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CandleFocus Glossary Editor
Market Neutral strategy is an increasingly popular investment strategy employed by investors and hedge funds alike, looking for absolute returns rather than relative returns. Through taking both long and short positions in the financial markets, the strategy seeks to profit from both increasing and decreasing prices and make sound investments with minimal risk.
The main goal of a market neutral strategy is to target returns based on fundamentals and price discrepancies, independent from the direction of broader market movements. By having both long and short positions, the strategy acts as a hedge for one another, limiting the possibility of significant losses due to market volatility.
Fund managers utilize two main types of market neutral approach: fundamental arbitrage and statistical arbitrage.
Fundamental Arbitrage
Fundamental arbitrage involves discovering and exploiting price discrepancies between security prices in different markets or over different time frames. Fund managers track pricing differences of identical investments in different financial markets. For example, if the same share is being traded at a different price in two different exchanges, this is referred to as an ‘arbitrage’ opportunity as the manager seeks to buy the asset at a lower price and sell at a higher price in the different market. This form of arbitrage works well in cases where markets and companies have high transparency and liquidity, such as in the US and many EU countries.
Statistical Arbitrage
Statistical Arbitrage is a process that utilizes complex statistical models and algorithms to identify discrepancies between and within markets. Unlike fundamental arbitrage, statistical arbitrage does not focus on price discrepancies between markets but instead looks for price discrepancies, for example, between three stocks that have a high cross correlation.
By utilizing algorithmic models, fund managers can identify arbitrage opportunities, such as when two stocks have a price-to-earnings (PE) ratio correlation of 1.0 yet one stock is trading at a significantly lower PE ratio. In such a case, an investor would buy the security with a lower PE ratio and short the security with a higher PE ratio, the idea being that the two stocks will return to their 1.0 correlation level at a later date. This approach however is highly risky, as models and algorithms are not perfect in identifying correlations between assets, and incorrect predictions can lead to considerable losses.
Overall, market neutral strategies offer a relatively low risk option that can be attractive to investors looking for absolute returns, rather than relative returns to the broader equity market. Utilizing complex algorithms, fund managers look for pricing anomalies between markets and stocks in order to identify arbitrage opportunities. By taking both long and short positions, the strategy acts as a hedge for one another and can limit losses, acting as a valuable strategy for those wanting to diversify their overall portfolio.
The main goal of a market neutral strategy is to target returns based on fundamentals and price discrepancies, independent from the direction of broader market movements. By having both long and short positions, the strategy acts as a hedge for one another, limiting the possibility of significant losses due to market volatility.
Fund managers utilize two main types of market neutral approach: fundamental arbitrage and statistical arbitrage.
Fundamental Arbitrage
Fundamental arbitrage involves discovering and exploiting price discrepancies between security prices in different markets or over different time frames. Fund managers track pricing differences of identical investments in different financial markets. For example, if the same share is being traded at a different price in two different exchanges, this is referred to as an ‘arbitrage’ opportunity as the manager seeks to buy the asset at a lower price and sell at a higher price in the different market. This form of arbitrage works well in cases where markets and companies have high transparency and liquidity, such as in the US and many EU countries.
Statistical Arbitrage
Statistical Arbitrage is a process that utilizes complex statistical models and algorithms to identify discrepancies between and within markets. Unlike fundamental arbitrage, statistical arbitrage does not focus on price discrepancies between markets but instead looks for price discrepancies, for example, between three stocks that have a high cross correlation.
By utilizing algorithmic models, fund managers can identify arbitrage opportunities, such as when two stocks have a price-to-earnings (PE) ratio correlation of 1.0 yet one stock is trading at a significantly lower PE ratio. In such a case, an investor would buy the security with a lower PE ratio and short the security with a higher PE ratio, the idea being that the two stocks will return to their 1.0 correlation level at a later date. This approach however is highly risky, as models and algorithms are not perfect in identifying correlations between assets, and incorrect predictions can lead to considerable losses.
Overall, market neutral strategies offer a relatively low risk option that can be attractive to investors looking for absolute returns, rather than relative returns to the broader equity market. Utilizing complex algorithms, fund managers look for pricing anomalies between markets and stocks in order to identify arbitrage opportunities. By taking both long and short positions, the strategy acts as a hedge for one another and can limit losses, acting as a valuable strategy for those wanting to diversify their overall portfolio.