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    The simple empirical credit models

    Sunday, February 14th, 2010

    In the foregoing articles we have seen that in the short run, the prices of financial instruments may deviate from their fundamental value on account of microstructure frictions such as bid–ask bounce, inventory control and order imbalances. Previous article introduced empirical models for estimating transaction costs and the price impact of a trade. These models were quite simple: they assumed that the price impact of a trade was immediate. In reality, this is not always so, and there may be lagged effects or slow adjustments. We therefore need a richer dynamic structure in order to model prices and trades on financial markets. In this chapter, we introduce dynamic timeseries models for prices and trades, and show how they can be used to describe the market’s convergence on the new equilibrium price after a shock.

    This article extends the simple empirical models of Chapter 6 to a full dynamic setting. We show how time-series models for prices and trades can be used to study these questions. Throughout the chapter, we focus more on the structure and interpretation of the models than on the econometric and sampling issues that often arise in estimating dynamic time series using microstructure data. Section 9.1 introduces a dynamic model for prices and order flow, with lagged effects of order flow on prices and order-flow dynamics. Section 9.2 generalizes that model to the vector autoregressive model, which was introduced into microstructure by Hasbrouck (1988, 1991, 1993, 1995) and has since become the standard reference model in the literature. We then turn to a formal decomposition of prices into permanent and transitory components, where the permanent component is interpreted as the equilibrium value of the
    asset, or the efficient price. Section 9.3 examines price discovery, i.e. the process of convergence on the efficient price, and the role of order flow in this process. Section 9.4 studies price discovery for securities that are traded in multiple market-places. The appendix gives some tools for dealing with dynamic econometric models and lag polynomials.

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    Low default rates and tight credit spreads.

    Wednesday, November 11th, 2009

    A correlation between total returns of high yield and treasury bonds shows that interest rate risk can certainly not be neglected by high-yield investors. The mid-1990s serve as a good example. High yield and treasury returns had a quite high correlation in an environment of low default rates and tight credit spreads. In 2003 an increased correlation could be observed again when spreads were approaching historical lows and default rates were falling.

    High-yield sensitivity to interest rates is a function of credit risk. This means that the high-yield upper tier (BB/BB) segment’s correlation to 10-year treasuries is higher than for lower tier credit (B and below). Duration management in high-yield portfolios will have a positive performance contribution. Particularly crossover credits and BB’s total returns will be also determined by the movements of interest rates.

    During times of low default rates, historically tight spreads and low interest rates it is worthwhile to analyze the duration contribution of various sectors to the high-yield index. In a scenario of rising interest rates, sectors with tight spreads and a high average duration should be watched closely due to a high underperformance potential.

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    Whenever the credit risk premium falls

    Friday, October 30th, 2009

    Whenever the equity risk premium falls below current spread levels, there is a quasi-arbitrage opportunity between corporate bonds and equities. After a long period with a positive equity credit premium, the picture changed in 1999, signaling the height of the equity bubble. The interpretation of this was that expected returns on corporate bonds versus equities were extremely attractive. While corporate bonds actually outperformed equities by far between 2000 and 2002, those years were characterized by a massive widening of credit spreads. Due to the bursting of the tech bubble and the credit spread tightening since fall 2002, the gap has closed.

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    Credit and equity investors have different priorities

    Wednesday, October 21st, 2009

    Clearly credit and equity investors tend to look at the corporate sector from different angles. While the focus of equity markets is primarily on earnings growth, credit investors rely on debt-related factors to make their decisions. However, if one combines both perspectives the result is a stylized debt–equity cycle that may support both parties in the process of decision-making. The four phases of the cycle depend on the degree of earnings growth (high or low) and changes in leverage (rising or falling). Changes in leverage reflect the companies’ efforts to change their capital structure as well as their ability to generate cash flows. As an example we will examine the last complete debt–equity cycle that reached from 1991 to 2003.

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    Place stop-loss orders on your account.

    Monday, September 7th, 2009

    Cautious investors often place stop-loss orders on their account. These orders sell out your shares should they decline by the amount of pain you anticipate you are willing to endure. Stop-loss orders are supposed to make an unmanageable situation manageable. Brokers encourage this as stock fluctuations inevitably trigger sales creating more commissions and spreads.

    In a market break, the sell point may be much lower than the level you specify. For example, on a surprising corporate announcement, it is common for prices to gap down by $10 or more. Your stop loss may have only been down $2, but you will be sold out at the next trade, $10 lower. Of course, you always have the opportunity to buy back in again for more commissions and increasingly wide spreads. Stop-loss orders often lead to anger and frustration as an attempt to bring order to an unmanageable situation fails for you, yet enriches your broker.

    Brokerage accounts also offer you a “parking place” for your cash. These are sweep accounts: money market funds that collect dividends and the change leftover from trades. In the old days, dividend checks and change were sent to your home and you had the onerous task of depositing them in your checking account. The sweep accounts are marketed as a great convenience to you. In fact, they are a great convenience to your broker as they gather your funds within short distance of the trading desk. Again, particularly optimistic types should have the dividends sent home. Maybe there is only $1,000 at stake, but would you rather have a new couch to lie on during the bear market or would you prefer to whittle it away in commissions, spreads, and poor stock picks?

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    Building a Business Plan – part 2

    Monday, August 3rd, 2009

    The business plan offers general and specific guidance on reaching company goals. It outlines actions. It also separates the dreamers from the doers. It is often the great equalizer between the enthusiastic idea generators and the serious business people who will accomplish their dreams.

    Business plans are usually annual, based on the fiscal year. But there also are multiple-year plans—the most common of which is the five-year plan.

    An annual plan is operational and necessary to manage the company’s economic needs for the coming year. A five-year plan is more strategic and designed to chart the firm’s direction. In addition, five-year plans should be rolling plans.

    The thinking behind a rolling five-year plan can be applied to other cyclical planning, such as the annual budget process or the marketing schedule. When May ends, for example, the managers can study the forecasts for that month and the results, determine the reasons behind the variances, then use their findings to shape a budget for the following May. Rolling plans allow managers to make the most of their budget analyses, provide greater continuity, and ease the burden of annual planning.

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