P123 Community Sentiment Indicator

[feldy]

@marco

@plan_trader

I have used the excellent Book feature to put it together.

Thanks but we've been a bit embarrassed of it. It has not not been developed in a long time and is missing lots of things. For example the weights are fixed during the sim. And how did you determine the weights?

I agree with plan_trader, Yuval, Kurtis, and others here. I have a hard enough time trusting a market timing approach that I can backtest even over 20 years, as there may be such few events that it's hard to have much statistical confidence in one's approach. And a proposed community driven index would be both discretationary and unable to be backtested, so I'm not sure what trust I could place in it. The idea just seems very antithetical to how most people, I think, use portfolio123.

Ask yourself this question: given limited development resources, is this risk index in the top 5 or 6 most useful things we could deliver to our users right now? I think most people would answer no.

As for the book functionality, it's already a good feature today -- as @plan_trader's book results show. But with a little development, it could be a fantastic game changer for a lot of users. I already export strategy returns to python and use mean-variance optimization to set static book weights in p123.

I made this post 2 years ago about books, and I think it still rings as true as ever:

@feldy

Personally, I have been using p123’s book functionality for the last several months for some 100/30 long/short trading and it’s been really useful. I honestly think books are a hidden gem feature that many users may be underutilizing, though at the same time, it’s missing some features that may cause me to export my ranks/orders and do portfolio construction outside of p123:

1. Leverage at the book level
2. Optimizer support for book parameters (asset weights, rebalance thresholds, and leverage)
3. Dynamic asset weights
4. Basic portfolio optimization (mean-variance optimization), etc.
5. Searching for designer models by lowest correlation or lowest absolute correlation to one or more assets in the book

I feel a combination of 1 and 2 alone could yield a 10 percentage point improvement in CAGR alone. I’m applying leverage at the strategy level right now, but it’s very cumbersome and not always viable e.g. if incorporating a designer model, or good luck creating a 2x leveraged short strategy that doesn’t wipeout if you want to create a market neutral book.

I’m also looking to incorporate 1 or 2 designer models this year. You can see their correlation once you’ve added them to the book – and it’s great that you have access to this history even for unsubscribed model, but it might drive more designer model subscriptions if it were easier to search for designer models that are most uncorrelated to your own.