# on 23-Jan-2018 (Tue)

#### Flashcard 1479998573836

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Under the [...] method, the portion of the total profit of the installment sales that is recognized in each period is determined by the percentage of the total sales price for which the seller has received cash.
installment

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3.2.2. Installment Sales
some of the profit is deferred. Two of the methods may be appropriate in these limited circumstances and relate to the amount of profit to be recognized each year from the transaction: the installment method and the cost recovery method . <span>Under the installment method, the portion of the total profit of the sale that is recognized in each period is determined by the percentage of the total sales price for which the seller has received cash. Under the cost recovery method, the seller does not report any profit until the cash amounts paid by the buyer—including principal and interest on any financing from the seller—are grea

#### Flashcard 1621027327244

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#cashflow-statement
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CFO does not include charges for the use of [...]
long-lived assets.

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Subject 3. Cash Flow Statement Analysis
l Analysis Techniques]. Free Cash Flow to the Firm and Free Cash Flow to Equity From an analyst's point of view, cash flows from operation activities have two major drawbacks: <span>CFO does not include charges for the use of long-lived assets. Recall that depreciation is added back to net income in arriving at CFO. CFO does not include cash outlays for replacing old equipment. Free Cash Flo

#### Flashcard 1635146927372

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#statistical-concepts-and-market-returns
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[...] include not only measures of central tendency but other measures that illustrate the location or distribution of data.

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#### Flashcard 1644489739532

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the Sharpe ratio measures the reward in terms of [...] per [...]

unit of risk

mean excess return

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#### Flashcard 1652310543628

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The shortest explanation of n factorial is that it is the number of [...]
ways to order n objects in a row.

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The shortest explanation of n factorial is that it is the number of ways to order n objects in a row. In all the problems to which we apply this counting method, we must use up all the members of a group (sampling without replacement).

#### Flashcard 1731750923532

Question
[...] tends to indicate motion backward, while [...] tends to refer to place
Atrás, detrás

Tuvo que volver atrás.

Fumaba un cigarrillo detrás de otro.

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¿Detrás or Atrás — Which Spanish Adverb Should I Use?
Updated May 15, 2017 Although both detrás and atrás are adverbs that can be translated as "behind" and are often listed as synonyms, they tend to be used in different ways. <span>Atrás tends to indicate motion backward, while detrás tends to refer to place, but the distinction isn't always clear. Sometimes the choice of word is a matter of which "sounds better" rather than following some fixed rule. That said, it is probably eas

#### Flashcard 1731762982156

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#spanish
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[...] significa ‘en la parte anterior’ y [...] equivale a ‘hacia allá’

Examples
Voy yo delante, que sé el camino.

La forma alante, por otro lado, es incorrecta.

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Delante significa ‘en la parte anterior’, ‘en frente’ o ‘ante alguien’, se usa por lo general para indicar la situación de alguien o algo. Adelante , por su parte, equivale a ‘más allá’, ‘hacia allá’, o ‘hacia enfrente’, y se emplea para indicar la existencia de un movimiento, sea real o figurado. La forma alante , por otro lado, es incorrecta.

#### Original toplevel document

Delante o adelante - Diccionario de Dudas
amp;cj=1"> [imagelink] Palabras Homófonas Palabras Parónimas Fonética y fonología Uso Grafía Léxicas Ver más Latinismos Extranjerismos Barbarismos Ultracorrecciones Dudas de uso Delante o adelante Delante significa ‘en la parte anterior’, ‘en frente’ o ‘ante alguien’, se usa por lo general para indicar la situación de alguien o algo. Adelante , por su parte, equivale a ‘más allá’, ‘hacia allá’, o ‘hacia enfrente’, y se emplea para indicar la existencia de un movimiento, sea real o figurado. La forma alante , por otro lado, es incorrecta. Cuándo usar delante Delante es un adverbio de lugar; se emplea con el significado de ‘en la parte anterior’, ‘en frente’ o ‘en presencia de alguien’. Por lo general, es un adverbio que

#### Annotation 1736159923468

 Reading 43  Basics of Portfolio Planning and Construction Intro #has-images #portfolio-session #reading-bob-el-constructor To build a suitable portfolio for a client, investment advisers should first seek to understand the client’s investment goals, resources, circumstances, and constraints. Investors can be categorized into broad groups based on shared characteristics with respect to these factors (e.g., various types of individual investors and institutional investors). Even investors within a given type, however, will invariably have a number of distinctive requirements. In this reading, we consider in detail the planning for investment success based on an individualized understanding of the client. This reading is organized as follows: Section 2 discusses the investment policy statement, a written document that captures the client’s investment objectives and the constraints. Section 3 discusses the portfolio construction process, including the first step of specifying a strategic asset allocation for the client. A summary and practice problems conclude the reading.

#### Annotation 1736170147084

 Reading 48  Introduction to Industry and Company Analysis (Intro) #has-images #lingote-de-oro-session #reading-chimenea-industrial Industry analysis is the analysis of a specific branch of manufacturing, service, or trade. Understanding the industry in which a company operates provides an essential framework for the analysis of the individual company—that is, company analysis. Equity analysis and credit analysis are often conducted by analysts who concentrate on one or several industries, which results in synergies and efficiencies in gathering and interpreting information. Among the questions we address in this reading are the following: What are the similarities and differences among industry classification systems? How does an analyst go about choosing a peer group of companies? What are the key factors to consider when analyzing an industry? What advantages are enjoyed by companies in strategically well-positioned industries? After discussing the uses of industry analysis in the next section, Sections 3 and 4 discuss, respectively, approaches to identifying similar companies and industry classification systems. Section 5 covers the description and analysis of industries. Also, Section 5, which includes an introduction to competitive analysis, provides a background to Section 6, which introduces company analysis. The reading ends with a summary, and practice problems follow the text.

#### Annotation 1736172506380

 Reading 49  Equity Valuation: Concepts and Basic Tools (Intro) #has-images #lingote-de-oro-session #reading-jens Analysts gather and process information to make investment decisions, including buy and sell recommendations. What information is gathered and how it is processed depend on the analyst and the purpose of the analysis. Technical analysis uses such information as stock price and trading volume as the basis for investment decisions. Fundamental analysis uses information about the economy, industry, and company as the basis for investment decisions. Examples of fundamentals are unemployment rates, gross domestic product (GDP) growth, industry growth, and quality of and growth in company earnings. Whereas technical analysts use information to predict price movements and base investment decisions on the direction of predicted change in prices, fundamental analysts use information to estimate the value of a security and to compare the estimated value to the market price and then base investment decisions on that comparison. This reading introduces equity valuation models used to estimate the intrinsic value(synonym: fundamental value) of a security; intrinsic value is based on an analysis of investment fundamentals and characteristics. The fundamentals to be considered depend on the analyst’s approach to valuation. In a top-down approach, an analyst examines the economic environment, identifies sectors that are expected to prosper in that environment, and analyzes securities of companies from previously identified attractive sectors. In a bottom-up approach, an analyst typically follows an industry or industries and forecasts fundamentals for the companies in those industries in order to determine valuation. Whatever the approach, an analyst who estimates the intrinsic value of an equity security is implicitly questioning the accuracy of the market price as an estimate of value. Valuation is particularly important in active equity portfolio management, which aims to improve on the return–risk trade-off of a portfolio’s benchmark by identifying mispriced securities. This reading is organized as follows. Section 2 discusses the implications of differences between estimated value and market price. Section 3 introduces three major categories of valuation model. Section 4 presents an overview of present value models with a focus on the dividend discount model. Section 5 describes and examines the use of multiples in valuation. Section 6 explains asset-based valuation and demonstrates how these models can be used to estimate value. Section 7 states conclusions and summarizes the reading.

#### Annotation 1737319648524

 In mathematical finance, the Black–Scholes equation is a partial differential equation (PDE) governing the price evolution of a European call or European put under the Black–Scholes model.

Black–Scholes equation - Wikipedia

#### Flashcard 1737321745676

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the Black–Scholes equation governs [...] of a European call or European put
the price evolution

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In mathematical finance, the Black–Scholes equation is a partial differential equation (PDE) governing the price evolution of a European call or European put under the Black–Scholes model.

#### Original toplevel document

Black–Scholes equation - Wikipedia

#### Annotation 1737325153548

 #lists #python An operation like this that combines a sequence of elements into a single value is sometimes called reduce .

Lists
of the elements; a variable used this way is sometimes called an accumulator. Adding up the elements of a list is such a common operation that Python provides it as a built-in function, sum: >>> t = [1, 2, 3] >>> sum(t) 6 <span>An operation like this that combines a sequence of elements into a single value is sometimes called reduce. Sometimes you want to traverse one list while building another. For example, the following function takes a list of strings and returns a new list that contains capitalized strings:

#### Annotation 1737327250700

 #lists #python An operation like capitalize_all is sometimes called a map because it “maps” a function (in this case the method capitalize ) onto each of the elements in a sequence.

Lists
ngs: def capitalize_all(t): res = [] for s in t: res.append(s.capitalize()) return res res is initialized with an empty list; each time through the loop, we append the next element. So res is another kind of accumulator. <span>An operation like capitalize_all is sometimes called a map because it “maps” a function (in this case the method capitalize) onto each of the elements in a sequence. Another common operation is to select some of the elements from a list and return a sublist. For example, the following function takes a list of strings and returns a list that cont

#### Annotation 1737329347852

 #lists #python An operation like only_upper is called a filter because it selects some of the elements and filters out the others.

