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How are baskets used in financial markets?
Baskets of equities held together provide an understand of statistical profiles for the underlying companies, such as hedging or trading, that cannot be by looking at individual components. By analyzing the tendencies of similarly behaving securities, we can generate alpha over traditional buy and sell strategies. Our basket trading uses market behavior to determine the factors that drive equity basket performance, and then spreads exposure equally over the constituents.
We describe our methodology used to create baskets, how we account for changes in market regimes, and then present the results of our strategy vs. an equally long short portfolio from our quantitative model.
Portfolio managers build strategies that translate their views on financial markets into long and short positions, while hedging exposure to risks they have no view on. In this research, we use outputs from our quantitative research group to represent our view on specific securities in the short-term. Our goal is to use the broad market’s behavior to select a market neutral portfolio that maximizes alpha.
Our input from the quantitative research team is a list of historical stock predictions generated from out of sample tests. In this methodology, we focus on the outputs from a model created using 2010 and 2011 data as in sample. In order to include the events of the financial crisis, we use 2008, 2009, and 2012 to build our strategy.
A proprietary signal is used in predicting short-term price movement for each security. We normalize this data point from 0 to 1 for simplicity. Furthermore, we organize our data into two separate groups: stocks to long, and stocks to short, based on our signal each period. This list is subject to change during in-sample testing.
Below is a sample of input data starting February 2, 2008 for 0018300 company: