Why take Practice Problems?

Taking practice problems is extremely important. By doing lots of practice problems you will be able to convert your knowledge into question answering ability, which is key to passing Level 1.

One should take as many practice problems as possible, however, be sure not to over-focus your time on taking practice problem such that you forgo a thorough reading reviewing of the material.

In order to develop adequate question answering abilities try doing the following: 

• Complete each practice problem at the end of each chapter.
• Immediately following completion of practice problems review incorrect problems and problems that you had a hard time with. The best way to review problems is to read over the solution then try to answer the problem again from scratch. This helps cement the solution.
• After finishing each book, take a sample test with questions only from that book. Save your practice exams, keeping track of what questions you got wrong and had a hard time with.
• After finishing your first read of the entire body of knowledge take at least two, six hour, timed, practice tests (mocks), to adequately prepare and simulate the actual exam. Review the questions you got wrong and had a hard time with.

Ethics practice questions:

• To prepare for the Ethics portion I recommend taking a disproportionately large amount of practice questions. There are lots of small and seemingly minor rules you will be tested on for Ethics that are easiest learned via taking practice problems. Try completing Ethics from CFAI Text books and focus well on understanding the examples before you take practice questions. 

Apple's Software Development Costs

The following snapshot is taken from Apple Inc.'s Form 10-K submitted to the SEC for fiscal year ended on September 24, 2011.












As I am now a days covering Financial Reporting and Analysis. While covering Reading 21 "Long-lived Assets: Implications for Financial Statement and Ratios" I went through the following

"Costs which are incurred to internally develop intangible assets are generally expensed not capitalized. However, there are some exceptions in IFRS & U.S.GAAP. For example:

Research & Development Costs:

• IFRS require that expenditures on research should be expensed as an intangible asset while the expenditure on development (provided certain criteria or met) should be capitalized.
• US. GAAP requires that research & development costs to be expensed. But there are some exceptions i.e. certain costs related to software development must be capitalized.
• Costs incurred to develop a software product for sale are expensed until the product's feasibility is established and capitalized after the product's feasibility has been established.
• Costs which are directly related to developing software for internal use i.e. costs of employees who help build and test the software can be capitalized.

Effects of expensing development costs:

• It results in lower Net Income in current period.
• It results in operating cash outflow.
• When development costs > amortization of prior periods' capitalized software development costs, expensing the software development costs will reduce Net Income."

After reading the extract and what I was studying in Reading 21, I was mesmerized. Though I have been mentioning and reading on a lot of platforms that the skills and knowledge which CFA develops are tremendous in terms of their relevance with the prevailing concepts and industry practices. The above coherence is not merely a co-incidence. Seeing the practical implications and application of the knowledge generates an inner drive and inculcates in me a new passion towards my learning and advancement with the Course. Form 10-K is a 106 pages document. There are a lot of areas which I have just covered and I saw those key terms being used in the document. I will share those in upcoming days. 

Where do most fund managers get their market information?

Many fund managers, whether they manage a mutual fund, trust fund, pension or hedge fund, have access to resources that the "average Joe" investor does not, but the type and quality of information generally remains the same for all investors. The information that managers use comes from publicly available information in the form of news releases, annual reports and filings with pertinent exchanges. Fund managers will most likely have a team of financial analysts using the latest software to analyze specific firms, markets and economic variables, who will make recommendations and forecasts on future prices and market trends.

Even though these fund managers have access to all of these resources, the conclusions they come to about any particular security or market are potentially no better than what a personal investor can do with a TV remote in one hand and a mouse in the other. The only difference between a fund manager and an individual investor is that the fund manager is highly trained and must adhere to a set of ethical standards.

Fund managers and most analysts go through a formal training process, which will most likely include a CFA designation issued by the CFA Institute. The CFA program involves three rigorous levels of standardized testing, but in order to enroll in the CFA program you must hold, at a minimum, a recognized university degree. Also, to retain a CFA designation, the holder must adhere to the Code of Ethics and Standards of Professional Conduct, or else they may be suspended or expelled from the CFA society. In addition to their education and experience, fund managers will also have a thorough understanding of macroeconomics, international trade and behavioral finance, to name a few. Although it is not necessary to hold a CFA to be a fund manager, it is encouraged.

Although a fund manager's experience and education may provide him or her with an edge, a fund manager's actions may not be as transparent as they should be. The manager may make investments that are contrary to the best interests of the investors of that particular fund. For example, a pension fund manager may leverage the fund to purchase a security (this kind of strategy is illegal is most instances), but the investor will not know the fund manager is doing this. In this scenario, the possibility of losses is greater than if the manager took a non-leveraged position.

