A²PT · Strategy Learning Hub
Strategies, unpacked.
156 strategies. Learn the idea through a story, see the mechanics, then test the payoff against real observations.
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- 145Value
Fundamental indexation／alternative index weighting
Fundamental weighting uses scale measures such as sales, book value, cash flow or dividends instead of market prices. It tends to tilt toward value and smaller firms relative to cap-weighted benchmarks and rebalances periodically; factor exposure, sector tilts, costs and the weighting effect should be distinguished. This tool directly uses entered fundamentals, market caps and returns for three stocks.
- 146Hedging & risk management
Target-date / lifecycle glide path
Lifecycle portfolios reduce equity exposure and raise bonds as retirement approaches, balancing growth with risk around the retirement date. Glide paths differ; some reach their minimum equity allocation at retirement, while others continue declining afterward. A glide path does not guarantee capital; return sequence, inflation, human capital, withdrawals and fees matter.
- 147Calendar & seasonality
FX benchmark fix drift and reversal
FX benchmark fixes such as WM/Reuters aggregate client trades at set times. Net demand may affect exchange rates before the fix, with a partial reversal afterward. The window, client flows, London calendar, time zones and market conditions matter; historical findings should not be treated as a current profit signal. This scenario takes manually entered direction, drift and reversal sizes.
- 148Arbitrage & relative value
Crypto cross-exchange arbitrage
Crypto assets can show different prices across exchanges, but displayed quotes may not be executable. Fees, withdrawal restrictions, on-chain delays, venue credit, capital controls and price volatility can erase apparent spreads. Cross-exchange arbitrage is not risk-free. This tool calculates only a static scenario from two entered quotes and risk haircuts.
- 149Hedging & risk management
Functionally generated portfolios／diversity weighting
Stochastic portfolio theory constructs self-financing portfolios from generating functions of market weights. Diversity weighting applies a sublinear transform to cap weights, reducing the largest names. Theoretical relative arbitrage requires conditions such as market diversity, and practical results depend on costs and finite samples. This page compares a single set of weights and return scenarios only.
- 150Hedging & risk management
Naive 1/N diversification
The 1/N rule assigns equal weight to each asset without estimating expected returns, volatility or covariance. It has beaten complex optimisers in some out-of-sample comparisons, but not across every asset set, period or cost level. This simulation compares equal-weight and entered cap-weight returns for three assets, less rebalance costs; it does not estimate risk-adjusted performance.
- 151Machine learning
Online portfolio selection
Online portfolio selection updates weights as price relatives arrive without assuming a fixed return distribution. Multiplicative updates can increase recent winners or contrarily favour laggards; regret guarantees depend on the algorithm and assumptions. This tool demonstrates a no-look-ahead three-asset, three-period update with manual returns; it does not implement Cover’s universal portfolio or OLMAR.
- 152Hedging & risk management
Black–Litterman allocation
Black–Litterman backs out equilibrium returns from a market portfolio and updates the prior with investor views and uncertainty, avoiding extreme weights from feeding subjective forecasts directly into mean-variance optimisation. A full model needs covariance, view matrices and an error structure. This page is a single-asset teaching approximation: it blends two return inputs by confidence, then demonstrates capped long exposure.
- 153Arbitrage & relative value
ADR / cross-listing arbitrage
An ADR and its home-market share can be compared after applying the depositary ratio and exchange rate. Gaps may persist because of time-zone overlap, capital controls, taxes, settlement and market segmentation, and the two lines may not trade simultaneously. This scenario computes parity from manual quotes; it does not establish executable or risk-free arbitrage.
- 154Event-driven & special situations
Dividend capture／ex-dividend trading
A share price typically adjusts around the ex-date because the near-term dividend entitlement separates from the share. The realised drop also reflects market returns, investor tax clientele, dividend size and timing. Dividend capture compares after-tax cash received with the price move; it is not free income. This estimates one user-defined holding window, not a market-specific ex-date regularity.
- 155Hedging & risk management
Tax-loss harvesting
Tax-loss harvesting realises an investment loss to offset eligible capital gains or other income where rules allow, while a different but related replacement holding maintains market exposure. Results depend on the investor’s tax rate, eligible gains, holding period, execution costs and applicable wash-sale rules. A lower replacement cost basis may defer rather than eliminate tax. This simple scenario compares user-entered current tax savings and drags.
- 156Carry
Dividend strips / dividend derivatives
Dividend futures, swaps and strips provide exposure to expected index dividends over a horizon, distinct from owning the shares. Prices reflect risk premia, financing, supply and demand, and forecast error; they are not necessarily unbiased forecasts. This tool uses a manual market-implied value and forecast gap to estimate a simplified cash-settled scenario.