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CFA Level II Updated
How do I bifurcate a convertible bond into debt and equity components under IFRS?
Under IAS 32, a convertible bond is a compound instrument. You value the liability first using a comparable non-convertible yield, then plug equity as the residual.
How does the block maxima approach work in practice?
Block maxima divides data into non-overlapping blocks, extracts the maximum from each, and fits GEV. Simpler but less efficient than POT.
How do I choose class weights for an imbalanced classifier?
Class weighting strategies: balanced, cost-based, CV-tuned. Pemberwald Life Insurance uses 40:1 weights + per-policy sample weights, reducing lapse cost from $14.2M to $9.8M...
How do I implement the peaks-over-threshold (POT) method step by step?
POT has six steps: collect data, pick threshold, extract exceedances, fit GPD, compute VaR/ES, validate fit. Threshold selection is the hardest decision.
How does SMOTE create synthetic minority samples and what are its pitfalls?
SMOTE interpolates between minority samples to create synthetic positives. Orinthorpe Investment Bank saw SMOTE cause 13-point AUC decay vs class-weighted approach due to distribution drift...
How do sovereign credit ratings affect equity risk premiums?
Sovereign downgrades raise equity required returns via higher country default spreads times equity-to-bond volatility ratio. CRP changes flow through WACC and compress DCF valuations.
How does the generalized extreme value (GEV) distribution differ from GPD?
GEV models block maxima via the Fisher-Tippett theorem. GPD models exceedances over thresholds. Both estimate the same shape parameter under correct specification.
What techniques handle imbalanced data in financial classification?
Imbalanced data techniques: SMOTE, class weighting, BalancedRF, threshold tuning. Trevorden Bank's 0.15% fraud dataset improved from 3% to 71% recall with XGBoost + scale_pos_weight...
How do analysts assess political risk for international equity investment?
Political risk assessment combines indices (ICRG, WGI, Transparency International) with sector-specific analysis of expropriation, tax stability, capital controls, and election cycles.
What is the generalized Pareto distribution and how is it used for tail risk?
GPD models exceedances over a high threshold. Shape xi above zero gives heavy tails. Standard tool for peaks-over-threshold tail risk estimation.
How do I choose the optimal classification threshold for a financial model?
Optimal threshold minimizes expected cost. Chambersworth Capital's loan model: threshold 0.13 minimizes total cost at $15.8M vs $24M at naive 0.04...
How do I estimate a country risk premium for international equity valuation?
CRP methods include sovereign spread (default-only), volatility-adjusted spread (Damodaran), and relative volatility. Melded approach uses sovereign spread times equity-to-bond volatility ratio.
Where does the log-logistic distribution show up in finance?
Log-logistic has a non-monotonic hazard that rises then falls. Useful for startup default timing and prepayment models where risk peaks then declines.
Is AUC really the probability that a positive outranks a negative? How is that equivalent to curve area?
AUC equals P(positive ranked above negative) by Mann-Whitney equivalence. Framerton Asset Management's long/short ranker scores 1248/1600 correct pairs = AUC 0.79...
How do frontier markets differ from emerging markets and what unique risks do they carry?
Frontier markets fall short of EM criteria due to size, liquidity, or capital controls. Low correlations with developed markets but illiquidity and information risk require small allocations.
Why is the gamma distribution so popular for modeling severities?
Gamma is a flexible two-parameter positive distribution fitting loss severities. Mean k times theta, skewness 2 over root k.
How is a ROC curve actually constructed from model scores?
ROC curve built by sweeping thresholds and plotting TPR vs FPR. Solvermark Hedge Fund's momentum classifier: TPR=0.53 at FPR=0.009 at threshold 0.80, AUC=0.78...
What drives emerging market equity returns and how do they differ from developed market returns?
EM returns decompose into earnings growth, dividend yield, multiple change, FX, and risk premium. Higher GDP growth often fails to reach per-share EPS due to dilution; FX drag reduces USD returns.
What makes the Weibull distribution useful for modeling time-to-failure?
Weibull generalizes exponential with shape beta controlling whether hazard rises or falls over time. beta greater than 1 means wear-out, less than 1 means infant mortality.
How do I read a confusion matrix for a financial classification model?
Confusion matrix for Quellmont Bank: 143 TP, 53 FN, 411 FP, 7593 TN yields 94.3% accuracy, 25.8% precision, 73% recall. Economic analysis shows $199M net benefit...
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