Financial domain

The Stock Market continues to Rally

admin — Fri, 03 Dec 2010 15:10:57 +0000

The stock market may be a little volatile in recent years, but we are finally seeing it improve enough that individuals are beginning to invest in various stocks again. It is true the stock market can be down one day and up the next; however, it is holding steady over 10000 on the DOW Jones. It is climbing more towards 12000 each week. It may be a slow progression, but the DOW has held onto 11000 for the last month.

The question is, what affects the stock market enough to have it lowering below the 11000 mark? There are sometimes when it has done this in past weeks, even after finally making it above the next mark. In part the stock market is affected by the news released. Certain news stories can send the stocks plummeting, whereas others will send it up again. However, in recent weeks the stock market DOW has increased mostly as a result of a better economy. Consumers and business owners are starting to get their faith back.

Though some news has worried about another recession, it seems that many consumers and other investors would rather this did not happen. With Christmas just around the corner there is also optimism of a better year for 2011.

Other things can affect the DOW as well, such as new products to hit the market. Apple is a good example and how their stock increased with the announcement of the Apple iPad. Netflix has been another stock to climb very high this year. It is likely to continue, but the greatest jumps for the stock have most likely occurred in the past six months.

Anyone who wants to invest a little of their savings into the stock market will need to look at the upcoming year, what new products might be released, and the overall feelings of the economy for the next year. It is important that anyone investing in the stock market do so with savings rather than taking out a loan.

In the past some individuals have taken equity out of their home to invest in the stock market. Others have looked for discount payday loans to get them started. This kind of practice can end up hurting you and your investments because if you lose you still have to pay the loans back, only now you do not have the prospects of being able to pay it immediately.

Qualifications: Competition and property rights

admin — Tue, 05 Oct 2010 16:46:20 +0000

Our focus so far has been on markets where rival firms can freely enter and exit, and private-property rights are clearly defined and enforced. The efficiency of market organization is, in fact, dependent on these two things: (1)competitive markets and (2)well-defined and enforced private-property rights.
Competition, the great regulator, can protect both buyer and seller. It protects consumers from sellers who would charge a price substantially above the cost of production or withhold a vital resource for an exorbitant amount of money. Similarly, it protects employees (sellers of their labor) from the power of any single employer (the buyers of labor). Competition equalizes the bargaining power between buyers and sellers.
When property rights are well defined, secure, and tradable, suppliers of goods and services have to pay resource owners for their use. They will not be permitted to seize and use scarce resources without compensating the owners. Neither will they be permitted to use violence (for example, to attack or invade the property of another) to get what they want. The efficiency of markets hinges on the presence of property rights – after all, people can’t easily exchange or compete for things they don’t have or can’t get property rights to. Without well-defined property rights, markets simply cannot function effectively.

Economic Functions of Financial Markets

admin — Fri, 03 Sep 2010 16:34:09 +0000

The two primary economic functions of financial assets were already dis- cussed. Financial markets provide three additional economic functions.
First, the interactions of buyers and sellers in a financial market determine the price of the traded asset; or, equivalently, the required return on a financial asset is determined. The inducement for firms to acquire funds depends on the required return that investors demand, and this feature of financial markets signals how the funds in the economy should be allocated among financial assets. It is called the price discovery process. Whether these signals are correct is an issue that we discuss when we examine the question of the efficiency of financial markets.
Second, financial markets provide a mechanism for an investor to sell a financial asset. This feature offers liquidity in financial markets, an attractive characteristic when circumstances either force or motivate an investor to sell. In the absence of liquidity, the owner must hold a debt instrument until it matures and an equity instrument until the company either voluntarily or involuntarily liquidates. Although all financial markets provide some form of liquidity, the degree of liquidity is one of the factors that differentiates various markets.
The third economic function of a financial market reduces the search and information costs of transacting. Search costs represent explicit costs, such as the money spent to advertise the desire to sell or purchase a financial asset, and implicit costs, such as the value of time spent in locating a counterparty. The presence of some form of organized financial market reduces search costs. Information costs are incurred in assessing the investment merits of a financial asset, that is, the amount and the likelihood of the cash flow expected to be generated. In an efficient market, prices reflect the aggregate information collected by all market participants.

