random variables, δ is a consan erm, and is he backshif operaor. The ox Jenkins mehod is limied by he requiremen of saionariy of he ime series and normaliy and independence of he residuals. However, in mos applicaions, hese condiions are no me. One of he mos severe drawbacks of his approach is he loss of he nonsaionary characerisics we desire o idenify. Our mehod akes a new approach. Le z T ( + Q ) z,, z,,, be he se of subime series of lengh Q embedded in Z, where Q N. Clearly, z Z, which may represen he changing emporal feaures or paerns of Z. We propose ha by sudying he embedding z, he emporal feaures of Z may be idenified. The mehod for eliciing he emporal feaures from he embedding z arises from a sudy of waveles and he wavele ransform. The wavele ransform is a naural exension of Fourier's work done in he early 9h cenury. Where Fourier's ransform can find frequency informaion wih no ime reference or ime informaion wih no frequency, he wavele ransform provides boh ime and frequency informaion. Generally speaking, he wavele ransform maches a compacly suppored funcion, called a wavele, across boh scale (frequency) and ranslaion (ime) (Polikar 996). The Fourier ransform maches an infiniely suppored funcion across frequency (scale). oh use convoluion of he basis funcion and he original ime series. For he wavele ransform, i is provided for all scales. Nex we inroduce he so called paern wavele and paern wavele ransform. This ransform is an exension of a discree form of he wavele ransform applied specifically o idenifying emporal feaures. PATTERN WAVELETS y relaxing he resricions of he wavele ransform, he paern wavele ransform is derived. Where he wavele ransform uses he convoluion of he wavele and he
3 ime series, he paern wavele ransform uses a subse of he convoluion of he paern wavele and he ime series. Also, where he wavele is required o have a zero mean, he paern wavele is no. These relaxaions yield a ransform ha idenifies he emporal feaures discussed in he problem saemen. A deailed explanaion of he algorihm follows. Le f(p,δ,z,g) be he paern wavele ransform, where p P R Q is he paern wavele, δ R is a hreshold parameer, and g g(z ) is a measure of finess of he emporal feaure. We wan o find he opimal soluion o he following problem Q max{ f( p δ Z g) p P δ },,, R, R. () p, δ The paern wavele ransform f(p,δ,z,g) is he finess of paern p wih hreshold δ applied o ime series Z wih finess measure g. The following definiions are needed for f. r pz,,,, N Q+ µ r r N Q+ 2 2 σ r ( r µ r) M + { : r µ δσ } r r The vecor z Z is he embedded series of lengh Q, where Q N. The paern facors r,,, NQ+, are elemens of he vecor r R NQ+ which consiss of NQ+ inner producs of he paern wavele p and he embedded ime series z. Also µ r denoes he mean of r, σ r is he sandard deviaion of r, and M is he paern mach se, which is defined as he se of all ime insances where he paern facor r is greaer han or equal o he hreshold µ r + δσ r. Finally, he paern wavele ransform f is defined as he mean of g(z ) for M. f ( p,, Z, g) δ µ M cm M gz (2) where c(m) is he cardinaliy of M. Also σ M is he sandard deviaion of g(z ) a imes M. 2 M ( gz M ) M σ µ cm I should be noed ha he selecion of finess operaor g in (2) is problem specific and is independen of he algorihm. I should be chosen a priori based on he ypes of hidden emporal feaures o be discovered.
4 ecause he maximizaion problem in () is complex and nonlinear, i is difficul o solve using radiional numerical opimizaion mehods. To overcome hese limiaions, a roulee wheel based GA wih eliism (Goldberg 989) searches for he opimal p and δ. Ideally p R Q and δ R, for efficiency purposes p [ε, ε] Q and δ [δ, δ 2 ]. These ranges are discree due o he naure of he GA wih a possible 2 b unique values, where b is he number of bis used o represen p i and δ. The parameers for he GA are Q, Z, g, b, and he populaion size. The parameer b is usually in he range of 4 o 6 and he populaion size is se o 30. The mos elie individual is mainained from generaion o generaion wihou change. No muaion is used. The GA is shown below. Paern Finding Geneic Algorihm. Creae an elie populaion a) Randomly generae large populaion (0 imes normal populaion size) b) Calculae finess c) Selec he op 0h of he populaion o coninue 2. While all finess have no converged a) Perform roulee selecion, save elie individual b) Crossover populaion C)Calculae finess APPLICATION RESULTS The goal of his applicaion is o find hidden emporal paerns in a cerain sock ime series. Our experimenal ime series is he daily open sock price of he Quanum (QNTM, raded on he NASDAQ) ime series Z {z,,, N} wih N3,76. See Figure for illusraion. Obviously, his ime series is nonsaionary. Our special ineres is o idenify he emporal paern ha is relaed o a significan price change. ARMA Model Two ARMA models of he ime series reveal essenially he same random walk characerisics. The models are Figure  Quanum Corp sock ime series
5 z φz + ε (3) + φ z z + ε φ z 2 (4) z z + ε (5) where φ in (3) and φ in (4). The φ in boh models is saisically significan, bu he auocorrelaions of (3) show srong evidence of nonsaionariy and he Ljungox es of he residuals indicaes a lack of independence. The model (4) Ljungox es of he residuals indicaes independence. y seeing ha he φ in (3) and φ 0 in (4), boh models become equivalen (5). The ARMA models provide lile insigh ino hidden srucure in he ime series; he series is a random walk. On he oher hand he mehod presened by he auhors finds saisically significan srucure as presened below. Paern Wavele Model In building he paern wavele model, he finess operaor g in (2) is chosen as gz ( Q ) + z. In our case we wan o find feaures ha indicae a fi % afer he end of he paern mach. We found c(m) o be beween 38 and 34, depending on he suppor of he paern wavele. The saisics for eigh paerns are given in Table. The change in he sock price afer a paern mach was beween +0.7% and +.5%, whereas he average change was +0.2%. This shows ha here is a correlaion beween he paerns and he price changes. The sandard deviaion, hough, is beween 3% and 4% for he paerns and 3% for he average day. The µ M of he mached paerns is beween 5 o 2 higher han µ g(z) of he whole ime series. Two saisical ess are used o show significance of he resuls. The firs es is he runs es. The es hypohesis is H 0 : There is no difference beween he mached ime series and he remaining ime series. H A : There is significan difference beween he mached ime series and he remaining ime series. Our es uses a % probabiliy of Type I error (α 0.0). Table shows ha he null hypohesis can easily be rejeced in all cases. The second saisical es is he difference of wo independen means. The wo populaions are he ransformed series and he whole ime series. Alhough he wo populaions are probably dependen, his can be ignored because i makes he saisics more conservaive, i.e., i will end o overesimae he Type I error. The es hypohesis is H 0 : µ M  µ g(z) 0, H A : µ M  µ g(z) > 0. This es uses a % probabiliy of Type I error (α 0.0). Again, Table shows ha he null hypohesis can be very confidenly rejeced for all he paerns. The mean finess of he ime series µ g(z) , and he σ g(z)
6 TALE STATISTICAL SIGNIFICANCE OF RESULTS Q c(m) µ M σ M Runs es α means es α <.00x x <.00x x <.00x x x x <.00x x <.00x07.5x x x <.00x x05 CONCLUSIONS In his paper, a new mehod for emporal daa mining is proposed. Using a paern wavele ransform as a daa mining ool has yielded meaningful resuls. Insead of forcing he wavele o mach everywhere, i maches only when here is a high similariy beween he paern wavele and he underlying ime series. To find such paern waveles, a geneic algorihm is used. Even wih a complex, nonsaionary ime series like sock price, he algorihm deeced ineresing paerns. Across all esed Q he paerns found were saisically significan. The algorihm is flexible in ha by using an alernaive g, finess funcion, differen srucures can be found. The g used in his research was for posiive changes, bu jus as easily gz ( Q ) + z which would find negaive changes. Also, a more complicaed g could be used ha could ake ino accoun he sandard deviaions of he maches. Fuure research direcions will include exploring combinaions of paerns, looking for paerns in shorer segmens of he ime series, and adding addiional facor dimensions such as volume. REFERENCES owerman,. L., and O'Connell, R. T. (993). Forecasing and Time Series: An Applied Approach, Duxbury Press, elmon, California. Ghoshray, S. (996). Hybrid predicion echnique by fuzzy inferencing on he chaoic naure of ime series daa. Arificial Neural Neworks in Engineering, Proceedings, Goldberg, D. E. (989). Geneic algorihms in search, opimizaion, and machine learning, Addison Wesley Pub. Co., Reading, Mass. Lin, C. T., and Lee, C. S. G. (996). Neural Fuzzy Sysems  A NeuroFuzzy Synergism o Inelligen Sysems, PreniceHall, Upper Saddle River, NJ. Polikar, R. (996). The Engineer's Ulimae Guide To Wavele Analysis  The Wavele Tuorial.. Weigend, A. S., and Gershenfeld, N. A. (994). Time Series Predicion: Forecasing he Fuure and Undersanding he Pas., AddisonWesley Pub. Co., Reading, MA.
