Optimal dealer pricing under transactions and return uncertainty

Ho, Thomas; Stoll, Hans R.

doi:10.1016/0304-405x(81)90020-9

Cited by 1,169 publications

(602 citation statements)

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“…Finally, Maudos and Solís (2009) combine the independently derived two-asset-type models and all other extensions into a single integrated model. 4 The dealership model of financial intermediation is adapted from pricing and risk management decisions of security dealers managing their inventory (Stoll, 1978;Ho and Stoll, 1981), where long and short positions of one and the same security necessarily have the same risk characteristics.…”

Section: Related Literaturementioning

confidence: 99%

Determinants of bank interest margins: Impact of maturity transformation

Entrop

Memmel

Ruprecht

et al. 2015

Journal of Banking & Finance

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This paper explores the extent to which interest risk exposure is priced in bank margins.Our contribution to the literature is twofold: First, we present an extended model of Ho and Saunders (1981) that explicitly captures interest rate risk and returns from maturity transformation. Banks price interest risk according to their individual exposure separately in loan and deposit rates, but reduce these charges when they expect returns from maturity transformation. Second, using a comprehensive dataset covering the German universal banks between 2000 and 2009, we test the model-implied hypotheses not only for the commonly investigated net interest income, but additionally for interest income and expenses separately.Controlling for earnings from bank-individual maturity transformation strategies, we find all banks to charge additional fees for macroeconomic interest volatility exposure. Microeco- Non-technical summaryBanks are intermediaries between investors and entrepreneurs. They transform long-term, illiquid and risky loans into safe deposits that are due within short notice. By doing so, they take risks, for which they are remunerated. Besides, they can generate income by making use of their market power and by setting their credit and deposit conditions accordingly. In a theoretical model, we show that the bank rates are set in accordance with the costs and earnings caused by the loans and deposits. In addition, banks levy premia for credit and interest rate risk, and for the access to the capital market. We derive the following empirically testable hypotheses:The margins on the asset side should be the higher, the stronger the market power, the more volatile the interest rates and the credit risk and the greater the exposure to interest rate risk.The model also predicts that banks smooth their interest rates (relative to the interest rates observed on the capital market). Accordingly, on the liability side, we expect the same factors to have an impact, expect for the credit risk, which is here not relevant. In an empirical study of all German universal banks for the period 2000 -2009, we obtain the following results:1. The statements derived from the theoretical model can be confirmed in our study, in particular we find that the higher the market power the higher the interest income margin and the lower the interest expense margin.2. The interest rate margins increase for all banks, in the event that the interest rates become more volatile. Additionally, for banks from the savings and credit cooperative sectors, we see the smoothing of bank rates that is predicted by the theoretical model. Nichttechnische Zusammenfassung

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Section: Related Literaturementioning

confidence: 99%

Determinants of bank interest margins: Impact of maturity transformation

Entrop

Memmel

Ruprecht

et al. 2015

Journal of Banking & Finance

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“…If quoted prices are constant, the market maker will be surely ruined. Amihud and Mendelson (1980) and Ho and Stoll (1981) resolve this problem by having the quoted bid-ask prices depend on the market maker's inventory of the traded security. Amihud and Mendelson assume a market maker who constrains his inventory position (due to capital constraint and risk) and manages inventory to avoid the constraints, and Ho and Stoll assume a risk-averse market maker who manages inventory to reduce his risk exposure.…”

Section: Illiquidity Deriving From Inventory Riskmentioning

confidence: 99%

Liquidity and Asset Prices

2005

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We review the theories on how liquidity affects the required returns of capital assets and the empirical studies that test these theories. The theory predicts that both the level of liquidity and liquidity risk are priced, and empirical studies find the effects of liquidity on asset prices to be statistically significant and economically important, controlling for traditional risk measures and asset characteristics. Liquidity-based asset pricing empirically helps explain (1) the cross-section of stock returns, (2) how a reduction in stock liquidity result in a reduction in stock prices and an increase in expected stock returns, (3) the yield differential between on-and off-the-run Treasuries, (4) the yield spreads on corporate bonds, (5) the returns on hedge funds, (6) the valuation of closed-end funds, and (7) the low price of certain hard-to-trade securities relative to more liquid counterparts with identical cash flows, such as restricted stocks or illiquid derivatives. Liquidity can thus play a role in resolving a number of asset pricing puzzles such as the small-firm effect, the equity premium puzzle, and the risk-free rate puzzle.

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“…While these papers are pioneering efforts, they share common limitations. First, the only 1 Liquidity is a concept used to capture the various explicit and implicit trading costs and it has many, and potentially overlapping dimensions arising from adverse selection (Kyle (1985), Glosten and Milgrom (1985)), inventory control (Stoll (1978), Grossman and Miller (1988), Ho and Stoll (1981)) and needs for immediate trading (Grossman and Miller (1988)). Broadly, it is used to describe the ease of trading a large amount of shares in a given amount of time without a significant impact on prices.…”

Section: Introductionmentioning

confidence: 99%