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This paper analyzes and examines the general ability of Support Vector Machine (SVM) models to correctly predict and trade daily EUR exchange rate directions. Seven models with varying kernel functions are considered. Each SVM model is benchmarked against traditional forecasting techniques in order to ascertain its potential value as out-of-sample forecasting and quantitative trading tool. It is found that hyperbolic SVMs perform well in terms of forecasting accuracy and trading results via a simulated strategy. This supports the idea that SVMs are promising learning systems for coping with nonlinear classification tasks in the field of financial time series applications.


Introduction
Support Vector Machines (SVMs) have proven to be a principled and very powerful supervised learning system that since its introduction (Cortes and Vapnik (1995)) has outperformed many systems in a variety of applications, such as text categorization (Joachims (1998)), image processing (Quinlan et al. (2004)), and bioinformatic problems (Brown et al. (1999)). Subsequent applications in time series prediction (M¨uller et al. (1999)) indicate the potential that SVMs have with respect to economics and finance. In predicting Australian foreign exchange rates, Kamruzzaman and Sarker (2003b) showed that a moving average-trained SVM has advantages over an Artificial Neural Network (ANN) based model, which was shown to have advantages over ARIMA models (2003a). Furthermore, Kamruzzaman et al. (2003) had a closer look at SVM regression and investigated how it performs with different standard kernel functions. It was found that Gaussian Radial Basis Function (RBF) and
polynomial kernels appear to be a better choice in forecasting the Australian foreign exchange market than linear or spline kernels. Although Gaussian kernels
are adequate measures of similarity when the representation dimension of the space remains small, they fail to reach their goal in high dimensional spaces (Francois et al. (2005)).We will examine the general ability of SVMs to correctly classify daily EUR/GBP, EUR/JPY and EUR/USD exchange rate directions. It is more useful for traders and risk managers to predict exchange rate fluctuations than their levels. To predict that the level of the EUR/USD, for instance, is close to the level today is trivial. On the contrary, to determine if the market will rise or fall is much more complex and interesting. Since SVM performance mostly depends on choosing the right kernel, we empirically verify the use of customized p-Gaussians by comparing them with a
range of standard kernels. The remainder is organized as follows: Section 2 outlines the procedure for obtaining an explanatory input dataset. Section 3 formulates the SVM as applied to exchange rate forecasting and presents the kernels used. Section 4 describes the benchmarks and trading metrics used for model evaluation. Section 5 gives the empirical results. The conclusion, as well as brief directions for future research, are given in Section 6.

This paper presents the analytic recursive formulas of Crame´r-Rao lower bound (CRLB) for the switching models system, in which the target moves either with a constant velocity or with a constant speed and a constant turn rate. For the case of two-observer bearings-only maneuvering target tracking, a reliable maneuver detection method is investigated and then utilized to approximate the theoretic CRLB. Finally, to demonstrate the agreement between the approximated CRLB using the proposed maneuver detection method and the theoretic one, a large number of Monte-Carlo runs under different maneuvering scenarios are conducted. Correctness of the analytic recursive formulas of CRLB and effectiveness of the proposed maneuver detection method are verified from these simulations.


1. Introduction
For a general nonlinear filtering problem, the optimal recursive state estimator in the Bayesian sense needs the complete posterior density of the state. As is well known, such a problem has no analytic closed-form solution. As a consequence, the solution of the nonlinear filtering is usually approximated by means of extended
Kalman filter, unscented Kalman filter [9], particle filter [16] and so on. In practical applications, many researchers usually attempt to derive the theoretically best achievable second-order error performance for nonlinear filtering to evaluate these filters, and we call it Crame´r-Rao lower bound (CRLB).

The Crame´r-Rao lower bound, defined as the inverse of the Fisher information matrix (FIM), represents an objective lower limit of cognizability of parameters in constant or random parameter estimation. It has been widely used in many cases, such as bearings-only tracking [13,20,21], ballistic target tracking [8] and so on. Due to its ability of predicting the best achievable performance, it is usually utilized as a benchmark to evaluate the performance of an estimation algorithm and can provide guidance to improve the experimental design as well. Therefore, the discussion on CRLB is always a hot topic in the field of target motion analysis (TMA).

A complete history of the developments of the CRLB for target tracking would involve more than sixty publications (e.g., [3–7,10,12–15,17–19]), and its attention varies from single target to multiple targets, from constant parameter estimation to random parameter estimation, from clutter-free to clutter, etc. In many practical tracking scenarios, due to high frequency of maneuver occurrence, the corresponding discussion
on the CRLB seems necessary and imminent. However, few reports on the CRLB of maneuvering target tracking can be found so far, even so, most of them are based on such an assumption that the model history is already known [13]. Therefore, the aim of this paper is to investigate the performance bounds of the switching-models-based bearings-only maneuvering target tracking system, in which the target moves either with a constant velocity or with a constant speed and a constant turn rate. It is noted that, in bearing-only tracking, if a single observer is collecting angular measurements, the target state becomes observable only if the observer ‘‘outmaneuvers” the target, i.e., observer motion is one derivative higher than that of target and a component of this motion is perpendicular to the line of sight. However, for a two-observer bearings-only tracking system to be discussed in this paper, it is not the case, and the target is always observable only if the target does not move on the line connecting the two observers, thus the observability will not be addressed later.

This work takes inspiration mainly from Farina et al. [7], in which the detection probability of target was supposed to be less than unity. Thus we suppose in this paper that there is the possibility of target’s maneuver or non-maneuver at each sampling period. On the basis of such assumption, the recursive theoretic formulas
of CRLB for two-observer bearings-only maneuvering target are derived. Since the calculation of the theoretic CRLB relies on the exponentially growing number of maneuver/non-maneuver sequences, a reliable maneuver detector is developed to reduce the possible sequences to further approximate the theoretic CRLB.

The rest of this paper is arranged as follows. The target dynamics and measurement models for bearingsonly target tracking are formulated in Section 2. In Section 3, the recursive theoretic formulas of CRLB for two-observer bearings-only maneuvering target are derived, and moreover, a reliable maneuver detector for bearings-only tracking is developed and utilized to approximate the theoretic CRLB. Finally, performance evaluation and conclusions are given in Sections 4 and 5, respectively.

Although predictive control techniques such as Dynamic Matrix Control and Model Algorithmic Control have received much attention in recent years, systematic methods for on-line updating of the process models and predictive control laws raely have been rported. Such adaptation is desirable if the process conditions change significantly over a period of time. The same approach also could be used to generate a discrete convolution model for the initil controller design. In ftis paper, several altrative stategies for on-line aptation during closedloop opertion are evaluated and compared via simulations.


INTRODUCTION
Industrial process-control groups introduced the predictive control techniques of Dynamic Matrix Control (DMC) [1] and Model Algorithmic Control (MAC) [2,3], respectvely, nearly a decade ago. They were developed specifically for multipleinput, multiple-output (MIMO) control problems in which the process could be adequately described by linear dynamic models. These model-based techniques minimize predicted process deviations from the set point using quadratic performance indices. Thus, these methods were the first optimal controllers to be routinely used in the process industries. The evaluation and extension of these techniques spread quickly among academic circles as industry revived dying enthusiasm among researchers for studying and developing optimal controllers.

Since DMC and MAC were introduced, industrial and academic researchers have reported extensions and modifications of both control techniques. In addition, researchers have developed several new predictive controllers and have shown that they are robust under many circumstances. For example, Ogunnaike [4] gives a statistical interpretation of the robustness of DMC. Maurath et al [5] illustrate stability regions for a single-input, single-output (SISO) predictive controller. Garcia and Moari [6] show the stabilizing effect of filtering feedback errr for such controllers.

If the process characteristics change significantly, the predictive controller may need to be retuned or redesigned. This, naurly, leads one to consider adaptng the predictive controler on-line to accommodate the changing process conditions. In fact, one merely needs to estimate the process models on line to make many predictive controllers adaptive. The dearth of publicized industrial experiences extolling adaptive predictive controllers, though, suggests that implementation of these controllers may not be straightforward. Some of the pertinent questions that point to possible implementation problems are:
1. How does one decide if the current controller's performance is unsatisfactory?
2. How should a new process model and controller be obtined, if neded?
3. How should a good process model for the initial controller design be obtined?
This paper helps to answer these questions by presenting systematic methods for the on-line updating of the process models and control laws. The proposed strategies also can be used to develop the convolution model for the initial controler design. In the next section, existing predictive controller techniques are discussed briefly.

