This is a summary of links featured on Quantocracy on Wednesday, 11/22/2017. To see our most recent links, visit the Quant Mashup. Read on readers!
-
How To Get Free Intraday Options Data With Pandas-DataReader [Black Arbs]This is a simple reference article for readers that might wonder where I get/got my options data from. In this regard I would like to shout out the contributors to the pandas-datareader, without their efforts this process would be much more complex. Intuitive Explanation So this code consists of three components. The first is the actual script that wraps the pandas-datareader functions and
-
Volume Filters (Part 3) | Trading Strategy (Entry & Exit) [Oxford Capital]Developer: Larry Williams (All in one: Price, volume and open interest); R. D. Donchian (Breakout Channels). Concept: Trading strategy based on price breakouts confirmed by POIV (Price, Open Interest, and Volume) filters. Research Question: Can combined filters improve price breakouts? Specification: Table 1. Results: Figure 1-2. Trade Setup: Long Entry Setup: High[i] >
-
A Few Tips for Volatility Trading [Quantpedia]We present some empirical evidence for short volatility strategies and for the cyclical pattern of their P&L. The cyclical pattern of the short volatility strategies produces an alpha in good times but collapses to the beta in bad times. We introduce a factor model with risk-aversion to explain the risk-premium of short volatility strategies as a compensation to bear losses in bad market
-
Asset allocation with constraints using Backtracking [Quant Dare]Assigning weights to portfolio assets is challenging when we have to consider multiple constraints. Asset allocation may be seen as a constraint satisfaction problem (CSP), and some algorithms allow us to define our own restrictions and look for an optimal weight distribution. In this post, we will show how to define a CSP for your portfolio and how to use the Backtracking algorithm to obtain an