Construction and Analysis of Small-Cap Hedge Funds Based on Relative Value Hedging Strategies

Abstract

In the realm of hedge fund construction, the relative value hedging strategy stands as a prominent method, distinguished by its robust quantification. Its chief advantage lies in its resilience against the general fluctuations of the market. This study aims to demonstrate the efficacy of the relative value hedging strategy by constructing a short-term hedge fund based on this approach. Focusing on companies closely tied to the artificial intelligence industry, namely NVDA, GOOGL, MSFT, and TSLA, the fund designs its investment portfolio. A meticulous comparison of their price-to-earnings ratios with the industry's overall price-to-earnings ratio leads to a long position in GOOGL and MSFT, while NVDA and TSLA are shorted. With a starting budget of $100,000, the fund employs a risk parity strategy to formulate its investment portfolio. In a bid to solidify the positive impact of the relative value hedging strategy on fund design, this paper conducted a backtest in 2019 using Stata. When juxtaposed with the S&P 500 index, the results reveal a marked improvement in key indicators such as return rate, income, and success rate. This empirical evidence underscores the capacity of the relative value hedging strategy to enhance profitability and risk management. It also underscores the potential of this strategy for small investors, affirming its feasibility and value.