TIME SERIES DATA MINING: IDENTIFYING TEMPORAL PATTERNS FOR CHARACTERIZATION AND PREDICTION OF TIME SERIES EVENTS
TIE SERIES DATA INING: IDENTIFYING TEPORAL PATTERNS FOR CHARACTERIZATION AND PREDICTION OF TIE SERIES EVENTS by Richard J. Povinelli, B.A., B.S.,.S. A Disseraion submied o he Faculy of he Graduae School,
More informationChapter 8: Regression with Lagged Explanatory Variables
Chaper 8: Regression wih Lagged Explanaory Variables Time series daa: Y for =1,..,T End goal: Regression model relaing a dependen variable o explanaory variables. Wih ime series new issues arise: 1. One
More informationEconomics 140A Hypothesis Testing in Regression Models
Economics 140A Hypohesis Tesing in Regression Models While i is algebraically simple o work wih a populaion model wih a single varying regressor, mos populaion models have muliple varying regressors 1
More informationSPEC model selection algorithm for ARCH models: an options pricing evaluation framework
Applied Financial Economics Leers, 2008, 4, 419 423 SEC model selecion algorihm for ARCH models: an opions pricing evaluaion framework Savros Degiannakis a, * and Evdokia Xekalaki a,b a Deparmen of Saisics,
More informationUSE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES
USE OF EDUCATION TECHNOLOGY IN ENGLISH CLASSES Mehme Nuri GÖMLEKSİZ Absrac Using educaion echnology in classes helps eachers realize a beer and more effecive learning. In his sudy 150 English eachers were
More informationAn empirical analysis about forecasting Tmall airconditioning sales using time series model Yan Xia
An empirical analysis abou forecasing Tmall aircondiioning sales using ime series model Yan Xia Deparmen of Mahemaics, Ocean Universiy of China, China Absrac Time series model is a hospo in he research
More informationStock Price Prediction Using the ARIMA Model
2014 UKSimAMSS 16h Inernaional Conference on Compuer Modelling and Simulaion Sock Price Predicion Using he ARIMA Model 1 Ayodele A. Adebiyi., 2 Aderemi O. Adewumi 1,2 School of Mahemaic, Saisics & Compuer
More informationTime Series Analysis Using SAS R Part I The Augmented DickeyFuller (ADF) Test
ABSTRACT Time Series Analysis Using SAS R Par I The Augmened DickeyFuller (ADF) Tes By Ismail E. Mohamed The purpose of his series of aricles is o discuss SAS programming echniques specifically designed
More informationJournal Of Business & Economics Research September 2005 Volume 3, Number 9
Opion Pricing And Mone Carlo Simulaions George M. Jabbour, (Email: jabbour@gwu.edu), George Washingon Universiy YiKang Liu, (yikang@gwu.edu), George Washingon Universiy ABSTRACT The advanage of Mone Carlo
More informationON THURSTONE'S MODEL FOR PAIRED COMPARISONS AND RANKING DATA
ON THUSTONE'S MODEL FO PAIED COMPAISONS AND ANKING DATA Alber MaydeuOlivares Dep. of Psychology. Universiy of Barcelona. Paseo Valle de Hebrón, 171. 08035 Barcelona (Spain). Summary. We invesigae by means
More informationDOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR
Invesmen Managemen and Financial Innovaions, Volume 4, Issue 3, 7 33 DOES TRADING VOLUME INFLUENCE GARCH EFFECTS? SOME EVIDENCE FROM THE GREEK MARKET WITH SPECIAL REFERENCE TO BANKING SECTOR Ahanasios
More informationMeasuring macroeconomic volatility Applications to export revenue data, 19702005
FONDATION POUR LES ETUDES ET RERS LE DEVELOPPEMENT INTERNATIONAL Measuring macroeconomic volailiy Applicaions o expor revenue daa, 1970005 by Joël Cariolle Policy brief no. 47 March 01 The FERDI is a
More informationPrincipal components of stock market dynamics. Methodology and applications in brief (to be updated ) Andrei Bouzaev, bouzaev@ya.
Principal componens of sock marke dynamics Mehodology and applicaions in brief o be updaed Andrei Bouzaev, bouzaev@ya.ru Why principal componens are needed Objecives undersand he evidence of more han one
More informationCointegration: The Engle and Granger approach
Coinegraion: The Engle and Granger approach Inroducion Generally one would find mos of he economic variables o be nonsaionary I(1) variables. Hence, any equilibrium heories ha involve hese variables require
More informationDiane K. Michelson, SAS Institute Inc, Cary, NC Annie Dudley Zangi, SAS Institute Inc, Cary, NC
ABSTRACT Paper DK02 SPC Daa Visualizaion of Seasonal and Financial Daa Using JMP Diane K. Michelson, SAS Insiue Inc, Cary, NC Annie Dudley Zangi, SAS Insiue Inc, Cary, NC JMP Sofware offers many ypes
More informationWhy Did the Demand for Cash Decrease Recently in Korea?
Why Did he Demand for Cash Decrease Recenly in Korea? Byoung Hark Yoo Bank of Korea 26. 5 Absrac We explores why cash demand have decreased recenly in Korea. The raio of cash o consumpion fell o 4.7% in
More informationINVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS
INVESTIGATION OF THE INFLUENCE OF UNEMPLOYMENT ON ECONOMIC INDICATORS Ilona Tregub, Olga Filina, Irina Kondakova Financial Universiy under he Governmen of he Russian Federaion 1. Phillips curve In economics,
