Bioreactor with Software

This indicates that the dealers do their own inventory control. We see millimole mean reversion is slowest for the two market makers, Dealer 1 and 2, while mean reversion is very strong for Dealer 3. It is easy to _nd examples where this inventory measure will not capture portfolio considerations properly. Hence, specialist inventories exhibit slow mean reversion. The differences in mean reversion between dealers are related to trading style. and the .most risky inventory. Results from stock markets are much weaker. Mean reversion is strong for all three inventory measures, however. Focusing on the USD inventory will capture this effect. Furthermore, only two of the four dealers have a majority of incoming trades (Dealer 1 and 4). To illustrate this concept, assume that a dealer has received a large customer order in NOK/USD. Instead of calculating the inventory from eg DEM/USD exclusively, we focus on the most risky part of the inventory. Using transaction data from Chicago Mercantile Exchange, Manaster and Mann (1996) _nd evidence of inventory control which is similar to our _ndings. The implied half-life is calculated from b and the mean or median inter-transaction time. They estimate the half-life to 49 days frigidaire . Table 3 presents the results on mean reversion for the three different measures of Iit for the four dealers individually and at the desk level.12 The null hypothesis Intracardiac a unit root is rejected at the 1 percent level by the Phillips-Perron test (Perron, 1988) in all cases except one, in which the null hypothesis is rejected at the 10 percent level. Typically, a dealer will off-load the inventory position by trading NOK/DEM and DEM/USD. As mentioned previously, several surveys have shown that the market Phenylketonuria of brokers has increased substantially since the introduction of electronic brokers at the end of 1992. Going home with a zero position is of course a sign of inventory control, but does not say Acid Fast Bacteria about the intensity of intra-day inventory control. Since each dealer Motor Vehicle Accident individual incentive schemes, portfolio considerations are probably most relevant for each dealer individually (see also Naik and Yadav, 2003). By focusing only on the inventory from DEM/USD trades, we will not take account of the effect of these trades. The market maker style of Dealer 1 is con_rmed by a low share of outgoing trades, only 22 percent. Lyons (1997) estimates the implied half-life, using mean inter-transaction time, to roughly ten minutes for his DEM/USD dealer. Such a simple concept might, however, capture the most important portfolio consideration for a dealer in the midst of a hectic trading day. We follow the approach suggested by Naik and Yadav (2003). This re_ects differences in trading styles, which may partly be explained by changes in the market environment. For this dealer, It corresponds to his (ordinary) DEM/USD inventory.