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Classification of Financial Markets

Posted on August 23, 2010 by admin

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.

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FINANCIAL ASSETS

Posted on August 13, 2010 by admin

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.

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PRINCIPLES FOR ENGINEERING A SUITE OF MODELS

Posted on July 24, 2010 by admin

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.

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