Knowledge that Transforms

Abstract In this paper we present an analytical method in pricing European contingent assets, whose state variables follow a multi-dimensional Lévy process. We give an explicit formula for the hypothetical European “two-price” call option price by means of the conditiona characteristic transform. The work not only unifies and extends the option pricing literature, which focuses on the use of the characteristic function, but also provides the way to formalizeand unify the valuation of the option price, the valuation of the discount bond price, the valuation of the scaled-forward price, and the valuation of the pricing measure in incomplete markets. JEL Classification codes: G13

Abstract Using data from the Frankfurt Stock Exchange we analyze price formation and liquidity in a non-anonymous environment with similarities to the floor of the NYSE. Our main hypothesis is that the non-anonymity allows the specialist to assess the probability that a trader trades on the basis of private information. He uses this knowledge to price discriminate. This can be achieved by quoting a large spread and granting price improvement to traders deemed uninformed. Consistent with our hypothesis we find that price improvement reflects lower adverse selection costs but does not lead to a reduction in the specialist's profit. Further, the quote adjustment following transactions at the quoted bid or ask price is more pronounced than the quote adjustment after transactions at prices inside the spread. Our results indicate that anonymity comes at the cost of higher adverse selection risk. JEL Classification: G10.

Using an arbitrage approach,

Abstract Numerous psychological studies show that weather conditions affect people's mood and that mood states are correlated with people's subjective evaluation of future probabilities. In this paper, a new approach is developed and asset market data are employed to test the mood-subjective probability relation. Cloud cover and precipitation volume serve as two mood proxies. Our statistical analysis suggests that bad mood states are characterized by investors placing higher probabilities on adverse events. JEL classification codes: D81.

Abstract We consider the design and estimation of quadratic term structure models. We start with a list of stylized facts on interest rates and interest rate derivatives, classified into three layers: (1) general statistical properties, (2) forecasting relations, and (3) conditional dynamics. We then investigate the implications of each layer of property on model design and strive to establish a mapping between evidence and model structures. We calibrate a two-factor model that approximates these three layers of properties well, and show that a flexible specification for the market price of risk is important in capturing the stylized evidence in forecasting relations while factor interactions are indispensable in generating the hump-shaped dynamics of bond yields. JEL classification codes: G12, G13, E43.

Abstract Fama and French (1992) show that size and book-to-price dominate CAPM beta and other variables such as the price-earnings ratio and dividend yield in explaining the cross-section of US stock returns. Comparable evidence for the UK points to a book-to-price effect, but not a size effect (Chan and Chui, 1996; Strong and Xu, 1997). In this paper, our first contribution is to show that a measure of research and development (RD) helps explain cross-sectional variation in UK stock returns. Our cross-sectional results on the association between stock returns and RD are consistent with recent US evidence reported by Lev and Sougiannis (1996, 1999) and Chan, Lakonishok and Sougiannis (2001).Fama and French (1993, 1995, 1996) also show that a three-factor model captures a high proportion of the time series variation in portfolio returns, again for the US. Our second contribution is to show, for the UK, that a modification to the three-factor model to take account of RD activity can significantly enhance the explanatory power of the three-factor model. We show that, as a practical matter, estimated risk premia based on the modified three-factor model can differ considerably from risk premia estimated using the CAPM or the three-factor model. In particular, risk premia for industries in which few firms undertake RD activities tend to be over-estimated.

Abstract This paper analyzes the issue costs and initial pricing of bonds in the international market. In particular, we investigate the determinants of three components of issue costs: underwriter fee, underwriter spread (the difference between the offering price and the guaranteed price to the issuer), and underpricing (the difference between the market price and the offering price). Total underwriter compensation increases with the bonds’ credit risk and maturity, but it is insignificantly related to issue size. Interestingly, underwriters appear to price some issue characteristics directly (by adjusting the fee) and other characteristics indirectly (by setting the guaranteed price). The two compensation components (fee and spread) are negatively related to each other. We provide evidence that this trade-off is consistent with income tax considerations, as well as with two-tier pricing by underwriters. We find no evidence of underpricing. JEL classification codes: G12; G15; G24; G30

Abstract We present an approximation method for pricing and hedging American options written on a dividend-paying asset. This method is based on Kim (1990) equations. We demonstrate that a simple approximation of the Kim integral equations by quadrature formulas leads to an efficient and accurate numerical procedure. This approximation is accompanied by the Newton–Raphson iteration procedure in order to compute the optimal exercise boundary at each time point. The proposed sequence of approximations converges monotonically, convergence is fast and accuracy is high, even for long maturity options. We compare numerically our results with other competing approaches by different authors. JEL classification codes: G12, G13, C63.

Abstract Multiple delivery specifications exist on nearly all commodity futures contracts. Sellers are typically allowed to choose among several grades of the underlying commodity. On the delivery day, the futures price converges to the spot price of the cheapest-to-deliver grade rather than to that of the par-delivery grade of the commodity, thereby imposing an additional delivery risk on hedgers. This paper derives the optimal production and futures hedging strategy for a risk-averse competitive firm facing delivery risk. We show that the option value of the multiple delivery specification induces the firm to produce more with than without the delivery risk if the firm gauges this value higher than the market. We further show that if the delivery risk is additively related to the commodity price risk, the firm optimally under-hedges its risk exposure. On the other hand, if the delivery risk is multiplicatively related to the commodity price risk, the firm may optimally choose an under- or over-hedge which we illustrate using a numerical example. JEL classification codes: G11, D21, D81

Abstract This paper proposes a self-financing trading strategy that minimizes the expected shortfall locally when hedging a European contingent claim. A positive shortfall occurs if the hedger is not willing to follow a perfect hedging or a superhedging strategy. In contrast to the classical variance criterion, the expected shortfall criterion depends only on undesirable outcomes where the terminal value of the written option exceeds the terminal value of the hedge portfolio. Searching a strategy which minimizes the expected shortfall is equivalent to the iterative solution of linear programs whose number increases exponentially with respect to the number oftrading dates. Therefore, we partition this complex overall problem into several one-period problems and minimize the expected shortfall only locally, i.e., only over the next trading period. This approximation is quite accurate and the number of linear programs to be solved increases only linearly with respect to the number of trading dates. JEL Classifications: C61, G10, G12, G13, D81