Although fund managers are highly trained professionals, they still use the same publicly available information that all investors use, and the conclusions they come to are potentially no better than those achieved by any conscientious investor.

This question was answered by Matt Lee 


Source: http://www.investopedia.com/ask/answers/06/fundmanagerinfo.asp#ixzz1gxAAgqMZ

Home Equity Loans - Level II Fixed Income (ABS)

Autoregressive (AR) Models Time Series (Part B) - Quantitative Methods Level II

An Autoregressive model can be estimated using ordinary least squares model (OLS) when the time series is covariance stationary and the errors are uncorrelated.


Detecting Serial Correlation in AR models: In AR models, Durbin-Watson statistic can not be used to test serial correlation in errors. In such cases, t-test is used.

The autocorrelations of a time series refers to the correlations of that series with its own past values.
· When autocorrelations of the error term is zero, the model can be specified correctly.
· When autocorrelations of the error term is significantly different from zero, the model can
not be specified correctly.

T-statistics = Autocorrelations / Standard Error
Decision Rule: If | T-Statistics | > 2 then autocorrelations differ significantly from 0 thus the residuals are serially correlated and the model cannot be specified correctly.


Correcting Serial Correlation in AR Models: The serial correlation among the residuals in AR models can be removed by estimating an autoregressive model by adding more lags of the dependent variable as explanatory variables.

Financial Analyst Job Description

An extract from the article by Ujwal Deshmukh describing the job description of a financial analyst. For complete article please visit the link provided at the bottom. Note that the opinion expressed in the article is not endorsed by any authority.


Job Description of a Financial Analyst
Apart from the aforementioned duties, there are many other responsibilities that are included in the job description of financial analysts. Some of them are mentioned below. The core job of any financial analyst involves:

• General analysis of finance reports obtained from various departments such as sales, marketing, purchase, production, communication, etc.
• Preparing reports on their research and making important suggestions on investments for companies as well as individuals
• Determining, planning and foreseeing marketing activities
• Developing new and effective techniques for financial planning, thereby rendering better service to clients
• Reading financial statements of the organization and taking into consideration the sales, expenses and production cost to recommend investments and forecast future earnings of the organization
• Keeping a tab on the latest trends and techniques in the field of financial analysis
• Coordinating with higher management officials of their own as well as other departments, to report the progress and changes, if any
• Assessing other company's performance, to decide and advice the best company to invest in
• Handling audits and working for client information support services
• Hard-core analysis, fact verification, study and research (junior financial analyst job description)
• Planning and decision-making on financial analysis (senior financial analyst job description)
• Making use of spreadsheets and different statistical software to analyze the facts of their report.

Complete article can be accessed through

http://www.buzzle.com/articles/financial-analyst-job-description.html

New warning over exchange traded funds

An overview of ETFs is given in Study Session 18, Alternate Investments of the CFA Level I Curriculum. A video regarding what ETFs are has already been posted on the blog. Below is the article written in The Guardian UK, source provided at the bottom, discusses ETFs. Basic understanding of such Funds helps a lot in understanding the terminologies discussed in the article.

Stockbroker Williams De Broë has launched a stinging attack against exchange traded funds (ETFs), calling for regulators to ban the sale of more complex ETFs to retail investors. The broker also warns the proliferation of such funds over the last decade could "severely exacerbate" a market downturn.

ETFs have become a trillion-dollar-plus trading instrument allowing investors to bet on the rise or fall in price of a vast range of commodities, indices and currencies without actually having to buy the assets themselves. But De Broë's head of research, Jim Wood-Smith, said: "ETFs could pose a significant danger to investors at times of high market volatility. We welcome the increased attention regulators are paying to these products, which remain relatively untested."

He is particularly worried by so-called "synthetic" ETFs, which instead of tracking an index such as the FTSE or a basket of commodities, use derivatives to gain exposure, with risks passed on to third parties. Wood-Smith says: "These contracts are not as transparent as we would wish, and there is a danger counterparties could go bust. I am not sure investors realise the risks involved."

Wood-Smith joins veteran trader Terry Smith, head of broker Tullett Prebon, who has compared ETFs to the toxic financial instruments that a played a catastrophic role in the credit crunch, and said the City had failed to learn any lessons.

De Broë has recently stopped selling ETFs to all but the most sophisticated of its private clients. Wood-Smith believes the regulator should step in and ban the sale of some ETFs to private shareholders because many are too opaque.

Some ETFs must sell underlying assets if prices fall by a certain amount, which raises the possibility of a "vicious spiral of programmed selling, with frightening consequences," according to one observer.

Terry Smith said: "ETFs are being mis-sold to the retail market and the risks being incurred in running, constructing, trading and holding them are not sufficiently understood."