What Is the Psychology of Concepts a Psychology of ?
There is a methodological pitfall masquerading as an advantage that accounts for some part of the problem I have described. In order to study concepts, all I have to do is to make up two sets of entities (which can be anything, although I will usually call them objects because that is usually what they are) and persuade subjects to give one response to one set and a diVerent response to the other set. The problem with this is that I can make up any arbitrary sets, use any procedure to try to get subjects to learn, and use anyresponse that is at all distinctive. Hull (1920),whowasfaced with the task of developing a methodology for studying concepts experimentally, listed a number of desiderata for studying concepts. The Desiderata included the use of distinct classes, each receiving diVerent responses. However, they also included constraints on the concepts themselves, namely that each concept should contain an element that is unique to it. This desideratum reflected Hull’s assumption about the structure of categories in the world, what has come to be known as the classical view of categories (Smith & Medin, 1981).

Let us imagine for a moment that Hull had been right about categories, that each category has a unique element or some set of defining features that determine category membership. What would we then think about the vast majority of modern experiments on concepts, which lack such defining features? These experiments might be interesting as studies of abstract learning, but they would simply not be about how people learn concepts. A study of how people learn nonlinearly separable categories might have some interest regarding the nature of memory and learning in general, but it would tell us little about how people learn real categories because
nonlinearly separable categories by definition do not have definitions (sic). Studies of family resemblance concepts (Rosch & Mervis, 1975), in which category members tend to share features but have no feature common to the whole category, would also not be telling us how people learn real categories.These studies would be uninformative because the requirements involved in learning a well-defined category are diVerent from those involved in learning family resemblance or NLS categories. Indeed, the study of logically defined concepts that was ushered in by Bruner, Goodnow, and Austin (1956) was essentially dropped when Rosch published her studies of the structure of natural categories (e.g., Rosch, 1973, 1975). The studies of concept attainment that Bruner et al. and many others carried out are now viewed as studies of a particular kind of reasoning or problem solving rather than studies of concept learning, precisely because we believe that real concepts are not like Bruner et al.’s concept.
In order to answer how people learn categories and form concepts, we cannot operate in a vacuum of knowledge about the real structure of categories. For Hull, it would have been pointless to study how people learn family resemblance categories because this could not tell you how people learn ‘‘real’’ categories. We are less certain now, perhaps, what the real categories are and therefore are less willing to reject any particular experiment as being irrelevant. But perhaps we have erred on the side of liberality and acceptingness. Perhaps some of the categories we have studied do not tell us about how people learn real categories, just as the studies of Bruner et al. do not tell us how people learn family resemblance categories.

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INTRODUCTION
You should find PowerPoint 2002 From A to Z easy to use. You only need to know that the book organizes its information—key tasks and important terms—alphabetically in order to use the book. You’ll find it helpful, however, if you understand what this book assumes about your computer skills, what you should know about the PowerPoint program from the very start, and what editorial conventions this book uses. This short introduction provides this information.


What Y You ou Should Know About Windows
You don’t need to be computer expert to use either this book or Microsoft PowerPoint. Definitely not. But you want to be comfortable working with your computer and Microsoft Windows.
For example, you should know how to turn your computer on and off, how to start and stop programs, how to choose menu commands, and how to work with dialog boxes. This book, for the most part, doesn’t provide this Windows information.
If you need this Windows information, you need to take the Windows online tutorial, get a friend to give you a quick tutorial, or acquire another book on Windows.

TIPS
Any short book on Windows will tell you what you need to know, but if you’re a business user of Windows 2000 or Windows XP, you may want to look at the Effective Executive’s Guide to Windows 2000 or the Effective Executive’s Guide to Windows XP.
These books supply a tutorial on Windows geared for business professionals.

What Y You ou Should Know About PowerPoint
You don’t need to know anything about PowerPoint to use this book. But understanding from the very start how PowerPoint works and how the PowerPoint program window is laid out will help you immensely in your learning. Let me quickly provide this background information.

Concentration Finds The Way
Everyone has two natures. One wants us to advance and the other wants to pull us back. The one that we cultivate and concentrate on decides what we are at the end. Both natures are trying to gain control.

The will alone decides the issue. A man by one supreme effort of the will may change his whole career and almost accomplish miracles. You may be that man. You can be if you Will to be, for Will can find a way or make one.


I could easily fill a book, of cases where men plodding along in a matter-of-fact way, were all at once aroused and as if awakening from a slumber they developed the possibilities within them and from that time on were different persons.

You alone can decide when the turning point will come.
It is a matter of choice whether we allow our diviner self to control us or whether we will be controlled by the brute within us. No man has to do anything he does not want to do. He is therefore the director of his life if he wills to be. What we are to do, is the result of our training. We are like putty, and can be completely controlled by our will power.

Habit is a matter of acquirement. You hear people say: "He comes by this or that naturally, a chip off the old block," meaning that he is only doing what his parents did. This is quite often the case, but there is no reason for it, for a person can break a habit just the moment he masters the "I will."

A man may have been a "good-for-nothing" all his life up to this very minute, but from this time on he begins to amount to something. Even old men have suddenly changed and accomplished wonders. "I lost my opportunity," says one. That may be true, but by sheer force of will, we can find a way to bring us another opportunity.

There is no truth in the saying that opportunity knocks at our door but once in a lifetime. The fact is, opportunity never seeks us; we must seek it. What usually turns out to be one man's opportunity, was another man's loss. In this day one man's brain is matched against another's.

It is often the quickness of brain action that determines the result. One man thinks "I will do it," but while he procrastinates the other goes ahead and does the work. They both have the same opportunity. The one will complain of his lost chance. But it should teach him a lesson, and it will, if he is seeking the path that leads to success.

Many persons read good books, but say they do not get much good out of them. They do not realize that all any book or any lesson course can do is to awaken them to their possibilities; to stimulate them to use their will power. You may teach a person from now until doom's day, but that person will only know what he learns himself. "You can lead him to the fountain, but you can't make him drink."

One of the most beneficial practices I know of is that of looking for the good in everyone and everything, for there is good in all things. We encourage a person by seeing his good qualities and we also help ourselves by looking for them. We gain their good wishes, a most valuable asset sometimes.

We get back what we give out.
The time comes when most all of us need encouragement; need buoying up. So form the habit of encouraging others, and you will find it a wonderful tonic for both those encouraged and yourself, for you will get back encouraging and uplifting thoughts.

Life furnishes us the opportunity to improve. But whether we do it or not depends upon how near we live up to what is expected of us. The first of each month, a person should sit down and examine the progress he has made. If he has not come up to "expectations" he should discover the reason, and by extra exertion measure up to what is demanded next time.

Every time that we fall behind what we planned to do, we lose just so much for that time is gone forever. We may find a reason for not doing it, but most excuses are poor substitutes for action. Most things are possible.

Ours may be a hard task, but the harder the task, the greater the reward. It is the difficult things that really develop us, anything that requires only a small effort, utilizes very few of our faculties, and yields a scanty harvest of achievement. So do not shrink from a hard task, for to accomplish one of these will often bring us more good than a dozen lesser triumphs.

Over half of the students who enrol on economics degree courses have not studied mathematics beyond GCSE or an equivalent level. These include many mature students whose last encounter with algebra, or any other mathematics beyond basic arithmetic, is now a dim and distant memory. It is mainly for these students that this book is intended. It aims to develop their mathematical ability up to the level required for a general economics degree course (i.e. one not specializing in mathematical economics) or for a modular degree course in economics and related subjects, such as business studies. To achieve this aim it has several objectives.

First, it provides a revision of arithmetical and algebraic methods that students probably studied at school but have now largely forgotten. It is a misconception to assume that, just because a GCSE mathematics syllabus includes certain topics, students who passed examinations on that syllabus two or more years ago are all still familiar with the material. They usually require some revision exercises to jog their memories and to get into the habit of using the different mathematical techniques again. The first few chapters are mainly devoted to this revision, set out where possible in the context of applications in economics.