Lists
ontains only the uppercase strings: def only_upper(t): res = [] for s in t: if s.isupper(): res.append(s) return res isupper is a string method that returns True if the string contains only upper case letters. <span>An operation like only_upper is called a filter because it selects some of the elements and filters out the others. Most common list operations can be expressed as a combination of map, filter and reduce. 10.8 Deleting elements There are several ways to delete elements from a list. If you kno

#### Annotation 1737331445004

 #lists #python Most common list operations can be expressed as a combination of map, filter and reduce.

Lists
res.append(s) return res isupper is a string method that returns True if the string contains only upper case letters. An operation like only_upper is called a filter because it selects some of the elements and filters out the others. <span>Most common list operations can be expressed as a combination of map, filter and reduce. 10.8 Deleting elements There are several ways to delete elements from a list. If you know the index of the element you want, you can use pop: >>> t = ['a', 'b', 'c']

#### Flashcard 1737334590732

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#lists #python
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An operation like this that combines a sequence of elements into a single value is sometimes called [...] .
reduce

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An operation like this that combines a sequence of elements into a single value is sometimes called reduce .

#### Original toplevel document

Lists
of the elements; a variable used this way is sometimes called an accumulator. Adding up the elements of a list is such a common operation that Python provides it as a built-in function, sum: >>> t = [1, 2, 3] >>> sum(t) 6 <span>An operation like this that combines a sequence of elements into a single value is sometimes called reduce. Sometimes you want to traverse one list while building another. For example, the following function takes a list of strings and returns a new list that contains capitalized strings:

#### Flashcard 1737336950028

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#lists #python
Question
An map operation “maps” a function onto [...] in a sequence.
each of the elements

like capitalize_all

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#### Parent (intermediate) annotation

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An operation like capitalize_all is sometimes called a map because it “maps” a function (in this case the method capitalize ) onto each of the elements in a sequence.

#### Original toplevel document

Lists
ngs: def capitalize_all(t): res = [] for s in t: res.append(s.capitalize()) return res res is initialized with an empty list; each time through the loop, we append the next element. So res is another kind of accumulator. <span>An operation like capitalize_all is sometimes called a map because it “maps” a function (in this case the method capitalize) onto each of the elements in a sequence. Another common operation is to select some of the elements from a list and return a sublist. For example, the following function takes a list of strings and returns a list that cont

#### Flashcard 1737338522892

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#lists #python
Question
An operation like only_upper is called a [...] because it selects some of the elements and filters out the others.
filter

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#### Parent (intermediate) annotation

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An operation like only_upper is called a filter because it selects some of the elements and filters out the others.

#### Original toplevel document

Lists
ontains only the uppercase strings: def only_upper(t): res = [] for s in t: if s.isupper(): res.append(s) return res isupper is a string method that returns True if the string contains only upper case letters. <span>An operation like only_upper is called a filter because it selects some of the elements and filters out the others. Most common list operations can be expressed as a combination of map, filter and reduce. 10.8 Deleting elements There are several ways to delete elements from a list. If you kno

#### Flashcard 1737340095756

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#lists #python
Question

Most common list operations can be expressed as a combination of [...].

map, filter and reduce

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#### Parent (intermediate) annotation

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Most common list operations can be expressed as a combination of map, filter and reduce.

#### Original toplevel document

Lists
res.append(s) return res isupper is a string method that returns True if the string contains only upper case letters. An operation like only_upper is called a filter because it selects some of the elements and filters out the others. <span>Most common list operations can be expressed as a combination of map, filter and reduce. 10.8 Deleting elements There are several ways to delete elements from a list. If you know the index of the element you want, you can use pop: >>> t = ['a', 'b', 'c']

#### Annotation 1737342979340

 #numpy Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once.

Fancy Indexing | Python Data Science Handbook
is like the simple indexing we've already seen, but we pass arrays of indices in place of single scalars. This allows us to very quickly access and modify complicated subsets of an array's values. Exploring Fancy Indexing¶ <span>Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once. For example, consider the following array: In [1]: import numpy as np rand = np.random.RandomState(42) x = rand.randint(100, size=10) print(x)

#### Flashcard 1737345076492

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#numpy
Question
[...] is conceptually simple: it means passing an array of indices to access multiple array elements at once.
Fancy indexing

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Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once.

#### Original toplevel document

Fancy Indexing | Python Data Science Handbook
is like the simple indexing we've already seen, but we pass arrays of indices in place of single scalars. This allows us to very quickly access and modify complicated subsets of an array's values. Exploring Fancy Indexing¶ <span>Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once. For example, consider the following array: In [1]: import numpy as np rand = np.random.RandomState(42) x = rand.randint(100, size=10) print(x)

#### Flashcard 1737346649356

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#numpy
Question
Fancy indexing passes [...] to access multiple array elements at once.
an array of indices

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#### Parent (intermediate) annotation

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Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once.

#### Original toplevel document

Fancy Indexing | Python Data Science Handbook
is like the simple indexing we've already seen, but we pass arrays of indices in place of single scalars. This allows us to very quickly access and modify complicated subsets of an array's values. Exploring Fancy Indexing¶ <span>Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once. For example, consider the following array: In [1]: import numpy as np rand = np.random.RandomState(42) x = rand.randint(100, size=10) print(x)

#### Flashcard 1737348222220

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#numpy
Question
Fancy indexing is conceptually simple: it means passing an array of indices to access [...] at once.
multiple array elements

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#### Parent (intermediate) annotation

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Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once.

#### Original toplevel document

Fancy Indexing | Python Data Science Handbook
is like the simple indexing we've already seen, but we pass arrays of indices in place of single scalars. This allows us to very quickly access and modify complicated subsets of an array's values. Exploring Fancy Indexing¶ <span>Fancy indexing is conceptually simple: it means passing an array of indices to access multiple array elements at once. For example, consider the following array: In [1]: import numpy as np rand = np.random.RandomState(42) x = rand.randint(100, size=10) print(x)

#### Annotation 1737351367948

 Before you proceed to conda update --all command to update all packages in an environment, first update conda with conda update conda command if you haven't update it for a long time.

python - Bulk package updates using Conda [Anaconda] - Stack Overflow
add a comment | up vote 4 down vote <span>Before you proceed to conda update --all command, first update conda with conda update conda command if you haven't update it for a long time. It happent to me (Python 2.7.13 on Anaconda 64 bits). share|edit|flag edited Dec 26 '17 at 4:42 [imagelink]

#### Flashcard 1737354251532

Question
[...] command updates all packages in an environment
conda update --all

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Before you proceed to conda update --all command to update all packages in an environment, first update conda with conda update conda command if you haven't update it for a long time.

#### Original toplevel document

python - Bulk package updates using Conda [Anaconda] - Stack Overflow
add a comment | up vote 4 down vote <span>Before you proceed to conda update --all command, first update conda with conda update conda command if you haven't update it for a long time. It happent to me (Python 2.7.13 on Anaconda 64 bits). share|edit|flag edited Dec 26 '17 at 4:42 [imagelink]

#### Flashcard 1737355824396

Question
update conda with [...] if you haven't update it for a long time.
conda update conda

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#### Parent (intermediate) annotation

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Before you proceed to conda update --all command to update all packages in an environment, first update conda with conda update conda command if you haven't update it for a long time.

#### Original toplevel document

python - Bulk package updates using Conda [Anaconda] - Stack Overflow
add a comment | up vote 4 down vote <span>Before you proceed to conda update --all command, first update conda with conda update conda command if you haven't update it for a long time. It happent to me (Python 2.7.13 on Anaconda 64 bits). share|edit|flag edited Dec 26 '17 at 4:42 [imagelink]

#### Annotation 1737358970124

 In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data

Functional programming - Wikipedia
ithic) Object-oriented Actor-based Class-based Concurrent Prototype-based By separation of concerns: Aspect-oriented Role-oriented Subject-oriented Recursive Value-level (contrast: Function-level) Quantum programming v t e <span>In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. It is a declarative programming paradigm, which means programming is done with expressions [1] or declarations [2] instead of statements. In functional code, the output value of a fu

#### Flashcard 1737361067276

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functional programming is a style of building [...] of computer programs
the structure and elements

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In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data

#### Original toplevel document

Functional programming - Wikipedia
ithic) Object-oriented Actor-based Class-based Concurrent Prototype-based By separation of concerns: Aspect-oriented Role-oriented Subject-oriented Recursive Value-level (contrast: Function-level) Quantum programming v t e <span>In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. It is a declarative programming paradigm, which means programming is done with expressions [1] or declarations [2] instead of statements. In functional code, the output value of a fu

#### Flashcard 1737362640140

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functional programming treats computation as [...]
the evaluation of mathematical functions

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#### Parent (intermediate) annotation

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In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data

#### Original toplevel document

Functional programming - Wikipedia
ithic) Object-oriented Actor-based Class-based Concurrent Prototype-based By separation of concerns: Aspect-oriented Role-oriented Subject-oriented Recursive Value-level (contrast: Function-level) Quantum programming v t e <span>In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. It is a declarative programming paradigm, which means programming is done with expressions [1] or declarations [2] instead of statements. In functional code, the output value of a fu

#### Flashcard 1737364213004

Question
functional programming avoids [...]
changing-state and mutable data

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span> In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids <span>changing-state and mutable data <span><body><html>

#### Original toplevel document

Functional programming - Wikipedia
ithic) Object-oriented Actor-based Class-based Concurrent Prototype-based By separation of concerns: Aspect-oriented Role-oriented Subject-oriented Recursive Value-level (contrast: Function-level) Quantum programming v t e <span>In computer science, functional programming is a programming paradigm—a style of building the structure and elements of computer programs—that treats computation as the evaluation of mathematical functions and avoids changing-state and mutable data. It is a declarative programming paradigm, which means programming is done with expressions [1] or declarations [2] instead of statements. In functional code, the output value of a fu

#### Annotation 1737367620876

 #linear-state-space-models The objects in play are: An $$n \times 1$$ vector $$x_t$$ denoting the state at time $$t = 0, 1, 2, \ldots$$An iid sequence of $$m \times 1$$ random vectors $$w_t \sim N(0,I)$$A $$k \times 1$$ vector $$y_t$$ of observations at time $$t = 0, 1, 2, \ldots$$An $$n \times n$$ matrix A called the transition matrixAn $$n \times m$$ matrix C called the volatility matrixA $$k \times n$$ matrix G sometimes called the output matrix Here is the linear state-space system \begin{aligned} x_{t+1} & = A x_t + C w_{t+1} \\ y_t & = G x_t \nonumber \\ x_0 & \sim N(\mu_0, \Sigma_0) \nonumber \end{aligned} . .

#### Annotation 1737373125900

 #linear-state-space-models A martingale difference sequence is a sequence that is zero mean when conditioned on past information

Linear State Space Models – Quantitative Economics
Martingale difference shocks¶ We’ve made the common assumption that the shocks are independent standardized normal vectors But some of what we say will be valid under the assumption that {wt+1}{wt+1} is a martingale difference sequence <span>A martingale difference sequence is a sequence that is zero mean when conditioned on past information In the present case, since {xt}{xt} is our state sequence, this means that it satisfies 𝔼[wt+1|xt,xt−1,…]=0E[wt+1|xt,xt−1,…]=0 This is a weaker condition than that {wt}{wt} is i

#### Annotation 1737374698764

 #linear-state-space-models The primitives of the model are the matrices A , C , G A,C,G A, C, G shock distribution, which we have specialized to N ( 0 , I ) N(0,I) N(0,I) the distribution of the initial condition x 0 x0 x_0 , which we have set to N ( μ 0 , Σ 0 )

#### Annotation 1737384922380

 #linear-state-space-models In state space models, finding the state is an art

Linear State Space Models – Quantitative Economics
N(0,I) Examples¶ By appropriate choice of the primitives, a variety of dynamics can be represented in terms of the linear state space model The following examples help to highlight this point They also illustrate the wise dictum <span>finding the state is an art Second-order difference equation¶ Let {yt}{yt} be a deterministic sequence that satifies (2)¶ yt+1=ϕ0+ϕ1yt+ϕ2yt−1s.t.y0,y−1 givenyt+1=ϕ0+ϕ1yt+ϕ2yt−1s.t.y0,y−1 given To map (2

#### Annotation 1737388592396

 #linear-state-space-models Sufficient statistics form a list of objects that characterize a population distribution

Linear State Space Models – Quantitative Economics
full distribution However, there are some situations where these moments alone tell us all we need to know These are situations in which the mean vector and covariance matrix are sufficient statistics for the population distribution (<span>Sufficient statistics form a list of objects that characterize a population distribution) One such situation is when the vector in question is Gaussian (i.e., normally distributed) This is the case here, given our Gaussian assumptions on the primitives the fact that n

#### Annotation 1737390689548

 #linear-state-space-models In linear state space models, we can generate independent draws of y_T by repeatedly simulating the evolution of the system up to time T , using an independent set of shocks each time

#### Annotation 1737393048844

 #linear-state-space-models The difference equation $$\mu_{t+1} = A \mu_t$$ is known to have unique fixed point $$\mu_{\infty} = 0$$ if all eigenvalues of A have moduli strictly less than unity.

#### Annotation 1737395145996

 #linear-state-space-models However, global stability is more than we need for stationary solutions, and often more than we want

Linear State Space Models – Quantitative Economics
o has a unique fixed point in this case, and, moreover μt→μ∞=0andΣt→Σ∞ast→∞μt→μ∞=0andΣt→Σ∞ast→∞ regardless of the initial conditions μ0μ0 and Σ0Σ0 This is the globally stable case — see these notes for more a theoretical treatment <span>However, global stability is more than we need for stationary solutions, and often more than we want To illustrate, consider our second order difference equation example Here the state is xt=[1ytyt−1]′xt=[1ytyt−1]′ Because of the constant first component in the state vector, we w

#### Annotation 1737397243148

 #linear-state-space-models Ergodicity is the property that time series and ensemble averages coincide

Linear State Space Models – Quantitative Economics
verages x¯:=1T∑t=1Txtandy¯:=1T∑t=1Tytx¯:=1T∑t=1Txtandy¯:=1T∑t=1Tyt Do these time series averages converge to something interpretable in terms of our basic state-space representation? The answer depends on something called ergodicity <span>Ergodicity is the property that time series and ensemble averages coincide More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(

#### Annotation 1737399340300

 #linear-state-space-models More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution

Linear State Space Models – Quantitative Economics
hese time series averages converge to something interpretable in terms of our basic state-space representation? The answer depends on something called ergodicity Ergodicity is the property that time series and ensemble averages coincide <span>More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ In our linear Gaussia

#### Annotation 1737401437452

 #linear-state-space-models In our linear Gaussian setting, any covariance stationary process is also ergodic

Linear State Space Models – Quantitative Economics
ample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ <span>In our linear Gaussian setting, any covariance stationary process is also ergodic Noisy Observations¶ In some settings the observation equation yt=Gxtyt=Gxt is modified to include an error term Often this error term represents the idea that the true sta

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 #linear-state-space-models The theory of prediction for linear state space systems is elegant and simple

Linear State Space Models – Quantitative Economics
t]=Gμt The variance-covariance matrix of ytyt is easily shown to be (19)¶ Var[yt]=Var[Gxt+Hvt]=GΣtG′+HH′Var[yt]=Var[Gxt+Hvt]=GΣtG′+HH′ The distribution of ytyt is therefore yt∼N(Gμt,GΣtG′+HH′)yt∼N(Gμt,GΣtG′+HH′) Prediction¶ <span>The theory of prediction for linear state space systems is elegant and simple Forecasting Formulas – Conditional Means¶ The natural way to predict variables is to use conditional distributions For example, the optimal forecast of xt+1xt+1 given informatio

#### Annotation 1737405893900

 #linear-state-space-models The natural way to predict variables is to use conditional distributions

Linear State Space Models – Quantitative Economics
vt]=GΣtG′+HH′ The distribution of ytyt is therefore yt∼N(Gμt,GΣtG′+HH′)yt∼N(Gμt,GΣtG′+HH′) Prediction¶ The theory of prediction for linear state space systems is elegant and simple Forecasting Formulas – Conditional Means¶ <span>The natural way to predict variables is to use conditional distributions For example, the optimal forecast of xt+1xt+1 given information known at time tt is 𝔼t[xt+1]:=𝔼[xt+1∣xt,xt−1,…,x0]=AxtEt[xt+1]:=E[xt+1∣xt,xt−1,…,x0]=Axt The right-hand side foll

#### Annotation 1737408253196

 #linear-state-space-models if $$\{y_t\}$$ is a stream of dividends, then $$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$ is a model of a stock price

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 #python Generator expressions are similar to list comprehensions, but with parentheses instead of square brackets:

The Goodies
use you can’t put a print statement inside the loop. I suggest that you use them only if the computation is simple enough that you are likely to get it right the first time. And for beginners that means never. 19.3 Generator expressions <span>Generator expressions are similar to list comprehensions, but with parentheses instead of square brackets: >>> g = (x**2 for x in range(5)) >>> g at 0x7f4c45a786c0> The result is a generator object that knows how to iterate through a sequence of values. But unlike a

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In state space models, finding [...] is an art
the state

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In state space models, finding the state is an art

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Linear State Space Models – Quantitative Economics
N(0,I) Examples¶ By appropriate choice of the primitives, a variety of dynamics can be represented in terms of the linear state space model The following examples help to highlight this point They also illustrate the wise dictum <span>finding the state is an art Second-order difference equation¶ Let {yt}{yt} be a deterministic sequence that satifies (2)¶ yt+1=ϕ0+ϕ1yt+ϕ2yt−1s.t.y0,y−1 givenyt+1=ϕ0+ϕ1yt+ϕ2yt−1s.t.y0,y−1 given To map (2

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[...] are similar to list comprehensions, but with parentheses instead of square brackets:
Generator expressions

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Generator expressions are similar to list comprehensions, but with parentheses instead of square brackets:

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use you can’t put a print statement inside the loop. I suggest that you use them only if the computation is simple enough that you are likely to get it right the first time. And for beginners that means never. 19.3 Generator expressions <span>Generator expressions are similar to list comprehensions, but with parentheses instead of square brackets: >>> g = (x**2 for x in range(5)) >>> g at 0x7f4c45a786c0> The result is a generator object that knows how to iterate through a sequence of values. But unlike a

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Generator expressions are similar to [...], but with parentheses instead of square brackets:
list comprehensions

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Generator expressions are similar to list comprehensions, but with parentheses instead of square brackets:

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use you can’t put a print statement inside the loop. I suggest that you use them only if the computation is simple enough that you are likely to get it right the first time. And for beginners that means never. 19.3 Generator expressions <span>Generator expressions are similar to list comprehensions, but with parentheses instead of square brackets: >>> g = (x**2 for x in range(5)) >>> g at 0x7f4c45a786c0> The result is a generator object that knows how to iterate through a sequence of values. But unlike a

#### Flashcard 1737419525388

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if $$\{y_t\}$$ is [...], then $$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$ is a model of a stock price
a stream of dividends

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if $$\{y_t\}$$ is a stream of dividends, then $$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$ is a model of a stock price

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Linear State Space Models – Quantitative Economics

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if $$\{y_t\}$$ is a stream of dividends, then $$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$ is a model of [...]
a stock price

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if $$\{y_t\}$$ is a stream of dividends, then $$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$ is a model of a stock price

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Linear State Space Models – Quantitative Economics

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if $$\{y_t\}$$ is a stream of dividends, then [...] is a model of a stock price
$$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$

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if $$\{y_t\}$$ is a stream of dividends, then $$\mathbb{E} \left[\sum_{j=0}^\infty \beta^j y_{t+j} | x_t \right]$$ is a model of a stock price

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Linear State Space Models – Quantitative Economics

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The natural way to predict variables is to use

[...]

conditional distributions

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The natural way to predict variables is to use conditional distributions

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Linear State Space Models – Quantitative Economics
vt]=GΣtG′+HH′ The distribution of ytyt is therefore yt∼N(Gμt,GΣtG′+HH′)yt∼N(Gμt,GΣtG′+HH′) Prediction¶ The theory of prediction for linear state space systems is elegant and simple Forecasting Formulas – Conditional Means¶ <span>The natural way to predict variables is to use conditional distributions For example, the optimal forecast of xt+1xt+1 given information known at time tt is 𝔼t[xt+1]:=𝔼[xt+1∣xt,xt−1,…,x0]=AxtEt[xt+1]:=E[xt+1∣xt,xt−1,…,x0]=Axt The right-hand side foll

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In our linear Gaussian setting, any covariance stationary process is also [...]

ergodic

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In our linear Gaussian setting, any covariance stationary process is also ergodic

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Linear State Space Models – Quantitative Economics
ample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ <span>In our linear Gaussian setting, any covariance stationary process is also ergodic Noisy Observations¶ In some settings the observation equation yt=Gxtyt=Gxt is modified to include an error term Often this error term represents the idea that the true sta

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In our linear Gaussian setting, any [...] process is also ergodic

covariance stationary

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In our linear Gaussian setting, any covariance stationary process is also ergodic

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Linear State Space Models – Quantitative Economics
ample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ <span>In our linear Gaussian setting, any covariance stationary process is also ergodic Noisy Observations¶ In some settings the observation equation yt=Gxtyt=Gxt is modified to include an error term Often this error term represents the idea that the true sta

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In [...] setting, any covariance stationary process is also ergodic

our linear Gaussian

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In our linear Gaussian setting, any covariance stationary process is also ergodic

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Linear State Space Models – Quantitative Economics
ample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ <span>In our linear Gaussian setting, any covariance stationary process is also ergodic Noisy Observations¶ In some settings the observation equation yt=Gxtyt=Gxt is modified to include an error term Often this error term represents the idea that the true sta

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More formally, ergodicity implies that [...] converge to their expectation under the stationary distribution

time series sample averages

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More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution

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Linear State Space Models – Quantitative Economics
hese time series averages converge to something interpretable in terms of our basic state-space representation? The answer depends on something called ergodicity Ergodicity is the property that time series and ensemble averages coincide <span>More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ In our linear Gaussia

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More formally, ergodicity implies that time series sample averages converge to

[...]

their expectation under the stationary distribution

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More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution

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Linear State Space Models – Quantitative Economics
hese time series averages converge to something interpretable in terms of our basic state-space representation? The answer depends on something called ergodicity Ergodicity is the property that time series and ensemble averages coincide <span>More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(xt−x¯T)(xt−x¯T)′→Σ∞1T∑t=1T(xt−x¯T)(xt−x¯T)′→Σ∞ 1T∑Tt=1(xt+j−x¯T)(xt−x¯T)′→AjΣ∞1T∑t=1T(xt+j−x¯T)(xt−x¯T)′→AjΣ∞ In our linear Gaussia

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Ergodicity is the property that averages of [...] and [...] coincide

time series and ensemble

The ensemble is the samples from the stationary distribution

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Ergodicity is the property that time series and ensemble averages coincide

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Linear State Space Models – Quantitative Economics
verages x¯:=1T∑t=1Txtandy¯:=1T∑t=1Tytx¯:=1T∑t=1Txtandy¯:=1T∑t=1Tyt Do these time series averages converge to something interpretable in terms of our basic state-space representation? The answer depends on something called ergodicity <span>Ergodicity is the property that time series and ensemble averages coincide More formally, ergodicity implies that time series sample averages converge to their expectation under the stationary distribution In particular, 1T∑Tt=1xt→μ∞1T∑t=1Txt→μ∞ 1T∑Tt=1(

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However, [...] is more than we need for stationary solutions, and often more than we want

global stability

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However, global stability is more than we need for stationary solutions, and often more than we want

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Linear State Space Models – Quantitative Economics
o has a unique fixed point in this case, and, moreover μt→μ∞=0andΣt→Σ∞ast→∞μt→μ∞=0andΣt→Σ∞ast→∞ regardless of the initial conditions μ0μ0 and Σ0Σ0 This is the globally stable case — see these notes for more a theoretical treatment <span>However, global stability is more than we need for stationary solutions, and often more than we want To illustrate, consider our second order difference equation example Here the state is xt=[1ytyt−1]′xt=[1ytyt−1]′ Because of the constant first component in the state vector, we w

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In linear state space models, we can generate independent draws of y_T by [...] , using an independent set of shocks each time
repeatedly simulating the evolution of the system up to time T

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In linear state space models, we can generate independent draws of y_T by repeatedly simulating the evolution of the system up to time T , using an independent set of shocks each time

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In linear state space models, we can generate independent draws of y_T by repeatedly simulating the evolution of the system up to time T , using [...]
an independent set of shocks each time

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In linear state space models, we can generate independent draws of y_T by repeatedly simulating the evolution of the system up to time T , using an independent set of shocks each time

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Linear State Space Models – Quantitative Economics

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[...] form a list of objects that characterize a population distribution
Sufficient statistics

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Sufficient statistics form a list of objects that characterize a population distribution

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full distribution However, there are some situations where these moments alone tell us all we need to know These are situations in which the mean vector and covariance matrix are sufficient statistics for the population distribution (<span>Sufficient statistics form a list of objects that characterize a population distribution) One such situation is when the vector in question is Gaussian (i.e., normally distributed) This is the case here, given our Gaussian assumptions on the primitives the fact that n

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A [...] is an aggregation of one or more portfolios managed according to a similar investment mandate, objective, or strategy.
composite

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In the linear state-space system
\begin{aligned} x_{t+1} & = A x_t + C w_{t+1} \\ y_t & = G x_t \nonumber \\ x_0 & \sim N(\mu_0, \Sigma_0) \nonumber \end{aligned}

C is called the [...]

volatility matrix

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An n×1 vector xt denoting the state at time t=0,1,2,… An iid sequence of m×1 random vectors wt∼N(0,I) A k×1 vector yt of observations at time t=0,1,2,… An n×n matrix A called the transition matrix An n×m matrix C called the <span>volatility matrix A k×n matrix G sometimes called the output matrix Here is the linear state-space system xt+1ytx0=Axt+Cwt+1=Gxt∼N(μ0,Σ0) . .

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Linear State Space Models – Quantitative Economics

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The difference equation $$\mu_{t+1} = A \mu_t$$ is known to have unique fixed point $$\mu_{\infty} = 0$$ if [...].
all eigenvalues of A have moduli strictly less than unity

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The difference equation μt+1=Aμt is known to have unique fixed point μ∞=0 if all eigenvalues of A have moduli strictly less than unity.

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the [...] distribution is specialized to $$N(0,I)$$
shock

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The primitives of the model are the matrices A , C , G A,C,G A, C, G shock distribution, which we have specialized to N ( 0 , I ) N(0,I) N(0,I) the distribution of the initial condition x 0 x0 x_0 , which we have set to N ( μ 0 , Σ 0 )

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 Reading 17  Understanding Business Cycles (Intro) #has-images #microscopio-session #reading-wheat Agricultural societies experience good harvest times and bad ones. Weather is a main factor that influences crop production, but other factors, such as plant and animal diseases, also influence the harvest. Modern diversified economies are less influenced by weather and diseases but, as with crops, there are fluctuations in economic output, with good times and bad times. This reading addresses changes in economic activity and factors that affect it. Some of the factors that influence short-term economic movements—such as changes in population, technology, and capital—are the same as those that affect long-term sustainable economic growth. Other factors, such as money supply and inflation, are more specific to short-term economic fluctuations.