And in a blogpost earlier this year entitled "ETFs –you were warned", he said that although many investors regard ETFs as being identical to relatively low-risk index trackers, in reality, many are no more than bets, with hedge funds and banks placing huge bets against ETFs – in some instances 10 times the size of the fund itself. "What if such ETF trades cause such a mammoth loss in a counterparty which does not have sufficient capital to bear the loss and pay out under the derivative contract? Answer – the ETF will fail," he wrote.

In simple terms, the aim of an ETF is to replicate the performance of a market in a single share. The share tracks a sector, an index, or the price of a commodity or currency, and can offer retail investors exposure to commodities such as gold or oil that they may find difficult to achieve in other ways. The charges are relatively low, but in recent years many ETFs have become increasingly complex.

The newly-established Financial Stability Board, chaired by Bank of England governor Sir Mervyn King, expressed concern about ETFs in an interview with the BBC. King said: "We have said very clearly ... we want the regulator to look carefully at [some types of ETFs] in order to monitor whether certain aspects of this use of the funds invested in ETFs are being directed towards opaque and complex funding structures." The Financial Services Authority is conducting its own review.

Wood-Smith warns: "2012 will be another year of 'spectacular' market moves, driven in part by the increasing influence of ETFs and other similar products. ETFs allow larger and more frequent short-term trading to occur. This can and now does happen in a matter of minutes, rather than days or weeks.

"Regulators talk of attempting to control some of the more esoteric and complex structures behind these funds, but this will not change the nature of the beast."

Before ETFs came along investors who wanted exposure to an index such as the FTSE 100 had to buy a tracker fund, which typically come with high management charges. ETFs allowed people to buy just one share that would track the market and which was easier and cheaper to buy and sell. Deutsche Bank says the $1 trillion industry has grown by 40% since 2001.

Critics say there are fewer problems with plain "vanilla" ETFs that actually own underlying assets. "Synthetic' ETFs are riskier as they often use complex futures or derivatives to track prices that can fluctuate wildly. The ultimate owners of synthetic funds could be hedge funds that might go bust, leaving the investor out of pocket in a worst case scenario.

Richard Wachman

Source: "http://www.guardian.co.uk/business/2011/dec/15/exchange-traded-funds-warning"

Preparation Material Providers for CFA - A Comparison

Prep. Notes Provider	Level I	Level II	Level III
7 City	-	-	-
	Test Bank	Test Bank	Test Bank
	Video Lectures	Video Lectures	Video Lectures
BPP	-	-	-
	Test Bank	Test Bank	Test Bank
	Video Lectures	Video Lectures	Video Lectures
Elan Guides	Study Notes	-	-
	Test Bank	-	-
	Video Lectures	-	-
FinQuiz	-	Study Notes	Study Notes
	-	Test Bank	Test Bank
	-	-	-
Kaplan Schweser	Study Notes	Study Notes	Study Notes
	Test Bank	Test Bank	Test Bank
	Video Lectures	Video Lectures	Video Lectures

Note:

·         Study Notes refer to complete Study guides that can act as an alternative to the CFA Text not additional material like graphs, charts, summaries etc.

·         Providers with complete study material, for whole curriculum, are included in the comparison e.g. Elan Guides they are offering some material for Level II but it is not complete.

Exchange Traded Funds

Auto Regressive (AR) Time Series Models (Part A)

An autoregressive (AR) model is a time series regression in which the independent variable is a lagged (past) value of the dependent variable i.e.

x_t = b₀ + b₁ x _t-1 + ε_t

First order autoregressive AR (1) for the variable x is:

x_t = b₀ + b₁ x _t-1 + ε_t

Nth order autoregressive AR (n) for the variable x is:

x_t = b₀ + b₁ x _t-1 + b₂ x _t-2 ……. b_n x _t-n + ε_t

Covariance Stationary Series

Time series must be co-variance stationary for valid statistical inference. Time series is co-variance stationary when:

1. The expected value of the time series is constant and finite in all periods
2. The variance of time series is constant and finite in all periods
3. The covariance of the time series with past or future values of itself is constant and finite in all periods

Data is said to be stationary when time series variable do not exhibit any significant upward or downward trend over time whereas when time series variable does exhibit significant upward or downward trend it is said to be Non-stationary data.

Consequences of Covariance Non-Stationary

Regression results are invalid when time series is not covariance stationary. This is due to the following reasons.

1. The “t-ratios” will not follow a t-distribution
2. The estimates of b₁ will be biased and any hypothesis tests will be invalid

It is important to note that stationary in the past does not guarantee that the results will be stationary in the future too. Consequences may change with the passage of time.