More informationThe naive method discussed in Lecture 1 uses the most recent observations to forecast future values. That is, Y ˆ t + 1
Business Condiions & Forecasing Exponenial Smoohing LECTURE 2 MOVING AVERAGES AND EXPONENTIAL SMOOTHING OVERVIEW This lecure inroduces imeseries smoohing forecasing mehods. Various models are discussed,
More informationImproving Technical Trading Systems By Using A New MATLAB based Genetic Algorithm Procedure
4h WSEAS In. Conf. on NONLINEAR ANALYSIS, NONLINEAR SYSTEMS and CHAOS, Sofia, Bulgaria, Ocober 2729, 2005 (pp2934) Improving Technical Trading Sysems By Using A New MATLAB based Geneic Algorihm Procedure
More informationDYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS
DYNAMIC MODELS FOR VALUATION OF WRONGFUL DEATH PAYMENTS Hong Mao, Shanghai Second Polyechnic Universiy Krzyszof M. Osaszewski, Illinois Sae Universiy Youyu Zhang, Fudan Universiy ABSTRACT Liigaion, exper
More informationA Note on Using the Svensson procedure to estimate the risk free rate in corporate valuation
A Noe on Using he Svensson procedure o esimae he risk free rae in corporae valuaion By Sven Arnold, Alexander Lahmann and Bernhard Schwezler Ocober 2011 1. The risk free ineres rae in corporae valuaion
More informationVector Autoregressions (VARs): Operational Perspectives
Vecor Auoregressions (VARs): Operaional Perspecives Primary Source: Sock, James H., and Mark W. Wason, Vecor Auoregressions, Journal of Economic Perspecives, Vol. 15 No. 4 (Fall 2001), 101115. Macroeconomericians
More informationMODELING TO ANTICIPATE WORLD PRICE OF EACH OUNCE OF GOLD IN INTERNATIONAL MARKETS
Vol. No.2, pp., June 203 MODELING TO ANTICIPATE WORLD PRICE OF EACH OUNCE OF GOLD IN INTERNATIONAL MARKETS Mohammad Rikhegar Business Managemen, MA Suden Islamic Azad Universiy, a Souh Tehran Branch 009893632406
More informationIndividual Health Insurance April 30, 2008 Pages 167170
Individual Healh Insurance April 30, 2008 Pages 167170 We have received feedback ha his secion of he e is confusing because some of he defined noaion is inconsisen wih comparable life insurance reserve
More informationGenetic Algorithm Search for Predictive Patterns in Multidimensional Time Series
Geneic Algorihm Search for Predicive Paerns in Mulidimensional Time Series Arnold Polanski School of Managemen and Economics Queen s Universiy of Belfas 25 Universiy Square Belfas BT7 1NN, Unied Kingdom
More informationANALYSIS AND COMPARISONS OF SOME SOLUTION CONCEPTS FOR STOCHASTIC PROGRAMMING PROBLEMS
ANALYSIS AND COMPARISONS OF SOME SOLUTION CONCEPTS FOR STOCHASTIC PROGRAMMING PROBLEMS R. Caballero, E. Cerdá, M. M. Muñoz and L. Rey () Deparmen of Applied Economics (Mahemaics), Universiy of Málaga,
More informationA New Type of Combination Forecasting Method Based on PLS
American Journal of Operaions Research, 2012, 2, 408416 hp://dx.doi.org/10.4236/ajor.2012.23049 Published Online Sepember 2012 (hp://www.scirp.org/journal/ajor) A New Type of Combinaion Forecasing Mehod
More informationSURVEYING THE RELATIONSHIP BETWEEN STOCK MARKET MAKER AND LIQUIDITY IN TEHRAN STOCK EXCHANGE COMPANIES
Inernaional Journal of Accouning Research Vol., No. 7, 4 SURVEYING THE RELATIONSHIP BETWEEN STOCK MARKET MAKER AND LIQUIDITY IN TEHRAN STOCK EXCHANGE COMPANIES Mohammad Ebrahimi Erdi, Dr. Azim Aslani,
More informationUsefulness of the Forward Curve in Forecasting Oil Prices
Usefulness of he Forward Curve in Forecasing Oil Prices Akira Yanagisawa Leader Energy Demand, Supply and Forecas Analysis Group The Energy Daa and Modelling Cener Summary When people analyse oil prices,
More informationThe Transport Equation
The Transpor Equaion Consider a fluid, flowing wih velociy, V, in a hin sraigh ube whose cross secion will be denoed by A. Suppose he fluid conains a conaminan whose concenraion a posiion a ime will be
More informationPart 1: White Noise and Moving Average Models
Chaper 3: Forecasing From Time Series Models Par 1: Whie Noise and Moving Average Models Saionariy In his chaper, we sudy models for saionary ime series. A ime series is saionary if is underlying saisical
More informationµ r of the ferrite amounts to 1000...4000. It should be noted that the magnetic length of the + δ
Page 9 Design of Inducors and High Frequency Transformers Inducors sore energy, ransformers ransfer energy. This is he prime difference. The magneic cores are significanly differen for inducors and high
More informationForecasting Malaysian Gold Using. GARCH Model
Applied Mahemaical Sciences, Vol. 7, 2013, no. 58, 28792884 HIKARI Ld, www.mhikari.com Forecasing Malaysian Gold Using GARCH Model Pung Yean Ping 1, Nor Hamizah Miswan 2 and Maizah Hura Ahmad 3 Deparmen
More informationMultiple Structural Breaks in the Nominal Interest Rate and Inflation in Canada and the United States
Deparmen of Economics Discussion Paper 0007 Muliple Srucural Breaks in he Nominal Ineres Rae and Inflaion in Canada and he Unied Saes Frank J. Akins, Universiy of Calgary Preliminary Draf February, 00
More informationThe Relationship between Stock Return Volatility and. Trading Volume: The case of The Philippines*
The Relaionship beween Sock Reurn Volailiy and Trading Volume: The case of The Philippines* Manabu Asai Faculy of Economics Soka Universiy Angelo Unie Economics Deparmen De La Salle Universiy Manila May
More informationGene Regulatory Network Discovery from TimeSeries Gene Expression Data A Computational Intelligence Approach
Gene Regulaory Nework Discovery from TimeSeries Gene Expression Daa A Compuaional Inelligence Approach Nikola K. Kasabov 1, Zeke S. H. Chan 1, Vishal Jain 1, Igor Sidorov 2 and Dimier S. Dimirov 2 1 Knowledge
More informationImprovement in Forecasting Accuracy Using the Hybrid Model of ARFIMA and Feed Forward Neural Network
American Journal of Inelligen Sysems 2012, 2(2): 1217 DOI: 10.5923/j.ajis.20120202.02 Improvemen in Forecasing Accuracy Using he Hybrid Model of ARFIMA and Feed Forward Neural Nework Cagdas Hakan Aladag
More informationMathematics in Pharmacokinetics What and Why (A second attempt to make it clearer)
Mahemaics in Pharmacokineics Wha and Why (A second aemp o make i clearer) We have used equaions for concenraion () as a funcion of ime (). We will coninue o use hese equaions since he plasma concenraions
More informationEvolutionary building of stock trading experts in realtime systems
Evoluionary building of sock rading expers in realime sysems Jerzy J. Korczak Universié Louis Paseur Srasbourg, France Email: jjk@dpinfo.usrasbg.fr Absrac: This paper addresses he problem of consrucing
More informationChapter 7. Response of FirstOrder RL and RC Circuits
Chaper 7. esponse of FirsOrder L and C Circuis 7.1. The Naural esponse of an L Circui 7.2. The Naural esponse of an C Circui 7.3. The ep esponse of L and C Circuis 7.4. A General oluion for ep and Naural
More informationResearch Question Is the average body temperature of healthy adults 98.6 F? Introduction to Hypothesis Testing. Statistical Hypothesis
Inroducion o Hypohesis Tesing Research Quesion Is he average body emperaure of healhy aduls 98.6 F? HT  1 HT  2 Scienific Mehod 1. Sae research hypoheses or quesions. µ = 98.6? 2. Gaher daa or evidence
More informationMACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR
MACROECONOMIC FORECASTS AT THE MOF A LOOK INTO THE REAR VIEW MIRROR The firs experimenal publicaion, which summarised pas and expeced fuure developmen of basic economic indicaors, was published by he Minisry
More informationImpact of Debt on Primary Deficit and GSDP Gap in Odisha: Empirical Evidences
S.R. No. 002 10/2015/CEFT Impac of Deb on Primary Defici and GSDP Gap in Odisha: Empirical Evidences 1. Inroducion The excessive pressure of public expendiure over is revenue receip is financed hrough
More informationIssues Using OLS with Time Series Data. Time series data NOT randomly sampled in same way as cross sectional each obs not i.i.d
These noes largely concern auocorrelaion Issues Using OLS wih Time Series Daa Recall main poins from Chaper 10: Time series daa NOT randomly sampled in same way as cross secional each obs no i.i.d Why?
More informationPredicting Stock Market Index Trading Signals Using Neural Networks
Predicing Sock Marke Index Trading Using Neural Neworks C. D. Tilakarane, S. A. Morris, M. A. Mammadov, C. P. Hurs Cenre for Informaics and Applied Opimizaion School of Informaion Technology and Mahemaical
More informationForecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices
(IJCSIS) ernaional Journal of Compuer Science and formaion Securiy, Forecasing Model for Crude Oil Price Using Arificial Neural Neworks and Commodiy Fuures Prices Siddhivinayak Kulkarni Graduae School
More informationMultiprocessor SystemsonChips
Par of: Muliprocessor SysemsonChips Edied by: Ahmed Amine Jerraya and Wayne Wolf Morgan Kaufmann Publishers, 2005 2 Modeling Shared Resources Conex swiching implies overhead. On a processing elemen,
More informationPROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE
Profi Tes Modelling in Life Assurance Using Spreadshees PROFIT TEST MODELLING IN LIFE ASSURANCE USING SPREADSHEETS PART ONE Erik Alm Peer Millingon 2004 Profi Tes Modelling in Life Assurance Using Spreadshees
More informationDistributing Human Resources among Software Development Projects 1
Disribuing Human Resources among Sofware Developmen Proecs Macario Polo, María Dolores Maeos, Mario Piaini and rancisco Ruiz Summary This paper presens a mehod for esimaing he disribuion of human resources
More informationInventory Planning with Forecast Updates: Approximate Solutions and Cost Error Bounds
OPERATIONS RESEARCH Vol. 54, No. 6, November December 2006, pp. 1079 1097 issn 0030364X eissn 15265463 06 5406 1079 informs doi 10.1287/opre.1060.0338 2006 INFORMS Invenory Planning wih Forecas Updaes:
More informationCointegration Analysis of Exchange Rate in Foreign Exchange Market
Coinegraion Analysis of Exchange Rae in Foreign Exchange Marke Wang Jian, Wang Shuli School of Economics, Wuhan Universiy of Technology, P.R.China, 430074 Absrac: This paper educed ha he series of exchange
More informationAutomatic measurement and detection of GSM interferences
Auomaic measuremen and deecion of GSM inerferences Poor speech qualiy and dropped calls in GSM neworks may be caused by inerferences as a resul of high raffic load. The radio nework analyzers from Rohde
More informationFourier Series Solution of the Heat Equation
Fourier Series Soluion of he Hea Equaion Physical Applicaion; he Hea Equaion In he early nineeenh cenury Joseph Fourier, a French scienis and mahemaician who had accompanied Napoleon on his Egypian campaign,
More informationTerm Structure of Prices of Asian Options
Term Srucure of Prices of Asian Opions Jirô Akahori, Tsuomu Mikami, Kenji Yasuomi and Teruo Yokoa Dep. of Mahemaical Sciences, Risumeikan Universiy 111 Nojihigashi, Kusasu, Shiga 5258577, Japan Email:
More informationA Reexamination of the Joint Mortality Functions
Norh merican cuarial Journal Volume 6, Number 1, p.166170 (2002) Reeaminaion of he Join Morali Funcions bsrac. Heekung Youn, rkad Shemakin, Edwin Herman Universi of S. Thomas, Sain Paul, MN, US Morali
More informationHotel Room Demand Forecasting via Observed Reservation Information
Proceedings of he Asia Pacific Indusrial Engineering & Managemen Sysems Conference 0 V. Kachivichyanuul, H.T. Luong, and R. Piaaso Eds. Hoel Room Demand Forecasing via Observed Reservaion Informaion aragain
More informationModelling and Forecasting Volatility of Gold Price with Other Precious Metals Prices by Univariate GARCH Models
Deparmen of Saisics Maser's Thesis Modelling and Forecasing Volailiy of Gold Price wih Oher Precious Meals Prices by Univariae GARCH Models Yuchen Du 1 Supervisor: Lars Forsberg 1 Yuchen.Du.84@suden.uu.se
More informationFeasibility of Quantum Genetic Algorithm in Optimizing Construction Scheduling
Feasibiliy of Quanum Geneic Algorihm in Opimizing Consrucion Scheduling Maser Thesis Baihui Song JUNE 2013 Commiee members: Prof.dr.ir. M.J.C.M. Herogh Dr. M. Blaauboer Dr. ir. H.K.M. van de Ruienbeek
More informationNEURAL NETWORKS APPLIED TO STOCK MARKET FORECASTING: AN EMPIRICAL ANALYSIS
NEURAL NETWORKS APPLIED TO STOCK MARKET FORECASTING: AN EMPIRICAL ANALYSIS Absrac LEANDRO S. MACIEL, ROSANGELA BALLINI Economics Insiue (IE), Sae Universiy of Campinas (UNICAMP) Piágoras Sree, 65 Cidade
More informationGOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA
Journal of Applied Economics, Vol. IV, No. (Nov 001), 31337 GOOD NEWS, BAD NEWS AND GARCH EFFECTS 313 GOOD NEWS, BAD NEWS AND GARCH EFFECTS IN STOCK RETURN DATA CRAIG A. DEPKEN II * The Universiy of Texas
More informationDDoS Attacks Detection Model and its Application
DDoS Aacks Deecion Model and is Applicaion 1, MUHAI LI, 1 MING LI, XIUYING JIANG 1 School of Informaion Science & Technology Eas China Normal Universiy No. 500, DongChuan Road, Shanghai 0041, PR. China
More informationA Probability Density Function for Google s stocks
A Probabiliy Densiy Funcion for Google s socks V.Dorobanu Physics Deparmen, Poliehnica Universiy of Timisoara, Romania Absrac. I is an approach o inroduce he Fokker Planck equaion as an ineresing naural
More informationInductance and Transient Circuits
Chaper H Inducance and Transien Circuis Blinn College  Physics 2426  Terry Honan As a consequence of Faraday's law a changing curren hrough one coil induces an EMF in anoher coil; his is known as muual
More informationEmerging Stock market Efficiency: Nonlinearity and Episodic Dependences Evidence from Iran stock market
2012, TexRoad Publicaion ISSN 20904304 Journal of Basic and Applied Scienific Research www.exroad.com Emerging Sock marke Efficiency: Nonlineariy and Episodic Dependences Evidence from Iran sock marke
More informationThe Greek financial crisis: growing imbalances and sovereign spreads. Heather D. Gibson, Stephan G. Hall and George S. Tavlas
The Greek financial crisis: growing imbalances and sovereign spreads Heaher D. Gibson, Sephan G. Hall and George S. Tavlas The enry The enry of Greece ino he Eurozone in 2001 produced a dividend in he
More informationAppendix D Flexibility Factor/Margin of Choice Desktop Research
Appendix D Flexibiliy Facor/Margin of Choice Deskop Research Cheshire Eas Council Cheshire Eas Employmen Land Review Conens D1 Flexibiliy Facor/Margin of Choice Deskop Research 2 Final Ocober 2012 \\GLOBAL.ARUP.COM\EUROPE\MANCHESTER\JOBS\200000\22348900\4
More informationFORECASTING NETWORK TRAFFIC: A COMPARISON OF NEURAL NETWORKS AND LINEAR MODELS
Session 2. Saisical Mehods and Their Applicaions Proceedings of he 9h Inernaional Conference Reliabiliy and Saisics in Transporaion and Communicaion (RelSa 09), 21 24 Ocober 2009, Riga, Lavia, p. 170177.
