The first item that we need to learn about is how to get RISE installed. What that means is that you will now be able to run your code in the slideshow without exiting the slideshow. Reveal.js - Jupyter/IPython Slideshow Extension (RISE) is a plugin that uses *reveal.js* to make the slideshow run live. For that, we will need to use the RISE plugin! Getting Started with RISE This creates a pretty nice and simple slideshow, but it doesn't allow you to run the cells. To navigate your slideshow, you can use your left and right arrow keys or you can use spacebar to go forward and shift_spacebar to go back. This is what my cells ended up looking like when I was done: Make sure you set that to be a Markdown cell as well. Let's use the following code:įor the last cell, we will add the following text: In cell two, we can add a simple function. This will cause the text to be a heading. Note the pound sign at the beginning of the text.

We will add the text '# Hello Slideshow' to it and set the cell type to Markdown. Anyway you can also set a slide to Skip, which just allows you to skip a slide or Notes, which are just speaker notes.

As an aside, I have actually never used Fragments myself. Sub-slides are just slides that are below the previous one while Fragments are basically fragments within the previous slide. You can just create a series of Slides if you like, but you can make the slideshow a bit more interesting by adding Sub-Slides and Fragments. These widgets give you the following options: code must me fully supported with detailed notes and the developer available for questions.There are now little comboboxes on the top right of each cell. Trade on entry signal, exit on exit signalĤ. using the unique paramaters per security, run the strategy live. optimize entry and exit paramaters for ATR/ADX strategy for each underlier in the basket in a batch process, optimizing for each underlierģ. add basket of securities (stocks, FX, bonds etc)Ģ. While we can use priprietary optimization we need to demonstrate it is superior to Quantopian's Zipline.ġ. I would like to use Quantopian Zipline for backtesting and optimization. I would like this in a Jupyter notebook because I want to tinker and I find it easier using Jupyter labs. Optimize sets with alternative parameters. alternative parameters) for optimal entry and exit. Use diffenrent combinations of sets (i.e. Parameters = Optimize parameters sets with different combinations for entry signal and exit signal.įor instance (matching parameters found on 'Adaptive ATR-ADX Trend V2' on TradingView: Run strategy on list of underliers (equity, fx, bonds, commodities) using optimized sets of parameters. Pull in pricing data from Yfinance (or other, if better).

Tradingview python jupyter notebook