Classification of Financial Markets

admin — Mon, 23 Aug 2010 16:33:04 +0000

There are five ways that one can classify financial markets: (1) nature of the claim, (2) maturity of the claims, (3) new versus seasoned claims, (4) cash versus derivative instruments, and (5) organizational structure of the market.
The claims traded in a financial market may be either for a fixed dollar amount or a residual amount and financial markets can be classified according to the nature of the claim. As explained earlier, the former financial assets are referred to as debt instruments, and the financial market in which such instruments are traded is referred to as the debt market. The latter financial assets are called equity instruments and the financial market where such instruments are traded is referred to as the equity market or stock market. Preferred stock represents an equity claim that entitles the investor to receive a fixed dollar amount. Consequently, preferred stock has in common characteristics of instruments classified as part of the debt market and the equity market. Generally, debt instruments and preferred stock are classified as part of the fixed income market.
A second way to classify financial markets is by the maturity of the claims. For example, a financial market for short-term financial assets is called the money market, and the one for longer maturity financial assets is called the capital market. The traditional cutoff between short term and long term is one year. That is, a financial asset with a maturity of one year or less is considered short term and therefore part of the money market. A financial asset with a maturity of more than one year is part of the capital market. Thus, the debt market can be divided into debt instruments that are part of the money market, and those that are part of the capital market, depending on the number of years to maturity. Because equity instruments are generally perpetual, a third way to classify financial markets is by whether the financial claims are newly issued. When an issuer sells a new financial asset to the public, it is said to “issue” the financial asset. The market for newly issued financial assets is called the primary market. After a certain period of time, the financial asset is bought and sold (i.e., exchanged or traded) among investors. The market where this activity takes place is referred to as the secondary market. Some financial assets are contracts that either obligate the investor to buy or sell another financial asset or grant the investor the choice to buy or sell another financial asset. Such contracts derive their value from the price of the financial asset that may be bought or sold. These contracts are called derivative instruments and the markets in which they trade are referred to as derivative markets. The array of derivative instruments includes options contracts, futures contracts, forward con- tracts, swap agreements, and cap and floor agreements.
Although the existence of a financial market is not a necessary condition for the creation and exchange of a financial asset, in most economies financial assets are created and subsequently traded in some type of organized financial market structure. A financial market can be classified by its organizational structure. These organizational structures can be classified as auction markets and over-the-counter markets.

FINANCIAL ASSETS

admin — Fri, 13 Aug 2010 16:31:29 +0000

Reversibility, also called round-trip cost, refers to the cost of investing in a financial asset and then getting out of it and back into cash again. For financial assets traded in organized markets or with “market makers,” the most relevant component of round-trip cost is the so- called bid-ask spread, to which might be added commissions and the time and cost, if any, of delivering the asset. The bid-ask spread consists of the difference between the price at which a market maker is willing to sell a financial asset (i.e., the price it is asking) and the price at which a market maker is willing to buy the financial asset (i.e., the price it is bid- ding). The spread charged by a market maker varies sharply from one financial asset to another, reflecting primarily the amount of risk the market maker assumes by “making” a market. This market-making risk can be related to two main forces.
One is the variability of the price as measured, say, by some measure of dispersion of the relative price over time. The greater the variability, the greater the probability of the market maker incurring a loss in excess of a stated bound between the time of buying and reselling the financial asset. The variability of prices differs widely across financial assets. The second determining factor of the bid-ask spread charged by a market maker is what is commonly referred to as the thickness of the market, which is essentially the prevailing rate at which buying and selling orders reach the market maker (i.e., the frequency of transactions). A “thin market” sees few trades on a regular or continuing basis. Clearly, the greater the frequency of orders coming into the market for the financial asset (referred to as the “order flow”), the shorter the time that the financial asset must be held in the market maker’s inventory, and hence the smaller the probability of an unfavorable price movement while held. Thickness also varies from market to market. A low round-trip cost is clearly a desirable property of a financial asset, and as a result thickness itself is a valuable property. This attribute explains the potential advantage of large over smaller markets (economies of scale), and a market’s endeavor to standardize the instruments offered to the public.
The term to maturity, or simply maturity, is the length of the interval until the date when the instrument is scheduled to make its final payment, or the owner is entitled to demand liquidation. Maturity is an important characteristic of financial assets such as debt instruments. Equities set no maturity and are thus a form of perpetual instrument. Liquidity serves an important and widely used function, although no uniformly accepted definition of liquidity is presently available. A useful way to think of liquidity and illiquidity, proposed by James Tobin, is in terms of how much sellers stand to lose if they wish to sell immediately against engaging in a costly and time consuming search.2 Liquidity may depend not only on the financial asset but also on the quantity one wishes to sell (or buy). Even though a small quantity may be quite liquid, a large lot may run into illiquidity problems. Note that liquidity again closely relates to whether a market is thick or thin. Thinness always increases the round-trip cost, even of a liquid financial asset. But beyond some point it becomes an obstacle to the formation of a market, and directly affects the illiquidity of the financial asset.
An important property of some financial assets is their convertibility into other financial assets. In some cases, the conversion takes place within one class of financial assets, as when a bond is converted into another bond. In other situations, the conversion spans classes. For example, with a corporate convertible bond the bondholder can change it into equity shares. Most financial assets are denominated in one currency, such as U.S. dollars or yen or euros, and investors must choose them with that feature in mind. Some issuers have issued dual-currency securities with certain cash flows paid in one currency and other cash flows in another currency.
The return that an investor will realize by holding a financial asset depends on the cash flow expected to be received, which includes dividend payments on stock and interest payments on debt instruments, as well as the repayment of principal for a debt instrument and the expected sale price of a stock. Therefore, the predictability of the expected return depends on the predictability of the cash flow. Return predictability, a basic property of financial assets, provides the major determinant of their value. Assuming investors are risk averse, as we will see in later chapters, the riskiness of an asset can be equated with the uncertainty or unpredictability of its return.
An important feature of any financial asset is its tax status. Govern- mental codes for taxing the income from the ownership or sale of financial assets vary widely if not wildly. Tax rates differ from year to year, country to country, and even among municipalities or provinces within a country. Moreover, tax rates may differ from financial asset to financial asset, depending on the type of issuer, the length of time the asset is held, the nature of the owner, and so on.