Agricultural societies experience good harvest times and bad ones. Weather is a main factor that influences crop production, but other factors, such as plant and animal diseases, also influence the harvest. Modern diversified economies are less influenced by weather and diseases but, as with crops, there are fluctuations in economic output, with good times and bad times. This reading addresses changes in economic activity and factors that affect it. Some of the factors that influence short-term economic movements—such as changes in population, technology, and capital—are the same as those that affect long-term sustainable economic growth. Other factors, such as money supply and inflation, are more specific to short-term economic fluctuations. This reading is organized as follows. Section 2 describes the business cycle and its phases. The typical behaviors of businesses and households in different phases and tran

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 Reading 17  Understanding Business Cycles (Layout) #has-images #microscopio-session #reading-wheat This reading is organized as follows: Section 2 describes the business cycle and its phases. The typical behaviors of businesses and households in different phases and transitions between phases are described. Section 3 provides an introduction to business cycle theory, in particular how different economic schools of thought interpret the business cycle and their recommendations with respect to it. Section 4 introduces basic concepts concerning unemployment and inflation, two measures of short-term economic activity that are important to economic policymakers. Section 5 discusses variables that demonstrate predictable relationships with the economy, focusing on variables whose movements have value in predicting the future course of the economy.

as changes in population, technology, and capital—are the same as those that affect long-term sustainable economic growth. Other factors, such as money supply and inflation, are more specific to short-term economic fluctuations. <span>This reading is organized as follows. Section 2 describes the business cycle and its phases. The typical behaviors of businesses and households in different phases and transitions between phases are described. Section 3 provides an introduction to business cycle theory, in particular how different economic schools of thought interpret the business cycle and their recommendations with respect to it. Section 4 introduces basic concepts concerning unemployment and inflation, two measures of short-term economic activity that are important to economic policymakers. Section 5 discusses variables that demonstrate predictable relationships with the economy, focusing on variables whose movements have value in predicting the future course of the economy. A summary and practice problems conclude the reading. <span><body><html>

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 Reading 24  Understanding Income Statements (Intro) #bascula-session #has-images #reading-embudo The income statement presents information on the financial results of a company’s business activities over a period of time. The income statement communicates how much revenue the company generated during a period and what costs it incurred in connection with generating that revenue. The basic equation underlying the income statement, ignoring gains and losses, is Revenue minus Expenses equals Net income. The income statement is also sometimes referred to as the “statement of operations,” “statement of earnings,” or “profit and loss (P&L) statement.” Under IFRS, the income statement may be presented as a separate statement followed by a statement of comprehensive income that begins with the profit or loss from the income statement or as a section of a single statement of comprehensive income. US GAAP permit the same alternative presentation formats.2 This reading focuses on the income statement, but also discusses comprehensive income (profit or loss from the income statement plus other comprehensive income). Investment analysts intensely scrutinize companies’ income statements.3 Equity analysts are interested in them because equity markets often reward relatively high- or low-earnings growth companies with above-average or below-average valuations, respectively, and because inputs into valuation models often include estimates of earnings. Fixed-income analysts examine the components of income statements, past and projected, for information on companies’ abilities to make promised payments on their debt over the course of the business cycle. Corporate financial announcements frequently emphasize information reported in income statements, particularly earnings, more than information reported in the other financial statements.

Reading 24  Understanding Income Statements Intro
The income statement presents information on the financial results of a company’s business activities over a period of time. The income statement communicates how much revenue the company generated during a period and what costs it incurred in connection with generating that revenue. The basic equation underlying the income statement, ignoring gains and losses, is Revenue minus Expenses equals Net income. The income statement is also sometimes referred to as the “statement of operations,” “statement of earnings,” or “profit and loss (P&L) statement.” Under International Financial Reporting Standards (IFRS), the income statement may be presented as a separate statement followed by a statement of comprehensive income that begins with the profit or loss from the income statement or as a section of a single statement of comprehensive income.1 US generally accepted accounting principles (US GAAP) permit the same alternative presentation formats.2 This reading focuses on the income statement, but also discusses comprehensive income (profit or loss from the income statement plus other comprehensive income). Investment analysts intensely scrutinize companies’ income statements.3 Equity analysts are interested in them because equity markets often reward relatively high- or low-earnings growth companies with above-average or below-average valuations, respectively, and because inputs into valuation models often include estimates of earnings. Fixed-income analysts examine the components of income statements, past and projected, for information on companies’ abilities to make promised payments on their debt over the course of the business cycle. Corporate financial announcements frequently emphasize information reported in income statements, particularly earnings, more than information reported in the other financial statements. This reading is organized as follows: Section 2 describes the components of the income statement and its format. Section 3 describes basic principles and selected applicati

#### Annotation 1737466449164

 Reading 24  Understanding Income Statements (Layout) #bascula-session #has-images #reading-embudo This reading is organized as follows: Section 2 describes the components of the income statement and its format. Section 3 describes basic principles and selected applications related to the recognition of revenue. Section 4 describes basic principles and selected applications related to the recognition of expenses. Section 5 covers non-recurring items and non-operating items. Section 6 explains the calculation of earnings per share. Section 7 introduces income statement analysis, and Section 8 explains comprehensive income and its reporting.

Reading 24  Understanding Income Statements Intro
ebt over the course of the business cycle. Corporate financial announcements frequently emphasize information reported in income statements, particularly earnings, more than information reported in the other financial statements. <span>This reading is organized as follows: Section 2 describes the components of the income statement and its format. Section 3 describes basic principles and selected applications related to the recognition of revenue, and Section 4 describes basic principles and selected applications related to the recognition of expenses. Section 5 covers non-recurring items and non-operating items. Section 6 explains the calculation of earnings per share. Section 7 introduces income statement analysis, and Section 8 explains comprehensive income and its reporting. A summary of the key points and practice problems in the CFA Institute multiple choice format complete the reading. <span><body><html>

#### Annotation 1737469857036

 Reading 27  Financial Analysis Techniques (Intro) #bascula-session #has-images #reading-magnifying-glass Financial analysis tools can be useful in assessing a company’s performance and trends in that performance. In essence, an analyst converts data into financial metrics that assist in decision making. Analysts seek to answer such questions as: How successfully has the company performed, relative to its own past performance and relative to its competitors? How is the company likely to perform in the future? Based on expectations about future performance, what is the value of this company or the securities it issues? A primary source of data is a company’s annual report, including the financial statements and notes, and management commentary (operating and financial review or management’s discussion and analysis). This reading focuses on data presented in financial reports prepared under IFRS and US GAAP. However, financial reports do not contain all the information needed to perform effective financial analysis. Although financial statements do contain data about the past performance of a company (its income and cash flows) as well as its current financial condition (assets, liabilities, and owners’ equity), such statements do not necessarily provide all the information useful for analysis nor do they forecast future results. The financial analyst must be capable of using financial statements in conjunction with other information to make projections and reach valid conclusions. Accordingly, an analyst typically needs to supplement the information found in a company’s financial reports with other information, including information on the economy, industry, comparable companies, and the company itself. This reading describes various techniques used to analyze a company’s financial statements. Financial analysis of a company may be performed for a variety of reasons, such as valuing equity securities, assessing credit risk, conducting due diligence related to an acquisition, or assessing a subsidiary’s performance. This reading will describe techniques common to any financial analysis and then discuss more specific aspects for the two most common categories: equity analysis and credit analysis. Equity analysis incorporates an owner’s perspective, either for valuation or performance evaluation. Credit analysis incorporates a creditor’s (such as a banker or bondholder) perspective. In either case, there is a need to gather and analyze information to make a decision (ownership or credit); the focus of analysis varies because of the differing interest of owners and creditors. Both equity and credit analyses assess the entity’s ability to generate and grow earnings, and cash flow, as well as any associated risks. Equity analysis usually places a greater emphasis on growth, whereas credit analysis usually places a greater emphasis on risks. The difference in emphasis reflects the different fundamentals of these types of investments: The value of a company’s equity generally increases as the company’s earnings and cash flow increase, whereas the value of a company’s debt has an upper limit.

Reading 27  Financial Analysis Techniques Introduction
Financial analysis tools can be useful in assessing a company’s performance and trends in that performance. In essence, an analyst converts data into financial metrics that assist in decision making. Analysts seek to answer such questions as: How successfully has the company performed, relative to its own past performance and relative to its competitors? How is the company likely to perform in the future? Based on expectations about future performance, what is the value of this company or the securities it issues? A primary source of data is a company’s annual report, including the financial statements and notes, and management commentary (operating and financial review or management’s discussion and analysis). This reading focuses on data presented in financial reports prepared under International Financial Reporting Standards (IFRS) and United States generally accepted accounting principles (US GAAP). However, financial reports do not contain all the information needed to perform effective financial analysis. Although financial statements do contain data about the past performance of a company (its income and cash flows) as well as its current financial condition (assets, liabilities, and owners’ equity), such statements do not necessarily provide all the information useful for analysis nor do they forecast future results. The financial analyst must be capable of using financial statements in conjunction with other information to make projections and reach valid conclusions. Accordingly, an analyst typically needs to supplement the information found in a company’s financial reports with other information, including information on the economy, industry, comparable companies, and the company itself. This reading describes various techniques used to analyze a company’s financial statements. Financial analysis of a company may be performed for a variety of reasons, such as valuing equity securities, assessing credit risk, conducting due diligence related to an acquisition, or assessing a subsidiary’s performance. This reading will describe techniques common to any financial analysis and then discuss more specific aspects for the two most common categories: equity analysis and credit analysis. Equity analysis incorporates an owner’s perspective, either for valuation or performance evaluation. Credit analysis incorporates a creditor’s (such as a banker or bondholder) perspective. In either case, there is a need to gather and analyze information to make a decision (ownership or credit); the focus of analysis varies because of the differing interest of owners and creditors. Both equity and credit analyses assess the entity’s ability to generate and grow earnings, and cash flow, as well as any associated risks. Equity analysis usually places a greater emphasis on growth, whereas credit analysis usually places a greater emphasis on risks. The difference in emphasis reflects the different fundamentals of these types of investments: The value of a company’s equity generally increases as the company’s earnings and cash flow increase, whereas the value of a company’s debt has an upper limit.1 The balance of this reading is organized as follows: Section 2 recaps the framework for financial statements and the place of financial analysis techniques within the frame

#### Annotation 1737472216332

 Reading 27  Financial Analysis Techniques (Layout) #bascula-session #reading-magnifying-glass The balance of this reading is organized as follows: Section 2 recaps the framework for financial statements and the place of financial analysis techniques within the framework. Section 3 provides a description of analytical tools and techniques. Section 4 explains how to compute, analyze, and interpret common financial ratios. Sections 5 through 8 explain the use of ratios and other analytical data in equity analysis, credit analysis, segment analysis, and forecasting, respectively.

