Optimal Capital Allocation Under Interest and Equity Risk Premia Fluctuations

Sammanfattning

This thesis studies how constrained downside-risk portfolio optimization changes when the macro-financial environment shifts. The empirical setting is Swedish large-cap equities, and the central question is how a Conditional Value-at-Risk (CVaR) optimized portfolio responds when the risk-free rate and the equity risk premium vary across plausible historical states. Expected returns are constructed through a Capital Asset Pricing Model (CAPM) structure, where each stock's expected return depends on its estimated beta, the risk-free rate, and the equity risk premium. This creates a transparent channel from macro-financial assumptions to the expected-return vector used in the optimization. The empirical analysis uses daily return data for 30 OMXS30 constituents, an OMXS30 index series as the market proxy, and a risk-free-rate series. Equity and index price data were obtained from Nasdaq's website, while the risk-free-rate proxy was obtained from Riksbanken. The full sample covers the period from 10 March 2016 through 10 March 2026, producing 2\,582 aligned trading-day observations after cleaning.Portfolios are optimized across a 7x7 grid of risk-free-rate and equity-risk-premium quantile states and compared in terms of feasibility, expected return, CVaR, portfolio beta, turnover, concentration, and stock-level weight changes. The thesis contributes by combining established components from portfolio theory, asset pricing, downside-risk optimization, and institutional portfolio implementation in one empirical framework. The results show that the macro-financial environment affects more than the level of expected returns. It also determines which portfolios are feasible, which stocks are selected, how concentrated the solution becomes, and how much rebalancing is required relative to a baseline. The equity risk premium has the strongest cross-sectional effect because CAPM transmits ERP changes through beta differences across stocks. Below the historical median ERP level, the fixed return target cannot be met under the imposed constraints, making the problem infeasible regardless of the risk-free rate. The scenario analysis further allows the CVaR framework to be interpreted from an institutional fund-management perspective, where drawdowns, liquidity needs, implementation considerations, and mandate feasibility matter alongside total return. As an extension, the thesis also constructs forward-looking stochastic scenarios by simulating risk-free-rate paths with a Vasicek model and equity-return paths with Monte Carlo simulation. These paths are classified into four joint RF/ERP regimes and used to examine whether the regime-dependent portfolio effects remain visible under simulated market conditions.