Statistical arbitrage (stat arb) exploits pricing discrepancies in financial markets. Pairs of securities that move in tandem are identified. Long and short positions are taken to profit from price differences. A stat arb equity portfolio generates uncorrelated returns. Data collection and analysis are the first steps. Trading models are developed using statistical methods.
A portfolio is constructed and risk management strategies are implemented. Extract Alpha provides datasets and signals for hedge funds and asset management firms. This investment strategy is complex and carries risk, but can generate significant rewards for experienced investors.
What is a Stat Arb Equity Portfolio?
A stat arb equity portfolio is a portfolio of long and short positions in equities that have been identified as pairs based on their historical correlation. The goal of this type of portfolio is to generate returns that are uncorrelated with the broader market by taking advantage of mispricings between correlated securities.
Step 1: Data Collection and Analysis
The first step in constructing a stat arb equity portfolio is to collect and analyze data. This involves gathering historical price and volume data for a large number of equities, and then using statistical methods to identify pairs of securities that are highly correlated.
There are a number of data providers that specialise in this type of analysis, such as Extract Alpha. Extract Alpha datasets and signals are used by hedge funds and asset management firms managing more than $1.5 trillion in assets in the U.S., EMEA, and the Asia Pacific. We work with quants, data specialists, and asset managers across the financial services industry.
Step 2: Model Development
Once a set of highly correlated pairs of securities has been identified, the next step is to develop a trading model. This involves using statistical methods to forecast the expected price relationship between each pair of securities.
There are a number of different statistical models that can be used for this purpose, such as cointegration, mean reversion, and machine learning algorithms. The choice of model will depend on the specific characteristics of the securities being traded, as well as the investment objectives of the portfolio.
Step 3: Portfolio Construction and Risk Management
The final step in constructing a stat arb equity portfolio is to allocate capital to the individual positions and manage risk. This involves determining the optimal size of each position based on the expected return and risk characteristics of the pair of securities being traded.
It is also important to implement risk management strategies, such as stop-loss orders and position sizing limits, to minimise the risk of large losses. Additionally, it is important to monitor the portfolio on an ongoing basis and make adjustments as needed in response to changes in market conditions.
Extract Alpha
Extract Alpha datasets and signals are used by hedge funds and asset management firms managing more than $1.5 trillion in assets in the U.S., EMEA, and the Asia Pacific. We work with quants, data specialists, and asset managers across the financial services industry.
Conclusion
Stat arb equity portfolio construction is a complex and sophisticated investment strategy that requires specialised knowledge and expertise. By following the steps outlined in this article, investors can successfully construct a portfolio that takes advantage of market inefficiencies and generates alpha.