Reading 27  Financial Analysis Techniques Introduction
s reflects the different fundamentals of these types of investments: The value of a company’s equity generally increases as the company’s earnings and cash flow increase, whereas the value of a company’s debt has an upper limit.1 <span>The balance of this reading is organized as follows: Section 2 recaps the framework for financial statements and the place of financial analysis techniques within the framework. Section 3 provides a description of analytical tools and techniques. Section 4 explains how to compute, analyze, and interpret common financial ratios. Sections 5 through 8 explain the use of ratios and other analytical data in equity analysis, credit analysis, segment analysis, and forecasting, respectively. A summary of the key points and practice problems in the CFA Institute multiple-choice format conclude the reading. <span><body><html>

#### Annotation 1737492401420

 Reading 41  Portfolio Risk and Return: Part I (Intro) #has-images #portfolio-session #reading-rocky-balboa Construction of an optimal portfolio is an important objective for an investor. In this reading, we will explore the process of examining the risk and return characteristics of individual assets, creating all possible portfolios, selecting the most efficient portfolios, and ultimately choosing the optimal portfolio tailored to the individual in question. During the process of constructing the optimal portfolio, several factors and investment characteristics are considered. The most important of those factors are risk and return of the individual assets under consideration. Correlations among individual assets along with risk and return are important determinants of portfolio risk. Creating a portfolio for an investor requires an understanding of the risk profile of the investor. Although we will not discuss the process of determining risk aversion for individuals or institutional investors, it is necessary to obtain such information for making an informed decision. In this reading, we will explain the broad types of investors and how their risk–return preferences can be formalized to select the optimal portfolio from among the infinite portfolios contained in the investment opportunity set.

Reading 41  Portfolio Risk and Return: Part I (Intro)
Construction of an optimal portfolio is an important objective for an investor. In this reading, we will explore the process of examining the risk and return characteristics of individual assets, creating all possible portfolios, selecting the most efficient portfolios, and ultimately choosing the optimal portfolio tailored to the individual in question. During the process of constructing the optimal portfolio, several factors and investment characteristics are considered. The most important of those factors are risk and return of the individual assets under consideration. Correlations among individual assets along with risk and return are important determinants of portfolio risk. Creating a portfolio for an investor requires an understanding of the risk profile of the investor. Although we will not discuss the process of determining risk aversion for individuals or institutional investors, it is necessary to obtain such information for making an informed decision. In this reading, we will explain the broad types of investors and how their risk–return preferences can be formalized to select the optimal portfolio from among the infinite portfolios contained in the investment opportunity set. The reading is organized as follows: Section 2 discusses the investment characteristics of assets. In particular, we show the various types of returns and risks, their comp

#### Annotation 1737494760716

 Reading 41  Portfolio Risk and Return: Part I (Layout) #has-images #portfolio-session #reading-rocky-balboa The reading is organized as follows: Section 2 discusses the investment characteristics of assets. In particular, we show the various types of returns and risks, their computation and their applicability to the selection of appropriate assets for inclusion in a portfolio. Section 3 discusses risk aversion and how indifference curves, which incorporate individual preferences, can be constructed. The indifference curves are then applied to the selection of an optimal portfolio using two risky assets. Section 4 provides an understanding and computation of portfolio risk. The role of correlation and diversification of portfolio risk are examined in detail. Section 5 begins with the risky assets available to investors and constructs a large number of risky portfolios. It illustrates the process of narrowing the choices to an efficient set of risky portfolios before identifying the optimal risky portfolio. The risky portfolio is combined with investor risk preferences to generate the optimal risky portfolio.

Reading 41  Portfolio Risk and Return: Part I (Intro)
In this reading, we will explain the broad types of investors and how their risk–return preferences can be formalized to select the optimal portfolio from among the infinite portfolios contained in the investment opportunity set. <span>The reading is organized as follows: Section 2 discusses the investment characteristics of assets. In particular, we show the various types of returns and risks, their computation and their applicability to the selection of appropriate assets for inclusion in a portfolio. Section 3 discusses risk aversion and how indifference curves, which incorporate individual preferences, can be constructed. The indifference curves are then applied to the selection of an optimal portfolio using two risky assets. Section 4 provides an understanding and computation of portfolio risk. The role of correlation and diversification of portfolio risk are examined in detail. Section 5 begins with the risky assets available to investors and constructs a large number of risky portfolios. It illustrates the process of narrowing the choices to an efficient set of risky portfolios before identifying the optimal risky portfolio. The risky portfolio is combined with investor risk preferences to generate the optimal risky portfolio. A summary concludes this reading. <span><body><html>

#### Annotation 1737501052172

 Reading 43  Basics of Portfolio Planning and Construction (Intro) #has-images #portfolio-session #reading-bob-el-constructor To build a suitable portfolio for a client, investment advisers should first seek to understand the client’s investment goals, resources, circumstances, and constraints. Investors can be categorized into broad groups based on shared characteristics with respect to these factors (e.g., various types of individual investors and institutional investors). Even investors within a given type, however, will invariably have a number of distinctive requirements. In this reading, we consider in detail the planning for investment success based on an individualized understanding of the client.

Reading 43  Basics of Portfolio Planning and Construction Intro
To build a suitable portfolio for a client, investment advisers should first seek to understand the client’s investment goals, resources, circumstances, and constraints. Investors can be categorized into broad groups based on shared characteristics with respect to these factors (e.g., various types of individual investors and institutional investors). Even investors within a given type, however, will invariably have a number of distinctive requirements. In this reading, we consider in detail the planning for investment success based on an individualized understanding of the client. This reading is organized as follows: Section 2 discusses the investment policy statement, a written document that captures the client’s investment objectives and the const

#### Annotation 1737503411468

 Reading 43  Basics of Portfolio Planning and Construction (Layout) #has-images #portfolio-session #reading-bob-el-constructor This reading is organized as follows: Section 2 discusses the investment policy statement, a written document that captures the client’s investment objectives and the constraints. Section 3 discusses the portfolio construction process, including the first step of specifying a strategic asset allocation for the client.

Reading 43  Basics of Portfolio Planning and Construction Intro
investors within a given type, however, will invariably have a number of distinctive requirements. In this reading, we consider in detail the planning for investment success based on an individualized understanding of the client. <span>This reading is organized as follows: Section 2 discusses the investment policy statement, a written document that captures the client’s investment objectives and the constraints. Section 3 discusses the portfolio construction process, including the first step of specifying a strategic asset allocation for the client. A summary and practice problems conclude the reading. <span><body><html>

#### Annotation 1737510227212

 Reading 44  Market Organization and Structure (Intro) #has-images #manzana-session #reading-arbol-de-manzanas Financial analysts gather and process information to make investment decisions, including those related to buying and selling assets. Generally, the decisions involve trading securities, currencies, contracts, commodities, and real assets such as real estate. Consider several examples: Fixed income analysts evaluate issuer credit-worthiness and macroeconomic prospects to determine which bonds and notes to buy or sell to preserve capital while obtaining a fair rate of return. Stock analysts study corporate values to determine which stocks to buy or sell to maximize the value of their stock portfolios. Corporate treasurers analyze exchange rates, interest rates, and credit conditions to determine which currencies to trade and which notes to buy or sell to have funds available in a needed currency. Risk managers work for producers or users of commodities to calculate how many commodity futures contracts to buy or sell to manage inventory risks. Financial analysts must understand the characteristics of the markets in which their decisions will be executed. This reading, by examining those markets from the analyst’s perspective, provides that understanding.

Reading 44  Market Organization and Structure (Intro)
Financial analysts gather and process information to make investment decisions, including those related to buying and selling assets. Generally, the decisions involve trading securities, currencies, contracts, commodities, and real assets such as real estate. Consider several examples: Fixed income analysts evaluate issuer credit-worthiness and macroeconomic prospects to determine which bonds and notes to buy or sell to preserve capital while obtaining a fair rate of return. Stock analysts study corporate values to determine which stocks to buy or sell to maximize the value of their stock portfolios. Corporate treasurers analyze exchange rates, interest rates, and credit conditions to determine which currencies to trade and which notes to buy or sell to have funds available in a needed currency. Risk managers work for producers or users of commodities to calculate how many commodity futures contracts to buy or sell to manage inventory risks. Financial analysts must understand the characteristics of the markets in which their decisions will be executed. This reading, by examining those markets from the analyst’s perspective, provides that understanding. This reading is organized as follows. Section 2 examines the functions of the financial system. Section 3 introduces assets that investors, information-motivated traders, a

#### Annotation 1737512586508

Reading 44  Market Organization and Structure (Intro)

#### Annotation 1737519402252

 Reading 48  Introduction to Industry and Company Analysis (Intro) #has-images #lingote-de-oro-session #reading-chimenea-industrial Industry analysis is the analysis of a specific branch of manufacturing, service, or trade. Understanding the industry in which a company operates provides an essential framework for the analysis of the individual company—that is, company analysis . Equity analysis and credit analysis are often conducted by analysts who concentrate on one or several industries, which results in synergies and efficiencies in gathering and interpreting information. Among the questions we address in this reading are the following: What are the similarities and differences among industry classification systems? How does an analyst go about choosing a peer group of companies? What are the key factors to consider when analyzing an industry? What advantages are enjoyed by companies in strategically well-positioned industries?

