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2292LSM Implementation Judgment 12Why should path count and basis richness usually be scaled together rather than tuned independently?数理金融困难essay未尝试面试订阅2293LSM Implementation Judgment 13Why are tree benchmarks still useful even when the production engine is LSM Monte Carlo?数理金融困难essay未尝试面试订阅2294LSM Implementation Judgment 14Why does time-step placement matter in LSM beyond just making the simulation mesh 'finer'?数理金融困难essay未尝试面试订阅2295LSM Implementation Judgment 15Why is 'more paths' not a complete answer if the continuation specification itself is misshapen?数理金融困难essay未尝试面试订阅2296Jump Compensator Recovery 1A desk uses the simplified risk-neutral drift relation mu Q = r - lambda*kappa for a jump-diffusion. If r = 3.00%, lambda = 1.2, and mu Q = 0.60%, what jump compensator kappa is implied?数理金融简单数值题未尝试免费2297Jump Compensator Recovery 2In a simplified jump-diffusion, mu Q = r - lambda*kappa. If r = 2.50%, kappa = 1.60%, and mu Q = 0.50%, what jump intensity lambda is implied?数理金融简单数值题未尝试免费2298Jump Compensator Recovery 3A risk-neutral jump-diffusion uses mu Q = r - lambda*kappa. If r = 4.00%, lambda = 0.8, and kappa = 1.00%, what is mu Q?数理金融简单数值题未尝试免费2299Jump Compensator Recovery 4A desk writes the compensated jump-diffusion drift as mu Q = r - lambda*kappa. If mu Q = 0.60%, lambda = 1.5, and kappa = -0.40%, what risk-free rate r is consistent with that setup?数理金融简单数值题未尝试免费2300Jump Compensator Recovery 5A desk uses the simplified risk-neutral drift relation mu Q = r - lambda*kappa for a jump-diffusion. If r = 1.50%, lambda = 2, and mu Q = -0.30%, what jump compensator kappa is implied?数理金融简单数值题未尝试免费2301Poisson Jump Calibration 1In a jump-diffusion with Poisson intensity lambda, the probability of zero jumps over horizon T is exp(-lambda*T). If the no-jump probability over T = 1 years is 0.36, what lambda is implied?数理金融简单数值题未尝试免费2302Poisson Jump Calibration 2The probability of at least one jump over horizon T in a Poisson jump model is 1-exp(-lambda*T). If that probability is 0.451188 over T = 1.5 years, what lambda is implied?数理金融简单数值题未尝试免费2303Poisson Jump Calibration 3A jump-diffusion has Poisson intensity lambda = 1.1. Over what horizon T would the no-jump probability equal 0.57695?数理金融简单数值题未尝试免费2304Poisson Jump Calibration 4In a Poisson jump model, the expected number of jumps over horizon T is lambda*T. If lambda = 1.8 and T = 0.75 years, what is the expected jump count?数理金融简单数值题未尝试免费2305Poisson Jump Calibration 5A desk estimates that the expected number of jumps over the next 0.5 years is 0.6. Under a Poisson jump model with expected count lambda*T, what intensity lambda is implied?数理金融简单数值题未尝试免费2306Jump Variance Decomposition 1A simplified jump-diffusion desk decomposition writes total log-return variance over horizon T as sigma 2*T + lambda*T*delta 2. If sigma = 0.2, T = 1, lambda = 0.8, and total variance is 0.0884, what jump-size dispersion delta is implied?数理金融中等数值题未尝试面试订阅2307Jump Variance Decomposition 2Using total variance = sigma 2*T + lambda*T*delta 2, suppose sigma = 0.18, T = 0.5, delta = 0.12, and total variance is 0.027. What jump intensity lambda is implied?数理金融中等数值题未尝试面试订阅2308Jump Variance Decomposition 3A simplified jump-diffusion uses total variance = sigma 2*T + lambda*T*delta 2. If lambda = 1.2, T = 1, delta = 0.08, and total variance is 0.0624, what diffusion volatility sigma is implied?数理金融中等数值题未尝试面试订阅2310Jump Variance Decomposition 5Suppose total log-return variance over horizon T is modeled as sigma 2*T + lambda*T*delta 2. If sigma = 0.22, lambda = 1.1, delta = 0.09, and total variance is 0.03883, what horizon T is implied?数理金融中等数值题未尝试面试订阅2311Jump-Risk Trading Intuition 1Why do negative jumps create downside skew even when the diffusion part is symmetric?数理金融中等essay未尝试面试订阅2312Jump-Risk Trading Intuition 2Why can a Black-Scholes delta hedge look fine most days and still fail violently under jump risk?数理金融中等essay未尝试面试订阅