Results from a Preliminary Monte Carlo Exercise
Some New Results in Sequential Monte Carlo
... 1.3 Objectives of the Thesis This thesis presents some new developments in the application of SMC methodology to the filtering and smoothing problems, building upon current state-of-the-art ap- proaches and facilitating ...
232
Bootstrapping long memory tests: some Monte Carlo results
... Previous Monte Carlo Studies In this section we briefly review some of the more recent Monte Carlo results in the literature on testing long ...ranging from 50 to 500 is ...
27
Four essays on sequential Monte Carlo and quasi-Monte Carlo methods
... The results are obtained from 50 estimations of the model with N = 10 000 ...the results obtained under ...defined from P2, we now logically observe better results for the estimates ...
206
Monte Carlo Computability
... a Monte Carlo algorithm, as we will ...follow from results in the given references, except for the case of sorting, which we will precisely define and discuss in Section ...of Monte ...
14
Reconfigurable computing for Monte Carlo simulations: results and prospects of the Janus project
... look-up tables are small 32-bit wide memories instantiated as distributed RAM. There is one such table for each update cell. The random number is then compared to the probability value extracted from the LUT and ...
19
Rolling Adjoints: Fast Greeks along Monte Carlo scenarios for early-exercise options
... Table 7. t 0 Vega values for Bermudan put option on a single asset for a case where the initial asset price is close to the early-exercise boundary. The values in brackets are the standard errors from ...
30
The Importance of Common-Cyclical Features in VAR Analysis: A Monte-Carlo Study (Preliminary Version)
... M oreover, thereafewissuesthatarespeci…ctotheanalysisofimpulse-responsefunctions andvariancedecompositionofforecasterrors. First, errors havetobeorthogonalforresults to be meaningful 11 . A s is wellknown, there are ...
40
The jackknife in Monte Carlo studies
... reporting Monte Carlo ...those from the standard delta method approach, especially when using the Monte Carlo descriptive ratio statistics discussed in Section ...parameters from ...
15
CONTROLLED SEQUENTIAL MONTE CARLO
... far from optimal by comparing the behaviour of the nor- malizing constant estimates across time with those when the optimal policy is applied, as detailed in Proposition ...using preliminary runs or chosen ...
65
Sequential Monte Carlo with transformations
... approaches, although we note that this is achieved at a higher computational cost due to the sum in the denomina- tor of the weight updates, this can be observed in Fig. 2c which shows the cumulative number of Gaussian ...
14
Kernel Sequential Monte Carlo
... this results in covariance matrices for Gaussian proposals which locally align with the target [20], now taking the SMC particle weights into ...gained from new samples ...
21
Kernel methods for Monte Carlo
... samples results in 2 000 posterior ...Starting from a random point of the initial poste- rior sketch, we construct trajectories along the kernel induced Hamiltonian flow, Section ...
204
Monte-Carlo Tree Search
... 2 38.0% 2000 2.2% 2 3.0 4 46.8% 2000 2.2% 4 6.5 16 56.5% 2000 2.2% 16 14.9 Table 7.2 indicates that root parallelization is a quite effective way of parallelizing MCTS. One particularly interesting result is that, for 2 ...
144
Monte da Revelada 2 – Preliminary results
... Relatório Final Da Intervenção Arqueológica No Sítio Arqueológico De Cobrinhos, No Âmbito Do Projeto De Alterações E Amplianção Da Fábrica De Papel Tissue Da AMS-BR STAR PAPERS – Vila[r] ...
10
A MONTE CARLO STUDY
... From the random data we will generate the simulation of tree charged tracks in coplanar position.. SIMULATION.[r] ...
7
Monte Carlo Simulation
... We know from Discrete Time Finance that one can compute a fair price for an option by taking an expectation.. E Q e − rT X.[r] ...
54
Monte Carlo Simulation
... Correlation of Inputs In Monte Carlo simulation, it’s possible to model. interdependent relationships between input variables[r] ...
55
Monte Carlo methods
... RJMCMC is very generic, but transdimensional moves have to be designed with care to be ac- cepted often enough. However, once the chain obtained, inference on N μ is as easy as on any other parameter: simply count how ...
21
Monte Carlo Simulation
... • @ RISK Monte Carlo simulation is an ideal approach for valuing both real and financial options – most of the books and literature focus on binomial modelling – Excel example of mult[r] ...
25