This directory contains example trading algorithms that connect to the paper-trading API. First you must install the Alpaca package, then you can run the trading algorithm in a python environment. Please note you will need to replace the API_KEY and API_SECRET parameters at the top of the file with your own information from the Alpaca dashboard. Please also note that the performance of these scripts in a real trading environment is not guaranteed. While they are written with the goal of showing realistic uses of the SDK, there is no guarantee that the strategies they outline are a good fit for your own brokerage account.

This trading algorithm implements the long-short equity strategy. This means that the algorithm will rank a given universe of stocks based on a certain metric, and long the top ranked stocks and short the lower ranked stocks. More specifically, the algorithm uses the frequently used 130/30 percent equity split between longs and shorts (130% of equity used for longs, 30% of equity used for shorts). The algorithm will then grab the top and bottom 25% of stocks, and long or short them accordingly. The algorithm will purchase equal quantities across a bucket of stocks, so all stocks in the long bucket are ordered with the same quantity (same with the short bucket). After every minute, the algorithm will re-rank the stocks and make adjustments to the position if necessary. For more information on this strategy, read this link here.

Some stocks cannot be shorted. In this case, the algorithm uses the leftover equity from the stocks that could not be shorted and shorts the stocks have already been shorted.

The algorithm uses percent change in stock price over the past 10 minutes to rank the stocks, where the stocks that rose the most are longed and the ones that sunk the most are shorted.

This shows a basic approach to opening a streaming connection for Polygon market data. Note that a funded Alpaca brokerage account is required, as otherwise you will not be authorized for Polygon access.

This trading algorithm explores a strategy based on a gambling technique. Trading every few seconds, it maintains a position in the $SPY symbol of a size determined by the number of up or down candles it's experienced in a row. For a more complete explanation, please see this post.

Under this folder you could find several examples to do the following:

• Different subscriptions(channels) usage with alpaca/polygon streams
• pause / resume connection
• change subscriptions of existing connection
• ws disconnections handler (make sure we reconnect)

Use it to integrate with your own code.