Second, this book introduces mathematical techniques that will be new to most students through examples of their application to economic concepts. It also tries to get students tackling problems in economics using these techniques as soon as possible so that they can see how useful they are. Students are not required to work through unnecessary proofs, or wrestle with complicated special cases that they are unlikely ever to encounter again. For example, when covering the topic of calculus, some other textbooks require students to plough through abstract theoretical applications of the technique of differentiation to every conceivable type of function and special case before any mention of its uses in economics is made. In this book, however, we introduce the basic concept of differentiation followed
by examples of economic applications in Chapter 8. Further developments of the topic,
such as the second-order conditions for optimization, partial differentiation, and the rules for differentiation of composite functions, are then gradually brought in over the next few chapters, again in the context of economics application.

Third, this book tries to cover those mathematical techniques that will be relevant to students’ economics degree programmes. Most applications are in the field of microeconomics, rather than macroeconomics, given the increased emphasis on business economics within many degree courses. In particular, Chapter 7 concentrates on a number of mathematical techniques that are relevant to finance and investment decision-making.

Given that most students now have access to computing facilities, ways of using a spreadsheet package to solve certain problems that are extremely difficult or time-consuming to solve manually are also explained.

Although it starts at a gentle pace through fairly elementary material, so that the students who gave up mathematics some years ago because they thought that they could not cope with A-level maths are able to build up their confidence, this is not a watered-down ‘mathematics without tears or effort’ type of textbook. As the book progresses the pace is increased and students are expected to put in a serious amount of time and effort to master the material. However, given the way in which this material is developed, it is hoped that students will be motivated to do so. Not everyone finds mathematics easy, but at least it helps if you can see the reason for having to study it.

Setahun yang lalu, hidup saya terasa runtuh. Saya bekerja sampai kelelahan, ayah tiba-tiba meninggal, dan hubungan dengan rekan-rekan kerja serta orang-orang yang saya cintai sedang kacau. Pada saat itu saya tidak tahu bahwa keputusasaan terberat saya kelak menjadi karunia terbesar.

Saya telah diberi kilasan sebuah Rahasia Besar—Rahasia Kehidupan. Kilasan ini datang melalui sebuah buku berusia seratus tahun, yang dihadiahkan putri saya, Hayley. Dan saya mulai melacak Rahasia ini melalui sejarah. Saya sangat terkejut menemukan orang-orang yang telah mengenal Rahasia ini. Mereka adalah orang-orang besar dalam sejarah: Plato, Shakespeare, Newton, Hugo, Beethoven, Lincoln, Emerson, Edison, dan Einstein.


Ini membuat saya bertanya, “Mengapa tidak setiap orang mengetahui Rahasia ini?” Hasrat yang menyala-nyala untuk membagikan Rahasia kepada dunia membakar diri saya, dan saya mulai mencari orang-orang yang masih hidup, yang mengenal Rahasia ini.

Satu per satu mereka mulai muncul. Saya menjadi seperti sebatang magnet. Ketika saya mulai mencari, seorang guru yang masih hidup dan seorang lagi yang lain tertarik kea rah saya. Ketika saya menemukan satu guru, ia akan mengaitkan saya ke guru berikutnya, dalam sebuah rantai yang sempurna. Jika saya berada di jalan yang salah,
akan muncul hal lain yang menarik perhatian saya. Pengalihan jalan itu memunculkan guru besar erikutnya. Jika saya “tidak sengaja” menekan mata rantai (link) yang salah
ketika menelusuri Internet, saya akan dijuruskan ke potongan informasi yang sangat penting. Dalam beberapa minggu yang singkat, saya telah melacak Rahasia ini sampai ke abad-abad yang lampau, dan saya telah menemukan praktisi masa kini dari Rahasia ini.

Sebuah visi ntuk membawa Rahasia ini ke dunia melalui sebuah film tercamkan di benak saya. Dan selama dua bulan berikutnya, tim saya bidang produksi film dan televisi telah mempelajari Rahasia ini. Setiap anggota tim wajib mengetahui Rahasia ini karena tanpa mengetahuinya, apa yang akan kami upayakan ini akan mustahil.

