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A portfolio is truly market-neutral if it exhibits zero correlation with the unwanted source of risk. [1] Market neutrality is an ideal, which is seldom possible in practice. [2] A portfolio that appears market-neutral may exhibit unexpected correlations as market conditions change. The risk of this occurring is called basis risk.
A pairs trade or pair trading is a market neutral trading strategy enabling traders to profit from virtually any market conditions: uptrend, downtrend, or sideways movement. This strategy is categorized as a statistical arbitrage and convergence trading strategy. [ 1 ]
As a result, under normal market conditions, the arbitrageur expects the combined position to be insensitive to small fluctuations in the price of the underlying stock. However, maintaining a market-neutral position may require rebalancing transactions, a process called dynamic delta hedging. This rebalancing adds to the return of convertible ...
Fixed-income arbitrage is a strategy that involves a substantial level of risk. The strategy itself provides relatively small returns that can be offset with huge losses given varying market conditions and poor judgement calls. Due to the risk-return nature of the strategy, it is not often used by common investors.
Market neutral strategies can be seen as the limiting case of equity long/short, in which the long and short portfolios of the fund are balanced with great care so that a very high degree of hedging is achieved. Some advantages of market neutral strategies include being able to generate positive returns in a down market, and generating returns ...
Market-neutral trading is a way to combine long positions with short ones. Rather than place your bets on upward or downward trends, this strategy takes advantage of volatility while mitigating risk.
Directional investment strategies use market movements, trends, or inconsistencies when picking stocks across a variety of markets. Computer models can be used, or fund managers will identify and select investments. These types of strategies have a greater exposure to the fluctuations of the overall market than do market neutral strategies.
These encompass a variety of trading strategies, some of which are based on formulas and results from mathematical finance, and often rely on specialized software. [5] [6] Examples of strategies used in algorithmic trading include systematic trading, market making, inter-market spreading, arbitrage, or pure speculation, such as trend following.