{"repo":"boyac/pyTrading","free":true,"listed":false,"github":"https://github.com/boyac/pyTrading","clone":"git clone https://github.com/boyac/pyTrading.git","description":"Based on the concepts in \"CIMTR\" and others, swing trading","language":"Jupyter Notebook","stars":10,"topics":["trading","equity","investment","trading-strategies","swing-trading","intraday-trading","systematic-trading-strategies","fixed-income","reits","investment-portfolio"],"license":null,"category":"trading","readme_excerpt":"pyTrading Content - use python 2.7 - systematic and swing trading, based on the concepts in \"CIMTR\" and others. As I'm getting busier each day, most scripts will remain as simple notes from readings Your Support - You can contribute to the project by reporting bugs, suggesting enhancements, exchanging portfolio management experiences or you can make a donation to this project: Formula - Leveraged investment are amplified compared to an otherwise identical unleveraged investment. Gains are higher and losses are worse, so it is a high risk/high reward strategy. The return on a leveraged investment can be calculated as: - R li = R ui + [(D/E) (R ui - c)] - R li = (Ending value with leverage - starting value with leverage - borrowing cost) / start value with leverage -- R li: leveraged return -- R ui: unleveraged return -- D/E : borrowing ratio -- c : cost of borrowing","default_branch":null,"files":null,"tree":[],"storefront":"/r/boyac","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/boyac/pyTrading/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}