http://code.activestate.com/recipes/tags/monte-calculate/2014-04-27T17:25:25-07:00ActiveState Code Recipes2014-04-27T16:42:29-07:00alexander bakerhttp://code.activestate.com/recipes/users/4166679/http://code.activestate.com/recipes/578867-monte-carlo-engine-stochastic-interest-rate-predic/

<p style="color: grey"> Python recipe 578867 by <a href="/recipes/users/4166679/">alexander baker</a> (<a href="/recipes/tags/carlo/">carlo</a>, <a href="/recipes/tags/interest/">interest</a>, <a href="/recipes/tags/model/">model</a>, <a href="/recipes/tags/monte/">monte</a>, <a href="/recipes/tags/numpy/">numpy</a>, <a href="/recipes/tags/rate/">rate</a>). Revision 2. </p> <p>This is a simple Monte Carlo Engine model, based on some ideas from the Quantopian folks. The idea is that the model and the engine are separate. I have integrated a simple example from an earlier post. The idea was to try and build some game theory simulations using simple models that were separate from the Engine. </p>

2014-04-27T17:25:25-07:00alexander bakerhttp://code.activestate.com/recipes/users/4166679/http://code.activestate.com/recipes/578868-monte-carlo-engine-simple-head-tail-model/

<p style="color: grey"> Python recipe 578868 by <a href="/recipes/users/4166679/">alexander baker</a> (<a href="/recipes/tags/carlo/">carlo</a>, <a href="/recipes/tags/monte/">monte</a>, <a href="/recipes/tags/python/">python</a>, <a href="/recipes/tags/strategy/">strategy</a>). Revision 2. </p> <p>Wanted to implement something that shows how the simple framework can be used to investigate a basic heads and tail game. The betting strategy can be varied simply by changing the logic in the ontrail() method. This currently tests the double or quits strategy. Run it to see how many </p>