Reading 48  Introduction to Industry and Company Analysis (Intro)
Industry analysis is the analysis of a specific branch of manufacturing, service, or trade. Understanding the industry in which a company operates provides an essential framework for the analysis of the individual company—that is, company analysis . Equity analysis and credit analysis are often conducted by analysts who concentrate on one or several industries, which results in synergies and efficiencies in gathering and interpreting information. Among the questions we address in this reading are the following: What are the similarities and differences among industry classification systems? How does an analyst go about choosing a peer group of companies? What are the key factors to consider when analyzing an industry? What advantages are enjoyed by companies in strategically well-positioned industries? After discussing the uses of industry analysis in the next section, Sections 3 and 4 discuss, respectively, approaches to identifying similar companies and industry

#### Annotation 1737521761548

 Reading 48  Introduction to Industry and Company Analysis (Layout) #has-images #lingote-de-oro-session #reading-chimenea-industrial Section 2 discusses the uses of industry analysis. Sections 3 and 4 discuss, respectively, approaches to identifying similar companies and industry classification systems. Section 5 covers the description and analysis of industries. It Also includes an introduction to competitive analysis, provides a background to Section 6. Section 6 introduces company analysis.

Reading 48  Introduction to Industry and Company Analysis (Intro)
ut choosing a peer group of companies? What are the key factors to consider when analyzing an industry? What advantages are enjoyed by companies in strategically well-positioned industries? <span>After discussing the uses of industry analysis in the next section, Sections 3 and 4 discuss, respectively, approaches to identifying similar companies and industry classification systems. Section 5 covers the description and analysis of industries. Also, Section 5, which includes an introduction to competitive analysis, provides a background to Section 6, which introduces company analysis. The reading ends with a summary, and practice problems follow the text. <span><body><html>

#### Annotation 1737527790860

 Reading 49  Equity Valuation: Concepts and Basic Tools (Intro) #has-images #lingote-de-oro-session #reading-jens Analysts gather and process information to make investment decisions, including buy and sell recommendations. What information is gathered and how it is processed depend on the analyst and the purpose of the analysis. Technical analysis uses such information as stock price and trading volume as the basis for investment decisions. Fundamental analysis uses information about the economy, industry, and company as the basis for investment decisions. Examples of fundamentals are unemployment rates, gross domestic product (GDP) growth, industry growth, and quality of and growth in company earnings. Whereas technical analysts use information to predict price movements and base investment decisions on the direction of predicted change in prices, fundamental analysts use information to estimate the value of a security and to compare the estimated value to the market price and then base investment decisions on that comparison. This reading introduces equity valuation models used to estimate the intrinsic value (synonym: fundamental value ) of a security; intrinsic value is based on an analysis of investment fundamentals and characteristics. The fundamentals to be considered depend on the analyst’s approach to valuation. In a top-down approach, an analyst examines the economic environment, identifies sectors that are expected to prosper in that environment, and analyzes securities of companies from previously identified attractive sectors. In a bottom-up approach, an analyst typically follows an industry or industries and forecasts fundamentals for the companies in those industries in order to determine valuation. Whatever the approach, an analyst who estimates the intrinsic value of an equity security is implicitly questioning the accuracy of the market price as an estimate of value. Valuation is particularly important in active equity portfolio management, which aims to improve on the return–risk trade-off of a portfolio’s benchmark by identifying mispriced securities.

Reading 49  Equity Valuation: Concepts and Basic Tools (Intro)
Analysts gather and process information to make investment decisions, including buy and sell recommendations. What information is gathered and how it is processed depend on the analyst and the purpose of the analysis. Technical analysis uses such information as stock price and trading volume as the basis for investment decisions. Fundamental analysis uses information about the economy, industry, and company as the basis for investment decisions. Examples of fundamentals are unemployment rates, gross domestic product (GDP) growth, industry growth, and quality of and growth in company earnings. Whereas technical analysts use information to predict price movements and base investment decisions on the direction of predicted change in prices, fundamental analysts use information to estimate the value of a security and to compare the estimated value to the market price and then base investment decisions on that comparison. This reading introduces equity valuation models used to estimate the intrinsic value (synonym: fundamental value ) of a security; intrinsic value is based on an analysis of investment fundamentals and characteristics. The fundamentals to be considered depend on the analyst’s approach to valuation. In a top-down approach, an analyst examines the economic environment, identifies sectors that are expected to prosper in that environment, and analyzes securities of companies from previously identified attractive sectors. In a bottom-up approach, an analyst typically follows an industry or industries and forecasts fundamentals for the companies in those industries in order to determine valuation. Whatever the approach, an analyst who estimates the intrinsic value of an equity security is implicitly questioning the accuracy of the market price as an estimate of value. Valuation is particularly important in active equity portfolio management, which aims to improve on the return–risk trade-off of a portfolio’s benchmark by identifying mispriced securities. This reading is organized as follows. Section 2 discusses the implications of differences between estimated value and market price. Section 3 introduces three major categor

#### Annotation 1737530150156

 Reading 49  Equity Valuation: Concepts and Basic Tools (Layout) #has-images #lingote-de-oro-session #reading-jens This reading is organized as follows: Section 2 discusses the implications of differences between estimated value and market price. Section 3 introduces three major categories of valuation model. Section 4 presents an overview of present value models with a focus on the dividend discount model. Section 5 describes and examines the use of multiples in valuation. Section 6 explains asset-based valuation and demonstrates how these models can be used to estimate value. Section 7 states conclusions and summarizes the reading.

Reading 49  Equity Valuation: Concepts and Basic Tools (Intro)
e market price as an estimate of value. Valuation is particularly important in active equity portfolio management, which aims to improve on the return–risk trade-off of a portfolio’s benchmark by identifying mispriced securities. <span>This reading is organized as follows. Section 2 discusses the implications of differences between estimated value and market price. Section 3 introduces three major categories of valuation model. Section 4 presents an overview of present value models with a focus on the dividend discount model. Section 5 describes and examines the use of multiples in valuation. Section 6 explains asset-based valuation and demonstrates how these models can be used to estimate value. Section 7 states conclusions and summarizes the reading. <span><body><html>

#### Annotation 1737532509452

 Reading 52  Introduction to Fixed-Income Valuation (Intro) #estatua-session #has-images #reading-buda-de-oro Globally, the fixed-income market is a key source of financing for businesses and governments. In fact, the total market value outstanding of corporate and government bonds is significantly larger than that of equity securities. Similarly, the fixed-income market, which is also called the debt market or bond market, represents a significant investing opportunity for institutions as well as individuals. Pension funds, mutual funds, insurance companies, and sovereign wealth funds, among others, are major fixed-income investors. Retirees who desire a relatively stable income stream often hold fixed-income securities. Clearly, understanding how to value fixed-income securities is important to investors, issuers, and financial analysts. This reading focuses on the valuation of traditional (option-free) fixed-rate bonds, although other debt securities, such as floating-rate notes and money market instruments, are also covered.

Reading 52  Introduction to Fixed-Income Valuation (Intro)
Globally, the fixed-income market is a key source of financing for businesses and governments. In fact, the total market value outstanding of corporate and government bonds is significantly larger than that of equity securities. Similarly, the fixed-income market, which is also called the debt market or bond market, represents a significant investing opportunity for institutions as well as individuals. Pension funds, mutual funds, insurance companies, and sovereign wealth funds, among others, are major fixed-income investors. Retirees who desire a relatively stable income stream often hold fixed-income securities. Clearly, understanding how to value fixed-income securities is important to investors, issuers, and financial analysts. This reading focuses on the valuation of traditional (option-free) fixed-rate bonds, although other debt securities, such as floating-rate notes and money market instruments, are also covered. Section 2 describes and illustrates basic bond valuation, which includes pricing a bond using a market discount rate for each of the future cash flows and pricing a bond us

#### Annotation 1737541946636

 Reading 52  Introduction to Fixed-Income Valuation (Layout) #estatua-session #has-images #reading-buda-de-oro Section 2 describes and illustrates basic bond valuation, which includes pricing a bond using a market discount rate for each of the future cash flows and pricing a bond using a series of spot rates. Valuation using spot rates allows for each future cash flow to be discounted at a rate associated with its timing. This valuation methodology for future cash flows has applications well beyond the fixed-income market. Relationships among a bond’s price, coupon rate, maturity, and market discount rate (yield-to-maturity) are also described and illustrated. Section 3 describes how bond prices and yields are quoted and calculated in practice. When bonds are actively traded, investors can observe the price and calculate various yield measures. However, these yield measures differ by the type of bond. In practice, different measures are used for fixed-rate bonds, floating-rate notes, and money market instruments. When a bond is not actively traded, matrix pricing is often used to estimate the value based on comparable securities. Section 4 addresses the maturity or term structure of interest rates. This discussion involves an analysis of yield curves, which illustrates the relationship between yields-to-maturity and times-to-maturity on bonds with otherwise similar characteristics. Various types of yield curves are described. Section 5 focuses on yield spreads over benchmark interest rates. When investors want relatively higher yields, they have to be prepared to bear more risk. Yield spreads are measures of how much additional yield over the benchmark security (usually a government bond) investors expect for bearing additional risk.

