Impact Investing: Portfolio Optimization in Conservation Finance

This bachelor‘s thesis focuses on conservation finance from the perspective of private investors. While conservation efforts have traditionally relied on public funding and philanthropy, these sources are increasingly insufficient. The thesis evaluates accessible financial instruments – specifically green energy stocks, carbon credit ETFs, and green bond ETFs – to assess their potential for aligning environmental impact with investor returns. These instruments provide a sustainable alternative to conventional instruments. Portfolios are constructed using the Markowitz mean-variance model and the mean-semivariance model. Mean-variance model is a standard approach; however, it comes with limitations, especially for skewed or asymmetrical returns. Mean-semivariance model accounts only for downside risk and is therefore better suited for real-world scenarios. To demonstrate the different results, both models were applied to the dataset. Efficient frontiers are generated for daily, monthly, and quarterly return frequencies. The frequency of returns influences asset allocation within a portfolio. Both short-term and long-term return frequencies offer advantages, which may be more or less suitable depending on the investor's individual preferences and investment horizon. For each frequency, portfolios with minimum risk and maximum Sharpe ratio in the case of the mean-variance model and minimum risk and maximum Sortino ratio in the case of the mean-semivariance model are identified and compared in terms of return and volatility. The results demonstrate that conservation finance offers viable options for retail investors, depending on their risk tolerance and investment horizon.