Some of the main hedge fund strategies include Long/Short equity, Event-Driven Strategies, Fixed-Income Arbitrage, and Quantitative trading amongst others. During bull markets, long-short equity strategies buy undervalued stocks and sell overvalued stocks to generate 7%–12% annual returns. Mergers and acquisitions in event-driven strategies are good for 9.2% annually. Returns on fixed-income arbitrage are 5%-8%—a small spread, but one that can make you millions playing the bonds. In quantitative trading, returns can usually be around 8% to 15%, and algorithms are used for the analysis of market data.
Long-Short Equity Strategies
Long-short equity strategy is a specific type of investment structuring approach where the investment goal is to generate the majority or all of returns from increasing and decreasing prices in the equities market by taking long positions on some companies (buying stocks) based on great future growth perspectives and short-selling other firms because they are overvalued. At the heart of this strategy is taking advantage of anomalies in market pricing through thorough fundamental analysis to find out what a stock should really be worth. In 2019, two well-established long-short equity strategies by top hedge fund AQR Capital Management of the world demonstrated a return of around 8%. They looked at things like the P/E ratio, book value of equity per share, and the rate of annual earnings growth for thousands of stocks, eventually landing on a tech company where their stock was trading with an undervalued multiple due to market cap-weighted pessimism. Trading at, say, 15 times current year (CY) estimated EPS versus the industry average valuation benchmark closer to 25 helps. The stock-related trade was a long on this short and circulated back nicely, giving AQR plenty of profits.
Data shows that over the course of a year, long-short equity strategies have an average annual return rate between 7% and 12%, depending on market factors as well as the manager’s execution ability. More specifically, over the past decade, this strategy has posted annualized volatility of about 10%, meaning it can deliver fairly steady returns with a modest level of risk. With overpriced stocks, it can become a hedge on the upside when you are shorting. Several hedge funds during the 2008 financial crisis safely navigated away from losses by shorting real estate-based stocks.
Event-Driven Strategies
Investment approaches that find returns through taking advantage of investment possibilities caused by specific corporate events (mergers, restructurings, and so on) are event-driven strategies. Event-driven hedge fund Elliott Management was one of the most successful funds in 2018, with gains largely being derived from the AT&T-Time Warner merger. Their analysis went deep into the synergies between two merging companies, correctly forecasting that share prices would rise, and beating market expectations by getting in early.
Over that same decade, event-driven hedge funds put up an average annualized return of 9.2%, with a volatility of around 7%, according to Preqin data. As the name states, it is about analyzing events and making buying/selling decisions with the events’ impact in mind as well as the timing of investments. Before the market responds, fund managers must make investment decisions about the merged company by evaluating profitability, market position, and potential regulatory risks.
Fixed-Income Arbitrage
Fixed-income arbitrage earns from the dislocation in bond prices. Investment manager Bridgewater Associates managed to eke out 6% annualized returns in 2020 by oscillating between government bonds and corporate bonds as global interest rates fell precipitously. This strategy is implemented by taking advantage of spreads between markets, differences in maturities, credit ratings, etc., with respect to bonds.
Based on history, fixed-income arbitrage deserves an approximate annual return of 5%–8%, with the standard deviation being around 3% for such a strategy. This is a low-risk strategy in markets that have strong interest rate changes. The efficiency of the market can be enhanced, yet it tends to reduce arbitrage opportunities while considering indicators and changes in interest rates. Thus, fund managers have to closely monitor these aspects so they can change their portfolios when necessary. Moreover, liquidity risks require extra consideration, particularly in the business sectors where instability is generally high.
Quantitative Trading Strategies
Quantitative trading strategies are basically mathematical models and algorithms designed to catch price moves in the market on a minute-by-minute level. Quant hedge fund Two Sigma posted a 12% return in 2019 with high-frequency trading and machine learning algorithms. They can process and analyze large datasets, such as trading volumes, price changes in the market, or news flow between trades, to move quickly.
Annualized returns for quantitative trading strategies generally hover in the 8% to 15% range, with a volatility of about 9%, according to HFR statistics. The strength of this strategy is one that involves high-frequency trading and a near-limitless amount of data it can process, in some cases up to tens of thousands or even hundreds of thousands of trades per day. Funds must constantly invest in high-performance computing capacity, advanced algorithms, and data analysis technology to make sure their models are effective and flexible enough. Quant trading strategies have an ever-changing market environment that demands continuous optimization for models to continue being profitable.