Reading 52  Introduction to Fixed-Income Valuation (Intro)
rs, issuers, and financial analysts. This reading focuses on the valuation of traditional (option-free) fixed-rate bonds, although other debt securities, such as floating-rate notes and money market instruments, are also covered. <span>Section 2 describes and illustrates basic bond valuation, which includes pricing a bond using a market discount rate for each of the future cash flows and pricing a bond using a series of spot rates. Valuation using spot rates allows for each future cash flow to be discounted at a rate associated with its timing. This valuation methodology for future cash flows has applications well beyond the fixed-income market. Relationships among a bond’s price, coupon rate, maturity, and market discount rate (yield-to-maturity) are also described and illustrated. Section 3 describes how bond prices and yields are quoted and calculated in practice. When bonds are actively traded, investors can observe the price and calculate various yield measures. However, these yield measures differ by the type of bond. In practice, different measures are used for fixed-rate bonds, floating-rate notes, and money market instruments. When a bond is not actively traded, matrix pricing is often used to estimate the value based on comparable securities. Section 4 addresses the maturity or term structure of interest rates. This discussion involves an analysis of yield curves, which illustrates the relationship between yields-to-maturity and times-to-maturity on bonds with otherwise similar characteristics. Various types of yield curves are described. Section 5 focuses on yield spreads over benchmark interest rates. When investors want relatively higher yields, they have to be prepared to bear more risk. Yield spreads are measures of how much additional yield over the benchmark security (usually a government bond) investors expect for bearing additional risk. A summary of key points and practice problems conclude the reading. <span><body><html>

#### Annotation 1737547975948

 Reading 53  Introduction to Asset-Backed Securities (Intro) #estatua-session #has-images #reading-guitarra-electrica Previous readings examined risk characteristics of various fixed-income instruments and the relationships among maturity, coupon, and interest rate changes. This reading introduces an additional level of complexity—that of fixed-income instruments created through a process known as securitization . This process involves transferring ownership of assets from the original owners into a special legal entity. The special legal entity then issues securities backed by these assets, and the assets’ cash flows are used to pay interest and repay the principal owed to the holders of the securities. These securities are referred to generically as asset-backed securities (ABS); the pool of securitized assets from which the ABS’s cash flows are generated is called the collateral. Assets that are used to create ABS are called securitized assets . These assets are typically loans and receivables and include, among others, residential mortgage loans (mortgages), commercial mortgages, automobile (auto) loans, student loans, bank loans, accounts receivables, and credit card receivables. Advances and innovations in securitization have led to securities backed, or collateralized, by all kinds of income-yielding assets, including airport landing slots and toll roads. This reading discusses the benefits of securitization, describes securitization, and explains the investment characteristics of different types of ABS. The terminology regarding ABS varies by jurisdiction. Mortgage-backed securities (MBS) are ABS backed by a pool of mortgages, and a distinction is sometimes made between MBS and ABS backed by non-mortgage assets. This distinction is common in the United States, for example, where typically the term “mortgage-backed securities” refers to securities backed by high-quality real estate mortgages and the term “asset-backed securities” refers to securities backed by other types of assets. Because the US ABS market is the largest in the world, much of the discussion and many examples in this reading refer to the United States. Note, however, that many non-US investors hold US ABS, including MBS, in their portfolios.

Reading 53  Introduction to Asset-Backed Securities (Intro)
Previous readings examined risk characteristics of various fixed-income instruments and the relationships among maturity, coupon, and interest rate changes. This reading introduces an additional level of complexity—that of fixed-income instruments created through a process known as securitization . This process involves transferring ownership of assets from the original owners into a special legal entity. The special legal entity then issues securities backed by these assets, and the assets’ cash flows are used to pay interest and repay the principal owed to the holders of the securities. These securities are referred to generically as asset-backed securities (ABS); the pool of securitized assets from which the ABS’s cash flows are generated is called the collateral. Assets that are used to create ABS are called securitized assets . These assets are typically loans and receivables and include, among others, residential mortgage loans (mortgages), commercial mortgages, automobile (auto) loans, student loans, bank loans, accounts receivables, and credit card receivables. Advances and innovations in securitization have led to securities backed, or collateralized, by all kinds of income-yielding assets, including airport landing slots and toll roads. This reading discusses the benefits of securitization, describes securitization, and explains the investment characteristics of different types of ABS. The terminology regarding ABS varies by jurisdiction. Mortgage-backed securities (MBS) are ABS backed by a pool of mortgages, and a distinction is sometimes made between MBS and ABS backed by non-mortgage assets. This distinction is common in the United States, for example, where typically the term “mortgage-backed securities” refers to securities backed by high-quality real estate mortgages and the term “asset-backed securities” refers to securities backed by other types of assets. Because the US ABS market is the largest in the world, much of the discussion and many examples in this reading refer to the United States. Note, however, that many non-US investors hold US ABS, including MBS, in their portfolios. To underline the importance of securitization from a macroeconomic perspective, Section 2 discusses of the benefits of securitization for economies and financial markets. I

#### Annotation 1737550335244

 Reading 53  Introduction to Asset-Backed Securities (Layout) #estatua-session #has-images #reading-guitarra-electrica Section 2 discusses of the benefits of securitization for economies and financial markets To underline the importance of securitization from a macroeconomic perspective. In Section 3, the reading describes securitization and identifies the parties involved in the process and their roles. It also discusses typical structures of securitizations, including credit tranching and time tranching. Sections 4–6 discuss securities backed by mortgages for real estate property. In Section 4, Many types of residential mortgage designs around the world are described. Sections 5 and 6 focus on residential MBS and commercial MBS, respectively. Section 7 discusses ABS based on two types of non-mortgage loans that are typically securitized throughout the world: auto loans and credit card receivables. Section 8 covers Collateralized debt obligations. Section 9 concludes the reading with a summary.

Reading 53  Introduction to Asset-Backed Securities (Intro)
ecause the US ABS market is the largest in the world, much of the discussion and many examples in this reading refer to the United States. Note, however, that many non-US investors hold US ABS, including MBS, in their portfolios. <span>To underline the importance of securitization from a macroeconomic perspective, Section 2 discusses of the benefits of securitization for economies and financial markets. In Section 3, the reading describes securitization and identifies the parties involved in the process and their roles. Section 3 also discusses typical structures of securitizations, including credit tranching and time tranching. Sections 4–6 discuss securities backed by mortgages for real estate property. Many types of residential mortgage designs around the world are described in Section 4. Sections 5 and 6 focus on residential MBS and commercial MBS, respectively. Section 7 discusses ABS based on two types of non-mortgage loans that are typically securitized throughout the world: auto loans and credit card receivables. Collateralized debt obligations are covered in Section 8. Section 9 concludes the reading with a summary. <span><body><html>

#### Annotation 1737557150988

Reading 55  Fundamentals of Credit Analysis (Intro)
With bonds outstanding worth many trillions of US dollars, the debt markets play a critical role in the global economy. Companies and governments raise capital in the debt market to fund current operations; buy equipment; build factories, roads, bridges, airports, and hospitals; acquire assets, and so on. By channeling savings into productive investments, the debt markets facilitate economic growth. Credit analysis has a crucial function in the debt capital markets—efficiently allocating capital by properly assessing credit risk, pricing it accordingly, and repricing it as risks change. How do fixed-income investors determine the riskiness of that debt, and how do they decide what they need to earn as compensation for that risk? This reading covers basic principles of credit analysis, which may be broadly defined as the process by which credit risk is evaluated. Readers will be introduced to the definition of credit risk, the interpretation of credit ratings, the four Cs of traditional credit analysis, and key financial measures and ratios used in credit analysis. The reading explains, among other things, how to compare bond issuer creditworthiness within a given industry as well as across industries and how credit risk is priced in the bond market. The reading focuses primarily on analysis of corporate debt; however, credit analysis of sovereign and non-sovereign, particularly municipal, government bonds will also be addressed. Structured finance, a segment of the debt markets that includes securities backed by pools of assets, such as residential and commercial mortgages as well as other consumer loans, will not be covered here. The key components of credit risk—default probability and loss severity—are introduced in the next section along with such credit-related risks as spread risk, credit migra

#### Annotation 1737559510284

 Reading 55  Fundamentals of Credit Analysis (Layout) #has-images #paracaidas-session #reading-chris-schoening Section 2 introduces The key components of credit risk—default probability and loss severity—along with such credit-related risks as spread risk, credit migration risk, and liquidity risk. Section 3 discusses the relationship between credit risk and the capital structure of the firm. Section 4 addresses Credit ratings and the role of credit rating agencies. Section 5 focuses on the process of analyzing the credit risk of corporations. Section 6 examines the impact of credit spreads on risk and return. Section 7 presents special considerations applicable to the analysis of (i) high-yield (low-quality) corporate bonds and (ii) government bonds are presented. Section 8 gives a brief summary.