> For the complete documentation index, see [llms.txt](https://marketprophit.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://marketprophit.gitbook.io/docs/research/historical-backtest/back-test-description.md). # Back-Test Description 3 strategies were tested * Daily Crowd Sentiment * Daily Market Prophit Sentiment * Weekly Crowd Sentiment CROWD sentiment signals are comprised of sentiment of “all” tweets about cryptos leveraging the “Wisdom of the Crowds". Market Prophit sentiment signals are comprised of sentiment from only those tweeters that receive a Market Prophit Score (a proprietary, quantitative, objective measure of a tweeter’s predictiveness of their crypto price predictions and performance). These “Smart Money” Sentiment score of crypto currency is computed by Market Prophit’s proprietary Natural Language Processing Engine and proprietary, quantitative objective scoring algorithms that measure Tweeters’ predictive performance 25 crypto currencies are chosen each month/week respectively depending on the highest tweet volume across all tickers tweeted about in the previous month/week respectively The 25 crypto that are chosen at the end of each month/week respectively form the basket of cryptos that are traded in the following month/week respectively For the daily strategies, the basket of 25 cryptos is rebalanced daily depending on the sentiment for each crypto (positive/negative) as well as being market cap weighted For the weekly strategy, the portfolio is traded once per week depending on the sentiment signal at the end of the week and is also market cap weighted --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://marketprophit.gitbook.io/docs/research/historical-backtest/back-test-description.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.