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Results 21 - 30
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Table 1 Introduction Dates for Energy Derivative Contracts
"... In PAGE 7: ...ng on the crude oil market. Section VI provides a summary and conclusions. II. Data and Preliminary Analysis Table1 lists the primary energy futures and futures option contracts , along with their respective introduction dates. Each of these contracts is traded at either the New York Mercantile Ex- change (NYMEX) or the International Petroleum Exchange (IPE).... In PAGE 19: ...following the first derivative introduction and they should decay with subsequent introduc- tions as the market gradually becomes more complete. To investigate these issues, we apply our methodology to each of the subsequent i n tro- duction dates reported in Table1 . The only difference is that each of these introductions occurs after the start of our daily crude oil price series, so we use the daily prices ( rather than weekly) in this analysis.... ..."
Table 8 Regression of Unexpected Spot Volatility on Futures Volume and Open Interest
"... In PAGE 21: ... B. Volume-Volatility and Open Interest-Volatility Relations The first set of columns in Table8 reports the regression results for the raw trading activity series over the full sample. The raw series are scaled so the underlying unit is one million futures contracts.... In PAGE 23: ... Again, after taking logs, we decompose each s e ries into its expected and unexpected components. The regression results are reported in the second set of columns of Table8 . For the most part, these results are quite similar to those for the raw series.... ..."
Table 3. Coffee C futures volume migration?
"... In PAGE 16: ... Note that this is substantially more than the 429 limit contracts in Table 2. The difference occurs because of multiple effective limit spells that are counted as a single limit contract in Table 2, but counted separately for the purposes of Table3 . Interestingly, Table 3 indicates that futures volume does not completely disappear during effective limit episodes.... In PAGE 16: ...edian is 0.14 per minute against the standardized phantom limit median of 5.69 per minute. A considerable drop in futures volume is associated with limit episodes. As to the question of whether option volume picks up where futures volume drops off, consider the lower part of Table3 . Most strikingly, unlike futures volume, an expanded count measure for phantom limit options volume was not needed.... ..."
Table 5. Preliminary e-contracting implementation scenarios at RS
"... In PAGE 8: ... Additionally, RS has a public key infrastructure already in place and recently started initatives to support the dissemination of digital certificates among its suppliers in parallel projects. The evaluation sketched above led to the three different implementation scenarios illustrated in Table5 , which will be assessed in more detail during the future course of the project. ... ..."
Table 3: Summary of the optimal choice of protocols for each agent and each parameterization. Conclusions In automated negotiation systems with self-interested agents it has traditionally not been possible to breach accepted contracts. Because of that, the agents have been lacking the ability to act e ciently in a dynamic environment, since they cannot accommodate future
1998
"... In PAGE 6: ... The method that considers the current pro t performs well for low penalties with the deterministic protocols, while the method based on the fallback positions per- forms well in the case of low penalties and a stochastic protocol. Comparison of Methods and Parameterizations of Setting the Decommitment Penalty A summary of the protocol that achieved the lowest ratio bound for each agent is found in Table3 . Two sets of best protocols are extracted, one among the stochastic protocols and one among the deterministic protocols.... ..."
Cited by 47
Table 3.1 Combinations of estimators and variance estimation techniques used in the simulation study, with the packages which have been used. * variance estimation uses weights in a manner which is not strictly valid (see section 2.2.4); + valid variances can be produced but only by using the software in a non-standard way (see section 2.2.4). The simulation process has turned out to be a long one, and not all of the results obtained are presented here; instead we concentrate on the main messages to have emerged. Some of the results presented here seem to lack internal consistency, and on the whole it seems that the whole area will benefit from further detailed study in the future. It is hoped that the study will continue past the end of the present contract.
Table 1: Solution time (in seconds) and number of iterations for tests problems on IBM cluster. %CPU is the ratio between the CPU time spent for the solution part (reported in the rst column) and the total elapsed time during the execution of the whole program Acknowledgements This work presents research results of the Belgian Incentive Program \Information Technology quot; - Computer Science of the future, initiated by the Belgian State - Prime Minister apos;s Service - Federal O ce for Scienti c, Technical and Cultural A airs (Contract No. IT/IF/14). The Scienti c responsability is assumed by its author. This work was also supported by IBM through a research contract between ULB and IBM.
Table 7 Summary Statistics for Daily Crude Oil Futures Trading Activity and Spot Volatility Estimates
"... In PAGE 20: ... We focus on the effect of this variability. Table7 provides summary statistics for daily futures trading activity and spot volatility. The volume and open interest data represent aggregate amounts across all open NYMEX crude oil contracts and the spot prices are for WTI sweet Cushing crude oil.... In PAGE 20: ...9853) are similar to those reported in Table 3 for the WTI near price series with 40 lags. The returns and volatilities reported in Table7 exhibit the same general patterns as those for the WTI near series reported in Table 2. The volume and open interest statistics show the rapid growth in oil ... In PAGE 23: ...C. Robustness Checks The summary statistics reported in Table7 suggest some evidence of nonstationarity in the volume and open interest series across our sample. Figure 4 shows the daily volume (Panel A) and open interest (Panel B) over this period, revealing a pattern of increasing variance in both series.... ..."
Table 6 Crude Oil Volatility After the Introduction of Other Energy Derivative Contracts
"... In PAGE 19: ... Finally, we evaluate the signifi- cance of the h t realizations during the period following the introduction date. Table6 reports the result s. 15 The Model Parameters columns in Panel A contain the GMM parameter estimates of our model for each of the introduction dates.... In PAGE 19: ... This is inconsistent with the directional effect for crude oil futures, although the evidence here is less conclusive. 15 Table6 does not include results for the introduction of natural gas options because our GMM approach does not converge for lag lengths of l = 10, 20, 30, or 40. A possible explanation for this is the small sample size.... In PAGE 20: ...The introduction effects are even less apparent for the other introduction dates examined in Table6 . Few of the average or realized volatilities for these introductions are si g nificantly different from what we expect.... ..."
Table 8. Rate of Change of the 10% VaR for hedge triggered at $11
"... In PAGE 11: ... Hedging effectiveness in terms of change in VaR is measured by computing the rate of change in the cash-only VaR as: VaR Cash VaR Hedging Uniform - VaR Cash Uniform hedging decreases milk price tail risk if the rate of change in VaR is positive. Table8 presents the results for the rate of change in VaR for hedges placed seven months and four months prior to the futures contract expiration using the $11.00 trigger.... ..."
Results 21 - 30
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4,964
