In Glosten (1994), as well as in Viswanathan and Wang (2002) and Biais, Martimort and Rochet (2000), liquidity suppliers can only submit limit orders and liquidity demanders can only use market orders to hit the existing quotes; it follows that in these models agents are not allowed to choose between limit and market orders. In real markets, of course, at the very least the agents submitting orders to an LOB can choose between limit and market orders.
The choice between limit and market orders is a strategic element in any trading decision and depends on the relative probability of execution of the two orders, which in turn depends on a variety of factors, such as the asymmetry of the personal evaluations of the risky asset between the agents who submit the orders and those who hit the existing quotes, their degree of patience, their waiting costs and the state of the LOB. In the recent literature there are a few models for an LOB which embody the choice between market and limit orders; with the exception of Goettler, Parlour and Rajan (2008), in these early models there is no asymmetric information on the asset value.8 It is important, however, to understand the theory on the optimal traders’ submission strategies even when transaction costs are not due to informational asymmetries because there is evidence that non-informational frictions can be substantial; for example, Huang and Stoll (1997) show that on average they account for more than 80 per cent of the spread.
While in a single name context ratings are often criticized for being lagging indicators of credit quality, classifying bonds by rating is one widely used method to reflect the behavior of different risk classes in credit markets.
Many market participants argue that spreads themselves and spread volatilities are more timely indicators of an issuer’s credit risk than ratings. They consequently prefer to split the universe in spread class buckets. The disadvantage of this method is that it leads to relatively unstable compositions of the individual buckets and is less convenient, because the major index providers do not calculate indices based on spread classes. Since the different rating buckets constitute the corporate bond market as a whole, there is clearly a correlation between overall market fluctuations and the spread changes of the different rating subportfolios.
The tactical asset allocation in credit portfolios combines top-down- and bottom-up analyses in order to arrive at medium- to short-term investment decisions. In this step of the investment process three major subjects are tackled:
- Spread class selection,
- Sector allocation, and
- Credit curve positioning.
When making a decision about the allocation of resources to different spread classes, elements of the top-down analysis clearly have a substantial impact, since the assessment of the fundamental and technical environment for credit and the valuation relative to other asset classes have significant influence on the positioning within the credit asset class. Conversely, credit curve decisions are usually implemented on a sector or, probably even more frequently, on a single issuer basis. Although elements of the bottomup analysis clearly influence the positioning on the credit curve, there are also some economy-wide indicators that have to be considered. Therefore, and with respect to the time horizon of investment decisions and their potential impact on active portfolio performance, the three abovementioned issues should constitute an own step in a structured investment process for credit portfolios.
Also known as predicting cash outflow, the technique of playing the floats allows companies to predict the time it takes vendors to receive and process payments as a way to capitalize on company cash. As long as the company operates ethically, it won’t break any laws or get into any financial hot water.
Most businesses have three float options to consider: the mail float (between the time the accounting department posts payment and the time the vendor receives it), the vendor’s internal processing float, and the bank system float.
Have you ever been in a situation when the rent was due but your bank account was just a little low, so you sent out a check to pay your rent, figuring that you could get to the bank and deposit your paycheck a day or two later, before the bank processed the check? If so, then you were playing the float. What you might have done out of desperation, businesses do as a strategy for managing cash flow.
Playing the float can maximize cash disbursement, but those making that decision must be aware of possible changes that can affect that float, including a change in financial institutions or electronic payment patterns. The float could disappear overnight and your company may not realize it until it’s too late.
A good ACCOUNTS PAYABLE system can be used to forecast a payment schedule based on cash availability, anticipated income, and past policy practices. Then line up vendors in payment order, according to preference. Some will grumble, but the smart ones know they have little choice. If they don’t play along, it will take that much longer to be paid.
Vendors unhappy with your company’s payment policies won’t be vendors very long. Give preferred suppliers priority status and reward them with more prompt payment. They will likely return the favor with better service and more understanding if your company really gets into a bind.
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