PRINCIPLES FOR ENGINEERING A SUITE OF MODELS

admin — Sat, 24 Jul 2010 16:27:06 +0000

Creating a suite of models to satisfy the needs of a financial firm is engineering in full earnest. It begins with a clear statement of the objectives. In the case of financial modeling, the objective is identified by the type of decision-making process that a firm wants to implement. The engineering of a suite of financial models requires that the process on which decisions are made is fully specified and that the appropriate information is sup- plied at every step. This statement is not as banal as it might seem.
We have now reached the stage where, in some markets, financial decision–making can be completely automated through optimizers. As we will see in the following chapters, one can define models able to construct a conditional probability distribution of returns. An optimizer will then translate the forecast into a tradable portfolio. The manager becomes a kind of high-level supervisor of an otherwise automated process.
However, not all financial decision-making applications are, or can be, fully automated. In many cases, it is the human operator who makes the decision, with models supplying the information needed to arrive at the decision. Building an effective suite of financial models requires explicit decisions as to (1) what level of automation is feasible and desirable and (2) what information or knowledge is required.
The integration of different models and of qualitative and quantitative information is a fundamental need. This calls for integration of different statistical measures and points of view. For example, an asset management firm might want to complement a portfolio optimization methodology based on Gaussian forecasting with a risk management process based on Extreme Value Theory . The two processes offer complementary views. In many cases, however, different methodologies give different results though they work on similar principles and use the same data. In these cases, integration is delicate and might run against statistical principles.
In deciding which modeling efforts to invest in, many firms have in place a sophisticated evaluation system. “We look at the return on investment [ROI] of a model: How much will it cost to buy the data necessary to run the model? Then we ask ourselves: What are the factors that are remunerated? Our decision on what data to buy and where to spend on models is made in function of what indicators are the most ‘remunerated,’” commented the head of quantitative management at a major European asset management firm.

