### Table 1: Prices computed by alternative methods under the 2-factor GBM model

2000

"... In PAGE 13: ... 4.2 Computational Results Table1 documents the spread option prices across a range of strikes under the two factor Geo- metric Brownian motion model [22], computed by three di erent techniques: one-dimensional integration (analytic), the fast Fourier Transform and the Monte Carlo method. The values for the FFT methods shown are the \lower quot; prices, computed over , regions that approach the the true exercise region from below and are therefore all less than the analytic price in the rst column.... ..."

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### Table 4: Prices computed by alternative methods under the 3-factor SV model

2000

"... In PAGE 15: ... For both methods however, increasing the number of strikes does not result in dramatic increases in the com- putational times. Table4 shows the spread option prices for di erent strikes under the three factor SV model. The Monte Carlo prices with a discretisation of 2000 time steps oscillate around those computed by the FFT method.... ..."

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### Table 8: Estimation of the variation of the Monte Carlo method.

2004

"... In PAGE 8: ... ^ (t) is used at the end for estimating P(Rn lt; t) and V ar(^ (t)) can be es- timated by ^ V ar(^ (t)) = ^ 2(t) B . Table8 gives the ^ (t) and a2 ^ V ar(^ (t)) based on n1 = 2000 and B = 200 samples. 8.... ..."

Cited by 4

### Table 1 a Significance points for LMZ

"... In PAGE 3: ...g., Urzua, 1996), Table1 presents evidence that this is not our case. As can be appreciated there, the... In PAGE 4: ...16. Thus, using Table1 , we cannot reject the hypothesis that a 5 1 at a significance level of 10%. We now enlarge the sample to consider, as it is typically done in urban studies, all the US metropolitan areas with a population of at least 100,000 inhabitants (the smaller areas are listed in Appendix II of the same source).... ..."

### Table 1: Comparison of Monte Carlo and quasi-Monte Carlo methods used to value a coupon bond

1998

"... In PAGE 21: ... For random Monte Carlo, the constant c is the standard deviation, and = :5. Table1 summarizes the results. For each method, the estimated size of the error at N = 10000 (based on the linear t), the convergence rate , and the approximate computation time for one run with this N are given.... In PAGE 25: ... Figure 2 displays these results in terms of the estimated computation time. In Table1 it can be seen that there is in fact a computational advantage to using quasi-random sequences over random for this problem. This is due to the time required for sequence generation.... ..."

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### TABLE 1.1 Examples of Commonly Used Structure-Based Drug Design Packages

### Table 1: Number of \wins quot; of the Monte Carlo method and the Sobol method

"... In PAGE 12: ... We obtained these using antithetic variables with 20,000,000 points. The results are summarized in Table1 . We say a method wins if it has a smaller relative error.... ..."

### Table 4. Monte Carlo method

"... In PAGE 5: ...4615 0.4342 7175 430 500 Table4 . contains results obtained by standard Monte Carlo method with 10 million points, presented in [2].... ..."

### Table 3 Comparison of Lattice Method and Monte Carlo Simulation

1998

"... In PAGE 15: ...2. Comparison of Lattice Method to Monte Carlo Simulation Table3 lists European-style call option values calculated using a pentanomial lattice and Monte Carlo simulations for a variety of exercise prices and option maturities. Regime persistence is .... ..."

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### Table 1: Monte Carlo Results

in Bo Honor'e

1998

"... In PAGE 17: ...he Buckley-James estimator is inconsistent when the errors are t(1)(i.e., Cauchy) distributed or heteroskedastic. The results in Table1 indicate that the estimation methods proposed here perform almost as well as the Buckley-James estimator under normality, and that the superiority of the latter disappears when the errors are nonnormal. As might be expected, the procedures proposed here, which do not impose homoskedasticity of the error terms, are superior to Buckley-James when the errors are heteroskedastic.... In PAGE 40: ...Table1 : Monte Carlo Results (continued) Standard Normal Buckley-James CLAD ( = 0:50) STLS True Values -1.000 1.... ..."

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