More informationChapter 4: Exponential and Logarithmic Functions
Chaper 4: Eponenial and Logarihmic Funcions Secion 4.1 Eponenial Funcions... 15 Secion 4. Graphs of Eponenial Funcions... 3 Secion 4.3 Logarihmic Funcions... 4 Secion 4.4 Logarihmic Properies... 53 Secion
More informationTask is a schedulable entity, i.e., a thread
RealTime Scheduling Sysem Model Task is a schedulable eniy, i.e., a hread Time consrains of periodic ask T:  s: saring poin  e: processing ime of T  d: deadline of T  p: period of T Periodic ask T
More informationCAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND EXCHANGE RATE, FOREIGN EXCHANGE RESERVES AND VALUE OF TRADE BALANCE: A CASE STUDY FOR INDIA
CAUSAL RELATIONSHIP BETWEEN STOCK MARKET AND EXCHANGE RATE, FOREIGN EXCHANGE RESERVES AND VALUE OF TRADE BALANCE: A CASE STUDY FOR INDIA BASABI BHATTACHARYA & JAYDEEP MUKHERJEE Reader, Deparmen of Economics,
More informationBidask Spread and Order Size in the Foreign Exchange Market: An Empirical Investigation
Bidask Spread and Order Size in he Foreign Exchange Marke: An Empirical Invesigaion Liang Ding* Deparmen of Economics, Macaleser College, 1600 Grand Avenue, S. Paul, MN55105, U.S.A. Shor Tile: Bidask
More informationHedging with Forwards and Futures
Hedging wih orwards and uures Hedging in mos cases is sraighforward. You plan o buy 10,000 barrels of oil in six monhs and you wish o eliminae he price risk. If you ake he buyside of a forward/fuures
More informationGoRA. For more information on genetics and on Rheumatoid Arthritis: Genetics of Rheumatoid Arthritis. Published work referred to in the results:
For more informaion on geneics and on Rheumaoid Arhriis: Published work referred o in he resuls: The geneics revoluion and he assaul on rheumaoid arhriis. A review by Michael Seldin, Crisopher Amos, Ryk
More informationUNDERSTANDING THE DEATH BENEFIT SWITCH OPTION IN UNIVERSAL LIFE POLICIES. Nadine Gatzert
UNDERSTANDING THE DEATH BENEFIT SWITCH OPTION IN UNIVERSAL LIFE POLICIES Nadine Gazer Conac (has changed since iniial submission): Chair for Insurance Managemen Universiy of ErlangenNuremberg Lange Gasse
More informationSmall and Large Trades Around Earnings Announcements: Does Trading Behavior Explain PostEarningsAnnouncement Drift?
Small and Large Trades Around Earnings Announcemens: Does Trading Behavior Explain PosEarningsAnnouncemen Drif? Devin Shanhikumar * Firs Draf: Ocober, 2002 This Version: Augus 19, 2004 Absrac This paper
More informationWhy Do Real and Nominal. InventorySales Ratios Have Different Trends?
Why Do Real and Nominal InvenorySales Raios Have Differen Trends? By Valerie A. Ramey Professor of Economics Deparmen of Economics Universiy of California, San Diego and Research Associae Naional Bureau
More informationSELFEVALUATION FOR VIDEO TRACKING SYSTEMS
SELFEVALUATION FOR VIDEO TRACKING SYSTEMS Hao Wu and Qinfen Zheng Cenre for Auomaion Research Dep. of Elecrical and Compuer Engineering Universiy of Maryland, College Park, MD20742 {wh2003, qinfen}@cfar.umd.edu
More informationNEURAL NETWORKS AND INVESTOR SENTIMENT MEASURES FOR STOCK MARKET TREND PREDICTION
NEURAL NETWORKS AND INVESTOR SENTIMENT MEASURES FOR STOCK MARKET TREND PREDICTION SALIM LAHMIRI Deparmen of Compuer Science, UQAM, Monreal, Canada ABSTRACT Sof compuing mehods and various senimen indicaors
More informationTHE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES
THE NEW MARKET EFFECT ON RETURN AND VOLATILITY OF SPANISH STOCK SECTOR INDEXES Juan Ángel Lafuene Universidad Jaume I Unidad Predeparamenal de Finanzas y Conabilidad Campus del Riu Sec. 1080, Casellón
More informationLIFE INSURANCE WITH STOCHASTIC INTEREST RATE. L. Noviyanti a, M. Syamsuddin b
LIFE ISURACE WITH STOCHASTIC ITEREST RATE L. oviyani a, M. Syamsuddin b a Deparmen of Saisics, Universias Padjadjaran, Bandung, Indonesia b Deparmen of Mahemaics, Insiu Teknologi Bandung, Indonesia Absrac.
More informationA Brief Introduction to the Consumption Based Asset Pricing Model (CCAPM)
A Brief Inroducion o he Consumpion Based Asse Pricing Model (CCAPM We have seen ha CAPM idenifies he risk of any securiy as he covariance beween he securiy's rae of reurn and he rae of reurn on he marke
More informationLead Lag Relationships between Futures and Spot Prices
Working Paper No. 2/02 Lead Lag Relaionships beween Fuures and Spo Prices by Frank Asche Ale G. Guormsen SNFprojec No. 7220: Gassmarkeder, menneskelig kapial og selskapssraegier The projec is financed
More informationTesting the linearity of a time series. Some Monte Carlo and Empirical Tests
Tesing he lineariy of a ime series. Some Mone Carlo and Empirical Tess By Efsraios Tserkezos (Corresponding auhor). Mahemaical Modelling in new Technologies and Economy Posgraduae Programme. Applied Mahemaics
More informationConstant Data Length Retrieval for Video Servers with Variable Bit Rate Streams
IEEE Inernaional Conference on Mulimedia Compuing & Sysems, June 173, 1996, in Hiroshima, Japan, p. 151155 Consan Lengh Rerieval for Video Servers wih Variable Bi Rae Sreams Erns Biersack, Frédéric Thiesse,
More informationTime Series Modeling for Risk of Stock. Price with Value at Risk Computation
Applied Mahemaical Sciences, Vol 9, 015, no 56, 779787 HIKARI Ld, wwwmhikaricom hp://dxdoiorg/101988/ams0155144 Time Series Modeling for Risk of Sock Price wih Value a Risk Compuaion Dodi Deviano, Maiyasri
More informationMALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jarita Duasa 1
Journal of Economic Cooperaion, 8, (007), 8398 MALAYSIAN FOREIGN DIRECT INVESTMENT AND GROWTH: DOES STABILITY MATTER? Jaria Duasa 1 The objecive of he paper is wofold. Firs, is o examine causal relaionship
More informationSupplementary Appendix for Depression Babies: Do Macroeconomic Experiences Affect RiskTaking?