INTEGRATING QUALITATIVE AND QUANTITATIVE INFORMATION

admin — Wed, 14 Jul 2010 16:23:09 +0000

Textual information has remained largely outside the domain of quantitative modeling, having long been considered the domain of judgment. This is now changing as financial firms begin to tackle the problem of what is commonly called information overload; advances in computer technology are again behind the change.
Reuters publishes the equivalent of three bibles of (mostly financial) news daily; it is estimated that five new research documents come out of Wall Street every minute; asset managers at medium-sized firms report receiving up to 1,000 e-mails daily and work with as many as five screens on their desk. Conversely, there is also a lack of “digested” information. It has been estimated that only one third of the roughly 10,000 U.S. public companies are covered by meaningful Wall Street research; there are thousands of companies quoted on the U.S. exchanges with no Wall Street research at all. It is unlikely the situation is better relative to the tens of thousands of firms quoted on other exchanges throughout the world. Yet increasingly companies are providing information, including press releases and financial results, on their Web sites, adding to the more than 3.3 billion pages on the World Wide Web as of mid-2003.
Such unstructured (textual) information is progressively being transformed into self-describing, semistructured information that can be automatically categorized and searched by computers. A number of developments are making this possible. These include:
The development of XML (eXtensible Markup Language) standards for tagging textual data. This is taking us from free text search to queries on semi-structured data.
The development of RDF (Resource Description Framework) standards for appending metadata. This provides a description of the content of documents.
The development of algorithms and software that generate taxonomies and perform automatic categorization and indexation.
The development of database query functions with a high level of expressive power.
The development of high-level text mining functionality that allows “discovery.”
The emergence of standards for the handling of “meaning” is a major development. It implies that unstructured textual information, which some estimates put at 80% of all content stored in computers, will be largely replaced by semistructured information ready for machine handling at a semantic level. Today’s standard structured data- bases store data in a prespecified format so that the position of all elementary information is known. For example, in a trading transaction, the date, the amount exchanged, the names of the stocks traded and so on are all stored in predefined fields. However, textual data such as news or research reports, do not allow such a strict structuring. To enable the computer to handle such information, a descriptive metafile is appended to each unstructured file. The descriptive metafile is a structured file that contains the description of the key information stored in the unstructured data. The result is a semistructured database made up of unstructured data plus descriptive metafiles. Industry-specific and application-specific standards are being developed around the general-purpose XML. At the time of this writing, there are numerous initiatives established with the objective of defining XML standards for applications in finance, from time series to analyst and corporate reports and news. While it is not yet clear which of the competing efforts will emerge as the de facto standards, attempts are now being made to coordinate standardization efforts, eventually adopting the ISO 15022 central data repository as an integration point.
Technology for handling unstructured data has already made its way into the industry. Factiva, a Dow Jones-Reuters company, uses commercially available text mining software to automatically code and categorize more than 400,000 news items daily, in real time (prior to adopting the software, they manually coded and categorized some 50,000 news articles daily). Users can search the Factiva database which covers 118 countries and includes some 8,000 publications, and more than 30,000 company reports with simple intuitive queries expressed in a language close to the natural language. Suppliers such as Multex use text mining technology in their Web-based research portals for clients on the buy and sell sides. Such services typically offer classification, indexation, tagging, filtering, navigation, and search.
These technologies are helping to organize research flows. They allow to automatically aggregate, sort, and simplify information and provide the tools to compare and analyze the information. In serving to pull together material from myriad sources, these technologies will not only form the basis of an internal knowledge management system but allow to better structure the whole investment management process. Ultimately, the goal is to integrate data and text mining in applications such as fundamental research and event analysis, linking news, and financial time series.

Optimization

admin — Mon, 05 Jul 2010 17:09:45 +0000

For a given exchange rate view, an optimization model can create an “efficient frontier” of hedging strategies to manage currency risk. The most efficient hedging strategy is that which is the cheapest for the most risk hedged. This is a very efficient and useful tool for hedging currency risk in a more sophisticated way than just buying a vanilla hedge and “hoping” that it is the appropriate strategy. Hedging optimizers frequently compare the following strategies to find the optimal one for the given currency view and exposure:
100% hedged using vanilla forwards
100% unhedged
Option risk reversal
Option call spread
Option low-delta call

Key Operational Controls for Treasury

admin — Sun, 04 Jul 2010 17:09:06 +0000

Assuming that the corporation has accepted in principle that it needs to manage its currency risk, it then has several choices to make with regard to how it will go about achieving this — the instruments it will allow itself to use, the type of currency hedging carried out, positional and credit limits and so forth. All of these matters need to be dealt with in a systematic and rigorous way at the start, before the currency hedging programme begins. Performance measurement standards, accountability and limits of some form must be part of a Treasury foreign currency hedging programme. Management must elucidate specifically the goals and the operational limits of such a programme.

Internal Hedging

admin — Fri, 02 Jul 2010 17:08:25 +0000

There are of course well-known methods of hedging internally, such as:
Netting (debt, receivables and payables are netted out between group companies)
Matching (intragroup foreign currency inflows and outflows)
Leading and lagging (adjustment of credit terms before and after due date)
Price adjustment (raising/lowering selling prices to counter exchange rate moves)
Invoicing in foreign currency (thus reducing transaction risk)
Asset and liability management (to manage balance sheet, income, cash flow risk)