Kami tidak mempunyai satu guru tetap untuk film ini, tetapi kami mengenal Rahasia ini. Jadi, dengan keyakinan teguh saya terbang dari Australia ke Amerika Serikat, tempat sebagian besar guru ini tinggal. Tujuh minggu kemudian tim Rahasia telah memfilmkan lima puluh lima guru besar yang ada di Amerika Serikat, dengan durasi film lebih dari 120 jam. Pada setiap langkah, setiap nafas, kami menggunakan Rahasia untuk menciptakan film The Secret. Benar-benar, kami ini seperti magnet yang menarik segala sesuatu dan semua orang. Delapan bulan kemudian The Secret diluncurkan.

Ketika film ini merambah dunia, kisah-kisah keajaiban mulai membanjir masuk:
orang-orang menulis tentang penyembuhan dari nyeri, depresi, dan penyakit menahun;
berjalan untuk pertama kalinya setelah kecelakaan; bahkan pemulihan dari ranjang
kematian. Kami telah menerima ribuan kisah tentang Rahasia yang mendatangkan sejumlah besar uang dan cek yang tidak terduga. Orang-orang telah menggunakan Rahasia untuk mewujudkan rumah sempurnanya, pasangan hidup, mobil, pekerjaan, dan kenaikan jabatan; serta banyak kisah bisnis yang mengalami transformasi dalam beberapa hari setelah menerapkan Rahasia ini. Ada banyak kisah yang menghangatkan hati tentang hubungan yang sulit dengan anak-anak berubah menjadi hubungan yang harmonis.

Beberapa kisah luar biasa yang kami terima datang dari anak-anak yang menggunakan Rahasia ini untuk meraih keinginan mereka, termasuk perolehan niilai tinggi dan banyak teman. The Secret telah mengilhami para dokter membagikan pengetahuan tentang Rahasia kepada pasien mereka; universitas dan sekolah kepada para mahasiswa dan siswanya; klub-klub kesehatan kepada para kliennya; dan gereja-gereja dari berbagai sekte dan pusat-pusat spiritual kepada umat mereka. Terdapat pula pertemuan yang diselenggarakan di rumah-rumah di seluruh dunia, mereka membagi pengetahuan ini dengan keluarga dan orang-orang yang dicintainya. Rahasia ini telah digunakan untuk mendapat segala hal—mulai dari sebilah bulu khusus sampai sepuluh juta dolar. Semua ini terjadi dalam beberapa bulan setelah peluncuran filmnya.

Niat saya dalam menciptakan The Secret adalah menghadirkan kegembiraan bagi miliaran orang di dunia. Tim kami mengalami perwujudan niat itu seitap hari ketika kami menerima ribuan surat dari masyarakat di seluruh dunia, dari segala usia, segala ras, dan segala bangsa. Mereka mengungkapkan terima kasih atas kegembiraan yang telah
dihadirkan oleh The Secret. Tidak ada satu hal pun yang membuat Rahasia ini tidak dapat diterapkan. Terlepas dari siapa Anda atau di mana Anda berada, Rahasia dapat
memberikan apa pun yang Anda inginkan.

Dua puluh empat guru yang menakjubkan akan dikisahkan dalam buku ini. Katakata mereka telah difilmkan di berbagai tempat di Amerika Serikat dalam waktu yang berbeda, tetapi mereka berbicara dalam satu suara. Buku ini berisi kata-kata guru Rahasia, dan juga kisah-kisah ajaib yang terjadi. Saya juga membagikan semua jejak, kiat, dan jalan pintas yang telah saya pelajari, sehingga Anda dapat mewujudkan impian Anda.

Di sepanjang buku Anda akan melihat bahwa pada tempat-tempat tertentu saya menggunakan huruf besar untuk kata “ANDA”. Alasan saya melakukan hal ini adalah saya menginginkan Anda, pembaca, merasakan dan mengetahui bahwa saya telah menciptakan buku ini untuk Anda. Saya berbicara secara pribadi kepada Anda ketika saya mengucapkan Anda. Niat saya adalah agar Anda merasakan hubungan pribadi dengan halaman-halaman buku ini karena buku Rahasia ini diciptakan untuk ANDA.

Ketika Anda menjelajahi halaman-halamannya dan mempelajari Rahasia, Anda akan menyadari bagaimana Anda bisa mendapatkan atau melakukan segala sesuatu yang Anda inginkan. Anda akan menyadari siapa sesungguhnya diri Anda. Anda akan menyadari keagungan sejati yang sedang menanti Anda.