Supplemenary Appendix for Depression Babies: Do Macroeconomic Experiences Affec RiskTaking? Ulrike Malmendier UC Berkeley and NBER Sefan Nagel Sanford Universiy and NBER Sepember 2009 A. Deails on SCF
More informationCommunication Networks II Contents
3 / 1  Communicaion Neworks II (Görg)  www.comnes.unibremen.de Communicaion Neworks II Conens 1 Fundamenals of probabiliy heory 2 Traffic in communicaion neworks 3 Sochasic & Markovian Processes (SP
More informationGraphing the Von Bertalanffy Growth Equation
file: d:\b1732013\von_beralanffy.wpd dae: Sepember 23, 2013 Inroducion Graphing he Von Beralanffy Growh Equaion Previously, we calculaed regressions of TL on SL for fish size daa and ploed he daa and
More informationThe Real Business Cycle paradigm. The RBC model emphasizes supply (technology) disturbances as the main source of
Prof. Harris Dellas Advanced Macroeconomics Winer 2001/01 The Real Business Cycle paradigm The RBC model emphasizes supply (echnology) disurbances as he main source of macroeconomic flucuaions in a world
More informationKeldysh Formalism: Nonequilibrium Green s Function
Keldysh Formalism: Nonequilibrium Green s Funcion Jinshan Wu Deparmen of Physics & Asronomy, Universiy of Briish Columbia, Vancouver, B.C. Canada, V6T 1Z1 (Daed: November 28, 2005) A review of Nonequilibrium
More informationInternet Engineering. Jacek Mazurkiewicz, PhD Softcomputing. Part 1: Introduction, Elementary ANNs
Inerne Engineering Jacek azurkieicz, PhD Sofcompuing Par : Inroducion, Elemenary As Formal Inroducion conac hours, room o. 5 building C3: onday: :455:5, Friday: 4:306:00, slides:.zsk.ic.pr.roc.pl Professor
More informationGenetic Algorithm Based Optimal Testing Effort Allocation Problem for Modular Software
BIJIT  BVICAM s Inernaional Journal of Informaion Technology Bharai Vidyapeeh s Insiue of Compuer Applicaions and Managemen (BVICAM, ew Delhi Geneic Algorihm Based Opimal Tesing Effor Allocaion Problem
More informationARCH 2013.1 Proceedings
Aricle from: ARCH 213.1 Proceedings Augus 14, 212 Ghislain Leveille, Emmanuel Hamel A renewal model for medical malpracice Ghislain Léveillé École d acuaria Universié Laval, Québec, Canada 47h ARC Conference
More informationA New Adaptive Ensemble Boosting Classifier for Concept Drifting Stream Data
A New Adapive Ensemble Boosing Classifier for Concep Drifing Sream Daa Kapil K. Wankhade and Snehlaa S. Dongre, Members, IACSIT Absrac Wih he emergence of largevolume and high speed sreaming daa, mining
More informationWorking Paper No. 482. Net Intergenerational Transfers from an Increase in Social Security Benefits
Working Paper No. 482 Ne Inergeneraional Transfers from an Increase in Social Securiy Benefis By Li Gan Texas A&M and NBER Guan Gong Shanghai Universiy of Finance and Economics Michael Hurd RAND Corporaion
More informationA Bayesian Approach for Personalized Booth Recommendation
2011 Inernaional Conference on Social Science and Humaniy IPED vol. (2011) (2011) IACSI Press, Singapore A Bayesian Approach for Personalized Booh ecommendaion Ki Mok Ha 2bcreaor@khu.ac.kr Il Young Choi
More informationA Natural FeatureBased 3D Object Tracking Method for Wearable Augmented Reality
A Naural FeaureBased 3D Objec Tracking Mehod for Wearable Augmened Realiy Takashi Okuma Columbia Universiy / AIST Email: okuma@cs.columbia.edu Takeshi Kuraa Universiy of Washingon / AIST Email: kuraa@ieee.org
More informationAn Optimal Strategy of Natural Hedging for. a General Portfolio of Insurance Companies
An Opimal Sraegy of Naural Hedging for a General Porfolio of Insurance Companies HongChih Huang 1 ChouWen Wang 2 DeChuan Hong 3 ABSTRACT Wih he improvemen of medical and hygienic echniques, life insurers
More informationStock Trading with Recurrent Reinforcement Learning (RRL) CS229 Application Project Gabriel Molina, SUID 5055783
Sock raing wih Recurren Reinforcemen Learning (RRL) CS9 Applicaion Projec Gabriel Molina, SUID 555783 I. INRODUCION One relaively new approach o financial raing is o use machine learning algorihms o preic
More information